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)
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Type 'contributors()' for more information and
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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
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+ ,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
+ ,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
+ ,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
+ ,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
+ ,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
+ ,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
+ ,21.209
+ ,0
+ ,0.462803
+ ,0.664357
+ ,-5.724056
+ ,0.190667
+ ,2.555477
+ ,0.148569)
+ ,dim=c(22
+ ,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'
+ ,'HNR'
+ ,'status'
+ ,'RPDE'
+ ,'DFA'
+ ,'spread1'
+ ,'spread2'
+ ,'D2'
+ ,'PPE')
+ ,1:195))
> y <- array(NA,dim=c(22,195),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','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 = 'Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '16'
> par3 <- '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
status MDVP:Fo(Hz) MDVP:Fhi(Hz) MDVP:Flo(Hz) MDVP:Jitter(%)
1 1 119.992 157.302 74.997 0.00784
2 1 122.400 148.650 113.819 0.00968
3 1 116.682 131.111 111.555 0.01050
4 1 116.676 137.871 111.366 0.00997
5 1 116.014 141.781 110.655 0.01284
6 1 120.552 131.162 113.787 0.00968
7 1 120.267 137.244 114.820 0.00333
8 1 107.332 113.840 104.315 0.00290
9 1 95.730 132.068 91.754 0.00551
10 1 95.056 120.103 91.226 0.00532
11 1 88.333 112.240 84.072 0.00505
12 1 91.904 115.871 86.292 0.00540
13 1 136.926 159.866 131.276 0.00293
14 1 139.173 179.139 76.556 0.00390
15 1 152.845 163.305 75.836 0.00294
16 1 142.167 217.455 83.159 0.00369
17 1 144.188 349.259 82.764 0.00544
18 1 168.778 232.181 75.603 0.00718
19 1 153.046 175.829 68.623 0.00742
20 1 156.405 189.398 142.822 0.00768
21 1 153.848 165.738 65.782 0.00840
22 1 153.880 172.860 78.128 0.00480
23 1 167.930 193.221 79.068 0.00442
24 1 173.917 192.735 86.180 0.00476
25 1 163.656 200.841 76.779 0.00742
26 1 104.400 206.002 77.968 0.00633
27 1 171.041 208.313 75.501 0.00455
28 1 146.845 208.701 81.737 0.00496
29 1 155.358 227.383 80.055 0.00310
30 1 162.568 198.346 77.630 0.00502
31 0 197.076 206.896 192.055 0.00289
32 0 199.228 209.512 192.091 0.00241
33 0 198.383 215.203 193.104 0.00212
34 0 202.266 211.604 197.079 0.00180
35 0 203.184 211.526 196.160 0.00178
36 0 201.464 210.565 195.708 0.00198
37 1 177.876 192.921 168.013 0.00411
38 1 176.170 185.604 163.564 0.00369
39 1 180.198 201.249 175.456 0.00284
40 1 187.733 202.324 173.015 0.00316
41 1 186.163 197.724 177.584 0.00298
42 1 184.055 196.537 166.977 0.00258
43 0 237.226 247.326 225.227 0.00298
44 0 241.404 248.834 232.483 0.00281
45 0 243.439 250.912 232.435 0.00210
46 0 242.852 255.034 227.911 0.00225
47 0 245.510 262.090 231.848 0.00235
48 0 252.455 261.487 182.786 0.00185
49 0 122.188 128.611 115.765 0.00524
50 0 122.964 130.049 114.676 0.00428
51 0 124.445 135.069 117.495 0.00431
52 0 126.344 134.231 112.773 0.00448
53 0 128.001 138.052 122.080 0.00436
54 0 129.336 139.867 118.604 0.00490
55 1 108.807 134.656 102.874 0.00761
56 1 109.860 126.358 104.437 0.00874
57 1 110.