R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(119.992
+ ,157.302
+ ,74.997
+ ,0.00784
+ ,0.00007
+ ,0.0037
+ ,0.00554
+ ,0.01109
+ ,0.04374
+ ,0.426
+ ,0.02182
+ ,0.0313
+ ,0.02971
+ ,0.06545
+ ,0.02211
+ ,21.033
+ ,1
+ ,0.414783
+ ,0.815285
+ ,-4.813031
+ ,0.266482
+ ,2.301442
+ ,0.284654
+ ,122.4
+ ,148.65
+ ,113.819
+ ,0.00968
+ ,0.00008
+ ,0.00465
+ ,0.00696
+ ,0.01394
+ ,0.06134
+ ,0.626
+ ,0.03134
+ ,0.04518
+ ,0.04368
+ ,0.09403
+ ,0.01929
+ ,19.085
+ ,1
+ ,0.458359
+ ,0.819521
+ ,-4.075192
+ ,0.33559
+ ,2.486855
+ ,0.368674
+ ,116.682
+ ,131.111
+ ,111.555
+ ,0.0105
+ ,0.00009
+ ,0.00544
+ ,0.00781
+ ,0.01633
+ ,0.05233
+ ,0.482
+ ,0.02757
+ ,0.03858
+ ,0.0359
+ ,0.0827
+ ,0.01309
+ ,20.651
+ ,1
+ ,0.429895
+ ,0.825288
+ ,-4.443179
+ ,0.311173
+ ,2.342259
+ ,0.332634
+ ,116.676
+ ,137.871
+ ,111.366
+ ,0.00997
+ ,0.00009
+ ,0.00502
+ ,0.00698
+ ,0.01505
+ ,0.05492
+ ,0.517
+ ,0.02924
+ ,0.04005
+ ,0.03772
+ ,0.08771
+ ,0.01353
+ ,20.644
+ ,1
+ ,0.434969
+ ,0.819235
+ ,-4.117501
+ ,0.334147
+ ,2.405554
+ ,0.368975
+ ,116.014
+ ,141.781
+ ,110.655
+ ,0.01284
+ ,0.00011
+ ,0.00655
+ ,0.00908
+ ,0.01966
+ ,0.06425
+ ,0.584
+ ,0.0349
+ ,0.04825
+ ,0.04465
+ ,0.1047
+ ,0.01767
+ ,19.649
+ ,1
+ ,0.417356
+ ,0.823484
+ ,-3.747787
+ ,0.234513
+ ,2.33218
+ ,0.410335
+ ,120.552
+ ,131.162
+ ,113.787
+ ,0.00968
+ ,0.00008
+ ,0.00463
+ ,0.0075
+ ,0.01388
+ ,0.04701
+ ,0.456
+ ,0.02328
+ ,0.03526
+ ,0.03243
+ ,0.06985
+ ,0.01222
+ ,21.378
+ ,1
+ ,0.415564
+ ,0.825069
+ ,-4.242867
+ ,0.299111
+ ,2.18756
+ ,0.357775
+ ,120.267
+ ,137.244
+ ,114.82
+ ,0.00333
+ ,0.00003
+ ,0.00155
+ ,0.00202
+ ,0.00466
+ ,0.01608
+ ,0.14
+ ,0.00779
+ ,0.00937
+ ,0.01351
+ ,0.02337
+ ,0.00607
+ ,24.886
+ ,1
+ ,0.59604
+ ,0.764112
+ ,-5.634322
+ ,0.257682
+ ,1.854785
+ ,0.211756
+ ,107.332
+ ,113.84
+ ,104.315
+ ,0.0029
+ ,0.00003
+ ,0.00144
+ ,0.00182
+ ,0.00431
+ ,0.01567
+ ,0.134
+ ,0.00829
+ ,0.00946
+ ,0.01256
+ ,0.02487
+ ,0.00344
+ ,26.892
+ ,1
+ ,0.63742
+ ,0.763262
+ ,-6.167603
+ ,0.183721
+ ,2.064693
+ ,0.163755
+ ,95.73
+ ,132.068
+ ,91.754
+ ,0.00551
+ ,0.00006
+ ,0.00293
+ ,0.00332
+ ,0.0088
+ ,0.02093
+ ,0.191
+ ,0.01073
+ ,0.01277
+ ,0.01717
+ ,0.03218
+ ,0.0107
+ ,21.812
+ ,1
+ ,0.615551
+ ,0.773587
+ ,-5.498678
+ ,0.327769
+ ,2.322511
+ ,0.231571
+ ,95.056
+ ,120.103
+ ,91.226
+ ,0.00532
+ ,0.00006
+ ,0.00268
+ ,0.00332
+ ,0.00803
+ ,0.02838
+ ,0.255
+ ,0.01441
+ ,0.01725
+ ,0.02444
+ ,0.04324
+ ,0.01022
+ ,21.862
+ ,1
+ ,0.547037
+ ,0.798463
+ ,-5.011879
+ ,0.325996
+ ,2.432792
+ ,0.271362
+ ,88.333
+ ,112.24
+ ,84.072
+ ,0.00505
+ ,0.00006
+ ,0.00254
+ ,0.0033
+ ,0.00763
+ ,0.02143
+ ,0.197
+ ,0.01079
+ ,0.01342
+ ,0.01892
+ ,0.03237
+ ,0.01166
+ ,21.118
+ ,1
+ ,0.611137
+ ,0.776156
+ ,-5.24977
+ ,0.391002
+ ,2.407313
+ ,0.24974
+ ,91.904
+ ,115.871
+ ,86.292
+ ,0.0054
+ ,0.00006
+ ,0.00281
+ ,0.00336
+ ,0.00844
+ ,0.02752
+ ,0.249
+ ,0.01424
+ ,0.01641
+ ,0.02214
+ ,0.04272
+ ,0.01141
+ ,21.414
+ ,1
+ ,0.58339
+ ,0.79252
+ ,-4.960234
+ ,0.363566
+ ,2.642476
+ ,0.275931
+ ,136.926
+ ,159.866
+ ,131.276
+ ,0.00293
+ ,0.00002
+ ,0.00118
+ ,0.00153
+ ,0.00355
+ ,0.01259
+ ,0.112
+ ,0.00656
+ ,0.00717
+ ,0.0114
+ ,0.01968
+ ,0.00581
+ ,25.703
+ ,1
+ ,0.4606
+ ,0.646846
+ ,-6.547148
+ ,0.152813
+ ,2.041277
+ ,0.138512
+ ,139.173
+ ,179.139
+ ,76.556
+ ,0.0039
+ ,0.00003
+ ,0.00165
+ ,0.00208
+ ,0.00496
+ ,0.01642
+ ,0.154
+ ,0.00728
+ ,0.00932
+ ,0.01797
+ ,0.02184
+ ,0.01041
+ ,24.889
+ ,1
+ ,0.430166
+ ,0.665833
+ ,-5.660217
+ ,0.254989
+ ,2.519422
+ ,0.199889
+ ,152.845
+ ,163.305
+ ,75.836
+ ,0.00294
+ ,0.00002
+ ,0.00121
+ ,0.00149
+ ,0.00364
+ ,0.01828
+ ,0.158
+ ,0.01064
+ ,0.00972
+ ,0.01246
+ ,0.03191
+ ,0.00609
+ ,24.922
+ ,1
+ ,0.474791
+ ,0.654027
+ ,-6.105098
+ ,0.203653
+ ,2.125618
+ ,0.1701
+ ,142.167
+ ,217.455
+ ,83.159
+ ,0.00369
+ ,0.00003
+ ,0.00157
+ ,0.00203
+ ,0.00471
+ ,0.01503
+ ,0.126
+ ,0.00772
+ ,0.00888
+ ,0.01359
+ ,0.02316
+ ,0.00839
+ ,25.175
+ ,1
+ ,0.565924
+ ,0.658245
+ ,-5.340115
+ ,0.210185
+ ,2.205546
+ ,0.234589
+ ,144.188
+ ,349.259
+ ,82.764
+ ,0.00544
+ ,0.00004
+ ,0.00211
+ ,0.00292
+ ,0.00632
+ ,0.02047
+ ,0.192
+ ,0.00969
+ ,0.012
+ ,0.02074
+ ,0.02908
+ ,0.01859
+ ,22.333
+ ,1
+ ,0.56738
+ ,0.644692
+ ,-5.44004
+ ,0.239764
+ ,2.264501
+ ,0.218164
+ ,168.778
+ ,232.181
+ ,75.603
+ ,0.00718
+ ,0.00004
+ ,0.00284
+ ,0.00387
+ ,0.00853
+ ,0.03327
+ ,0.348
+ ,0.01441
+ ,0.01893
+ ,0.0343
+ ,0.04322
+ ,0.02919
+ ,20.376
+ ,1
+ ,0.631099
+ ,0.605417
+ ,-2.93107
+ ,0.434326
+ ,3.007463
+ ,0.430788
+ ,153.046
+ ,175.829
+ ,68.623
+ ,0.00742
+ ,0.00005
+ ,0.00364
+ ,0.00432
+ ,0.01092
+ ,0.05517
+ ,0.542
+ ,0.02471
+ ,0.03572
+ ,0.05767
+ ,0.07413
+ ,0.0316
+ ,17.28
+ ,1
+ ,0.665318
+ ,0.719467
+ ,-3.949079
+ ,0.35787
+ ,3.10901
+ ,0.377429
+ ,156.405
+ ,189.398
+ ,142.822
+ ,0.00768
+ ,0.00005
+ ,0.00372
+ ,0.00399
+ ,0.01116
+ ,0.03995
+ ,0.348
+ ,0.01721
+ ,0.02374
+ ,0.0431
+ ,0.05164
+ ,0.03365
+ ,17.153
+ ,1
+ ,0.649554
+ ,0.68608
+ ,-4.554466
+ ,0.340176
+ ,2.856676
+ ,0.322111
+ ,153.848
+ ,165.738
+ ,65.782
+ ,0.0084
+ ,0.00005
+ ,0.00428
+ ,0.0045
+ ,0.01285
+ ,0.0381
+ ,0.328
+ ,0.01667
+ ,0.02383
+ ,0.04055
+ ,0.05
+ ,0.03871
+ ,17.536
+ ,1
+ ,0.660125
+ ,0.704087
+ ,-4.095442
+ ,0.262564
+ ,2.73971
+ ,0.365391
+ ,153.88
+ ,172.86
+ ,78.128
+ ,0.0048
+ ,0.00003
+ ,0.00232
+ ,0.00267
+ ,0.00696
+ ,0.04137
+ ,0.37
+ ,0.02021
+ ,0.02591
+ ,0.04525
+ ,0.06062
+ ,0.01849
+ ,19.493
+ ,1
+ ,0.629017
+ ,0.698951
+ ,-5.18696
+ ,0.237622
+ ,2.557536
+ ,0.259765
+ ,167.93
+ ,193.221
+ ,79.068
+ ,0.00442
+ ,0.00003
+ ,0.0022
+ ,0.00247
+ ,0.00661
+ ,0.04351
+ ,0.377
+ ,0.02228
+ ,0.0254
+ ,0.04246
+ ,0.06685
+ ,0.0128
+ ,22.468
+ ,1
+ ,0.61906
+ ,0.679834
+ ,-4.330956
+ ,0.262384
+ ,2.916777
+ ,0.285695
+ ,173.917
+ ,192.735
+ ,86.18
+ ,0.00476
+ ,0.00003
+ ,0.00221
+ ,0.00258
+ ,0.00663
+ ,0.04192
+ ,0.364
+ ,0.02187
+ ,0.0247
+ ,0.03772
+ ,0.06562
+ ,0.0184
+ ,20.422
+ ,1
+ ,0.537264
+ ,0.686894
+ ,-5.248776
+ ,0.210279
+ ,2.547508
+ ,0.253556
+ ,163.656
+ ,200.841
+ ,76.779
+ ,0.00742
+ ,0.00005
+ ,0.0038
+ ,0.0039
+ ,0.0114
+ ,0.01659
+ ,0.164
+ ,0.00738
+ ,0.00948
+ ,0.01497
+ ,0.02214
+ ,0.01778
+ ,23.831
+ ,1
+ ,0.397937
+ ,0.732479
+ ,-5.557447
+ ,0.22089
+ ,2.692176
+ ,0.215961
+ ,104.4
+ ,206.002
+ ,77.968
+ ,0.00633
+ ,0.00006
+ ,0.00316
+ ,0.00375
+ ,0.00948
+ ,0.03767
+ ,0.381
+ ,0.01732
+ ,0.02245
+ ,0.0378
+ ,0.05197
+ ,0.02887
+ ,22.066
+ ,1
+ ,0.522746
+ ,0.737948
+ ,-5.571843
+ ,0.236853
+ ,2.846369
+ ,0.219514
+ ,171.041
+ ,208.313
+ ,75.501
+ ,0.00455
+ ,0.00003
+ ,0.0025
+ ,0.00234
+ ,0.0075
+ ,0.01966
+ ,0.186
+ ,0.00889
+ ,0.01169
+ ,0.01872
+ ,0.02666
+ ,0.01095
+ ,25.908
+ ,1
+ ,0.418622
+ ,0.720916
+ ,-6.18359
+ ,0.226278
+ ,2.589702
+ ,0.147403
+ ,146.845
+ ,208.701
+ ,81.737
+ ,0.00496
+ ,0.00003
+ ,0.0025
+ ,0.00275
+ ,0.00749
+ ,0.01919
+ ,0.198
+ ,0.00883
+ ,0.01144
+ ,0.01826
+ ,0.0265
+ ,0.01328
+ ,25.119
+ ,1
+ ,0.358773
+ ,0.726652
+ ,-6.27169
+ ,0.196102
+ ,2.314209
+ ,0.162999
+ ,155.358
+ ,227.383
+ ,80.055
+ ,0.0031
+ ,0.00002
+ ,0.00159
+ ,0.00176
+ ,0.00476
+ ,0.01718
+ ,0.161
+ ,0.00769
+ ,0.01012
+ ,0.01661
+ ,0.02307
+ ,0.00677
+ ,25.97
+ ,1
+ ,0.470478
+ ,0.676258
+ ,-7.120925
+ ,0.279789
+ ,2.241742
+ ,0.108514
+ ,162.568
+ ,198.346
+ ,77.63
+ ,0.00502
+ ,0.00003
+ ,0.0028
+ ,0.00253
+ ,0.00841
+ ,0.01791
+ ,0.168
+ ,0.00793
+ ,0.01057
+ ,0.01799
+ ,0.0238
+ ,0.0117
+ ,25.678
+ ,1
+ ,0.427785
+ ,0.723797
+ ,-6.635729
+ ,0.209866
+ ,1.957961
+ ,0.135242
+ ,197.076
+ ,206.896
+ ,192.055
+ ,0.00289
+ ,0.00001
+ ,0.00166
+ ,0.00168
+ ,0.00498
+ ,0.01098
+ ,0.097
+ ,0.00563
+ ,0.0068
+ ,0.00802
+ ,0.01689
+ ,0.00339
+ ,26.775
+ ,0
+ ,0.422229
+ ,0.741367
+ ,-7.3483
+ ,0.177551
+ ,1.743867
+ ,0.085569
+ ,199.228
+ ,209.512
+ ,192.091
+ ,0.00241
+ ,0.00001
+ ,0.00134
+ ,0.00138
+ ,0.00402
+ ,0.01015
+ ,0.089
+ ,0.00504
+ ,0.00641
+ ,0.00762
+ ,0.01513
+ ,0.00167
+ ,30.94
+ ,0
+ ,0.432439
+ ,0.742055
+ ,-7.682587
+ ,0.173319
+ ,2.103106
+ ,0.068501
+ ,198.383
+ ,215.203
+ ,193.104
+ ,0.00212
+ ,0.00001
+ ,0.00113
+ ,0.00135
+ ,0.00339
+ ,0.01263
+ ,0.111
+ ,0.0064
+ ,0.00825
+ ,0.00951
+ ,0.01919
+ ,0.00119
+ ,30.775
+ ,0
+ ,0.465946
+ ,0.738703
+ ,-7.067931
+ ,0.175181
+ ,1.512275
+ ,0.09632
+ ,202.266
+ ,211.604
+ ,197.079
+ ,0.0018
+ ,0.000009
+ ,0.00093
+ ,0.00107
+ ,0.00278
+ ,0.00954
+ ,0.085
+ ,0.00469
+ ,0.00606
+ ,0.00719
+ ,0.01407
+ ,0.00072
+ ,32.684
+ ,0
+ ,0.368535
+ ,0.742133
+ ,-7.695734
+ ,0.17854
+ ,1.544609
+ ,0.056141
+ ,203.184
+ ,211.526
+ ,196.16
+ ,0.00178
+ ,0.000009
+ ,0.00094
+ ,0.00106
+ ,0.00283
+ ,0.00958
+ ,0.085
+ ,0.00468
+ ,0.0061
+ ,0.00726
+ ,0.01403
+ ,0.00065
+ ,33.047
+ ,0
+ ,0.340068
+ ,0.741899
+ ,-7.964984
+ ,0.163519
+ ,1.423287
+ ,0.044539
+ ,201.464
+ ,210.565
+ ,195.708
+ ,0.00198
+ ,0.00001
+ ,0.00105
+ ,0.00115
+ ,0.00314
+ ,0.01194
+ ,0.107
+ ,0.00586
+ ,0.0076
+ ,0.00957
+ ,0.01758
+ ,0.00135
+ ,31.732
+ ,0
+ ,0.344252
+ ,0.742737
+ ,-7.777685
+ ,0.170183
+ ,2.447064
+ ,0.05761
+ ,177.876
+ ,192.921
+ ,168.013
+ ,0.00411
+ ,0.00002
+ ,0.00233
+ ,0.00241
+ ,0.007
+ ,0.02126
+ ,0.189
+ ,0.01154
+ ,0.01347
+ ,0.01612
+ ,0.03463
+ ,0.00586
+ ,23.216
+ ,1
+ ,0.360148
+ ,0.778834
+ ,-6.149653
+ ,0.218037
+ ,2.477082
+ ,0.165827
+ ,176.17
+ ,185.604
+ ,163.564
+ ,0.00369
+ ,0.00002
+ ,0.00205
+ ,0.00218
+ ,0.00616
+ ,0.01851
+ ,0.168
+ ,0.00938
+ ,0.0116
+ ,0.01491
+ ,0.02814
+ ,0.0034
+ ,24.951
+ ,1
+ ,0.341435
+ ,0.783626
+ ,-6.006414
+ ,0.196371
+ ,2.536527
+ ,0.173218
+ ,180.198
+ ,201.249
+ ,175.456
+ ,0.00284
+ ,0.00002
+ ,0.00153
+ ,0.00166
+ ,0.00459
+ ,0.01444
+ ,0.131
+ ,0.00726
+ ,0.00885
+ ,0.0119
+ ,0.02177
+ ,0.00231
+ ,26.738
+ ,1
+ ,0.403884
+ ,0.766209
+ ,-6.452058
+ ,0.212294
+ ,2.269398
+ ,0.141929
+ ,187.733
+ ,202.324
+ ,173.015
+ ,0.00316
+ ,0.00002
+ ,0.00168
+ ,0.00182
+ ,0.00504
+ ,0.01663
+ ,0.151
+ ,0.00829
+ ,0.01003
+ ,0.01366
+ ,0.02488
+ ,0.00265
+ ,26.31
+ ,1
+ ,0.396793
+ ,0.758324
+ ,-6.006647
+ ,0.266892
+ ,2.382544
+ ,0.160691
+ ,186.163
+ ,197.724
+ ,177.584
+ ,0.00298
+ ,0.00002
+ ,0.00165
+ ,0.00175
+ ,0.00496
+ ,0.01495
+ ,0.135
+ ,0.00774
+ ,0.00941
+ ,0.01233
+ ,0.02321
+ ,0.00231
+ ,26.822
+ ,1
+ ,0.32648
+ ,0.765623
+ ,-6.647379
+ ,0.201095
+ ,2.374073
+ ,0.130554
+ ,184.055
+ ,196.537
+ ,166.977
+ ,0.00258
+ ,0.00001
+ ,0.00134
+ ,0.00147
+ ,0.00403
+ ,0.01463
+ ,0.132
+ ,0.00742
+ ,0.00901
+ ,0.01234
+ ,0.02226
+ ,0.00257
+ ,26.453
+ ,1
+ ,0.306443
+ ,0.759203
+ ,-7.044105
+ ,0.063412
+ ,2.361532
+ ,0.11573
+ ,237.226
+ ,247.326
+ ,225.227
+ ,0.00298
+ ,0.00001
+ ,0.00169
+ ,0.00182
+ ,0.00507
+ ,0.01752
+ ,0.164
+ ,0.01035
+ ,0.01024
+ ,0.01133
+ ,0.03104
+ ,0.0074
+ ,22.736
+ ,0
+ ,0.305062
+ ,0.654172
+ ,-7.31055
+ ,0.098648
+ ,2.416838
+ ,0.095032
+ ,241.404
+ ,248.834
+ ,232.483
+ ,0.00281
+ ,0.00001
+ ,0.00157
+ ,0.00173
+ ,0.0047
+ ,0.0176
+ ,0.154
+ ,0.01006
+ ,0.01038
+ ,0.01251
+ ,0.03017
+ ,0.00675
+ ,23.145
+ ,0
+ ,0.457702
+ ,0.634267
+ ,-6.793547
+ ,0.158266
+ ,2.256699
+ ,0.117399
+ ,243.439
+ ,250.912
+ ,232.435
+ ,0.0021
+ ,0.000009
+ ,0.00109
+ ,0.00137
+ ,0.00327
+ ,0.01419
+ ,0.126
+ ,0.00777
+ ,0.00898
+ ,0.01033
+ ,0.0233
+ ,0.00454
+ ,25.368
+ ,0
+ ,0.438296
+ ,0.635285
+ ,-7.057869
+ ,0.091608
+ ,2.330716
+ ,0.09147
+ ,242.852
+ ,255.034
+ ,227.911
+ ,0.00225
+ ,0.000009
+ ,0.00117
+ ,0.00139
+ ,0.0035
+ ,0.01494
+ ,0.134
+ ,0.00847
+ ,0.00879
+ ,0.01014
+ ,0.02542
+ ,0.00476
+ ,25.032
+ ,0
+ ,0.431285
+ ,0.638928
+ ,-6.99582
+ ,0.102083
+ ,2.3658
+ ,0.102706
+ ,245.51
+ ,262.09
+ ,231.848
+ ,0.00235
+ ,0.00001
+ ,0.00127
+ ,0.00148
+ ,0.0038
+ ,0.01608
+ ,0.141
+ ,0.00906
+ ,0.00977
+ ,0.01149
+ ,0.02719
+ ,0.00476
+ ,24.602
+ ,0
+ ,0.467489
+ ,0.631653
+ ,-7.156076
+ ,0.127642
+ ,2.392122
+ ,0.097336
+ ,252.455
+ ,261.487
+ ,182.786
+ ,0.00185
+ ,0.000007
+ ,0.00092
+ ,0.00113
+ ,0.00276
+ ,0.01152
+ ,0.103
+ ,0.00614
+ ,0.0073
+ ,0.0086
+ ,0.01841
+ ,0.00432
+ ,26.805
+ ,0
+ ,0.610367
+ ,0.635204
+ ,-7.31951
+ ,0.200873
+ ,2.028612
+ ,0.086398
+ ,122.188
+ ,128.611
+ ,115.765
+ ,0.00524
+ ,0.00004
+ ,0.00169
+ ,0.00203
+ ,0.00507
+ ,0.01613
+ ,0.143
+ ,0.00855
+ ,0.00776
+ ,0.01433
+ ,0.02566
+ ,0.00839
+ ,23.162
+ ,0
+ ,0.579597
+ ,0.733659
+ ,-6.439398
+ ,0.266392
+ ,2.079922
+ ,0.133867
+ ,122.964
+ ,130.049
+ ,114.676
+ ,0.00428
+ ,0.00003
+ ,0.00124
+ ,0.00155
+ ,0.00373
+ ,0.01681
+ ,0.154
+ ,0.0093
+ ,0.00802
+ ,0.014
+ ,0.02789
+ ,0.00462
+ ,24.971
+ ,0
+ ,0.538688
+ ,0.754073
+ ,-6.482096
+ ,0.264967
+ ,2.054419
+ ,0.128872
+ ,124.445
+ ,135.069
+ ,117.495
+ ,0.00431
+ ,0.00003
+ ,0.00141
+ ,0.00167
+ ,0.00422
+ ,0.02184
+ ,0.197
+ ,0.01241
+ ,0.01024
+ ,0.01685
+ ,0.03724
+ ,0.00479
+ ,25.135
+ ,0
+ ,0.553134
+ ,0.775933
+ ,-6.650471
+ ,0.254498
+ ,1.840198
+ ,0.103561
+ ,126.344
+ ,134.231
+ ,112.773
+ ,0.00448
+ ,0.00004
+ ,0.00131
+ ,0.00169
+ ,0.00393
+ ,0.02033
+ ,0.185
+ ,0.01143
+ ,0.00959
+ ,0.01614
+ ,0.03429
+ ,0.00474
+ ,25.03
+ ,0
+ ,0.507504
+ ,0.760361
+ ,-6.689151
+ ,0.291954
+ ,2.431854
+ ,0.105993
+ ,128.001
+ ,138.052
+ ,122.08
+ ,0.00436
+ ,0.00003
+ ,0.00137
+ ,0.00166
+ ,0.00411
+ ,0.02297
+ ,0.21
+ ,0.01323
+ ,0.01072
+ ,0.01677
+ ,0.03969
+ ,0.00481
+ ,24.692
+ ,0
+ ,0.459766
+ ,0.766204
+ ,-7.072419
+ ,0.220434
+ ,1.972297
+ ,0.119308
+ ,129.336
+ ,139.867
+ ,118.604
+ ,0.0049
+ ,0.00004
+ ,0.00165
+ ,0.00183
+ ,0.00495
+ ,0.02498
+ ,0.228
+ ,0.01396
+ ,0.01219
+ ,0.01947
+ ,0.04188
+ ,0.00484
+ ,25.429
+ ,0
+ ,0.420383
+ ,0.785714
+ ,-6.836811
+ ,0.269866
+ ,2.223719
+ ,0.147491
+ ,108.807
+ ,134.656
+ ,102.874
+ ,0.00761
+ ,0.00007
+ ,0.00349
+ ,0.00486
+ ,0.01046
+ ,0.02719
+ ,0.255
+ ,0.01483
+ ,0.01609
+ ,0.02067
+ ,0.0445
+ ,0.01036
+ ,21.028
+ ,1
+ ,0.536009
+ ,0.819032
+ ,-4.649573
+ ,0.205558
+ ,1.986899
+ ,0.3167
+ ,109.86
+ ,126.358
+ ,104.437
+ ,0.00874
+ ,0.00008
+ ,0.00398
+ ,0.00539
+ ,0.01193
+ ,0.03209
+ ,0.307
+ ,0.01789
+ ,0.01992
+ ,0.02454
+ ,0.05368
+ ,0.0118
+ ,20.767
+ ,1
+ ,0.558586
+ ,0.811843
+ ,-4.333543
+ ,0.221727
+ ,2.014606
+ ,0.344834
+ ,110.417
+ ,131.067
+ ,103.37
+ ,0.00784
+ ,0.00007
+ ,0.00352
+ ,0.00514
+ ,0.01056
+ ,0.03715
+ ,0.334
+ ,0.02032
+ ,0.02302
+ ,0.02802
+ ,0.06097
+ ,0.00969
+ ,21.422
+ ,1
+ ,0.541781
+ ,0.821364
+ ,-4.438453
+ ,0.238298
+ ,1.92294
+ ,0.335041
+ ,117.274
+ ,129.916
+ ,110.402
+ ,0.00752
+ ,0.00006
+ ,0.00299
+ ,0.00469
+ ,0.00898
+ ,0.02293
+ ,0.221
+ ,0.01189
+ ,0.01459
+ ,0.01948
+ ,0.03568
+ ,0.00681
+ ,22.817
+ ,1
+ ,0.530529
+ ,0.817756
+ ,-4.60826
+ ,0.290024
+ ,2.021591
+ ,0.314464
+ ,116.879
+ ,131.897
+ ,108.153
+ ,0.00788
+ ,0.00007
+ ,0.00334
+ ,0.00493
+ ,0.01003
+ ,0.02645
+ ,0.265
+ ,0.01394
+ ,0.01625
+ ,0.02137
+ ,0.04183
+ ,0.00786
+ ,22.603
+ ,1
+ ,0.540049
+ ,0.813432
+ ,-4.476755
+ ,0.262633
+ ,1.827012
+ ,0.326197
+ ,114.847
+ ,271.314
+ ,104.68
+ ,0.00867
+ ,0.00008
+ ,0.00373
+ ,0.0052
+ ,0.0112
+ ,0.03225
+ ,0.35
+ ,0.01805
+ ,0.01974
+ ,0.02519
+ ,0.05414
+ ,0.01143
+ ,21.66
+ ,1
+ ,0.547975
+ ,0.817396
+ ,-4.609161
+ ,0.221711
+ ,1.831691
+ ,0.316395
+ ,209.144
+ ,237.494
+ ,109.379
+ ,0.00282
+ ,0.00001
+ ,0.00147
+ ,0.00152
+ ,0.00442
+ ,0.01861
+ ,0.17
+ ,0.00975
+ ,0.01258
+ ,0.01382
+ ,0.02925
+ ,0.00871
+ ,25.554
+ ,0
+ ,0.341788
+ ,0.678874
+ ,-7.040508
+ ,0.066994
+ ,2.460791
+ ,0.101516
+ ,223.365
+ ,238.987
+ ,98.664
+ ,0.00264
+ ,0.00001
+ ,0.00154
+ ,0.00151
+ ,0.00461
+ ,0.01906
+ ,0.165
+ ,0.01013
+ ,0.01296
+ ,0.0134
+ ,0.03039
+ ,0.00301
+ ,26.138
+ ,0
+ ,0.447979
+ ,0.686264
+ ,-7.293801
+ ,0.086372
+ ,2.32156
+ ,0.098555
+ ,222.236
+ ,231.345
+ ,205.495
+ ,0.00266
+ ,0.00001
+ ,0.00152
+ ,0.00144
+ ,0.00457
+ ,0.01643
+ ,0.145
+ ,0.00867
+ ,0.01108
+ ,0.012
+ ,0.02602
+ ,0.0034
+ ,25.856
+ ,0
+ ,0.364867
+ ,0.694399
+ ,-6.966321
+ ,0.095882
+ ,2.278687
+ ,0.103224
+ ,228.832
+ ,234.619
+ ,223.634
+ ,0.00296
+ ,0.00001
+ ,0.00175
+ ,0.00155
+ ,0.00526
+ ,0.01644
+ ,0.145
+ ,0.00882
+ ,0.01075
+ ,0.01179
+ ,0.02647
+ ,0.00351
+ ,25.964
+ ,0
+ ,0.25657
+ ,0.683296
+ ,-7.24562
+ ,0.018689
+ ,2.498224
+ ,0.093534
+ ,229.401
+ ,252.221
+ ,221.156
+ ,0.00205
+ ,0.000009
+ ,0.00114
+ ,0.00113
+ ,0.00342
+ ,0.01457
+ ,0.129
+ ,0.00769
+ ,0.00957
+ ,0.01016
+ ,0.02308
+ ,0.003
+ ,26.415
+ ,0
+ ,0.27685
+ ,0.673636
+ ,-7.496264
+ ,0.056844
+ ,2.003032
+ ,0.073581
+ ,228.969
+ ,239.541
+ ,113.201
+ ,0.00238
+ ,0.00001
+ ,0.00136
+ ,0.0014
+ ,0.00408
+ ,0.01745
+ ,0.154
+ ,0.00942
+ ,0.0116
+ ,0.01234
+ ,0.02827
+ ,0.0042
+ ,24.547
+ ,0
+ ,0.305429
+ ,0.681811
+ ,-7.314237
+ ,0.006274
+ ,2.118596
+ ,0.091546
+ ,140.341
+ ,159.774
+ ,67.021
+ ,0.00817
+ ,0.00006
+ ,0.0043
+ ,0.0044
+ ,0.01289
+ ,0.03198
+ ,0.313
+ ,0.0183
+ ,0.0181
+ ,0.02428
+ ,0.0549
+ ,0.02183
+ ,19.56
+ ,1
+ ,0.460139
+ ,0.720908
+ ,-5.409423
+ ,0.22685
+ ,2.359973
+ ,0.226156
+ ,136.969
+ ,166.607
+ ,66.004
+ ,0.00923
+ ,0.00007
+ ,0.00507
+ ,0.00463
+ ,0.0152
+ ,0.03111
+ ,0.308
+ ,0.01638
+ ,0.01759
+ ,0.02603
+ ,0.04914
+ ,0.02659
+ ,19.979
+ ,1
+ ,0.498133
+ ,0.729067
+ ,-5.324574
+ ,0.20566
+ ,2.291558
+ ,0.226247
+ ,143.533
+ ,162.215
+ ,65.809
+ ,0.01101
+ ,0.00008
+ ,0.00647
+ ,0.00467
+ ,0.01941
+ ,0.05384
+ ,0.478
+ ,0.03152
+ ,0.02422
+ ,0.03392
+ ,0.09455
+ ,0.04882
+ ,20.338
+ ,1
+ ,0.513237
+ ,0.731444
+ ,-5.86975
+ ,0.151814
+ ,2.118496
+ ,0.18558
+ ,148.09
+ ,162.824
+ ,67.343
+ ,0.00762
+ ,0.00005
+ ,0.00467
+ ,0.00354
+ ,0.014
+ ,0.05428
+ ,0.497
+ ,0.03357
+ ,0.02494
+ ,0.03635
+ ,0.1007
+ ,0.02431
+ ,21.718
+ ,1
+ ,0.487407
+ ,0.727313
+ ,-6.261141
+ ,0.120956
+ ,2.137075
+ ,0.141958
+ ,142.729
+ ,162.408
+ ,65.476
+ ,0.00831
+ ,0.00006
+ ,0.00469
+ ,0.00419
+ ,0.01407
+ ,0.03485
+ ,0.365
+ ,0.01868
+ ,0.01906
+ ,0.02949
+ ,0.05605
+ ,0.02599
+ ,20.264
+ ,1
+ ,0.489345
+ ,0.730387
+ ,-5.720868
+ ,0.15883
+ ,2.277927
+ ,0.180828
+ ,136.358
+ ,176.595
+ ,65.75
+ ,0.00971
+ ,0.00007
+ ,0.00534
+ ,0.00478
+ ,0.01601
+ ,0.04978
+ ,0.483
+ ,0.02749
+ ,0.02466
+ ,0.03736
+ ,0.08247
+ ,0.03361
+ ,18.57
+ ,1
+ ,0.543299
+ ,0.733232
+ ,-5.207985
+ ,0.224852
+ ,2.642276
+ ,0.242981
+ ,120.08
+ ,139.71
+ ,111.208
+ ,0.00405
+ ,0.00003
+ ,0.0018
+ ,0.0022
+ ,0.0054
+ ,0.01706
+ ,0.152
+ ,0.00974
+ ,0.00925
+ ,0.01345
+ ,0.02921
+ ,0.00442
+ ,25.742
+ ,1
+ ,0.495954
+ ,0.762959
+ ,-5.79182
+ ,0.329066
+ ,2.205024
+ ,0.18818
+ ,112.014
+ ,588.518
+ ,107.024
+ ,0.00533
+ ,0.00005
+ ,0.00268
+ ,0.00329
+ ,0.00805
+ ,0.02448
+ ,0.226
+ ,0.01373
+ ,0.01375
+ ,0.01956
+ ,0.0412
+ ,0.00623
+ ,24.178
+ ,1
+ ,0.509127
+ ,0.789532
+ ,-5.389129
+ ,0.306636
+ ,1.928708
+ ,0.225461
+ ,110.793
+ ,128.101
+ ,107.316
+ ,0.00494
+ ,0.00004
+ ,0.0026
+ ,0.00283
+ ,0.0078
+ ,0.02442
+ ,0.216
+ ,0.01432
+ ,0.01325
+ ,0.01831
+ ,0.04295
+ ,0.00479
+ ,25.438
+ ,1
+ ,0.437031
+ ,0.815908
+ ,-5.31336
+ ,0.201861
+ ,2.225815
+ ,0.244512
+ ,110.707
+ ,122.611
+ ,105.007
+ ,0.00516
+ ,0.00005
+ ,0.00277
+ ,0.00289
+ ,0.00831
+ ,0.02215
+ ,0.206
+ ,0.01284
+ ,0.01219
+ ,0.01715
+ ,0.03851
+ ,0.00472
+ ,25.197
+ ,1
+ ,0.463514
+ ,0.807217
+ ,-5.477592
+ ,0.315074
+ ,1.862092
+ ,0.228624
+ ,112.876
+ ,148.826
+ ,106.981
+ ,0.005
+ ,0.00004
+ ,0.0027
+ ,0.00289
+ ,0.0081
+ ,0.03999
+ ,0.35
+ ,0.02413
+ ,0.02231
+ ,0.02704
+ ,0.07238
+ ,0.00905
+ ,23.37
+ ,1
+ ,0.489538
+ ,0.789977
+ ,-5.775966
+ ,0.341169
+ ,2.007923
+ ,0.193918
+ ,110.568
+ ,125.394
+ ,106.821
+ ,0.00462
+ ,0.00004
+ ,0.00226
+ ,0.0028
+ ,0.00677
+ ,0.02199
+ ,0.197
+ ,0.01284
+ ,0.01199
+ ,0.01636
+ ,0.03852
+ ,0.0042
+ ,25.82
+ ,1
+ ,0.429484
+ ,0.81634
+ ,-5.391029
+ ,0.250572
+ ,1.777901
+ ,0.232744
+ ,95.385
+ ,102.145
+ ,90.264
+ ,0.00608
+ ,0.00006
+ ,0.00331
+ ,0.00332
+ ,0.00994
+ ,0.03202
+ ,0.263
+ ,0.01803
+ ,0.01886
+ ,0.02455
+ ,0.05408
+ ,0.01062
+ ,21.875
+ ,1
+ ,0.644954
+ ,0.779612
+ ,-5.115212
+ ,0.249494
+ ,2.017753
+ ,0.260015
+ ,100.77
+ ,115.697
+ ,85.545
+ ,0.01038
+ ,0.0001
+ ,0.00622
+ ,0.00576
+ ,0.01865
+ ,0.03121
+ ,0.361
+ ,0.01773
+ ,0.01783
+ ,0.02139
+ ,0.0532
+ ,0.0222
+ ,19.2
+ ,1
+ ,0.594387
+ ,0.790117
+ ,-4.913885
+ ,0.265699
+ ,2.398422
+ ,0.277948
+ ,96.106
+ ,108.664
+ ,84.51
+ ,0.00694
+ ,0.00007
+ ,0.00389
+ ,0.00415
+ ,0.01168
+ ,0.04024
+ ,0.364
+ ,0.02266
+ ,0.02451
+ ,0.02876
+ ,0.06799
+ ,0.01823
+ ,19.055
+ ,1
+ ,0.544805
+ ,0.770466
+ ,-4.441519
+ ,0.155097
+ ,2.645959
+ ,0.327978
+ ,95.605
+ ,107.715
+ ,87.549
+ ,0.00702
+ ,0.00007
+ ,0.00428
+ ,0.00371
+ ,0.01283
+ ,0.03156
+ ,0.296
+ ,0.01792
+ ,0.01841
+ ,0.0219
+ ,0.05377
+ ,0.01825
+ ,19.659
+ ,1
+ ,0.576084
+ ,0.778747
+ ,-5.132032
+ ,0.210458
+ ,2.232576
+ ,0.260633
+ ,100.96
+ ,110.019
+ ,95.628
+ ,0.00606
+ ,0.00006
+ ,0.00351
+ ,0.00348
+ ,0.01053
+ ,0.02427
+ ,0.216
+ ,0.01371
+ ,0.01421
+ ,0.01751
+ ,0.04114
+ ,0.01237
+ ,20.536
+ ,1
+ ,0.55461
+ ,0.787896
+ ,-5.022288
+ ,0.146948
+ ,2.428306
+ ,0.264666
+ ,98.804
+ ,102.305
+ ,87.804
+ ,0.00432
+ ,0.00004
+ ,0.00247
+ ,0.00258
+ ,0.00742
+ ,0.02223
+ ,0.202
+ ,0.01277
+ ,0.01343
+ ,0.01552
+ ,0.03831
+ ,0.00882
+ ,22.244
+ ,1
+ ,0.576644
+ ,0.772416
+ ,-6.025367
+ ,0.078202
+ ,2.053601
+ ,0.177275
+ ,176.858
+ ,205.56
+ ,75.344
+ ,0.00747
+ ,0.00004
+ ,0.00418
+ ,0.0042
+ ,0.01254
+ ,0.04795
+ ,0.435
+ ,0.02679
+ ,0.03022
+ ,0.0351
+ ,0.08037
+ ,0.0547
+ ,13.893
+ ,1
+ ,0.556494
+ ,0.729586
+ ,-5.288912
+ ,0.343073
+ ,3.099301
+ ,0.242119
+ ,180.978
+ ,200.125
+ ,155.495
+ ,0.00406
+ ,0.00002
+ ,0.0022
+ ,0.00244
+ ,0.00659
+ ,0.03852
+ ,0.331
+ ,0.02107
+ ,0.02493
+ ,0.02877
+ ,0.06321
+ ,0.02782
+ ,16.176
+ ,1
+ ,0.583574
+ ,0.727747
+ ,-5.657899
+ ,0.315903
+ ,3.098256
+ ,0.200423
+ ,178.222
+ ,202.45
+ ,141.047
+ ,0.00321
+ ,0.00002
+ ,0.00163
+ ,0.00194
+ ,0.00488
+ ,0.03759
+ ,0.327
+ ,0.02073
+ ,0.02415
+ ,0.02784
+ ,0.06219
+ ,0.03151
+ ,15.924
+ ,1
+ ,0.598714
+ ,0.712199
+ ,-6.366916
+ ,0.335753
+ ,2.654271
+ ,0.144614
+ ,176.281
+ ,227.381
+ ,125.61
+ ,0.0052
+ ,0.00003
+ ,0.00287
+ ,0.00312
+ ,0.00862
+ ,0.06511
+ ,0.58
+ ,0.03671
+ ,0.04159
+ ,0.04683
+ ,0.11012
+ ,0.04824
+ ,13.922
+ ,1
+ ,0.602874
+ ,0.740837
+ ,-5.515071
+ ,0.299549
+ ,3.13655
+ ,0.220968
+ ,173.898
+ ,211.35
+ ,74.677
+ ,0.00448
+ ,0.00003
+ ,0.00237
+ ,0.00254
+ ,0.0071
+ ,0.06727
+ ,0.65
+ ,0.03788
+ ,0.04254
+ ,0.04802
+ ,0.11363
+ ,0.04214
+ ,14.739
+ ,1
+ ,0.599371
+ ,0.743937
+ ,-5.783272
+ ,0.299793
+ ,3.007096
+ ,0.194052
+ ,179.711
+ ,225.93
+ ,144.878
+ ,0.00709
+ ,0.00004
+ ,0.00391
+ ,0.00419
+ ,0.01172
+ ,0.04313
+ ,0.442
+ ,0.02297
+ ,0.02768
+ ,0.03455
+ ,0.06892
+ ,0.07223
+ ,11.866
+ ,1
+ ,0.590951
+ ,0.745526
+ ,-4.379411
+ ,0.375531
+ ,3.671155
+ ,0.332086
+ ,166.605
+ ,206.008
+ ,78.032
+ ,0.00742
+ ,0.00004
+ ,0.00387
+ ,0.00453
+ ,0.01161
+ ,0.0664
+ ,0.634
+ ,0.0365
+ ,0.04282
+ ,0.05114
+ ,0.10949
+ ,0.08725
+ ,11.744
+ ,1
+ ,0.65341
+ ,0.733165
+ ,-4.508984
+ ,0.389232
+ ,3.317586
+ ,0.301952
+ ,151.955
+ ,163.335
+ ,147.226
+ ,0.00419
+ ,0.00003
+ ,0.00224
+ ,0.00227
+ ,0.00672
+ ,0.07959
+ ,0.772
+ ,0.04421
+ ,0.04962
+ ,0.0569
+ ,0.13262
+ ,0.01658
+ ,19.664
+ ,1
+ ,0.501037
+ ,0.71436
+ ,-6.411497
+ ,0.207156
+ ,2.344876
+ ,0.13412
+ ,148.272
+ ,164.989
+ ,142.299
+ ,0.00459
+ ,0.00003
+ ,0.0025
+ ,0.00256
+ ,0.0075
+ ,0.0419
+ ,0.383
+ ,0.02383
+ ,0.02521
+ ,0.03051
+ ,0.0715
+ ,0.01914
+ ,18.78
+ ,1
+ ,0.454444
+ ,0.734504
+ ,-5.952058
+ ,0.08784
+ ,2.344336
+ ,0.186489
+ ,152.125
+ ,161.469
+ ,76.596
+ ,0.00382
+ ,0.00003
+ ,0.00191
+ ,0.00226
+ ,0.00574
+ ,0.05925
+ ,0.637
+ ,0.03341
+ ,0.03794
+ ,0.04398
+ ,0.10024
+ ,0.01211
+ ,20.969
+ ,1
+ ,0.447456
+ ,0.69779
+ ,-6.152551
+ ,0.17352
+ ,2.080121
+ ,0.160809
+ ,157.821
+ ,172.975
+ ,68.401
+ ,0.00358
+ ,0.00002
+ ,0.00196
+ ,0.00196
+ ,0.00587
+ ,0.03716
+ ,0.307
+ ,0.02062
+ ,0.02321
+ ,0.02764
+ ,0.06185
+ ,0.0085
+ ,22.219
+ ,1
+ ,0.50238
+ ,0.71217
+ ,-6.251425
+ ,0.188056
+ ,2.143851
+ ,0.160812
+ ,157.447
+ ,163.267
+ ,149.605
+ ,0.00369
+ ,0.00002
+ ,0.00201
+ ,0.00197
+ ,0.00602
+ ,0.03272
+ ,0.283
+ ,0.01813
+ ,0.01909
+ ,0.02571
+ ,0.05439
+ ,0.01018
+ ,21.693
+ ,1
+ ,0.447285
+ ,0.705658
+ ,-6.247076
+ ,0.180528
+ ,2.344348
+ ,0.164916
+ ,159.116
+ ,168.913
+ ,144.811
+ ,0.00342
+ ,0.00002
+ ,0.00178
+ ,0.00184
+ ,0.00535
+ ,0.03381
+ ,0.307
+ ,0.01806
+ ,0.02024
+ ,0.02809
+ ,0.05417
+ ,0.00852
+ ,22.663
+ ,1
+ ,0.366329
+ ,0.693429
+ ,-6.41744
+ ,0.194627
+ ,2.473239
+ ,0.151709
+ ,125.036
+ ,143.946
+ ,116.187
+ ,0.0128
+ ,0.0001
+ ,0.00743
+ ,0.00623
+ ,0.02228
+ ,0.03886
+ ,0.342
+ ,0.02135
+ ,0.02174
+ ,0.03088
+ ,0.06406
+ ,0.08151
+ ,15.338
+ ,1
+ ,0.629574
+ ,0.714485
+ ,-4.020042
+ ,0.265315
+ ,2.671825
+ ,0.340623
+ ,125.791
+ ,140.557
+ ,96.206
+ ,0.01378
+ ,0.00011
+ ,0.00826
+ ,0.00655
+ ,0.02478
+ ,0.04689
+ ,0.422
+ ,0.02542
+ ,0.0263
+ ,0.03908
+ ,0.07625
+ ,0.10323
+ ,15.433
+ ,1
+ ,0.57101
+ ,0.690892
+ ,-5.159169
+ ,0.202146
+ ,2.441612
+ ,0.260375
+ ,126.512
+ ,141.756
+ ,99.77
+ ,0.01936
+ ,0.00015
+ ,0.01159
+ ,0.0099
+ ,0.03476
+ ,0.06734
+ ,0.659
+ ,0.03611
+ ,0.03963
+ ,0.05783
+ ,0.10833
+ ,0.16744
+ ,12.435
+ ,1
+ ,0.638545
+ ,0.674953
+ ,-3.760348
+ ,0.242861
+ ,2.634633
+ ,0.378483
+ ,125.641
+ ,141.068
+ ,116.346
+ ,0.03316
+ ,0.00026
+ ,0.02144
+ ,0.01522
+ ,0.06433
+ ,0.09178
+ ,0.891
+ ,0.05358
+ ,0.04791
+ ,0.06196
+ ,0.16074
+ ,0.31482
+ ,8.867
+ ,1
+ ,0.671299
+ ,0.656846
+ ,-3.700544
+ ,0.260481
+ ,2.991063
+ ,0.370961
+ ,128.451
+ ,150.449
+ ,75.632
+ ,0.01551
+ ,0.00012
+ ,0.00905
+ ,0.00909
+ ,0.02716
+ ,0.0617
+ ,0.584
+ ,0.03223
+ ,0.03672
+ ,0.05174
+ ,0.09669
+ ,0.11843
+ ,15.06
+ ,1
+ ,0.639808
+ ,0.643327
+ ,-4.20273
+ ,0.310163
+ ,2.638279
+ ,0.356881
+ ,139.224
+ ,586.567
+ ,66.157
+ ,0.03011
+ ,0.00022
+ ,0.01854
+ ,0.01628
+ ,0.05563
+ ,0.09419
+ ,0.93
+ ,0.05551
+ ,0.05005
+ ,0.06023
+ ,0.16654
+ ,0.2593
+ ,10.489
+ ,1
+ ,0.596362
+ ,0.641418
+ ,-3.269487
+ ,0.270641
+ ,2.690917
+ ,0.444774
+ ,150.258
+ ,154.609
+ ,75.349
+ ,0.00248
+ ,0.00002
+ ,0.00105
+ ,0.00136
+ ,0.00315
+ ,0.01131
+ ,0.107
+ ,0.00522
+ ,0.00659
+ ,0.01009
+ ,0.01567
+ ,0.00495
+ ,26.759
+ ,1
+ ,0.296888
+ ,0.722356
+ ,-6.878393
+ ,0.089267
+ ,2.004055
+ ,0.113942
+ ,154.003
+ ,160.267
+ ,128.621
+ ,0.00183
+ ,0.00001
+ ,0.00076
+ ,0.001
+ ,0.00229
+ ,0.0103
+ ,0.094
+ ,0.00469
+ ,0.00582
+ ,0.00871
+ ,0.01406
+ ,0.00243
+ ,28.409
+ ,1
+ ,0.263654
+ ,0.691483
+ ,-7.111576
+ ,0.14478
+ ,2.065477
+ ,0.093193
+ ,149.689
+ ,160.368
+ ,133.608
+ ,0.00257
+ ,0.00002
+ ,0.00116
+ ,0.00134
+ ,0.00349
+ ,0.01346
+ ,0.126
+ ,0.0066
+ ,0.00818
+ ,0.01059
+ ,0.01979
+ ,0.00578
+ ,27.421
+ ,1
+ ,0.365488
+ ,0.719974
+ ,-6.997403
+ ,0.210279
+ ,1.994387
+ ,0.112878
+ ,155.078
+ ,163.736
+ ,144.148
+ ,0.00168
+ ,0.00001
+ ,0.00068
+ ,0.00092
+ ,0.00204
+ ,0.01064
+ ,0.097
+ ,0.00522
+ ,0.00632
+ ,0.00928
+ ,0.01567
+ ,0.00233
+ ,29.746
+ ,1
+ ,0.334171
+ ,0.67793
+ ,-6.981201
+ ,0.18455
+ ,2.129924
+ ,0.106802
+ ,151.884
+ ,157.765
+ ,133.751
+ ,0.00258
+ ,0.00002
+ ,0.00115
+ ,0.00122
+ ,0.00346
+ ,0.0145
+ ,0.137
+ ,0.00633
+ ,0.00788
+ ,0.01267
+ ,0.01898
+ ,0.00659
+ ,26.833
+ ,1
+ ,0.393563
+ ,0.700246
+ ,-6.600023
+ ,0.249172
+ ,2.499148
+ ,0.105306
+ ,151.989
+ ,157.339
+ ,132.857
+ ,0.00174
+ ,0.00001
+ ,0.00075
+ ,0.00096
+ ,0.00225
+ ,0.01024
+ ,0.093
+ ,0.00455
+ ,0.00576
+ ,0.00993
+ ,0.01364
+ ,0.00238
+ ,29.928
+ ,1
+ ,0.311369
+ ,0.676066
+ ,-6.739151
+ ,0.160686
+ ,2.296873
+ ,0.11513
+ ,193.03
+ ,208.9
+ ,80.297
+ ,0.00766
+ ,0.00004
+ ,0.0045
+ ,0.00389
+ ,0.01351
+ ,0.03044
+ ,0.275
+ ,0.01771
+ ,0.01815
+ ,0.02084
+ ,0.05312
+ ,0.00947
+ ,21.934
+ ,1
+ ,0.497554
+ ,0.740539
+ ,-5.845099
+ ,0.278679
+ ,2.608749
+ ,0.185668
+ ,200.714
+ ,223.982
+ ,89.686
+ ,0.00621
+ ,0.00003
+ ,0.00371
+ ,0.00337
+ ,0.01112
+ ,0.02286
+ ,0.207
+ ,0.01192
+ ,0.01439
+ ,0.01852
+ ,0.03576
+ ,0.00704
+ ,23.239
+ ,1
+ ,0.436084
+ ,0.727863
+ ,-5.25832
+ ,0.256454
+ ,2.550961
+ ,0.23252
+ ,208.519
+ ,220.315
+ ,199.02
+ ,0.00609
+ ,0.00003
+ ,0.00368
+ ,0.00339
+ ,0.01105
+ ,0.01761
+ ,0.155
+ ,0.00952
+ ,0.01058
+ ,0.01307
+ ,0.02855
+ ,0.0083
+ ,22.407
+ ,1
+ ,0.338097
+ ,0.712466
+ ,-6.471427
+ ,0.184378
+ ,2.502336
+ ,0.13639
+ ,204.664
+ ,221.3
+ ,189.621
+ ,0.00841
+ ,0.00004
+ ,0.00502
+ ,0.00485
+ ,0.01506
+ ,0.02378
+ ,0.21
+ ,0.01277
+ ,0.01483
+ ,0.01767
+ ,0.03831
+ ,0.01316
+ ,21.305
+ ,1
+ ,0.498877
+ ,0.722085
+ ,-4.876336
+ ,0.212054
+ ,2.376749
+ ,0.268144
+ ,210.141
+ ,232.706
+ ,185.258
+ ,0.00534
+ ,0.00003
+ ,0.00321
+ ,0.0028
+ ,0.00964
+ ,0.0168
+ ,0.149
+ ,0.00861
+ ,0.01017
+ ,0.01301
+ ,0.02583
+ ,0.0062
+ ,23.671
+ ,1
+ ,0.441097
+ ,0.722254
+ ,-5.96304
+ ,0.250283
+ ,2.489191
+ ,0.177807
+ ,206.327
+ ,226.355
+ ,92.02
+ ,0.00495
+ ,0.00002
+ ,0.00302
+ ,0.00246
+ ,0.00905
+ ,0.02105
+ ,0.209
+ ,0.01107
+ ,0.01284
+ ,0.01604
+ ,0.0332
+ ,0.01048
+ ,21.864
+ ,1
+ ,0.331508
+ ,0.715121
+ ,-6.729713
+ ,0.181701
+ ,2.938114
+ ,0.115515
+ ,151.872
+ ,492.892
+ ,69.085
+ ,0.00856
+ ,0.00006
+ ,0.00404
+ ,0.00385
+ ,0.01211
+ ,0.01843
+ ,0.235
+ ,0.00796
+ ,0.00832
+ ,0.01271
+ ,0.02389
+ ,0.06051
+ ,23.693
+ ,1
+ ,0.407701
+ ,0.662668
+ ,-4.673241
+ ,0.261549
+ ,2.702355
+ ,0.274407
+ ,158.219
+ ,442.557
+ ,71.948
+ ,0.00476
+ ,0.00003
+ ,0.00214
+ ,0.00207
+ ,0.00642
+ ,0.01458
+ ,0.148
+ ,0.00606
+ ,0.00747
+ ,0.01312
+ ,0.01818
+ ,0.01554
+ ,26.356
+ ,1
+ ,0.450798
+ ,0.653823
+ ,-6.051233
+ ,0.27328
+ ,2.640798
+ ,0.170106
+ ,170.756
+ ,450.247
+ ,79.032
+ ,0.00555
+ ,0.00003
+ ,0.00244
+ ,0.00261
+ ,0.00731
+ ,0.01725
+ ,0.175
+ ,0.00757
+ ,0.00971
+ ,0.01652
+ ,0.0227
+ ,0.01802
+ ,25.69
+ ,1
+ ,0.486738
+ ,0.676023
+ ,-4.597834
+ ,0.372114
+ ,2.975889
+ ,0.28278
+ ,178.285
+ ,442.824
+ ,82.063
+ ,0.00462
+ ,0.00003
+ ,0.00157
+ ,0.00194
+ ,0.00472
+ ,0.01279
+ ,0.129
+ ,0.00617
+ ,0.00744
+ ,0.01151
+ ,0.01851
+ ,0.00856
+ ,25.02
+ ,1
+ ,0.470422
+ ,0.655239
+ ,-4.913137
+ ,0.393056
+ ,2.816781
+ ,0.251972
+ ,217.116
+ ,233.481
+ ,93.978
+ ,0.00404
+ ,0.00002
+ ,0.00127
+ ,0.00128
+ ,0.00381
+ ,0.01299
+ ,0.124
+ ,0.00679
+ ,0.00631
+ ,0.01075
+ ,0.02038
+ ,0.00681
+ ,24.581
+ ,1
+ ,0.462516
+ ,0.58271
+ ,-5.517173
+ ,0.389295
+ ,2.925862
+ ,0.220657
+ ,128.94
+ ,479.697
+ ,88.251
+ ,0.00581
+ ,0.00005
+ ,0.00241
+ ,0.00314
+ ,0.00723
+ ,0.02008
+ ,0.221
+ ,0.00849
+ ,0.01117
+ ,0.01734
+ ,0.02548
+ ,0.0235
+ ,24.743
+ ,1
+ ,0.487756
+ ,0.68413
+ ,-6.186128
+ ,0.279933
+ ,2.68624
+ ,0.152428
+ ,176.824
+ ,215.293
+ ,83.961
+ ,0.0046
+ ,0.00003
+ ,0.00209
+ ,0.00221
+ ,0.00628
+ ,0.01169
+ ,0.117
+ ,0.00534
+ ,0.0063
+ ,0.01104
+ ,0.01603
+ ,0.01161
+ ,27.166
+ ,1
+ ,0.400088
+ ,0.656182
+ ,-4.711007
+ ,0.281618
+ ,2.655744
+ ,0.234809
+ ,138.19
+ ,203.522
+ ,83.34
+ ,0.00704
+ ,0.00005
+ ,0.00406
+ ,0.00398
+ ,0.01218
+ ,0.04479
+ ,0.441
+ ,0.02587
+ ,0.02567
+ ,0.0322
+ ,0.07761
+ ,0.01968
+ ,18.305
+ ,1
+ ,0.538016
+ ,0.74148
+ ,-5.418787
+ ,0.160267
+ ,2.090438
+ ,0.229892
+ ,182.018
+ ,197.173
+ ,79.187
+ ,0.00842
+ ,0.00005
+ ,0.00506
+ ,0.00449
+ ,0.01517
+ ,0.02503
+ ,0.231
+ ,0.01372
+ ,0.0158
+ ,0.01931
+ ,0.04115
+ ,0.01813
+ ,18.784
+ ,1
+ ,0.589956
+ ,0.732903
+ ,-5.44514
+ ,0.142466
+ ,2.174306
+ ,0.215558
+ ,156.239
+ ,195.107
+ ,79.82
+ ,0.00694
+ ,0.00004
+ ,0.00403
+ ,0.00395
+ ,0.01209
+ ,0.02343
+ ,0.224
+ ,0.01289
+ ,0.0142
+ ,0.0172
+ ,0.03867
+ ,0.0202
+ ,19.196
+ ,1
+ ,0.618663
+ ,0.728421
+ ,-5.944191
+ ,0.143359
+ ,1.929715
+ ,0.181988
+ ,145.174
+ ,198.109
+ ,80.637
+ ,0.00733
+ ,0.00005
+ ,0.00414
+ ,0.00422
+ ,0.01242
+ ,0.02362
+ ,0.233
+ ,0.01235
+ ,0.01495
+ ,0.01944
+ ,0.03706
+ ,0.01874
+ ,18.857
+ ,1
+ ,0.637518
+ ,0.735546
+ ,-5.594275
+ ,0.12795
+ ,1.765957
+ ,0.222716
+ ,138.145
+ ,197.238
+ ,81.114
+ ,0.00544
+ ,0.00004
+ ,0.00294
+ ,0.00327
+ ,0.00883
+ ,0.02791
+ ,0.246
+ ,0.01484
+ ,0.01805
+ ,0.02259
+ ,0.04451
+ ,0.01794
+ ,18.178
+ ,1
+ ,0.623209
+ ,0.738245
+ ,-5.540351
+ ,0.087165
+ ,1.821297
+ ,0.214075
+ ,166.888
+ ,198.966
+ ,79.512
+ ,0.00638
+ ,0.00004
+ ,0.00368
+ ,0.00351
+ ,0.01104
+ ,0.02857
+ ,0.257
+ ,0.01547
+ ,0.01859
+ ,0.02301
+ ,0.04641
+ ,0.01796
+ ,18.33
+ ,1
+ ,0.585169
+ ,0.736964
+ ,-5.825257
+ ,0.115697
+ ,1.996146
+ ,0.196535
+ ,119.031
+ ,127.533
+ ,109.216
+ ,0.0044
+ ,0.00004
+ ,0.00214
+ ,0.00192
+ ,0.00641
+ ,0.01033
+ ,0.098
+ ,0.00538
+ ,0.0057
+ ,0.00811
+ ,0.01614
+ ,0.01724
+ ,26.842
+ ,1
+ ,0.457541
+ ,0.699787
+ ,-6.890021
+ ,0.152941
+ ,2.328513
+ ,0.112856
+ ,120.078
+ ,126.632
+ ,105.667
+ ,0.0027
+ ,0.00002
+ ,0.00116
+ ,0.00135
+ ,0.00349
+ ,0.01022
+ ,0.09
+ ,0.00476
+ ,0.00588
+ ,0.00903
+ ,0.01428
+ ,0.00487
+ ,26.369
+ ,1
+ ,0.491345
+ ,0.718839
+ ,-5.892061
+ ,0.195976
+ ,2.108873
+ ,0.183572
+ ,120.289
+ ,128.143
+ ,100.209
+ ,0.00492
+ ,0.00004
+ ,0.00269
+ ,0.00238
+ ,0.00808
+ ,0.01412
+ ,0.125
+ ,0.00703
+ ,0.0082
+ ,0.01194
+ ,0.0211
+ ,0.0161
+ ,23.949
+ ,1
+ ,0.46716
+ ,0.724045
+ ,-6.135296
+ ,0.20363
+ ,2.539724
+ ,0.169923
+ ,120.256
+ ,125.306
+ ,104.773
+ ,0.00407
+ ,0.00003
+ ,0.00224
+ ,0.00205
+ ,0.00671
+ ,0.01516
+ ,0.138
+ ,0.00721
+ ,0.00815
+ ,0.0131
+ ,0.02164
+ ,0.01015
+ ,26.017
+ ,1
+ ,0.468621
+ ,0.735136
+ ,-6.112667
+ ,0.217013
+ ,2.527742
+ ,0.170633
+ ,119.056
+ ,125.213
+ ,86.795
+ ,0.00346
+ ,0.00003
+ ,0.00169
+ ,0.0017
+ ,0.00508
+ ,0.01201
+ ,0.106
+ ,0.00633
+ ,0.00701
+ ,0.00915
+ ,0.01898
+ ,0.00903
+ ,23.389
+ ,1
+ ,0.470972
+ ,0.721308
+ ,-5.436135
+ ,0.254909
+ ,2.51632
+ ,0.232209
+ ,118.747
+ ,123.723
+ ,109.836
+ ,0.00331
+ ,0.00003
+ ,0.00168
+ ,0.00171
+ ,0.00504
+ ,0.01043
+ ,0.099
+ ,0.0049
+ ,0.00621
+ ,0.00903
+ ,0.01471
+ ,0.00504
+ ,25.619
+ ,1
+ ,0.482296
+ ,0.723096
+ ,-6.448134
+ ,0.178713
+ ,2.034827
+ ,0.141422
+ ,106.516
+ ,112.777
+ ,93.105
+ ,0.00589
+ ,0.00006
+ ,0.00291
+ ,0.00319
+ ,0.00873
+ ,0.04932
+ ,0.441
+ ,0.02683
+ ,0.03112
+ ,0.03651
+ ,0.0805
+ ,0.03031
+ ,17.06
+ ,1
+ ,0.637814
+ ,0.744064
+ ,-5.301321
+ ,0.320385
+ ,2.375138
+ ,0.24308
+ ,110.453
+ ,127.611
+ ,105.554
+ ,0.00494
+ ,0.00004
+ ,0.00244
+ ,0.00315
+ ,0.00731
+ ,0.04128
+ ,0.379
+ ,0.02229
+ ,0.02592
+ ,0.03316
+ ,0.06688
+ ,0.02529
+ ,17.707
+ ,1
+ ,0.653427
+ ,0.706687
+ ,-5.333619
+ ,0.322044
+ ,2.631793
+ ,0.228319
+ ,113.4
+ ,133.344
+ ,107.816
+ ,0.00451
+ ,0.00004
+ ,0.00219
+ ,0.00283
+ ,0.00658
+ ,0.04879
+ ,0.431
+ ,0.02385
+ ,0.02973
+ ,0.0437
+ ,0.07154
+ ,0.02278
+ ,19.013
+ ,1
+ ,0.6479
+ ,0.708144
+ ,-4.378916
+ ,0.300067
+ ,2.445502
+ ,0.259451
+ ,113.166
+ ,130.27
+ ,100.673
+ ,0.00502
+ ,0.00004
+ ,0.00257
+ ,0.00312
+ ,0.00772
+ ,0.05279
+ ,0.476
+ ,0.02896
+ ,0.03347
+ ,0.04134
+ ,0.08689
+ ,0.0369
+ ,16.747
+ ,1
+ ,0.625362
+ ,0.708617
+ ,-4.654894
+ ,0.304107
+ ,2.672362
+ ,0.274387
+ ,112.239
+ ,126.609
+ ,104.095
+ ,0.00472
+ ,0.00004
+ ,0.00238
+ ,0.0029
+ ,0.00715
+ ,0.05643
+ ,0.517
+ ,0.0307
+ ,0.0353
+ ,0.04451
+ ,0.09211
+ ,0.02629
+ ,17.366
+ ,1
+ ,0.640945
+ ,0.701404
+ ,-5.634576
+ ,0.306014
+ ,2.419253
+ ,0.209191
+ ,116.15
+ ,131.731
+ ,109.815
+ ,0.00381
+ ,0.00003
+ ,0.00181
+ ,0.00232
+ ,0.00542
+ ,0.03026
+ ,0.267
+ ,0.01514
+ ,0.01812
+ ,0.0277
+ ,0.04543
+ ,0.01827
+ ,18.801
+ ,1
+ ,0.624811
+ ,0.696049
+ ,-5.866357
+ ,0.23307
+ ,2.445646
+ ,0.184985
+ ,170.368
+ ,268.796
+ ,79.543
+ ,0.00571
+ ,0.00003
+ ,0.00232
+ ,0.00269
+ ,0.00696
+ ,0.03273
+ ,0.281
+ ,0.01713
+ ,0.01964
+ ,0.02824
+ ,0.05139
+ ,0.02485
+ ,18.54
+ ,1
+ ,0.677131
+ ,0.685057
+ ,-4.796845
+ ,0.397749
+ ,2.963799
+ ,0.277227
+ ,208.083
+ ,253.792
+ ,91.802
+ ,0.00757
+ ,0.00004
+ ,0.00428
+ ,0.00428
+ ,0.01285
+ ,0.06725
+ ,0.571
+ ,0.04016
+ ,0.04003
+ ,0.04464
+ ,0.12047
+ ,0.04238
+ ,15.648
+ ,1
+ ,0.606344
+ ,0.665945
+ ,-5.410336
+ ,0.288917
+ ,2.665133
+ ,0.231723
+ ,198.458
+ ,219.29
+ ,148.691
+ ,0.00376
+ ,0.00002
+ ,0.00182
+ ,0.00215
+ ,0.00546
+ ,0.03527
+ ,0.297
+ ,0.02055
+ ,0.02076
+ ,0.0253
+ ,0.06165
+ ,0.01728
+ ,18.702
+ ,1
+ ,0.606273
+ ,0.661735
+ ,-5.585259
+ ,0.310746
+ ,2.465528
+ ,0.209863
+ ,202.805
+ ,231.508
+ ,86.232
+ ,0.0037
+ ,0.00002
+ ,0.00189
+ ,0.00211
+ ,0.00568
+ ,0.01997
+ ,0.18
+ ,0.01117
+ ,0.01177
+ ,0.01506
+ ,0.0335
+ ,0.0201
+ ,18.687
+ ,1
+ ,0.536102
+ ,0.632631
+ ,-5.898673
+ ,0.213353
+ ,2.470746
+ ,0.189032
+ ,202.544
+ ,241.35
+ ,164.168
+ ,0.00254
+ ,0.00001
+ ,0.001
+ ,0.00133
+ ,0.00301
+ ,0.02662
+ ,0.228
+ ,0.01475
+ ,0.01558
+ ,0.02006
+ ,0.04426
+ ,0.01049
+ ,20.68
+ ,1
+ ,0.49748
+ ,0.630409
+ ,-6.132663
+ ,0.220617
+ ,2.576563
+ ,0.159777
+ ,223.361
+ ,263.872
+ ,87.638
+ ,0.00352
+ ,0.00002
+ ,0.00169
+ ,0.00188
+ ,0.00506
+ ,0.02536
+ ,0.225
+ ,0.01379
+ ,0.01478
+ ,0.01909
+ ,0.04137
+ ,0.01493
+ ,20.366
+ ,1
+ ,0.566849
+ ,0.574282
+ ,-5.456811
+ ,0.345238
+ ,2.840556
+ ,0.232861
+ ,169.774
+ ,191.759
+ ,151.451
+ ,0.01568
+ ,0.00009
+ ,0.00863
+ ,0.00946
+ ,0.02589
+ ,0.08143
+ ,0.821
+ ,0.03804
+ ,0.05426
+ ,0.08808
+ ,0.11411
+ ,0.0753
+ ,12.359
+ ,1
+ ,0.56161
+ ,0.793509
+ ,-3.297668
+ ,0.414758
+ ,3.413649
+ ,0.457533
+ ,183.52
+ ,216.814
+ ,161.34
+ ,0.01466
+ ,0.00008
+ ,0.00849
+ ,0.00819
+ ,0.02546
+ ,0.0605
+ ,0.618
+ ,0.02865
+ ,0.04101
+ ,0.06359
+ ,0.08595
+ ,0.06057
+ ,14.367
+ ,1
+ ,0.478024
+ ,0.768974
+ ,-4.276605
+ ,0.355736
+ ,3.142364
+ ,0.336085
+ ,188.62
+ ,216.302
+ ,165.982
+ ,0.01719
+ ,0.00009
+ ,0.00996
+ ,0.01027
+ ,0.02987
+ ,0.07118
+ ,0.722
+ ,0.03474
+ ,0.0458
+ ,0.06824
+ ,0.10422
+ ,0.08069
+ ,12.298
+ ,1
+ ,0.55287
+ ,0.764036
+ ,-3.377325
+ ,0.335357
+ ,3.274865
+ ,0.418646
+ ,202.632
+ ,565.74
+ ,177.258
+ ,0.01627
+ ,0.00008
+ ,0.00919
+ ,0.00963
+ ,0.02756
+ ,0.0717
+ ,0.833
+ ,0.03515
+ ,0.04265
+ ,0.0646
+ ,0.10546
+ ,0.07889
+ ,14.989
+ ,1
+ ,0.427627
+ ,0.775708
+ ,-4.892495
+ ,0.262281
+ ,2.910213
+ ,0.270173
+ ,186.695
+ ,211.961
+ ,149.442
+ ,0.01872
+ ,0.0001
+ ,0.01075
+ ,0.01154
+ ,0.03225
+ ,0.0583
+ ,0.784
+ ,0.02699
+ ,0.03714
+ ,0.06259
+ ,0.08096
+ ,0.10952
+ ,12.529
+ ,1
+ ,0.507826
+ ,0.762726
+ ,-4.484303
+ ,0.340256
+ ,2.958815
+ ,0.301487
+ ,192.818
+ ,224.429
+ ,168.793
+ ,0.03107
+ ,0.00016
+ ,0.018
+ ,0.01958
+ ,0.05401
+ ,0.11908
+ ,1.302
+ ,0.05647
+ ,0.0794
+ ,0.13778
+ ,0.16942
+ ,0.21713
+ ,8.441
+ ,1
+ ,0.625866
+ ,0.76832
+ ,-2.434031
+ ,0.450493
+ ,3.079221
+ ,0.527367
+ ,198.116
+ ,233.099
+ ,174.478
+ ,0.02714
+ ,0.00014
+ ,0.01568
+ ,0.01699
+ ,0.04705
+ ,0.08684
+ ,1.018
+ ,0.04284
+ ,0.05556
+ ,0.08318
+ ,0.12851
+ ,0.16265
+ ,9.449
+ ,1
+ ,0.584164
+ ,0.754449
+ ,-2.839756
+ ,0.356224
+ ,3.184027
+ ,0.454721
+ ,121.345
+ ,139.644
+ ,98.25
+ ,0.00684
+ ,0.00006
+ ,0.00388
+ ,0.00332
+ ,0.01164
+ ,0.02534
+ ,0.241
+ ,0.0134
+ ,0.01399
+ ,0.02056
+ ,0.04019
+ ,0.04179
+ ,21.52
+ ,1
+ ,0.566867
+ ,0.670475
+ ,-4.865194
+ ,0.246404
+ ,2.01353
+ ,0.168581
+ ,119.1
+ ,128.442
+ ,88.833
+ ,0.00692
+ ,0.00006
+ ,0.00393
+ ,0.003
+ ,0.01179
+ ,0.02682
+ ,0.236
+ ,0.01484
+ ,0.01405
+ ,0.02018
+ ,0.04451
+ ,0.04611
+ ,21.824
+ ,1
+ ,0.65168
+ ,0.659333
+ ,-4.239028
+ ,0.175691
+ ,2.45113
+ ,0.247455
+ ,117.87
+ ,127.349
+ ,95.654
+ ,0.00647
+ ,0.00005
+ ,0.00356
+ ,0.003
+ ,0.01067
+ ,0.03087
+ ,0.276
+ ,0.01659
+ ,0.01804
+ ,0.02402
+ ,0.04977
+ ,0.02631
+ ,22.431
+ ,1
+ ,0.6283
+ ,0.652025
+ ,-3.583722
+ ,0.207914
+ ,2.439597
+ ,0.206256
+ ,122.336
+ ,142.369
+ ,94.794
+ ,0.00727
+ ,0.00006
+ ,0.00415
+ ,0.00339
+ ,0.01246
+ ,0.02293
+ ,0.223
+ ,0.01205
+ ,0.01289
+ ,0.01771
+ ,0.03615
+ ,0.03191
+ ,22.953
+ ,1
+ ,0.611679
+ ,0.623731
+ ,-5.4351
+ ,0.230532
+ ,2.699645
+ ,0.220546
+ ,117.963
+ ,134.209
+ ,100.757
+ ,0.01813
+ ,0.00015
+ ,0.01117
+ ,0.00718
+ ,0.03351
+ ,0.04912
+ ,0.438
+ ,0.0261
+ ,0.02161
+ ,0.02916
+ ,0.0783
+ ,0.10748
+ ,19.075
+ ,1
+ ,0.630547
+ ,0.646786
+ ,-3.444478
+ ,0.303214
+ ,2.964568
+ ,0.261305
+ ,126.144
+ ,154.284
+ ,97.543
+ ,0.00975
+ ,0.00008
+ ,0.00593
+ ,0.00454
+ ,0.01778
+ ,0.02852
+ ,0.266
+ ,0.015
+ ,0.01581
+ ,0.02157
+ ,0.04499
+ ,0.03828
+ ,21.534
+ ,1
+ ,0.635015
+ ,0.627337
+ ,-5.070096
+ ,0.280091
+ ,2.8923
+ ,0.249703
+ ,127.93
+ ,138.752
+ ,112.173
+ ,0.00605
+ ,0.00005
+ ,0.00321
+ ,0.00318
+ ,0.00962
+ ,0.03235
+ ,0.339
+ ,0.0136
+ ,0.0165
+ ,0.03105
+ ,0.04079
+ ,0.02663
+ ,19.651
+ ,1
+ ,0.654945
+ ,0.675865
+ ,-5.498456
+ ,0.234196
+ ,2.103014
+ ,0.216638
+ ,114.238
+ ,124.393
+ ,77.022
+ ,0.00581
+ ,0.00005
+ ,0.00299
+ ,0.00316
+ ,0.00896
+ ,0.04009
+ ,0.406
+ ,0.01579
+ ,0.01994
+ ,0.04114
+ ,0.04736
+ ,0.02073
+ ,20.437
+ ,1
+ ,0.653139
+ ,0.694571
+ ,-5.185987
+ ,0.259229
+ ,2.151121
+ ,0.244948
+ ,115.322
+ ,135.738
+ ,107.802
+ ,0.00619
+ ,0.00005
+ ,0.00352
+ ,0.00329
+ ,0.01057
+ ,0.03273
+ ,0.325
+ ,0.01644
+ ,0.01722
+ ,0.02931
+ ,0.04933
+ ,0.0281
+ ,19.388
+ ,1
+ ,0.577802
+ ,0.684373
+ ,-5.283009
+ ,0.226528
+ ,2.442906
+ ,0.238281
+ ,114.554
+ ,126.778
+ ,91.121
+ ,0.00651
+ ,0.00006
+ ,0.00366
+ ,0.0034
+ ,0.01097
+ ,0.03658
+ ,0.369
+ ,0.01864
+ ,0.0194
+ ,0.03091
+ ,0.05592
+ ,0.02707
+ ,18.954
+ ,1
+ ,0.685151
+ ,0.719576
+ ,-5.529833
+ ,0.24275
+ ,2.408689
+ ,0.22052
+ ,112.15
+ ,131.669
+ ,97.527
+ ,0.00519
+ ,0.00005
+ ,0.00291
+ ,0.00284
+ ,0.00873
+ ,0.01756
+ ,0.155
+ ,0.00967
+ ,0.01033
+ ,0.01363
+ ,0.02902
+ ,0.01435
+ ,21.219
+ ,1
+ ,0.557045
+ ,0.673086
+ ,-5.617124
+ ,0.184896
+ ,1.871871
+ ,0.212386
+ ,102.273
+ ,142.83
+ ,85.902
+ ,0.00907
+ ,0.00009
+ ,0.00493
+ ,0.00461
+ ,0.0148
+ ,0.02814
+ ,0.272
+ ,0.01579
+ ,0.01553
+ ,0.02073
+ ,0.04736
+ ,0.03882
+ ,18.447
+ ,1
+ ,0.671378
+ ,0.674562
+ ,-2.929379
+ ,0.396746
+ ,2.560422
+ ,0.367233
+ ,236.2
+ ,244.663
+ ,102.137
+ ,0.00277
+ ,0.00001
+ ,0.00154
+ ,0.00153
+ ,0.00462
+ ,0.02448
+ ,0.217
+ ,0.0141
+ ,0.01426
+ ,0.01621
+ ,0.04231
+ ,0.0062
+ ,24.078
+ ,0
+ ,0.469928
+ ,0.628232
+ ,-6.816086
+ ,0.17227
+ ,2.235197
+ ,0.119652
+ ,237.323
+ ,243.709
+ ,229.256
+ ,0.00303
+ ,0.00001
+ ,0.00173
+ ,0.00159
+ ,0.00519
+ ,0.01242
+ ,0.116
+ ,0.00696
+ ,0.00747
+ ,0.00882
+ ,0.02089
+ ,0.00533
+ ,24.679
+ ,0
+ ,0.384868
+ ,0.62671
+ ,-7.018057
+ ,0.176316
+ ,1.852402
+ ,0.091604
+ ,260.105
+ ,264.919
+ ,237.303
+ ,0.00339
+ ,0.00001
+ ,0.00205
+ ,0.00186
+ ,0.00616
+ ,0.0203
+ ,0.197
+ ,0.01186
+ ,0.0123
+ ,0.01367
+ ,0.03557
+ ,0.0091
+ ,21.083
+ ,0
+ ,0.440988
+ ,0.628058
+ ,-7.517934
+ ,0.160414
+ ,1.881767
+ ,0.075587
+ ,197.569
+ ,217.627
+ ,90.794
+ ,0.00803
+ ,0.00004
+ ,0.0049
+ ,0.00448
+ ,0.0147
+ ,0.02177
+ ,0.189
+ ,0.01279
+ ,0.01272
+ ,0.01439
+ ,0.03836
+ ,0.01337
+ ,19.269
+ ,0
+ ,0.372222
+ ,0.725216
+ ,-5.736781
+ ,0.164529
+ ,2.88245
+ ,0.202879
+ ,240.301
+ ,245.135
+ ,219.783
+ ,0.00517
+ ,0.00002
+ ,0.00316
+ ,0.00283
+ ,0.00949
+ ,0.02018
+ ,0.212
+ ,0.01176
+ ,0.01191
+ ,0.01344
+ ,0.03529
+ ,0.00965
+ ,21.02
+ ,0
+ ,0.371837
+ ,0.646167
+ ,-7.169701
+ ,0.073298
+ ,2.266432
+ ,0.100881
+ ,244.99
+ ,272.21
+ ,239.17
+ ,0.00451
+ ,0.00002
+ ,0.00279
+ ,0.00237
+ ,0.00837
+ ,0.01897
+ ,0.181
+ ,0.01084
+ ,0.01121
+ ,0.01255
+ ,0.03253
+ ,0.01049
+ ,21.528
+ ,0
+ ,0.522812
+ ,0.646818
+ ,-7.3045
+ ,0.171088
+ ,2.095237
+ ,0.09622
+ ,112.547
+ ,133.374
+ ,105.715
+ ,0.00355
+ ,0.00003
+ ,0.00166
+ ,0.0019
+ ,0.00499
+ ,0.01358
+ ,0.129
+ ,0.00664
+ ,0.00786
+ ,0.0114
+ ,0.01992
+ ,0.00435
+ ,26.436
+ ,0
+ ,0.413295
+ ,0.7567
+ ,-6.323531
+ ,0.218885
+ ,2.193412
+ ,0.160376
+ ,110.739
+ ,113.597
+ ,100.139
+ ,0.00356
+ ,0.00003
+ ,0.0017
+ ,0.002
+ ,0.0051
+ ,0.01484
+ ,0.133
+ ,0.00754
+ ,0.0095
+ ,0.01285
+ ,0.02261
+ ,0.0043
+ ,26.55
+ ,0
+ ,0.36909
+ ,0.776158
+ ,-6.085567
+ ,0.192375
+ ,1.889002
+ ,0.174152
+ ,113.715
+ ,116.443
+ ,96.913
+ ,0.00349
+ ,0.00003
+ ,0.00171
+ ,0.00203
+ ,0.00514
+ ,0.01472
+ ,0.133
+ ,0.00748
+ ,0.00905
+ ,0.01148
+ ,0.02245
+ ,0.00478
+ ,26.547
+ ,0
+ ,0.380253
+ ,0.7667
+ ,-5.943501
+ ,0.19215
+ ,1.852542
+ ,0.179677
+ ,117.004
+ ,144.466
+ ,99.923
+ ,0.00353
+ ,0.00003
+ ,0.00176
+ ,0.00218
+ ,0.00528
+ ,0.01657
+ ,0.145
+ ,0.00881
+ ,0.01062
+ ,0.01318
+ ,0.02643
+ ,0.0059
+ ,25.445
+ ,0
+ ,0.387482
+ ,0.756482
+ ,-6.012559
+ ,0.229298
+ ,1.872946
+ ,0.163118
+ ,115.38
+ ,123.109
+ ,108.634
+ ,0.00332
+ ,0.00003
+ ,0.0016
+ ,0.00199
+ ,0.0048
+ ,0.01503
+ ,0.137
+ ,0.00812
+ ,0.00933
+ ,0.01133
+ ,0.02436
+ ,0.00401
+ ,26.005
+ ,0
+ ,0.405991
+ ,0.761255
+ ,-5.966779
+ ,0.197938
+ ,1.974857
+ ,0.184067
+ ,116.388
+ ,129.038
+ ,108.97
+ ,0.00346
+ ,0.00003
+ ,0.00169
+ ,0.00213
+ ,0.00507
+ ,0.01725
+ ,0.155
+ ,0.00874
+ ,0.01021
+ ,0.01331
+ ,0.02623
+ ,0.00415
+ ,26.143
+ ,0
+ ,0.361232
+ ,0.763242
+ ,-6.016891
+ ,0.109256
+ ,2.004719
+ ,0.174429
+ ,151.737
+ ,190.204
+ ,129.859
+ ,0.00314
+ ,0.00002
+ ,0.00135
+ ,0.00162
+ ,0.00406
+ ,0.01469
+ ,0.132
+ ,0.00728
+ ,0.00886
+ ,0.0123
+ ,0.02184
+ ,0.0057
+ ,24.151
+ ,1
+ ,0.39661
+ ,0.745957
+ ,-6.486822
+ ,0.197919
+ ,2.449763
+ ,0.132703
+ ,148.79
+ ,158.359
+ ,138.99
+ ,0.00309
+ ,0.00002
+ ,0.00152
+ ,0.00186
+ ,0.00456
+ ,0.01574
+ ,0.142
+ ,0.00839
+ ,0.00956
+ ,0.01309
+ ,0.02518
+ ,0.00488
+ ,24.412
+ ,1
+ ,0.402591
+ ,0.762508
+ ,-6.311987
+ ,0.182459
+ ,2.251553
+ ,0.160306
+ ,148.143
+ ,155.982
+ ,135.041
+ ,0.00392
+ ,0.00003
+ ,0.00204
+ ,0.00231
+ ,0.00612
+ ,0.0145
+ ,0.131
+ ,0.00725
+ ,0.00876
+ ,0.01263
+ ,0.02175
+ ,0.0054
+ ,23.683
+ ,1
+ ,0.398499
+ ,0.778349
+ ,-5.711205
+ ,0.240875
+ ,2.845109
+ ,0.19273
+ ,150.44
+ ,163.441
+ ,144.736
+ ,0.00396
+ ,0.00003
+ ,0.00206
+ ,0.00233
+ ,0.00619
+ ,0.02551
+ ,0.237
+ ,0.01321
+ ,0.01574
+ ,0.02148
+ ,0.03964
+ ,0.00611
+ ,23.133
+ ,1
+ ,0.352396
+ ,0.75932
+ ,-6.261446
+ ,0.183218
+ ,2.264226
+ ,0.144105
+ ,148.462
+ ,161.078
+ ,141.998
+ ,0.00397
+ ,0.00003
+ ,0.00202
+ ,0.00235
+ ,0.00605
+ ,0.01831
+ ,0.163
+ ,0.0095
+ ,0.01103
+ ,0.01559
+ ,0.02849
+ ,0.00639
+ ,22.866
+ ,1
+ ,0.408598
+ ,0.768845
+ ,-5.704053
+ ,0.216204
+ ,2.679185
+ ,0.19771
+ ,149.818
+ ,163.417
+ ,144.786
+ ,0.00336
+ ,0.00002
+ ,0.00174
+ ,0.00198
+ ,0.00521
+ ,0.02145
+ ,0.198
+ ,0.01155
+ ,0.01341
+ ,0.01666
+ ,0.03464
+ ,0.00595
+ ,23.008
+ ,1
+ ,0.329577
+ ,0.75718
+ ,-6.27717
+ ,0.109397
+ ,2.209021
+ ,0.156368
+ ,117.226
+ ,123.925
+ ,106.656
+ ,0.00417
+ ,0.00004
+ ,0.00186
+ ,0.0027
+ ,0.00558
+ ,0.01909
+ ,0.171
+ ,0.00864
+ ,0.01223
+ ,0.01949
+ ,0.02592
+ ,0.00955
+ ,23.079
+ ,0
+ ,0.603515
+ ,0.669565
+ ,-5.61907
+ ,0.191576
+ ,2.027228
+ ,0.215724
+ ,116.848
+ ,217.552
+ ,99.503
+ ,0.00531
+ ,0.00005
+ ,0.0026
+ ,0.00346
+ ,0.0078
+ ,0.01795
+ ,0.163
+ ,0.0081
+ ,0.01144
+ ,0.01756
+ ,0.02429
+ ,0.01179
+ ,22.085
+ ,0
+ ,0.663842
+ ,0.656516
+ ,-5.198864
+ ,0.206768
+ ,2.120412
+ ,0.252404
+ ,116.286
+ ,177.291
+ ,96.983
+ ,0.00314
+ ,0.00003
+ ,0.00134
+ ,0.00192
+ ,0.00403
+ ,0.01564
+ ,0.136
+ ,0.00667
+ ,0.0099
+ ,0.01691
+ ,0.02001
+ ,0.00737
+ ,24.199
+ ,0
+ ,0.598515
+ ,0.654331
+ ,-5.592584
+ ,0.133917
+ ,2.058658
+ ,0.214346
+ ,116.556
+ ,592.03
+ ,86.228
+ ,0.00496
+ ,0.00004
+ ,0.00254
+ ,0.00263
+ ,0.00762
+ ,0.0166
+ ,0.154
+ ,0.0082
+ ,0.00972
+ ,0.01491
+ ,0.0246
+ ,0.01397
+ ,23.958
+ ,0
+ ,0.566424
+ ,0.667654
+ ,-6.431119
+ ,0.15331
+ ,2.161936
+ ,0.120605
+ ,116.342
+ ,581.289
+ ,94.246
+ ,0.00267
+ ,0.00002
+ ,0.00115
+ ,0.00148
+ ,0.00345
+ ,0.013
+ ,0.117
+ ,0.00631
+ ,0.00789
+ ,0.01144
+ ,0.01892
+ ,0.0068
+ ,25.023
+ ,0
+ ,0.528485
+ ,0.663884
+ ,-6.359018
+ ,0.116636
+ ,2.152083
+ ,0.138868
+ ,114.563
+ ,119.167
+ ,86.647
+ ,0.00327
+ ,0.00003
+ ,0.00146
+ ,0.00184
+ ,0.00439
+ ,0.01185
+ ,0.106
+ ,0.00557
+ ,0.00721
+ ,0.01095
+ ,0.01672
+ ,0.00703
+ ,24.775
+ ,0
+ ,0.555303
+ ,0.659132
+ ,-6.710219
+ ,0.149694
+ ,1.91399
+ ,0.121777
+ ,201.774
+ ,262.707
+ ,78.228
+ ,0.00694
+ ,0.00003
+ ,0.00412
+ ,0.00396
+ ,0.01235
+ ,0.02574
+ ,0.255
+ ,0.01454
+ ,0.01582
+ ,0.01758
+ ,0.04363
+ ,0.04441
+ ,19.368
+ ,0
+ ,0.508479
+ ,0.683761
+ ,-6.934474
+ ,0.15989
+ ,2.316346
+ ,0.112838
+ ,174.188
+ ,230.978
+ ,94.261
+ ,0.00459
+ ,0.00003
+ ,0.00263
+ ,0.00259
+ ,0.0079
+ ,0.04087
+ ,0.405
+ ,0.02336
+ ,0.02498
+ ,0.02745
+ ,0.07008
+ ,0.02764
+ ,19.517
+ ,0
+ ,0.448439
+ ,0.657899
+ ,-6.538586
+ ,0.121952
+ ,2.657476
+ ,0.13305
+ ,209.516
+ ,253.017
+ ,89.488
+ ,0.00564
+ ,0.00003
+ ,0.00331
+ ,0.00292
+ ,0.00994
+ ,0.02751
+ ,0.263
+ ,0.01604
+ ,0.01657
+ ,0.01879
+ ,0.04812
+ ,0.0181
+ ,19.147
+ ,0
+ ,0.431674
+ ,0.683244
+ ,-6.195325
+ ,0.129303
+ ,2.784312
+ ,0.168895
+ ,174.688
+ ,240.005
+ ,74.287
+ ,0.0136
+ ,0.00008
+ ,0.00624
+ ,0.00564
+ ,0.01873
+ ,0.02308
+ ,0.256
+ ,0.01268
+ ,0.01365
+ ,0.01667
+ ,0.03804
+ ,0.10715
+ ,17.883
+ ,0
+ ,0.407567
+ ,0.655683
+ ,-6.787197
+ ,0.158453
+ ,2.679772
+ ,0.131728
+ ,198.764
+ ,396.961
+ ,74.904
+ ,0.0074
+ ,0.00004
+ ,0.0037
+ ,0.0039
+ ,0.01109
+ ,0.02296
+ ,0.241
+ ,0.01265
+ ,0.01321
+ ,0.01588
+ ,0.03794
+ ,0.07223
+ ,19.02
+ ,0
+ ,0.451221
+ ,0.643956
+ ,-6.744577
+ ,0.207454
+ ,2.138608
+ ,0.123306
+ ,214.289
+ ,260.277
+ ,77.973
+ ,0.00567
+ ,0.00003
+ ,0.00295
+ ,0.00317
+ ,0.00885
+ ,0.01884
+ ,0.19
+ ,0.01026
+ ,0.01161
+ ,0.01373
+ ,0.03078
+ ,0.04398
+ ,21.209
+ ,0
+ ,0.462803
+ ,0.664357
+ ,-5.724056
+ ,0.190667
+ ,2.555477
+ ,0.148569)
+ ,dim=c(23
+ ,195)
+ ,dimnames=list(c('MDVP:Fo(Hz)'
+ ,'MDVP:Fhi(Hz)'
+ ,'MDVP:Flo(Hz)'
+ ,'MDVP:Jitter(%)'
+ ,'MDVP:Jitter(Abs)'
+ ,'MDVP:RAP'
+ ,'MDVP:PPQ'
+ ,'Jitter:DDP'
+ ,'MDVP:Shimmer'
+ ,'MDVP:Shimmer(dB)'
+ ,'Shimmer:APQ3'
+ ,'Shimmer:APQ5'
+ ,'MDVP:APQ'
+ ,'Shimmer:DDA'
+ ,'NHR'
+ ,'HNR'
+ ,'status'
+ ,'RPDE'
+ ,'DFA'
+ ,'spread1'
+ ,'spread2'
+ ,'D2'
+ ,'PPE')
+ ,1:195))
> y <- array(NA,dim=c(23,195),dimnames=list(c('MDVP:Fo(Hz)','MDVP:Fhi(Hz)','MDVP:Flo(Hz)','MDVP:Jitter(%)','MDVP:Jitter(Abs)','MDVP:RAP','MDVP:PPQ','Jitter:DDP','MDVP:Shimmer','MDVP:Shimmer(dB)','Shimmer:APQ3','Shimmer:APQ5','MDVP:APQ','Shimmer:DDA','NHR','HNR','status','RPDE','DFA','spread1','spread2','D2','PPE'),1:195))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '16'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '16'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 ()
> #Author: root
> #To cite this work: Wessa P., (2013), Multiple Regression (v1.0.29) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_multipleregression.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following objects are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
HNR MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%)
1 21.033 119.992 157.302 74.997 0.00784
2 19.085 122.400 148.650 113.819 0.00968
3 20.651 116.682 131.111 111.555 0.01050
4 20.644 116.676 137.871 111.366 0.00997
5 19.649 116.014 141.781 110.655 0.01284
6 21.378 120.552 131.162 113.787 0.00968
7 24.886 120.267 137.244 114.820 0.00333
8 26.892 107.332 113.840 104.315 0.00290
9 21.812 95.730 132.068 91.754 0.00551
10 21.862 95.056 120.103 91.226 0.00532
11 21.118 88.333 112.240 84.072 0.00505
12 21.414 91.904 115.871 86.292 0.00540
13 25.703 136.926 159.866 131.276 0.00293
14 24.889 139.173 179.139 76.556 0.00390
15 24.922 152.845 163.305 75.836 0.00294
16 25.175 142.167 217.455 83.159 0.00369
17 22.333 144.188 349.259 82.764 0.00544
18 20.376 168.778 232.181 75.603 0.00718
19 17.280 153.046 175.829 68.623 0.00742
20 17.153 156.405 189.398 142.822 0.00768
21 17.536 153.848 165.738 65.782 0.00840
22 19.493 153.880 172.860 78.128 0.00480
23 22.468 167.930 193.221 79.068 0.00442
24 20.422 173.917 192.735 86.180 0.00476
25 23.831 163.656 200.841 76.779 0.00742
26 22.066 104.400 206.002 77.968 0.00633
27 25.908 171.041 208.313 75.501 0.00455
28 25.119 146.845 208.701 81.737 0.00496
29 25.970 155.358 227.383 80.055 0.00310
30 25.678 162.568 198.346 77.630 0.00502
31 26.775 197.076 206.896 192.055 0.00289
32 30.940 199.228 209.512 192.091 0.00241
33 30.775 198.383 215.203 193.104 0.00212
34 32.684 202.266 211.604 197.079 0.00180
35 33.047 203.184 211.526 196.160 0.00178
36 31.732 201.464 210.565 195.708 0.00198
37 23.216 177.876 192.921 168.013 0.00411
38 24.951 176.170 185.604 163.564 0.00369
39 26.738 180.198 201.249 175.456 0.00284
40 26.310 187.733 202.324 173.015 0.00316
41 26.822 186.163 197.724 177.584 0.00298
42 26.453 184.055 196.537 166.977 0.00258
43 22.736 237.226 247.326 225.227 0.00298
44 23.145 241.404 248.834 232.483 0.00281
45 25.368 243.439 250.912 232.435 0.00210
46 25.032 242.852 255.034 227.911 0.00225
47 24.602 245.510 262.090 231.848 0.00235
48 26.805 252.455 261.487 182.786 0.00185
49 23.162 122.188 128.611 115.765 0.00524
50 24.971 122.964 130.049 114.676 0.00428
51 25.135 124.445 135.069 117.495 0.00431
52 25.030 126.344 134.231 112.773 0.00448
53 24.692 128.001 138.052 122.080 0.00436
54 25.429 129.336 139.867 118.604 0.00490
55 21.028 108.807 134.656 102.874 0.00761
56 20.767 109.860 126.358 104.437 0.00874
57 21.422 110.417 131.067 103.370 0.00784
58 22.817 117.274 129.916 110.402 0.00752
59 22.603 116.879 131.897 108.153 0.00788
60 21.660 114.847 271.314 104.680 0.00867
61 25.554 209.144 237.494 109.379 0.00282
62 26.138 223.365 238.987 98.664 0.00264
63 25.856 222.236 231.345 205.495 0.00266
64 25.964 228.832 234.619 223.634 0.00296
65 26.415 229.401 252.221 221.156 0.00205
66 24.547 228.969 239.541 113.201 0.00238
67 19.560 140.341 159.774 67.021 0.00817
68 19.979 136.969 166.607 66.004 0.00923
69 20.338 143.533 162.215 65.809 0.01101
70 21.718 148.090 162.824 67.343 0.00762
71 20.264 142.729 162.408 65.476 0.00831
72 18.570 136.358 176.595 65.750 0.00971
73 25.742 120.080 139.710 111.208 0.00405
74 24.178 112.014 588.518 107.024 0.00533
75 25.438 110.793 128.101 107.316 0.00494
76 25.197 110.707 122.611 105.007 0.00516
77 23.370 112.876 148.826 106.981 0.00500
78 25.820 110.568 125.394 106.821 0.00462
79 21.875 95.385 102.145 90.264 0.00608
80 19.200 100.770 115.697 85.545 0.01038
81 19.055 96.106 108.664 84.510 0.00694
82 19.659 95.605 107.715 87.549 0.00702
83 20.536 100.960 110.019 95.628 0.00606
84 22.244 98.804 102.305 87.804 0.00432
85 13.893 176.858 205.560 75.344 0.00747
86 16.176 180.978 200.125 155.495 0.00406
87 15.924 178.222 202.450 141.047 0.00321
88 13.922 176.281 227.381 125.610 0.00520
89 14.739 173.898 211.350 74.677 0.00448
90 11.866 179.711 225.930 144.878 0.00709
91 11.744 166.605 206.008 78.032 0.00742
92 19.664 151.955 163.335 147.226 0.00419
93 18.780 148.272 164.989 142.299 0.00459
94 20.969 152.125 161.469 76.596 0.00382
95 22.219 157.821 172.975 68.401 0.00358
96 21.693 157.447 163.267 149.605 0.00369
97 22.663 159.116 168.913 144.811 0.00342
98 15.338 125.036 143.946 116.187 0.01280
99 15.433 125.791 140.557 96.206 0.01378
100 12.435 126.512 141.756 99.770 0.01936
101 8.867 125.641 141.068 116.346 0.03316
102 15.060 128.451 150.449 75.632 0.01551
103 10.489 139.224 586.567 66.157 0.03011
104 26.759 150.258 154.609 75.349 0.00248
105 28.409 154.003 160.267 128.621 0.00183
106 27.421 149.689 160.368 133.608 0.00257
107 29.746 155.078 163.736 144.148 0.00168
108 26.833 151.884 157.765 133.751 0.00258
109 29.928 151.989 157.339 132.857 0.00174
110 21.934 193.030 208.900 80.297 0.00766
111 23.239 200.714 223.982 89.686 0.00621
112 22.407 208.519 220.315 199.020 0.00609
113 21.305 204.664 221.300 189.621 0.00841
114 23.671 210.141 232.706 185.258 0.00534
115 21.864 206.327 226.355 92.020 0.00495
116 23.693 151.872 492.892 69.085 0.00856
117 26.356 158.219 442.557 71.948 0.00476
118 25.690 170.756 450.247 79.032 0.00555
119 25.020 178.285 442.824 82.063 0.00462
120 24.581 217.116 233.481 93.978 0.00404
121 24.743 128.940 479.697 88.251 0.00581
122 27.166 176.824 215.293 83.961 0.00460
123 18.305 138.190 203.522 83.340 0.00704
124 18.784 182.018 197.173 79.187 0.00842
125 19.196 156.239 195.107 79.820 0.00694
126 18.857 145.174 198.109 80.637 0.00733
127 18.178 138.145 197.238 81.114 0.00544
128 18.330 166.888 198.966 79.512 0.00638
129 26.842 119.031 127.533 109.216 0.00440
130 26.369 120.078 126.632 105.667 0.00270
131 23.949 120.289 128.143 100.209 0.00492
132 26.017 120.256 125.306 104.773 0.00407
133 23.389 119.056 125.213 86.795 0.00346
134 25.619 118.747 123.723 109.836 0.00331
135 17.060 106.516 112.777 93.105 0.00589
136 17.707 110.453 127.611 105.554 0.00494
137 19.013 113.400 133.344 107.816 0.00451
138 16.747 113.166 130.270 100.673 0.00502
139 17.366 112.239 126.609 104.095 0.00472
140 18.801 116.150 131.731 109.815 0.00381
141 18.540 170.368 268.796 79.543 0.00571
142 15.648 208.083 253.792 91.802 0.00757
143 18.702 198.458 219.290 148.691 0.00376
144 18.687 202.805 231.508 86.232 0.00370
145 20.680 202.544 241.350 164.168 0.00254
146 20.366 223.361 263.872 87.638 0.00352
147 12.359 169.774 191.759 151.451 0.01568
148 14.367 183.520 216.814 161.340 0.01466
149 12.298 188.620 216.302 165.982 0.01719
150 14.989 202.632 565.740 177.258 0.01627
151 12.529 186.695 211.961 149.442 0.01872
152 8.441 192.818 224.429 168.793 0.03107
153 9.449 198.116 233.099 174.478 0.02714
154 21.520 121.345 139.644 98.250 0.00684
155 21.824 119.100 128.442 88.833 0.00692
156 22.431 117.870 127.349 95.654 0.00647
157 22.953 122.336 142.369 94.794 0.00727
158 19.075 117.963 134.209 100.757 0.01813
159 21.534 126.144 154.284 97.543 0.00975
160 19.651 127.930 138.752 112.173 0.00605
161 20.437 114.238 124.393 77.022 0.00581
162 19.388 115.322 135.738 107.802 0.00619
163 18.954 114.554 126.778 91.121 0.00651
164 21.219 112.150 131.669 97.527 0.00519
165 18.447 102.273 142.830 85.902 0.00907
166 24.078 236.200 244.663 102.137 0.00277
167 24.679 237.323 243.709 229.256 0.00303
168 21.083 260.105 264.919 237.303 0.00339
169 19.269 197.569 217.627 90.794 0.00803
170 21.020 240.301 245.135 219.783 0.00517
171 21.528 244.990 272.210 239.170 0.00451
172 26.436 112.547 133.374 105.715 0.00355
173 26.550 110.739 113.597 100.139 0.00356
174 26.547 113.715 116.443 96.913 0.00349
175 25.445 117.004 144.466 99.923 0.00353
176 26.005 115.380 123.109 108.634 0.00332
177 26.143 116.388 129.038 108.970 0.00346
178 24.151 151.737 190.204 129.859 0.00314
179 24.412 148.790 158.359 138.990 0.00309
180 23.683 148.143 155.982 135.041 0.00392
181 23.133 150.440 163.441 144.736 0.00396
182 22.866 148.462 161.078 141.998 0.00397
183 23.008 149.818 163.417 144.786 0.00336
184 23.079 117.226 123.925 106.656 0.00417
185 22.085 116.848 217.552 99.503 0.00531
186 24.199 116.286 177.291 96.983 0.00314
187 23.958 116.556 592.030 86.228 0.00496
188 25.023 116.342 581.289 94.246 0.00267
189 24.775 114.563 119.167 86.647 0.00327
190 19.368 201.774 262.707 78.228 0.00694
191 19.517 174.188 230.978 94.261 0.00459
192 19.147 209.516 253.017 89.488 0.00564
193 17.883 174.688 240.005 74.287 0.01360
194 19.020 198.764 396.961 74.904 0.00740
195 21.209 214.289 260.277 77.973 0.00567
MDVP:Jitter(Abs) MDVP:RAP MDVP:PPQ Jitter:DDP MDVP:Shimmer MDVP:Shimmer(dB)
1 7.0e-05 0.00370 0.00554 0.01109 0.04374 0.426
2 8.0e-05 0.00465 0.00696 0.01394 0.06134 0.626
3 9.0e-05 0.00544 0.00781 0.01633 0.05233 0.482
4 9.0e-05 0.00502 0.00698 0.01505 0.05492 0.517
5 1.1e-04 0.00655 0.00908 0.01966 0.06425 0.584
6 8.0e-05 0.00463 0.00750 0.01388 0.04701 0.456
7 3.0e-05 0.00155 0.00202 0.00466 0.01608 0.140
8 3.0e-05 0.00144 0.00182 0.00431 0.01567 0.134
9 6.0e-05 0.00293 0.00332 0.00880 0.02093 0.191
10 6.0e-05 0.00268 0.00332 0.00803 0.02838 0.255
11 6.0e-05 0.00254 0.00330 0.00763 0.02143 0.197
12 6.0e-05 0.00281 0.00336 0.00844 0.02752 0.249
13 2.0e-05 0.00118 0.00153 0.00355 0.01259 0.112
14 3.0e-05 0.00165 0.00208 0.00496 0.01642 0.154
15 2.0e-05 0.00121 0.00149 0.00364 0.01828 0.158
16 3.0e-05 0.00157 0.00203 0.00471 0.01503 0.126
17 4.0e-05 0.00211 0.00292 0.00632 0.02047 0.192
18 4.0e-05 0.00284 0.00387 0.00853 0.03327 0.348
19 5.0e-05 0.00364 0.00432 0.01092 0.05517 0.542
20 5.0e-05 0.00372 0.00399 0.01116 0.03995 0.348
21 5.0e-05 0.00428 0.00450 0.01285 0.03810 0.328
22 3.0e-05 0.00232 0.00267 0.00696 0.04137 0.370
23 3.0e-05 0.00220 0.00247 0.00661 0.04351 0.377
24 3.0e-05 0.00221 0.00258 0.00663 0.04192 0.364
25 5.0e-05 0.00380 0.00390 0.01140 0.01659 0.164
26 6.0e-05 0.00316 0.00375 0.00948 0.03767 0.381
27 3.0e-05 0.00250 0.00234 0.00750 0.01966 0.186
28 3.0e-05 0.00250 0.00275 0.00749 0.01919 0.198
29 2.0e-05 0.00159 0.00176 0.00476 0.01718 0.161
30 3.0e-05 0.00280 0.00253 0.00841 0.01791 0.168
31 1.0e-05 0.00166 0.00168 0.00498 0.01098 0.097
32 1.0e-05 0.00134 0.00138 0.00402 0.01015 0.089
33 1.0e-05 0.00113 0.00135 0.00339 0.01263 0.111
34 9.0e-06 0.00093 0.00107 0.00278 0.00954 0.085
35 9.0e-06 0.00094 0.00106 0.00283 0.00958 0.085
36 1.0e-05 0.00105 0.00115 0.00314 0.01194 0.107
37 2.0e-05 0.00233 0.00241 0.00700 0.02126 0.189
38 2.0e-05 0.00205 0.00218 0.00616 0.01851 0.168
39 2.0e-05 0.00153 0.00166 0.00459 0.01444 0.131
40 2.0e-05 0.00168 0.00182 0.00504 0.01663 0.151
41 2.0e-05 0.00165 0.00175 0.00496 0.01495 0.135
42 1.0e-05 0.00134 0.00147 0.00403 0.01463 0.132
43 1.0e-05 0.00169 0.00182 0.00507 0.01752 0.164
44 1.0e-05 0.00157 0.00173 0.00470 0.01760 0.154
45 9.0e-06 0.00109 0.00137 0.00327 0.01419 0.126
46 9.0e-06 0.00117 0.00139 0.00350 0.01494 0.134
47 1.0e-05 0.00127 0.00148 0.00380 0.01608 0.141
48 7.0e-06 0.00092 0.00113 0.00276 0.01152 0.103
49 4.0e-05 0.00169 0.00203 0.00507 0.01613 0.143
50 3.0e-05 0.00124 0.00155 0.00373 0.01681 0.154
51 3.0e-05 0.00141 0.00167 0.00422 0.02184 0.197
52 4.0e-05 0.00131 0.00169 0.00393 0.02033 0.185
53 3.0e-05 0.00137 0.00166 0.00411 0.02297 0.210
54 4.0e-05 0.00165 0.00183 0.00495 0.02498 0.228
55 7.0e-05 0.00349 0.00486 0.01046 0.02719 0.255
56 8.0e-05 0.00398 0.00539 0.01193 0.03209 0.307
57 7.0e-05 0.00352 0.00514 0.01056 0.03715 0.334
58 6.0e-05 0.00299 0.00469 0.00898 0.02293 0.221
59 7.0e-05 0.00334 0.00493 0.01003 0.02645 0.265
60 8.0e-05 0.00373 0.00520 0.01120 0.03225 0.350
61 1.0e-05 0.00147 0.00152 0.00442 0.01861 0.170
62 1.0e-05 0.00154 0.00151 0.00461 0.01906 0.165
63 1.0e-05 0.00152 0.00144 0.00457 0.01643 0.145
64 1.0e-05 0.00175 0.00155 0.00526 0.01644 0.145
65 9.0e-06 0.00114 0.00113 0.00342 0.01457 0.129
66 1.0e-05 0.00136 0.00140 0.00408 0.01745 0.154
67 6.0e-05 0.00430 0.00440 0.01289 0.03198 0.313
68 7.0e-05 0.00507 0.00463 0.01520 0.03111 0.308
69 8.0e-05 0.00647 0.00467 0.01941 0.05384 0.478
70 5.0e-05 0.00467 0.00354 0.01400 0.05428 0.497
71 6.0e-05 0.00469 0.00419 0.01407 0.03485 0.365
72 7.0e-05 0.00534 0.00478 0.01601 0.04978 0.483
73 3.0e-05 0.00180 0.00220 0.00540 0.01706 0.152
74 5.0e-05 0.00268 0.00329 0.00805 0.02448 0.226
75 4.0e-05 0.00260 0.00283 0.00780 0.02442 0.216
76 5.0e-05 0.00277 0.00289 0.00831 0.02215 0.206
77 4.0e-05 0.00270 0.00289 0.00810 0.03999 0.350
78 4.0e-05 0.00226 0.00280 0.00677 0.02199 0.197
79 6.0e-05 0.00331 0.00332 0.00994 0.03202 0.263
80 1.0e-04 0.00622 0.00576 0.01865 0.03121 0.361
81 7.0e-05 0.00389 0.00415 0.01168 0.04024 0.364
82 7.0e-05 0.00428 0.00371 0.01283 0.03156 0.296
83 6.0e-05 0.00351 0.00348 0.01053 0.02427 0.216
84 4.0e-05 0.00247 0.00258 0.00742 0.02223 0.202
85 4.0e-05 0.00418 0.00420 0.01254 0.04795 0.435
86 2.0e-05 0.00220 0.00244 0.00659 0.03852 0.331
87 2.0e-05 0.00163 0.00194 0.00488 0.03759 0.327
88 3.0e-05 0.00287 0.00312 0.00862 0.06511 0.580
89 3.0e-05 0.00237 0.00254 0.00710 0.06727 0.650
90 4.0e-05 0.00391 0.00419 0.01172 0.04313 0.442
91 4.0e-05 0.00387 0.00453 0.01161 0.06640 0.634
92 3.0e-05 0.00224 0.00227 0.00672 0.07959 0.772
93 3.0e-05 0.00250 0.00256 0.00750 0.04190 0.383
94 3.0e-05 0.00191 0.00226 0.00574 0.05925 0.637
95 2.0e-05 0.00196 0.00196 0.00587 0.03716 0.307
96 2.0e-05 0.00201 0.00197 0.00602 0.03272 0.283
97 2.0e-05 0.00178 0.00184 0.00535 0.03381 0.307
98 1.0e-04 0.00743 0.00623 0.02228 0.03886 0.342
99 1.1e-04 0.00826 0.00655 0.02478 0.04689 0.422
100 1.5e-04 0.01159 0.00990 0.03476 0.06734 0.659
101 2.6e-04 0.02144 0.01522 0.06433 0.09178 0.891
102 1.2e-04 0.00905 0.00909 0.02716 0.06170 0.584
103 2.2e-04 0.01854 0.01628 0.05563 0.09419 0.930
104 2.0e-05 0.00105 0.00136 0.00315 0.01131 0.107
105 1.0e-05 0.00076 0.00100 0.00229 0.01030 0.094
106 2.0e-05 0.00116 0.00134 0.00349 0.01346 0.126
107 1.0e-05 0.00068 0.00092 0.00204 0.01064 0.097
108 2.0e-05 0.00115 0.00122 0.00346 0.01450 0.137
109 1.0e-05 0.00075 0.00096 0.00225 0.01024 0.093
110 4.0e-05 0.00450 0.00389 0.01351 0.03044 0.275
111 3.0e-05 0.00371 0.00337 0.01112 0.02286 0.207
112 3.0e-05 0.00368 0.00339 0.01105 0.01761 0.155
113 4.0e-05 0.00502 0.00485 0.01506 0.02378 0.210
114 3.0e-05 0.00321 0.00280 0.00964 0.01680 0.149
115 2.0e-05 0.00302 0.00246 0.00905 0.02105 0.209
116 6.0e-05 0.00404 0.00385 0.01211 0.01843 0.235
117 3.0e-05 0.00214 0.00207 0.00642 0.01458 0.148
118 3.0e-05 0.00244 0.00261 0.00731 0.01725 0.175
119 3.0e-05 0.00157 0.00194 0.00472 0.01279 0.129
120 2.0e-05 0.00127 0.00128 0.00381 0.01299 0.124
121 5.0e-05 0.00241 0.00314 0.00723 0.02008 0.221
122 3.0e-05 0.00209 0.00221 0.00628 0.01169 0.117
123 5.0e-05 0.00406 0.00398 0.01218 0.04479 0.441
124 5.0e-05 0.00506 0.00449 0.01517 0.02503 0.231
125 4.0e-05 0.00403 0.00395 0.01209 0.02343 0.224
126 5.0e-05 0.00414 0.00422 0.01242 0.02362 0.233
127 4.0e-05 0.00294 0.00327 0.00883 0.02791 0.246
128 4.0e-05 0.00368 0.00351 0.01104 0.02857 0.257
129 4.0e-05 0.00214 0.00192 0.00641 0.01033 0.098
130 2.0e-05 0.00116 0.00135 0.00349 0.01022 0.090
131 4.0e-05 0.00269 0.00238 0.00808 0.01412 0.125
132 3.0e-05 0.00224 0.00205 0.00671 0.01516 0.138
133 3.0e-05 0.00169 0.00170 0.00508 0.01201 0.106
134 3.0e-05 0.00168 0.00171 0.00504 0.01043 0.099
135 6.0e-05 0.00291 0.00319 0.00873 0.04932 0.441
136 4.0e-05 0.00244 0.00315 0.00731 0.04128 0.379
137 4.0e-05 0.00219 0.00283 0.00658 0.04879 0.431
138 4.0e-05 0.00257 0.00312 0.00772 0.05279 0.476
139 4.0e-05 0.00238 0.00290 0.00715 0.05643 0.517
140 3.0e-05 0.00181 0.00232 0.00542 0.03026 0.267
141 3.0e-05 0.00232 0.00269 0.00696 0.03273 0.281
142 4.0e-05 0.00428 0.00428 0.01285 0.06725 0.571
143 2.0e-05 0.00182 0.00215 0.00546 0.03527 0.297
144 2.0e-05 0.00189 0.00211 0.00568 0.01997 0.180
145 1.0e-05 0.00100 0.00133 0.00301 0.02662 0.228
146 2.0e-05 0.00169 0.00188 0.00506 0.02536 0.225
147 9.0e-05 0.00863 0.00946 0.02589 0.08143 0.821
148 8.0e-05 0.00849 0.00819 0.02546 0.06050 0.618
149 9.0e-05 0.00996 0.01027 0.02987 0.07118 0.722
150 8.0e-05 0.00919 0.00963 0.02756 0.07170 0.833
151 1.0e-04 0.01075 0.01154 0.03225 0.05830 0.784
152 1.6e-04 0.01800 0.01958 0.05401 0.11908 1.302
153 1.4e-04 0.01568 0.01699 0.04705 0.08684 1.018
154 6.0e-05 0.00388 0.00332 0.01164 0.02534 0.241
155 6.0e-05 0.00393 0.00300 0.01179 0.02682 0.236
156 5.0e-05 0.00356 0.00300 0.01067 0.03087 0.276
157 6.0e-05 0.00415 0.00339 0.01246 0.02293 0.223
158 1.5e-04 0.01117 0.00718 0.03351 0.04912 0.438
159 8.0e-05 0.00593 0.00454 0.01778 0.02852 0.266
160 5.0e-05 0.00321 0.00318 0.00962 0.03235 0.339
161 5.0e-05 0.00299 0.00316 0.00896 0.04009 0.406
162 5.0e-05 0.00352 0.00329 0.01057 0.03273 0.325
163 6.0e-05 0.00366 0.00340 0.01097 0.03658 0.369
164 5.0e-05 0.00291 0.00284 0.00873 0.01756 0.155
165 9.0e-05 0.00493 0.00461 0.01480 0.02814 0.272
166 1.0e-05 0.00154 0.00153 0.00462 0.02448 0.217
167 1.0e-05 0.00173 0.00159 0.00519 0.01242 0.116
168 1.0e-05 0.00205 0.00186 0.00616 0.02030 0.197
169 4.0e-05 0.00490 0.00448 0.01470 0.02177 0.189
170 2.0e-05 0.00316 0.00283 0.00949 0.02018 0.212
171 2.0e-05 0.00279 0.00237 0.00837 0.01897 0.181
172 3.0e-05 0.00166 0.00190 0.00499 0.01358 0.129
173 3.0e-05 0.00170 0.00200 0.00510 0.01484 0.133
174 3.0e-05 0.00171 0.00203 0.00514 0.01472 0.133
175 3.0e-05 0.00176 0.00218 0.00528 0.01657 0.145
176 3.0e-05 0.00160 0.00199 0.00480 0.01503 0.137
177 3.0e-05 0.00169 0.00213 0.00507 0.01725 0.155
178 2.0e-05 0.00135 0.00162 0.00406 0.01469 0.132
179 2.0e-05 0.00152 0.00186 0.00456 0.01574 0.142
180 3.0e-05 0.00204 0.00231 0.00612 0.01450 0.131
181 3.0e-05 0.00206 0.00233 0.00619 0.02551 0.237
182 3.0e-05 0.00202 0.00235 0.00605 0.01831 0.163
183 2.0e-05 0.00174 0.00198 0.00521 0.02145 0.198
184 4.0e-05 0.00186 0.00270 0.00558 0.01909 0.171
185 5.0e-05 0.00260 0.00346 0.00780 0.01795 0.163
186 3.0e-05 0.00134 0.00192 0.00403 0.01564 0.136
187 4.0e-05 0.00254 0.00263 0.00762 0.01660 0.154
188 2.0e-05 0.00115 0.00148 0.00345 0.01300 0.117
189 3.0e-05 0.00146 0.00184 0.00439 0.01185 0.106
190 3.0e-05 0.00412 0.00396 0.01235 0.02574 0.255
191 3.0e-05 0.00263 0.00259 0.00790 0.04087 0.405
192 3.0e-05 0.00331 0.00292 0.00994 0.02751 0.263
193 8.0e-05 0.00624 0.00564 0.01873 0.02308 0.256
194 4.0e-05 0.00370 0.00390 0.01109 0.02296 0.241
195 3.0e-05 0.00295 0.00317 0.00885 0.01884 0.190
Shimmer:APQ3 Shimmer:APQ5 MDVP:APQ Shimmer:DDA NHR status RPDE
1 0.02182 0.03130 0.02971 0.06545 0.02211 1 0.414783
2 0.03134 0.04518 0.04368 0.09403 0.01929 1 0.458359
3 0.02757 0.03858 0.03590 0.08270 0.01309 1 0.429895
4 0.02924 0.04005 0.03772 0.08771 0.01353 1 0.434969
5 0.03490 0.04825 0.04465 0.10470 0.01767 1 0.417356
6 0.02328 0.03526 0.03243 0.06985 0.01222 1 0.415564
7 0.00779 0.00937 0.01351 0.02337 0.00607 1 0.596040
8 0.00829 0.00946 0.01256 0.02487 0.00344 1 0.637420
9 0.01073 0.01277 0.01717 0.03218 0.01070 1 0.615551
10 0.01441 0.01725 0.02444 0.04324 0.01022 1 0.547037
11 0.01079 0.01342 0.01892 0.03237 0.01166 1 0.611137
12 0.01424 0.01641 0.02214 0.04272 0.01141 1 0.583390
13 0.00656 0.00717 0.01140 0.01968 0.00581 1 0.460600
14 0.00728 0.00932 0.01797 0.02184 0.01041 1 0.430166
15 0.01064 0.00972 0.01246 0.03191 0.00609 1 0.474791
16 0.00772 0.00888 0.01359 0.02316 0.00839 1 0.565924
17 0.00969 0.01200 0.02074 0.02908 0.01859 1 0.567380
18 0.01441 0.01893 0.03430 0.04322 0.02919 1 0.631099
19 0.02471 0.03572 0.05767 0.07413 0.03160 1 0.665318
20 0.01721 0.02374 0.04310 0.05164 0.03365 1 0.649554
21 0.01667 0.02383 0.04055 0.05000 0.03871 1 0.660125
22 0.02021 0.02591 0.04525 0.06062 0.01849 1 0.629017
23 0.02228 0.02540 0.04246 0.06685 0.01280 1 0.619060
24 0.02187 0.02470 0.03772 0.06562 0.01840 1 0.537264
25 0.00738 0.00948 0.01497 0.02214 0.01778 1 0.397937
26 0.01732 0.02245 0.03780 0.05197 0.02887 1 0.522746
27 0.00889 0.01169 0.01872 0.02666 0.01095 1 0.418622
28 0.00883 0.01144 0.01826 0.02650 0.01328 1 0.358773
29 0.00769 0.01012 0.01661 0.02307 0.00677 1 0.470478
30 0.00793 0.01057 0.01799 0.02380 0.01170 1 0.427785
31 0.00563 0.00680 0.00802 0.01689 0.00339 0 0.422229
32 0.00504 0.00641 0.00762 0.01513 0.00167 0 0.432439
33 0.00640 0.00825 0.00951 0.01919 0.00119 0 0.465946
34 0.00469 0.00606 0.00719 0.01407 0.00072 0 0.368535
35 0.00468 0.00610 0.00726 0.01403 0.00065 0 0.340068
36 0.00586 0.00760 0.00957 0.01758 0.00135 0 0.344252
37 0.01154 0.01347 0.01612 0.03463 0.00586 1 0.360148
38 0.00938 0.01160 0.01491 0.02814 0.00340 1 0.341435
39 0.00726 0.00885 0.01190 0.02177 0.00231 1 0.403884
40 0.00829 0.01003 0.01366 0.02488 0.00265 1 0.396793
41 0.00774 0.00941 0.01233 0.02321 0.00231 1 0.326480
42 0.00742 0.00901 0.01234 0.02226 0.00257 1 0.306443
43 0.01035 0.01024 0.01133 0.03104 0.00740 0 0.305062
44 0.01006 0.01038 0.01251 0.03017 0.00675 0 0.457702
45 0.00777 0.00898 0.01033 0.02330 0.00454 0 0.438296
46 0.00847 0.00879 0.01014 0.02542 0.00476 0 0.431285
47 0.00906 0.00977 0.01149 0.02719 0.00476 0 0.467489
48 0.00614 0.00730 0.00860 0.01841 0.00432 0 0.610367
49 0.00855 0.00776 0.01433 0.02566 0.00839 0 0.579597
50 0.00930 0.00802 0.01400 0.02789 0.00462 0 0.538688
51 0.01241 0.01024 0.01685 0.03724 0.00479 0 0.553134
52 0.01143 0.00959 0.01614 0.03429 0.00474 0 0.507504
53 0.01323 0.01072 0.01677 0.03969 0.00481 0 0.459766
54 0.01396 0.01219 0.01947 0.04188 0.00484 0 0.420383
55 0.01483 0.01609 0.02067 0.04450 0.01036 1 0.536009
56 0.01789 0.01992 0.02454 0.05368 0.01180 1 0.558586
57 0.02032 0.02302 0.02802 0.06097 0.00969 1 0.541781
58 0.01189 0.01459 0.01948 0.03568 0.00681 1 0.530529
59 0.01394 0.01625 0.02137 0.04183 0.00786 1 0.540049
60 0.01805 0.01974 0.02519 0.05414 0.01143 1 0.547975
61 0.00975 0.01258 0.01382 0.02925 0.00871 0 0.341788
62 0.01013 0.01296 0.01340 0.03039 0.00301 0 0.447979
63 0.00867 0.01108 0.01200 0.02602 0.00340 0 0.364867
64 0.00882 0.01075 0.01179 0.02647 0.00351 0 0.256570
65 0.00769 0.00957 0.01016 0.02308 0.00300 0 0.276850
66 0.00942 0.01160 0.01234 0.02827 0.00420 0 0.305429
67 0.01830 0.01810 0.02428 0.05490 0.02183 1 0.460139
68 0.01638 0.01759 0.02603 0.04914 0.02659 1 0.498133
69 0.03152 0.02422 0.03392 0.09455 0.04882 1 0.513237
70 0.03357 0.02494 0.03635 0.10070 0.02431 1 0.487407
71 0.01868 0.01906 0.02949 0.05605 0.02599 1 0.489345
72 0.02749 0.02466 0.03736 0.08247 0.03361 1 0.543299
73 0.00974 0.00925 0.01345 0.02921 0.00442 1 0.495954
74 0.01373 0.01375 0.01956 0.04120 0.00623 1 0.509127
75 0.01432 0.01325 0.01831 0.04295 0.00479 1 0.437031
76 0.01284 0.01219 0.01715 0.03851 0.00472 1 0.463514
77 0.02413 0.02231 0.02704 0.07238 0.00905 1 0.489538
78 0.01284 0.01199 0.01636 0.03852 0.00420 1 0.429484
79 0.01803 0.01886 0.02455 0.05408 0.01062 1 0.644954
80 0.01773 0.01783 0.02139 0.05320 0.02220 1 0.594387
81 0.02266 0.02451 0.02876 0.06799 0.01823 1 0.544805
82 0.01792 0.01841 0.02190 0.05377 0.01825 1 0.576084
83 0.01371 0.01421 0.01751 0.04114 0.01237 1 0.554610
84 0.01277 0.01343 0.01552 0.03831 0.00882 1 0.576644
85 0.02679 0.03022 0.03510 0.08037 0.05470 1 0.556494
86 0.02107 0.02493 0.02877 0.06321 0.02782 1 0.583574
87 0.02073 0.02415 0.02784 0.06219 0.03151 1 0.598714
88 0.03671 0.04159 0.04683 0.11012 0.04824 1 0.602874
89 0.03788 0.04254 0.04802 0.11363 0.04214 1 0.599371
90 0.02297 0.02768 0.03455 0.06892 0.07223 1 0.590951
91 0.03650 0.04282 0.05114 0.10949 0.08725 1 0.653410
92 0.04421 0.04962 0.05690 0.13262 0.01658 1 0.501037
93 0.02383 0.02521 0.03051 0.07150 0.01914 1 0.454444
94 0.03341 0.03794 0.04398 0.10024 0.01211 1 0.447456
95 0.02062 0.02321 0.02764 0.06185 0.00850 1 0.502380
96 0.01813 0.01909 0.02571 0.05439 0.01018 1 0.447285
97 0.01806 0.02024 0.02809 0.05417 0.00852 1 0.366329
98 0.02135 0.02174 0.03088 0.06406 0.08151 1 0.629574
99 0.02542 0.02630 0.03908 0.07625 0.10323 1 0.571010
100 0.03611 0.03963 0.05783 0.10833 0.16744 1 0.638545
101 0.05358 0.04791 0.06196 0.16074 0.31482 1 0.671299
102 0.03223 0.03672 0.05174 0.09669 0.11843 1 0.639808
103 0.05551 0.05005 0.06023 0.16654 0.25930 1 0.596362
104 0.00522 0.00659 0.01009 0.01567 0.00495 1 0.296888
105 0.00469 0.00582 0.00871 0.01406 0.00243 1 0.263654
106 0.00660 0.00818 0.01059 0.01979 0.00578 1 0.365488
107 0.00522 0.00632 0.00928 0.01567 0.00233 1 0.334171
108 0.00633 0.00788 0.01267 0.01898 0.00659 1 0.393563
109 0.00455 0.00576 0.00993 0.01364 0.00238 1 0.311369
110 0.01771 0.01815 0.02084 0.05312 0.00947 1 0.497554
111 0.01192 0.01439 0.01852 0.03576 0.00704 1 0.436084
112 0.00952 0.01058 0.01307 0.02855 0.00830 1 0.338097
113 0.01277 0.01483 0.01767 0.03831 0.01316 1 0.498877
114 0.00861 0.01017 0.01301 0.02583 0.00620 1 0.441097
115 0.01107 0.01284 0.01604 0.03320 0.01048 1 0.331508
116 0.00796 0.00832 0.01271 0.02389 0.06051 1 0.407701
117 0.00606 0.00747 0.01312 0.01818 0.01554 1 0.450798
118 0.00757 0.00971 0.01652 0.02270 0.01802 1 0.486738
119 0.00617 0.00744 0.01151 0.01851 0.00856 1 0.470422
120 0.00679 0.00631 0.01075 0.02038 0.00681 1 0.462516
121 0.00849 0.01117 0.01734 0.02548 0.02350 1 0.487756
122 0.00534 0.00630 0.01104 0.01603 0.01161 1 0.400088
123 0.02587 0.02567 0.03220 0.07761 0.01968 1 0.538016
124 0.01372 0.01580 0.01931 0.04115 0.01813 1 0.589956
125 0.01289 0.01420 0.01720 0.03867 0.02020 1 0.618663
126 0.01235 0.01495 0.01944 0.03706 0.01874 1 0.637518
127 0.01484 0.01805 0.02259 0.04451 0.01794 1 0.623209
128 0.01547 0.01859 0.02301 0.04641 0.01796 1 0.585169
129 0.00538 0.00570 0.00811 0.01614 0.01724 1 0.457541
130 0.00476 0.00588 0.00903 0.01428 0.00487 1 0.491345
131 0.00703 0.00820 0.01194 0.02110 0.01610 1 0.467160
132 0.00721 0.00815 0.01310 0.02164 0.01015 1 0.468621
133 0.00633 0.00701 0.00915 0.01898 0.00903 1 0.470972
134 0.00490 0.00621 0.00903 0.01471 0.00504 1 0.482296
135 0.02683 0.03112 0.03651 0.08050 0.03031 1 0.637814
136 0.02229 0.02592 0.03316 0.06688 0.02529 1 0.653427
137 0.02385 0.02973 0.04370 0.07154 0.02278 1 0.647900
138 0.02896 0.03347 0.04134 0.08689 0.03690 1 0.625362
139 0.03070 0.03530 0.04451 0.09211 0.02629 1 0.640945
140 0.01514 0.01812 0.02770 0.04543 0.01827 1 0.624811
141 0.01713 0.01964 0.02824 0.05139 0.02485 1 0.677131
142 0.04016 0.04003 0.04464 0.12047 0.04238 1 0.606344
143 0.02055 0.02076 0.02530 0.06165 0.01728 1 0.606273
144 0.01117 0.01177 0.01506 0.03350 0.02010 1 0.536102
145 0.01475 0.01558 0.02006 0.04426 0.01049 1 0.497480
146 0.01379 0.01478 0.01909 0.04137 0.01493 1 0.566849
147 0.03804 0.05426 0.08808 0.11411 0.07530 1 0.561610
148 0.02865 0.04101 0.06359 0.08595 0.06057 1 0.478024
149 0.03474 0.04580 0.06824 0.10422 0.08069 1 0.552870
150 0.03515 0.04265 0.06460 0.10546 0.07889 1 0.427627
151 0.02699 0.03714 0.06259 0.08096 0.10952 1 0.507826
152 0.05647 0.07940 0.13778 0.16942 0.21713 1 0.625866
153 0.04284 0.05556 0.08318 0.12851 0.16265 1 0.584164
154 0.01340 0.01399 0.02056 0.04019 0.04179 1 0.566867
155 0.01484 0.01405 0.02018 0.04451 0.04611 1 0.651680
156 0.01659 0.01804 0.02402 0.04977 0.02631 1 0.628300
157 0.01205 0.01289 0.01771 0.03615 0.03191 1 0.611679
158 0.02610 0.02161 0.02916 0.07830 0.10748 1 0.630547
159 0.01500 0.01581 0.02157 0.04499 0.03828 1 0.635015
160 0.01360 0.01650 0.03105 0.04079 0.02663 1 0.654945
161 0.01579 0.01994 0.04114 0.04736 0.02073 1 0.653139
162 0.01644 0.01722 0.02931 0.04933 0.02810 1 0.577802
163 0.01864 0.01940 0.03091 0.05592 0.02707 1 0.685151
164 0.00967 0.01033 0.01363 0.02902 0.01435 1 0.557045
165 0.01579 0.01553 0.02073 0.04736 0.03882 1 0.671378
166 0.01410 0.01426 0.01621 0.04231 0.00620 0 0.469928
167 0.00696 0.00747 0.00882 0.02089 0.00533 0 0.384868
168 0.01186 0.01230 0.01367 0.03557 0.00910 0 0.440988
169 0.01279 0.01272 0.01439 0.03836 0.01337 0 0.372222
170 0.01176 0.01191 0.01344 0.03529 0.00965 0 0.371837
171 0.01084 0.01121 0.01255 0.03253 0.01049 0 0.522812
172 0.00664 0.00786 0.01140 0.01992 0.00435 0 0.413295
173 0.00754 0.00950 0.01285 0.02261 0.00430 0 0.369090
174 0.00748 0.00905 0.01148 0.02245 0.00478 0 0.380253
175 0.00881 0.01062 0.01318 0.02643 0.00590 0 0.387482
176 0.00812 0.00933 0.01133 0.02436 0.00401 0 0.405991
177 0.00874 0.01021 0.01331 0.02623 0.00415 0 0.361232
178 0.00728 0.00886 0.01230 0.02184 0.00570 1 0.396610
179 0.00839 0.00956 0.01309 0.02518 0.00488 1 0.402591
180 0.00725 0.00876 0.01263 0.02175 0.00540 1 0.398499
181 0.01321 0.01574 0.02148 0.03964 0.00611 1 0.352396
182 0.00950 0.01103 0.01559 0.02849 0.00639 1 0.408598
183 0.01155 0.01341 0.01666 0.03464 0.00595 1 0.329577
184 0.00864 0.01223 0.01949 0.02592 0.00955 0 0.603515
185 0.00810 0.01144 0.01756 0.02429 0.01179 0 0.663842
186 0.00667 0.00990 0.01691 0.02001 0.00737 0 0.598515
187 0.00820 0.00972 0.01491 0.02460 0.01397 0 0.566424
188 0.00631 0.00789 0.01144 0.01892 0.00680 0 0.528485
189 0.00557 0.00721 0.01095 0.01672 0.00703 0 0.555303
190 0.01454 0.01582 0.01758 0.04363 0.04441 0 0.508479
191 0.02336 0.02498 0.02745 0.07008 0.02764 0 0.448439
192 0.01604 0.01657 0.01879 0.04812 0.01810 0 0.431674
193 0.01268 0.01365 0.01667 0.03804 0.10715 0 0.407567
194 0.01265 0.01321 0.01588 0.03794 0.07223 0 0.451221
195 0.01026 0.01161 0.01373 0.03078 0.04398 0 0.462803
DFA spread1 spread2 D2 PPE
1 0.815285 -4.813031 0.266482 2.301442 0.284654
2 0.819521 -4.075192 0.335590 2.486855 0.368674
3 0.825288 -4.443179 0.311173 2.342259 0.332634
4 0.819235 -4.117501 0.334147 2.405554 0.368975
5 0.823484 -3.747787 0.234513 2.332180 0.410335
6 0.825069 -4.242867 0.299111 2.187560 0.357775
7 0.764112 -5.634322 0.257682 1.854785 0.211756
8 0.763262 -6.167603 0.183721 2.064693 0.163755
9 0.773587 -5.498678 0.327769 2.322511 0.231571
10 0.798463 -5.011879 0.325996 2.432792 0.271362
11 0.776156 -5.249770 0.391002 2.407313 0.249740
12 0.792520 -4.960234 0.363566 2.642476 0.275931
13 0.646846 -6.547148 0.152813 2.041277 0.138512
14 0.665833 -5.660217 0.254989 2.519422 0.199889
15 0.654027 -6.105098 0.203653 2.125618 0.170100
16 0.658245 -5.340115 0.210185 2.205546 0.234589
17 0.644692 -5.440040 0.239764 2.264501 0.218164
18 0.605417 -2.931070 0.434326 3.007463 0.430788
19 0.719467 -3.949079 0.357870 3.109010 0.377429
20 0.686080 -4.554466 0.340176 2.856676 0.322111
21 0.704087 -4.095442 0.262564 2.739710 0.365391
22 0.698951 -5.186960 0.237622 2.557536 0.259765
23 0.679834 -4.330956 0.262384 2.916777 0.285695
24 0.686894 -5.248776 0.210279 2.547508 0.253556
25 0.732479 -5.557447 0.220890 2.692176 0.215961
26 0.737948 -5.571843 0.236853 2.846369 0.219514
27 0.720916 -6.183590 0.226278 2.589702 0.147403
28 0.726652 -6.271690 0.196102 2.314209 0.162999
29 0.676258 -7.120925 0.279789 2.241742 0.108514
30 0.723797 -6.635729 0.209866 1.957961 0.135242
31 0.741367 -7.348300 0.177551 1.743867 0.085569
32 0.742055 -7.682587 0.173319 2.103106 0.068501
33 0.738703 -7.067931 0.175181 1.512275 0.096320
34 0.742133 -7.695734 0.178540 1.544609 0.056141
35 0.741899 -7.964984 0.163519 1.423287 0.044539
36 0.742737 -7.777685 0.170183 2.447064 0.057610
37 0.778834 -6.149653 0.218037 2.477082 0.165827
38 0.783626 -6.006414 0.196371 2.536527 0.173218
39 0.766209 -6.452058 0.212294 2.269398 0.141929
40 0.758324 -6.006647 0.266892 2.382544 0.160691
41 0.765623 -6.647379 0.201095 2.374073 0.130554
42 0.759203 -7.044105 0.063412 2.361532 0.115730
43 0.654172 -7.310550 0.098648 2.416838 0.095032
44 0.634267 -6.793547 0.158266 2.256699 0.117399
45 0.635285 -7.057869 0.091608 2.330716 0.091470
46 0.638928 -6.995820 0.102083 2.365800 0.102706
47 0.631653 -7.156076 0.127642 2.392122 0.097336
48 0.635204 -7.319510 0.200873 2.028612 0.086398
49 0.733659 -6.439398 0.266392 2.079922 0.133867
50 0.754073 -6.482096 0.264967 2.054419 0.128872
51 0.775933 -6.650471 0.254498 1.840198 0.103561
52 0.760361 -6.689151 0.291954 2.431854 0.105993
53 0.766204 -7.072419 0.220434 1.972297 0.119308
54 0.785714 -6.836811 0.269866 2.223719 0.147491
55 0.819032 -4.649573 0.205558 1.986899 0.316700
56 0.811843 -4.333543 0.221727 2.014606 0.344834
57 0.821364 -4.438453 0.238298 1.922940 0.335041
58 0.817756 -4.608260 0.290024 2.021591 0.314464
59 0.813432 -4.476755 0.262633 1.827012 0.326197
60 0.817396 -4.609161 0.221711 1.831691 0.316395
61 0.678874 -7.040508 0.066994 2.460791 0.101516
62 0.686264 -7.293801 0.086372 2.321560 0.098555
63 0.694399 -6.966321 0.095882 2.278687 0.103224
64 0.683296 -7.245620 0.018689 2.498224 0.093534
65 0.673636 -7.496264 0.056844 2.003032 0.073581
66 0.681811 -7.314237 0.006274 2.118596 0.091546
67 0.720908 -5.409423 0.226850 2.359973 0.226156
68 0.729067 -5.324574 0.205660 2.291558 0.226247
69 0.731444 -5.869750 0.151814 2.118496 0.185580
70 0.727313 -6.261141 0.120956 2.137075 0.141958
71 0.730387 -5.720868 0.158830 2.277927 0.180828
72 0.733232 -5.207985 0.224852 2.642276 0.242981
73 0.762959 -5.791820 0.329066 2.205024 0.188180
74 0.789532 -5.389129 0.306636 1.928708 0.225461
75 0.815908 -5.313360 0.201861 2.225815 0.244512
76 0.807217 -5.477592 0.315074 1.862092 0.228624
77 0.789977 -5.775966 0.341169 2.007923 0.193918
78 0.816340 -5.391029 0.250572 1.777901 0.232744
79 0.779612 -5.115212 0.249494 2.017753 0.260015
80 0.790117 -4.913885 0.265699 2.398422 0.277948
81 0.770466 -4.441519 0.155097 2.645959 0.327978
82 0.778747 -5.132032 0.210458 2.232576 0.260633
83 0.787896 -5.022288 0.146948 2.428306 0.264666
84 0.772416 -6.025367 0.078202 2.053601 0.177275
85 0.729586 -5.288912 0.343073 3.099301 0.242119
86 0.727747 -5.657899 0.315903 3.098256 0.200423
87 0.712199 -6.366916 0.335753 2.654271 0.144614
88 0.740837 -5.515071 0.299549 3.136550 0.220968
89 0.743937 -5.783272 0.299793 3.007096 0.194052
90 0.745526 -4.379411 0.375531 3.671155 0.332086
91 0.733165 -4.508984 0.389232 3.317586 0.301952
92 0.714360 -6.411497 0.207156 2.344876 0.134120
93 0.734504 -5.952058 0.087840 2.344336 0.186489
94 0.697790 -6.152551 0.173520 2.080121 0.160809
95 0.712170 -6.251425 0.188056 2.143851 0.160812
96 0.705658 -6.247076 0.180528 2.344348 0.164916
97 0.693429 -6.417440 0.194627 2.473239 0.151709
98 0.714485 -4.020042 0.265315 2.671825 0.340623
99 0.690892 -5.159169 0.202146 2.441612 0.260375
100 0.674953 -3.760348 0.242861 2.634633 0.378483
101 0.656846 -3.700544 0.260481 2.991063 0.370961
102 0.643327 -4.202730 0.310163 2.638279 0.356881
103 0.641418 -3.269487 0.270641 2.690917 0.444774
104 0.722356 -6.878393 0.089267 2.004055 0.113942
105 0.691483 -7.111576 0.144780 2.065477 0.093193
106 0.719974 -6.997403 0.210279 1.994387 0.112878
107 0.677930 -6.981201 0.184550 2.129924 0.106802
108 0.700246 -6.600023 0.249172 2.499148 0.105306
109 0.676066 -6.739151 0.160686 2.296873 0.115130
110 0.740539 -5.845099 0.278679 2.608749 0.185668
111 0.727863 -5.258320 0.256454 2.550961 0.232520
112 0.712466 -6.471427 0.184378 2.502336 0.136390
113 0.722085 -4.876336 0.212054 2.376749 0.268144
114 0.722254 -5.963040 0.250283 2.489191 0.177807
115 0.715121 -6.729713 0.181701 2.938114 0.115515
116 0.662668 -4.673241 0.261549 2.702355 0.274407
117 0.653823 -6.051233 0.273280 2.640798 0.170106
118 0.676023 -4.597834 0.372114 2.975889 0.282780
119 0.655239 -4.913137 0.393056 2.816781 0.251972
120 0.582710 -5.517173 0.389295 2.925862 0.220657
121 0.684130 -6.186128 0.279933 2.686240 0.152428
122 0.656182 -4.711007 0.281618 2.655744 0.234809
123 0.741480 -5.418787 0.160267 2.090438 0.229892
124 0.732903 -5.445140 0.142466 2.174306 0.215558
125 0.728421 -5.944191 0.143359 1.929715 0.181988
126 0.735546 -5.594275 0.127950 1.765957 0.222716
127 0.738245 -5.540351 0.087165 1.821297 0.214075
128 0.736964 -5.825257 0.115697 1.996146 0.196535
129 0.699787 -6.890021 0.152941 2.328513 0.112856
130 0.718839 -5.892061 0.195976 2.108873 0.183572
131 0.724045 -6.135296 0.203630 2.539724 0.169923
132 0.735136 -6.112667 0.217013 2.527742 0.170633
133 0.721308 -5.436135 0.254909 2.516320 0.232209
134 0.723096 -6.448134 0.178713 2.034827 0.141422
135 0.744064 -5.301321 0.320385 2.375138 0.243080
136 0.706687 -5.333619 0.322044 2.631793 0.228319
137 0.708144 -4.378916 0.300067 2.445502 0.259451
138 0.708617 -4.654894 0.304107 2.672362 0.274387
139 0.701404 -5.634576 0.306014 2.419253 0.209191
140 0.696049 -5.866357 0.233070 2.445646 0.184985
141 0.685057 -4.796845 0.397749 2.963799 0.277227
142 0.665945 -5.410336 0.288917 2.665133 0.231723
143 0.661735 -5.585259 0.310746 2.465528 0.209863
144 0.632631 -5.898673 0.213353 2.470746 0.189032
145 0.630409 -6.132663 0.220617 2.576563 0.159777
146 0.574282 -5.456811 0.345238 2.840556 0.232861
147 0.793509 -3.297668 0.414758 3.413649 0.457533
148 0.768974 -4.276605 0.355736 3.142364 0.336085
149 0.764036 -3.377325 0.335357 3.274865 0.418646
150 0.775708 -4.892495 0.262281 2.910213 0.270173
151 0.762726 -4.484303 0.340256 2.958815 0.301487
152 0.768320 -2.434031 0.450493 3.079221 0.527367
153 0.754449 -2.839756 0.356224 3.184027 0.454721
154 0.670475 -4.865194 0.246404 2.013530 0.168581
155 0.659333 -4.239028 0.175691 2.451130 0.247455
156 0.652025 -3.583722 0.207914 2.439597 0.206256
157 0.623731 -5.435100 0.230532 2.699645 0.220546
158 0.646786 -3.444478 0.303214 2.964568 0.261305
159 0.627337 -5.070096 0.280091 2.892300 0.249703
160 0.675865 -5.498456 0.234196 2.103014 0.216638
161 0.694571 -5.185987 0.259229 2.151121 0.244948
162 0.684373 -5.283009 0.226528 2.442906 0.238281
163 0.719576 -5.529833 0.242750 2.408689 0.220520
164 0.673086 -5.617124 0.184896 1.871871 0.212386
165 0.674562 -2.929379 0.396746 2.560422 0.367233
166 0.628232 -6.816086 0.172270 2.235197 0.119652
167 0.626710 -7.018057 0.176316 1.852402 0.091604
168 0.628058 -7.517934 0.160414 1.881767 0.075587
169 0.725216 -5.736781 0.164529 2.882450 0.202879
170 0.646167 -7.169701 0.073298 2.266432 0.100881
171 0.646818 -7.304500 0.171088 2.095237 0.096220
172 0.756700 -6.323531 0.218885 2.193412 0.160376
173 0.776158 -6.085567 0.192375 1.889002 0.174152
174 0.766700 -5.943501 0.192150 1.852542 0.179677
175 0.756482 -6.012559 0.229298 1.872946 0.163118
176 0.761255 -5.966779 0.197938 1.974857 0.184067
177 0.763242 -6.016891 0.109256 2.004719 0.174429
178 0.745957 -6.486822 0.197919 2.449763 0.132703
179 0.762508 -6.311987 0.182459 2.251553 0.160306
180 0.778349 -5.711205 0.240875 2.845109 0.192730
181 0.759320 -6.261446 0.183218 2.264226 0.144105
182 0.768845 -5.704053 0.216204 2.679185 0.197710
183 0.757180 -6.277170 0.109397 2.209021 0.156368
184 0.669565 -5.619070 0.191576 2.027228 0.215724
185 0.656516 -5.198864 0.206768 2.120412 0.252404
186 0.654331 -5.592584 0.133917 2.058658 0.214346
187 0.667654 -6.431119 0.153310 2.161936 0.120605
188 0.663884 -6.359018 0.116636 2.152083 0.138868
189 0.659132 -6.710219 0.149694 1.913990 0.121777
190 0.683761 -6.934474 0.159890 2.316346 0.112838
191 0.657899 -6.538586 0.121952 2.657476 0.133050
192 0.683244 -6.195325 0.129303 2.784312 0.168895
193 0.655683 -6.787197 0.158453 2.679772 0.131728
194 0.643956 -6.744577 0.207454 2.138608 0.123306
195 0.664357 -5.724056 0.190667 2.555477 0.148569
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `MDVP:Fo(Hz)` `MDVP:Fhi(Hz)` `MDVP:Flo(Hz)`
4.454e+01 -1.827e-03 2.478e-03 2.102e-03
`MDVP:Jitter(%)` `MDVP:Jitter(Abs)` `MDVP:RAP` `MDVP:PPQ`
-6.075e+02 5.789e+04 -2.710e+04 2.541e+01
`Jitter:DDP` `MDVP:Shimmer` `MDVP:Shimmer(dB)` `Shimmer:APQ3`
9.120e+03 3.089e+02 -1.075e+01 2.766e+04
`Shimmer:APQ5` `MDVP:APQ` `Shimmer:DDA` NHR
-1.930e+02 5.899e+01 -9.349e+03 -1.643e+01
status RPDE DFA spread1
-4.404e-01 -1.732e+01 -2.398e+00 4.123e-01
spread2 D2 PPE
9.433e+00 -3.015e+00 -1.159e+01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3.9904 -0.9766 -0.1385 0.8344 5.0830
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.454e+01 5.190e+00 8.583 5.32e-15 ***
`MDVP:Fo(Hz)` -1.827e-03 8.056e-03 -0.227 0.820860
`MDVP:Fhi(Hz)` 2.478e-03 1.691e-03 1.465 0.144700
`MDVP:Flo(Hz)` 2.102e-03 4.292e-03 0.490 0.624890
`MDVP:Jitter(%)` -6.075e+02 3.592e+02 -1.691 0.092640 .
`MDVP:Jitter(Abs)` 5.789e+04 2.414e+04 2.398 0.017565 *
`MDVP:RAP` -2.710e+04 4.940e+04 -0.549 0.584023
`MDVP:PPQ` 2.541e+01 4.685e+02 0.054 0.956811
`Jitter:DDP` 9.120e+03 1.647e+04 0.554 0.580490
`MDVP:Shimmer` 3.089e+02 1.804e+02 1.712 0.088658 .
`MDVP:Shimmer(dB)` -1.075e+01 6.305e+00 -1.706 0.089856 .
`Shimmer:APQ3` 2.766e+04 4.749e+04 0.582 0.561007
`Shimmer:APQ5` -1.930e+02 1.061e+02 -1.819 0.070652 .
`MDVP:APQ` 5.899e+01 5.754e+01 1.025 0.306707
`Shimmer:DDA` -9.349e+03 1.582e+04 -0.591 0.555429
NHR -1.643e+01 1.047e+01 -1.570 0.118322
status -4.404e-01 4.025e-01 -1.094 0.275444
RPDE -1.732e+01 1.961e+00 -8.834 1.14e-15 ***
DFA -2.398e+00 3.915e+00 -0.612 0.541082
spread1 4.123e-01 5.202e-01 0.792 0.429161
spread2 9.433e+00 2.481e+00 3.801 0.000199 ***
D2 -3.015e+00 5.607e-01 -5.378 2.43e-07 ***
PPE -1.159e+01 7.293e+00 -1.590 0.113756
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.731 on 172 degrees of freedom
Multiple R-squared: 0.8644, Adjusted R-squared: 0.8471
F-statistic: 49.85 on 22 and 172 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.24568624 4.913725e-01 7.543138e-01
[2,] 0.16488642 3.297728e-01 8.351136e-01
[3,] 0.08467087 1.693417e-01 9.153291e-01
[4,] 0.09452461 1.890492e-01 9.054754e-01
[5,] 0.05068873 1.013775e-01 9.493113e-01
[6,] 0.02471842 4.943684e-02 9.752816e-01
[7,] 0.13964927 2.792985e-01 8.603507e-01
[8,] 0.16419877 3.283975e-01 8.358012e-01
[9,] 0.28109113 5.621823e-01 7.189089e-01
[10,] 0.27228137 5.445627e-01 7.277186e-01
[11,] 0.28131805 5.626361e-01 7.186820e-01
[12,] 0.21633476 4.326695e-01 7.836652e-01
[13,] 0.17897606 3.579521e-01 8.210239e-01
[14,] 0.13535545 2.707109e-01 8.646446e-01
[15,] 0.10550606 2.110121e-01 8.944939e-01
[16,] 0.07513833 1.502767e-01 9.248617e-01
[17,] 0.07150447 1.430089e-01 9.284955e-01
[18,] 0.37416101 7.483220e-01 6.258390e-01
[19,] 0.33002153 6.600431e-01 6.699785e-01
[20,] 0.33066161 6.613232e-01 6.693384e-01
[21,] 0.28345355 5.669071e-01 7.165465e-01
[22,] 0.24607515 4.921503e-01 7.539248e-01
[23,] 0.31218644 6.243729e-01 6.878136e-01
[24,] 0.66995048 6.600990e-01 3.300495e-01
[25,] 0.62947669 7.410466e-01 3.705233e-01
[26,] 0.59670926 8.065815e-01 4.032907e-01
[27,] 0.55089824 8.982035e-01 4.491018e-01
[28,] 0.49880918 9.976184e-01 5.011908e-01
[29,] 0.44771973 8.954395e-01 5.522803e-01
[30,] 0.39221572 7.844314e-01 6.077843e-01
[31,] 0.38216521 7.643304e-01 6.178348e-01
[32,] 0.33729527 6.745905e-01 6.627047e-01
[33,] 0.29599796 5.919959e-01 7.040020e-01
[34,] 0.26386631 5.277326e-01 7.361337e-01
[35,] 0.24313773 4.862755e-01 7.568623e-01
[36,] 0.35611534 7.122307e-01 6.438847e-01
[37,] 0.55315968 8.936806e-01 4.468403e-01
[38,] 0.60280071 7.943986e-01 3.971993e-01
[39,] 0.59563448 8.087310e-01 4.043655e-01
[40,] 0.65317769 6.936446e-01 3.468223e-01
[41,] 0.76196314 4.760737e-01 2.380369e-01
[42,] 0.77784645 4.443071e-01 2.221536e-01
[43,] 0.75884124 4.823175e-01 2.411588e-01
[44,] 0.85418810 2.916238e-01 1.458119e-01
[45,] 0.82872253 3.425549e-01 1.712775e-01
[46,] 0.80505459 3.898908e-01 1.949454e-01
[47,] 0.77314120 4.537176e-01 2.268588e-01
[48,] 0.75104568 4.979086e-01 2.489543e-01
[49,] 0.75704593 4.859081e-01 2.429541e-01
[50,] 0.77240158 4.551968e-01 2.275984e-01
[51,] 0.73647026 5.270595e-01 2.635297e-01
[52,] 0.69648357 6.070329e-01 3.035164e-01
[53,] 0.67186375 6.562725e-01 3.281363e-01
[54,] 0.66881858 6.623628e-01 3.311814e-01
[55,] 0.63050620 7.389876e-01 3.694938e-01
[56,] 0.60092381 7.981524e-01 3.990762e-01
[57,] 0.56690197 8.661961e-01 4.330980e-01
[58,] 0.53530137 9.293973e-01 4.646986e-01
[59,] 0.54201348 9.159730e-01 4.579865e-01
[60,] 0.56789501 8.642100e-01 4.321050e-01
[61,] 0.56072232 8.785554e-01 4.392777e-01
[62,] 0.62839383 7.432123e-01 3.716062e-01
[63,] 0.60939952 7.812010e-01 3.906005e-01
[64,] 0.59556490 8.088702e-01 4.044351e-01
[65,] 0.66727418 6.654516e-01 3.327258e-01
[66,] 0.69769426 6.046115e-01 3.023057e-01
[67,] 0.76111761 4.777648e-01 2.388824e-01
[68,] 0.74448920 5.110216e-01 2.555108e-01
[69,] 0.76796474 4.640705e-01 2.320353e-01
[70,] 0.76051181 4.789764e-01 2.394882e-01
[71,] 0.73055282 5.388944e-01 2.694472e-01
[72,] 0.71694617 5.661077e-01 2.830538e-01
[73,] 0.80205008 3.958998e-01 1.979499e-01
[74,] 0.82238374 3.552325e-01 1.776163e-01
[75,] 0.85226577 2.954685e-01 1.477342e-01
[76,] 0.93454260 1.309148e-01 6.545740e-02
[77,] 0.92157889 1.568422e-01 7.842111e-02
[78,] 0.92175077 1.564985e-01 7.824923e-02
[79,] 0.90603411 1.879318e-01 9.396589e-02
[80,] 0.88712530 2.257494e-01 1.128747e-01
[81,] 0.87510077 2.497985e-01 1.248992e-01
[82,] 0.91111659 1.777668e-01 8.888341e-02
[83,] 0.89682420 2.063516e-01 1.031758e-01
[84,] 0.93214803 1.357039e-01 6.785197e-02
[85,] 0.93754255 1.249149e-01 6.245745e-02
[86,] 0.92840069 1.431986e-01 7.159931e-02
[87,] 0.93317458 1.336508e-01 6.682542e-02
[88,] 0.91688529 1.662294e-01 8.311471e-02
[89,] 0.90729865 1.854027e-01 9.270135e-02
[90,] 0.88868475 2.226305e-01 1.113152e-01
[91,] 0.86541583 2.691683e-01 1.345842e-01
[92,] 0.85663854 2.867229e-01 1.433615e-01
[93,] 0.90301053 1.939789e-01 9.698947e-02
[94,] 0.89127714 2.174457e-01 1.087229e-01
[95,] 0.88522157 2.295569e-01 1.147784e-01
[96,] 0.87854076 2.429185e-01 1.214592e-01
[97,] 0.90547934 1.890413e-01 9.452066e-02
[98,] 0.89379351 2.124130e-01 1.062065e-01
[99,] 0.87822763 2.435447e-01 1.217724e-01
[100,] 0.85986351 2.802730e-01 1.401365e-01
[101,] 0.84214721 3.157056e-01 1.578528e-01
[102,] 0.84146135 3.170773e-01 1.585386e-01
[103,] 0.81821267 3.635747e-01 1.817873e-01
[104,] 0.90777046 1.844591e-01 9.222954e-02
[105,] 0.90988107 1.802379e-01 9.011893e-02
[106,] 0.88700945 2.259811e-01 1.129906e-01
[107,] 0.90880868 1.823826e-01 9.119132e-02
[108,] 0.88829722 2.234056e-01 1.117028e-01
[109,] 0.88679754 2.264049e-01 1.132025e-01
[110,] 0.86944736 2.611053e-01 1.305526e-01
[111,] 0.85222811 2.955438e-01 1.477719e-01
[112,] 0.83216362 3.356728e-01 1.678364e-01
[113,] 0.83046726 3.390655e-01 1.695327e-01
[114,] 0.82118978 3.576204e-01 1.788102e-01
[115,] 0.92089690 1.582062e-01 7.910310e-02
[116,] 0.90007338 1.998532e-01 9.992662e-02
[117,] 0.90061137 1.987773e-01 9.938863e-02
[118,] 0.87348322 2.530336e-01 1.265168e-01
[119,] 0.86741763 2.651647e-01 1.325824e-01
[120,] 0.85672469 2.865506e-01 1.432753e-01
[121,] 0.82950633 3.409873e-01 1.704937e-01
[122,] 0.78591766 4.281647e-01 2.140823e-01
[123,] 0.81874419 3.625116e-01 1.812558e-01
[124,] 0.96223694 7.552612e-02 3.776306e-02
[125,] 0.94685765 1.062847e-01 5.314235e-02
[126,] 0.92680116 1.463977e-01 7.319884e-02
[127,] 0.93283289 1.343342e-01 6.716711e-02
[128,] 0.99970666 5.866790e-04 2.933395e-04
[129,] 0.99943442 1.131153e-03 5.655767e-04
[130,] 0.99948130 1.037399e-03 5.186993e-04
[131,] 0.99902116 1.957688e-03 9.788441e-04
[132,] 0.99966490 6.702049e-04 3.351024e-04
[133,] 0.99920599 1.588018e-03 7.940091e-04
[134,] 0.99999110 1.779145e-05 8.895724e-06
[135,] 0.99997333 5.333376e-05 2.666688e-05
[136,] 0.99995109 9.781153e-05 4.890577e-05
[137,] 0.99984231 3.153770e-04 1.576885e-04
[138,] 0.99975672 4.865590e-04 2.432795e-04
[139,] 0.99925140 1.497191e-03 7.485956e-04
[140,] 0.99779269 4.414619e-03 2.207309e-03
[141,] 0.99904942 1.901169e-03 9.505845e-04
[142,] 0.99987161 2.567850e-04 1.283925e-04
[143,] 0.99967090 6.581927e-04 3.290963e-04
[144,] 0.99934407 1.311855e-03 6.559274e-04
> postscript(file="/var/fisher/rcomp/tmp/1fwgw1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2jmrv1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3qkey1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/40j6d1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/59ksr1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 195
Frequency = 1
1 2 3 4 5 6
-0.78167302 1.20500037 0.03680685 0.74630019 1.80562469 0.29687459
7 8 9 10 11 12
0.92253225 4.93477988 -1.04783311 -0.92660013 -2.10477933 -0.56849523
13 14 15 16 17 18
0.57249264 -0.30478438 0.80681628 2.38278566 -0.39458531 1.57806450
19 20 21 22 23 24
1.04271289 -2.07514587 -0.16058805 0.34056754 3.95752227 0.61398952
25 26 27 28 29 30
0.09901452 0.78039640 1.27574125 -0.13847132 0.34717701 -0.37624433
31 32 33 34 35 36
-0.20194973 4.95761446 3.54286679 3.46628999 2.78757054 5.08304862
37 38 39 40 41 42
-1.06901341 -0.02383687 0.91086854 0.62211917 0.15168048 1.08127477
43 44 45 46 47 48
-2.69692617 -0.97785272 0.92885126 1.04126517 1.07754545 3.28396658
49 50 51 52 53 54
-0.83212491 0.26774677 0.66317855 0.45976010 -0.29268438 -0.01298221
55 56 57 58 59 60
-0.67861649 0.31053859 0.28039393 0.30072732 -0.05879324 -0.03053857
61 62 63 64 65 66
1.22046964 3.18780350 0.66646461 0.35494562 -1.28887434 -1.01611450
67 68 69 70 71 72
-1.96253344 -1.72193603 0.46316491 2.11717535 -0.97538758 0.10253027
73 74 75 76 77 78
1.11672031 -1.58573067 2.07202550 -0.60179774 0.17920249 0.33312729
79 80 81 82 83 84
0.76643325 -0.44799932 0.74520004 -0.87636359 0.05455290 1.29420919
85 86 87 88 89 90
-2.15088828 -1.39554995 -3.55991005 -0.19925813 0.55538312 -1.70740831
91 92 93 94 95 96
0.12655964 2.22672592 -1.06370948 1.48158889 0.62047758 -0.65895394
97 98 99 100 101 102
-1.37637686 -1.64226920 -2.90478230 -0.59899660 1.71331478 -0.35779842
103 104 105 106 107 108
2.02005298 -0.80878622 -0.56100056 -0.12222503 2.25280272 0.17941287
109 110 111 112 113 114
2.30012061 1.40540430 0.84336666 -2.61176688 0.53342767 -0.42985436
115 116 117 118 119 120
-1.17212192 0.46174373 1.42205810 2.91376493 0.66740264 1.16169027
121 122 123 124 125 126
0.36538798 2.12264776 -0.91973173 -0.65920462 -0.81956432 -1.33126260
127 128 129 130 131 132
-2.16430228 -1.65727930 2.43245331 1.64227509 0.36013787 2.39783196
133 134 135 136 137 138
-0.44740552 0.40512571 -1.74778750 -0.40815013 -1.23626845 -0.22726431
139 140 141 142 143 144
-0.63326915 -1.63691659 0.79635809 1.00181100 -0.91812843 -2.77390666
145 146 147 148 149 150
-1.19094088 -0.23436528 -0.91960526 -2.23641263 -0.16505404 -0.88542851
151 152 153 154 155 156
-1.86965600 2.84993573 2.22009759 -2.16676498 2.46098446 2.20730793
157 158 159 160 161 162
3.00121280 0.71805629 2.52675656 -2.35672515 -2.30271095 -1.58014903
163 164 165 166 167 168
-0.26467050 -2.33973247 -1.85015728 0.98808303 -2.49245021 -3.99043155
169 170 171 172 173 174
-2.44540174 -2.54690496 -1.54367371 0.05999685 -0.87077744 -0.73469146
175 176 177 178 179 180
-1.95941718 -0.33767514 -0.19389743 -0.98450661 -0.33830326 -0.33182903
181 182 183 184 185 186
-2.40146875 -0.88579336 -1.92270207 -0.28130365 -0.22780146 0.82545061
187 188 189 190 191 192
-0.59092370 0.09909850 0.02161336 -0.88205594 -0.39627918 -1.44100537
193 194 195
-1.84580325 -3.93442473 -0.94920296
> postscript(file="/var/fisher/rcomp/tmp/68kms1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 195
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.78167302 NA
1 1.20500037 -0.78167302
2 0.03680685 1.20500037
3 0.74630019 0.03680685
4 1.80562469 0.74630019
5 0.29687459 1.80562469
6 0.92253225 0.29687459
7 4.93477988 0.92253225
8 -1.04783311 4.93477988
9 -0.92660013 -1.04783311
10 -2.10477933 -0.92660013
11 -0.56849523 -2.10477933
12 0.57249264 -0.56849523
13 -0.30478438 0.57249264
14 0.80681628 -0.30478438
15 2.38278566 0.80681628
16 -0.39458531 2.38278566
17 1.57806450 -0.39458531
18 1.04271289 1.57806450
19 -2.07514587 1.04271289
20 -0.16058805 -2.07514587
21 0.34056754 -0.16058805
22 3.95752227 0.34056754
23 0.61398952 3.95752227
24 0.09901452 0.61398952
25 0.78039640 0.09901452
26 1.27574125 0.78039640
27 -0.13847132 1.27574125
28 0.34717701 -0.13847132
29 -0.37624433 0.34717701
30 -0.20194973 -0.37624433
31 4.95761446 -0.20194973
32 3.54286679 4.95761446
33 3.46628999 3.54286679
34 2.78757054 3.46628999
35 5.08304862 2.78757054
36 -1.06901341 5.08304862
37 -0.02383687 -1.06901341
38 0.91086854 -0.02383687
39 0.62211917 0.91086854
40 0.15168048 0.62211917
41 1.08127477 0.15168048
42 -2.69692617 1.08127477
43 -0.97785272 -2.69692617
44 0.92885126 -0.97785272
45 1.04126517 0.92885126
46 1.07754545 1.04126517
47 3.28396658 1.07754545
48 -0.83212491 3.28396658
49 0.26774677 -0.83212491
50 0.66317855 0.26774677
51 0.45976010 0.66317855
52 -0.29268438 0.45976010
53 -0.01298221 -0.29268438
54 -0.67861649 -0.01298221
55 0.31053859 -0.67861649
56 0.28039393 0.31053859
57 0.30072732 0.28039393
58 -0.05879324 0.30072732
59 -0.03053857 -0.05879324
60 1.22046964 -0.03053857
61 3.18780350 1.22046964
62 0.66646461 3.18780350
63 0.35494562 0.66646461
64 -1.28887434 0.35494562
65 -1.01611450 -1.28887434
66 -1.96253344 -1.01611450
67 -1.72193603 -1.96253344
68 0.46316491 -1.72193603
69 2.11717535 0.46316491
70 -0.97538758 2.11717535
71 0.10253027 -0.97538758
72 1.11672031 0.10253027
73 -1.58573067 1.11672031
74 2.07202550 -1.58573067
75 -0.60179774 2.07202550
76 0.17920249 -0.60179774
77 0.33312729 0.17920249
78 0.76643325 0.33312729
79 -0.44799932 0.76643325
80 0.74520004 -0.44799932
81 -0.87636359 0.74520004
82 0.05455290 -0.87636359
83 1.29420919 0.05455290
84 -2.15088828 1.29420919
85 -1.39554995 -2.15088828
86 -3.55991005 -1.39554995
87 -0.19925813 -3.55991005
88 0.55538312 -0.19925813
89 -1.70740831 0.55538312
90 0.12655964 -1.70740831
91 2.22672592 0.12655964
92 -1.06370948 2.22672592
93 1.48158889 -1.06370948
94 0.62047758 1.48158889
95 -0.65895394 0.62047758
96 -1.37637686 -0.65895394
97 -1.64226920 -1.37637686
98 -2.90478230 -1.64226920
99 -0.59899660 -2.90478230
100 1.71331478 -0.59899660
101 -0.35779842 1.71331478
102 2.02005298 -0.35779842
103 -0.80878622 2.02005298
104 -0.56100056 -0.80878622
105 -0.12222503 -0.56100056
106 2.25280272 -0.12222503
107 0.17941287 2.25280272
108 2.30012061 0.17941287
109 1.40540430 2.30012061
110 0.84336666 1.40540430
111 -2.61176688 0.84336666
112 0.53342767 -2.61176688
113 -0.42985436 0.53342767
114 -1.17212192 -0.42985436
115 0.46174373 -1.17212192
116 1.42205810 0.46174373
117 2.91376493 1.42205810
118 0.66740264 2.91376493
119 1.16169027 0.66740264
120 0.36538798 1.16169027
121 2.12264776 0.36538798
122 -0.91973173 2.12264776
123 -0.65920462 -0.91973173
124 -0.81956432 -0.65920462
125 -1.33126260 -0.81956432
126 -2.16430228 -1.33126260
127 -1.65727930 -2.16430228
128 2.43245331 -1.65727930
129 1.64227509 2.43245331
130 0.36013787 1.64227509
131 2.39783196 0.36013787
132 -0.44740552 2.39783196
133 0.40512571 -0.44740552
134 -1.74778750 0.40512571
135 -0.40815013 -1.74778750
136 -1.23626845 -0.40815013
137 -0.22726431 -1.23626845
138 -0.63326915 -0.22726431
139 -1.63691659 -0.63326915
140 0.79635809 -1.63691659
141 1.00181100 0.79635809
142 -0.91812843 1.00181100
143 -2.77390666 -0.91812843
144 -1.19094088 -2.77390666
145 -0.23436528 -1.19094088
146 -0.91960526 -0.23436528
147 -2.23641263 -0.91960526
148 -0.16505404 -2.23641263
149 -0.88542851 -0.16505404
150 -1.86965600 -0.88542851
151 2.84993573 -1.86965600
152 2.22009759 2.84993573
153 -2.16676498 2.22009759
154 2.46098446 -2.16676498
155 2.20730793 2.46098446
156 3.00121280 2.20730793
157 0.71805629 3.00121280
158 2.52675656 0.71805629
159 -2.35672515 2.52675656
160 -2.30271095 -2.35672515
161 -1.58014903 -2.30271095
162 -0.26467050 -1.58014903
163 -2.33973247 -0.26467050
164 -1.85015728 -2.33973247
165 0.98808303 -1.85015728
166 -2.49245021 0.98808303
167 -3.99043155 -2.49245021
168 -2.44540174 -3.99043155
169 -2.54690496 -2.44540174
170 -1.54367371 -2.54690496
171 0.05999685 -1.54367371
172 -0.87077744 0.05999685
173 -0.73469146 -0.87077744
174 -1.95941718 -0.73469146
175 -0.33767514 -1.95941718
176 -0.19389743 -0.33767514
177 -0.98450661 -0.19389743
178 -0.33830326 -0.98450661
179 -0.33182903 -0.33830326
180 -2.40146875 -0.33182903
181 -0.88579336 -2.40146875
182 -1.92270207 -0.88579336
183 -0.28130365 -1.92270207
184 -0.22780146 -0.28130365
185 0.82545061 -0.22780146
186 -0.59092370 0.82545061
187 0.09909850 -0.59092370
188 0.02161336 0.09909850
189 -0.88205594 0.02161336
190 -0.39627918 -0.88205594
191 -1.44100537 -0.39627918
192 -1.84580325 -1.44100537
193 -3.93442473 -1.84580325
194 -0.94920296 -3.93442473
195 NA -0.94920296
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.20500037 -0.78167302
[2,] 0.03680685 1.20500037
[3,] 0.74630019 0.03680685
[4,] 1.80562469 0.74630019
[5,] 0.29687459 1.80562469
[6,] 0.92253225 0.29687459
[7,] 4.93477988 0.92253225
[8,] -1.04783311 4.93477988
[9,] -0.92660013 -1.04783311
[10,] -2.10477933 -0.92660013
[11,] -0.56849523 -2.10477933
[12,] 0.57249264 -0.56849523
[13,] -0.30478438 0.57249264
[14,] 0.80681628 -0.30478438
[15,] 2.38278566 0.80681628
[16,] -0.39458531 2.38278566
[17,] 1.57806450 -0.39458531
[18,] 1.04271289 1.57806450
[19,] -2.07514587 1.04271289
[20,] -0.16058805 -2.07514587
[21,] 0.34056754 -0.16058805
[22,] 3.95752227 0.34056754
[23,] 0.61398952 3.95752227
[24,] 0.09901452 0.61398952
[25,] 0.78039640 0.09901452
[26,] 1.27574125 0.78039640
[27,] -0.13847132 1.27574125
[28,] 0.34717701 -0.13847132
[29,] -0.37624433 0.34717701
[30,] -0.20194973 -0.37624433
[31,] 4.95761446 -0.20194973
[32,] 3.54286679 4.95761446
[33,] 3.46628999 3.54286679
[34,] 2.78757054 3.46628999
[35,] 5.08304862 2.78757054
[36,] -1.06901341 5.08304862
[37,] -0.02383687 -1.06901341
[38,] 0.91086854 -0.02383687
[39,] 0.62211917 0.91086854
[40,] 0.15168048 0.62211917
[41,] 1.08127477 0.15168048
[42,] -2.69692617 1.08127477
[43,] -0.97785272 -2.69692617
[44,] 0.92885126 -0.97785272
[45,] 1.04126517 0.92885126
[46,] 1.07754545 1.04126517
[47,] 3.28396658 1.07754545
[48,] -0.83212491 3.28396658
[49,] 0.26774677 -0.83212491
[50,] 0.66317855 0.26774677
[51,] 0.45976010 0.66317855
[52,] -0.29268438 0.45976010
[53,] -0.01298221 -0.29268438
[54,] -0.67861649 -0.01298221
[55,] 0.31053859 -0.67861649
[56,] 0.28039393 0.31053859
[57,] 0.30072732 0.28039393
[58,] -0.05879324 0.30072732
[59,] -0.03053857 -0.05879324
[60,] 1.22046964 -0.03053857
[61,] 3.18780350 1.22046964
[62,] 0.66646461 3.18780350
[63,] 0.35494562 0.66646461
[64,] -1.28887434 0.35494562
[65,] -1.01611450 -1.28887434
[66,] -1.96253344 -1.01611450
[67,] -1.72193603 -1.96253344
[68,] 0.46316491 -1.72193603
[69,] 2.11717535 0.46316491
[70,] -0.97538758 2.11717535
[71,] 0.10253027 -0.97538758
[72,] 1.11672031 0.10253027
[73,] -1.58573067 1.11672031
[74,] 2.07202550 -1.58573067
[75,] -0.60179774 2.07202550
[76,] 0.17920249 -0.60179774
[77,] 0.33312729 0.17920249
[78,] 0.76643325 0.33312729
[79,] -0.44799932 0.76643325
[80,] 0.74520004 -0.44799932
[81,] -0.87636359 0.74520004
[82,] 0.05455290 -0.87636359
[83,] 1.29420919 0.05455290
[84,] -2.15088828 1.29420919
[85,] -1.39554995 -2.15088828
[86,] -3.55991005 -1.39554995
[87,] -0.19925813 -3.55991005
[88,] 0.55538312 -0.19925813
[89,] -1.70740831 0.55538312
[90,] 0.12655964 -1.70740831
[91,] 2.22672592 0.12655964
[92,] -1.06370948 2.22672592
[93,] 1.48158889 -1.06370948
[94,] 0.62047758 1.48158889
[95,] -0.65895394 0.62047758
[96,] -1.37637686 -0.65895394
[97,] -1.64226920 -1.37637686
[98,] -2.90478230 -1.64226920
[99,] -0.59899660 -2.90478230
[100,] 1.71331478 -0.59899660
[101,] -0.35779842 1.71331478
[102,] 2.02005298 -0.35779842
[103,] -0.80878622 2.02005298
[104,] -0.56100056 -0.80878622
[105,] -0.12222503 -0.56100056
[106,] 2.25280272 -0.12222503
[107,] 0.17941287 2.25280272
[108,] 2.30012061 0.17941287
[109,] 1.40540430 2.30012061
[110,] 0.84336666 1.40540430
[111,] -2.61176688 0.84336666
[112,] 0.53342767 -2.61176688
[113,] -0.42985436 0.53342767
[114,] -1.17212192 -0.42985436
[115,] 0.46174373 -1.17212192
[116,] 1.42205810 0.46174373
[117,] 2.91376493 1.42205810
[118,] 0.66740264 2.91376493
[119,] 1.16169027 0.66740264
[120,] 0.36538798 1.16169027
[121,] 2.12264776 0.36538798
[122,] -0.91973173 2.12264776
[123,] -0.65920462 -0.91973173
[124,] -0.81956432 -0.65920462
[125,] -1.33126260 -0.81956432
[126,] -2.16430228 -1.33126260
[127,] -1.65727930 -2.16430228
[128,] 2.43245331 -1.65727930
[129,] 1.64227509 2.43245331
[130,] 0.36013787 1.64227509
[131,] 2.39783196 0.36013787
[132,] -0.44740552 2.39783196
[133,] 0.40512571 -0.44740552
[134,] -1.74778750 0.40512571
[135,] -0.40815013 -1.74778750
[136,] -1.23626845 -0.40815013
[137,] -0.22726431 -1.23626845
[138,] -0.63326915 -0.22726431
[139,] -1.63691659 -0.63326915
[140,] 0.79635809 -1.63691659
[141,] 1.00181100 0.79635809
[142,] -0.91812843 1.00181100
[143,] -2.77390666 -0.91812843
[144,] -1.19094088 -2.77390666
[145,] -0.23436528 -1.19094088
[146,] -0.91960526 -0.23436528
[147,] -2.23641263 -0.91960526
[148,] -0.16505404 -2.23641263
[149,] -0.88542851 -0.16505404
[150,] -1.86965600 -0.88542851
[151,] 2.84993573 -1.86965600
[152,] 2.22009759 2.84993573
[153,] -2.16676498 2.22009759
[154,] 2.46098446 -2.16676498
[155,] 2.20730793 2.46098446
[156,] 3.00121280 2.20730793
[157,] 0.71805629 3.00121280
[158,] 2.52675656 0.71805629
[159,] -2.35672515 2.52675656
[160,] -2.30271095 -2.35672515
[161,] -1.58014903 -2.30271095
[162,] -0.26467050 -1.58014903
[163,] -2.33973247 -0.26467050
[164,] -1.85015728 -2.33973247
[165,] 0.98808303 -1.85015728
[166,] -2.49245021 0.98808303
[167,] -3.99043155 -2.49245021
[168,] -2.44540174 -3.99043155
[169,] -2.54690496 -2.44540174
[170,] -1.54367371 -2.54690496
[171,] 0.05999685 -1.54367371
[172,] -0.87077744 0.05999685
[173,] -0.73469146 -0.87077744
[174,] -1.95941718 -0.73469146
[175,] -0.33767514 -1.95941718
[176,] -0.19389743 -0.33767514
[177,] -0.98450661 -0.19389743
[178,] -0.33830326 -0.98450661
[179,] -0.33182903 -0.33830326
[180,] -2.40146875 -0.33182903
[181,] -0.88579336 -2.40146875
[182,] -1.92270207 -0.88579336
[183,] -0.28130365 -1.92270207
[184,] -0.22780146 -0.28130365
[185,] 0.82545061 -0.22780146
[186,] -0.59092370 0.82545061
[187,] 0.09909850 -0.59092370
[188,] 0.02161336 0.09909850
[189,] -0.88205594 0.02161336
[190,] -0.39627918 -0.88205594
[191,] -1.44100537 -0.39627918
[192,] -1.84580325 -1.44100537
[193,] -3.93442473 -1.84580325
[194,] -0.94920296 -3.93442473
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.20500037 -0.78167302
2 0.03680685 1.20500037
3 0.74630019 0.03680685
4 1.80562469 0.74630019
5 0.29687459 1.80562469
6 0.92253225 0.29687459
7 4.93477988 0.92253225
8 -1.04783311 4.93477988
9 -0.92660013 -1.04783311
10 -2.10477933 -0.92660013
11 -0.56849523 -2.10477933
12 0.57249264 -0.56849523
13 -0.30478438 0.57249264
14 0.80681628 -0.30478438
15 2.38278566 0.80681628
16 -0.39458531 2.38278566
17 1.57806450 -0.39458531
18 1.04271289 1.57806450
19 -2.07514587 1.04271289
20 -0.16058805 -2.07514587
21 0.34056754 -0.16058805
22 3.95752227 0.34056754
23 0.61398952 3.95752227
24 0.09901452 0.61398952
25 0.78039640 0.09901452
26 1.27574125 0.78039640
27 -0.13847132 1.27574125
28 0.34717701 -0.13847132
29 -0.37624433 0.34717701
30 -0.20194973 -0.37624433
31 4.95761446 -0.20194973
32 3.54286679 4.95761446
33 3.46628999 3.54286679
34 2.78757054 3.46628999
35 5.08304862 2.78757054
36 -1.06901341 5.08304862
37 -0.02383687 -1.06901341
38 0.91086854 -0.02383687
39 0.62211917 0.91086854
40 0.15168048 0.62211917
41 1.08127477 0.15168048
42 -2.69692617 1.08127477
43 -0.97785272 -2.69692617
44 0.92885126 -0.97785272
45 1.04126517 0.92885126
46 1.07754545 1.04126517
47 3.28396658 1.07754545
48 -0.83212491 3.28396658
49 0.26774677 -0.83212491
50 0.66317855 0.26774677
51 0.45976010 0.66317855
52 -0.29268438 0.45976010
53 -0.01298221 -0.29268438
54 -0.67861649 -0.01298221
55 0.31053859 -0.67861649
56 0.28039393 0.31053859
57 0.30072732 0.28039393
58 -0.05879324 0.30072732
59 -0.03053857 -0.05879324
60 1.22046964 -0.03053857
61 3.18780350 1.22046964
62 0.66646461 3.18780350
63 0.35494562 0.66646461
64 -1.28887434 0.35494562
65 -1.01611450 -1.28887434
66 -1.96253344 -1.01611450
67 -1.72193603 -1.96253344
68 0.46316491 -1.72193603
69 2.11717535 0.46316491
70 -0.97538758 2.11717535
71 0.10253027 -0.97538758
72 1.11672031 0.10253027
73 -1.58573067 1.11672031
74 2.07202550 -1.58573067
75 -0.60179774 2.07202550
76 0.17920249 -0.60179774
77 0.33312729 0.17920249
78 0.76643325 0.33312729
79 -0.44799932 0.76643325
80 0.74520004 -0.44799932
81 -0.87636359 0.74520004
82 0.05455290 -0.87636359
83 1.29420919 0.05455290
84 -2.15088828 1.29420919
85 -1.39554995 -2.15088828
86 -3.55991005 -1.39554995
87 -0.19925813 -3.55991005
88 0.55538312 -0.19925813
89 -1.70740831 0.55538312
90 0.12655964 -1.70740831
91 2.22672592 0.12655964
92 -1.06370948 2.22672592
93 1.48158889 -1.06370948
94 0.62047758 1.48158889
95 -0.65895394 0.62047758
96 -1.37637686 -0.65895394
97 -1.64226920 -1.37637686
98 -2.90478230 -1.64226920
99 -0.59899660 -2.90478230
100 1.71331478 -0.59899660
101 -0.35779842 1.71331478
102 2.02005298 -0.35779842
103 -0.80878622 2.02005298
104 -0.56100056 -0.80878622
105 -0.12222503 -0.56100056
106 2.25280272 -0.12222503
107 0.17941287 2.25280272
108 2.30012061 0.17941287
109 1.40540430 2.30012061
110 0.84336666 1.40540430
111 -2.61176688 0.84336666
112 0.53342767 -2.61176688
113 -0.42985436 0.53342767
114 -1.17212192 -0.42985436
115 0.46174373 -1.17212192
116 1.42205810 0.46174373
117 2.91376493 1.42205810
118 0.66740264 2.91376493
119 1.16169027 0.66740264
120 0.36538798 1.16169027
121 2.12264776 0.36538798
122 -0.91973173 2.12264776
123 -0.65920462 -0.91973173
124 -0.81956432 -0.65920462
125 -1.33126260 -0.81956432
126 -2.16430228 -1.33126260
127 -1.65727930 -2.16430228
128 2.43245331 -1.65727930
129 1.64227509 2.43245331
130 0.36013787 1.64227509
131 2.39783196 0.36013787
132 -0.44740552 2.39783196
133 0.40512571 -0.44740552
134 -1.74778750 0.40512571
135 -0.40815013 -1.74778750
136 -1.23626845 -0.40815013
137 -0.22726431 -1.23626845
138 -0.63326915 -0.22726431
139 -1.63691659 -0.63326915
140 0.79635809 -1.63691659
141 1.00181100 0.79635809
142 -0.91812843 1.00181100
143 -2.77390666 -0.91812843
144 -1.19094088 -2.77390666
145 -0.23436528 -1.19094088
146 -0.91960526 -0.23436528
147 -2.23641263 -0.91960526
148 -0.16505404 -2.23641263
149 -0.88542851 -0.16505404
150 -1.86965600 -0.88542851
151 2.84993573 -1.86965600
152 2.22009759 2.84993573
153 -2.16676498 2.22009759
154 2.46098446 -2.16676498
155 2.20730793 2.46098446
156 3.00121280 2.20730793
157 0.71805629 3.00121280
158 2.52675656 0.71805629
159 -2.35672515 2.52675656
160 -2.30271095 -2.35672515
161 -1.58014903 -2.30271095
162 -0.26467050 -1.58014903
163 -2.33973247 -0.26467050
164 -1.85015728 -2.33973247
165 0.98808303 -1.85015728
166 -2.49245021 0.98808303
167 -3.99043155 -2.49245021
168 -2.44540174 -3.99043155
169 -2.54690496 -2.44540174
170 -1.54367371 -2.54690496
171 0.05999685 -1.54367371
172 -0.87077744 0.05999685
173 -0.73469146 -0.87077744
174 -1.95941718 -0.73469146
175 -0.33767514 -1.95941718
176 -0.19389743 -0.33767514
177 -0.98450661 -0.19389743
178 -0.33830326 -0.98450661
179 -0.33182903 -0.33830326
180 -2.40146875 -0.33182903
181 -0.88579336 -2.40146875
182 -1.92270207 -0.88579336
183 -0.28130365 -1.92270207
184 -0.22780146 -0.28130365
185 0.82545061 -0.22780146
186 -0.59092370 0.82545061
187 0.09909850 -0.59092370
188 0.02161336 0.09909850
189 -0.88205594 0.02161336
190 -0.39627918 -0.88205594
191 -1.44100537 -0.39627918
192 -1.84580325 -1.44100537
193 -3.93442473 -1.84580325
194 -0.94920296 -3.93442473
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/7krju1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8pskz1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/95c7u1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10tvvq1386010214.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/11dog71386010214.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,signif(mysum$coefficients[i,1],6))
+ a<-table.element(a, signif(mysum$coefficients[i,2],6))
+ a<-table.element(a, signif(mysum$coefficients[i,3],4))
+ a<-table.element(a, signif(mysum$coefficients[i,4],6))
+ a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/12rr6x1386010214.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, signif(sqrt(mysum$r.squared),6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, signif(mysum$r.squared,6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, signif(mysum$adj.r.squared,6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[1],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[2],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[3],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, signif(mysum$sigma,6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, signif(sum(myerror*myerror),6))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/137mxe1386010214.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,signif(x[i],6))
+ a<-table.element(a,signif(x[i]-mysum$resid[i],6))
+ a<-table.element(a,signif(mysum$resid[i],6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/fisher/rcomp/tmp/1413nd1386010214.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
+ a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
+ a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/15i54c1386010214.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,signif(numsignificant1,6))
+ a<-table.element(a,signif(numsignificant1/numgqtests,6))
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,signif(numsignificant5,6))
+ a<-table.element(a,signif(numsignificant5/numgqtests,6))
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,signif(numsignificant10,6))
+ a<-table.element(a,signif(numsignificant10/numgqtests,6))
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/168grh1386010214.tab")
+ }
>
> try(system("convert tmp/1fwgw1386010214.ps tmp/1fwgw1386010214.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jmrv1386010214.ps tmp/2jmrv1386010214.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qkey1386010214.ps tmp/3qkey1386010214.png",intern=TRUE))
character(0)
> try(system("convert tmp/40j6d1386010214.ps tmp/40j6d1386010214.png",intern=TRUE))
character(0)
> try(system("convert tmp/59ksr1386010214.ps tmp/59ksr1386010214.png",intern=TRUE))
character(0)
> try(system("convert tmp/68kms1386010214.ps tmp/68kms1386010214.png",intern=TRUE))
character(0)
> try(system("convert tmp/7krju1386010214.ps tmp/7krju1386010214.png",intern=TRUE))
character(0)
> try(system("convert tmp/8pskz1386010214.ps tmp/8pskz1386010214.png",intern=TRUE))
character(0)
> try(system("convert tmp/95c7u1386010214.ps tmp/95c7u1386010214.png",intern=TRUE))
character(0)
> try(system("convert tmp/10tvvq1386010214.ps tmp/10tvvq1386010214.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
29.750 3.909 33.664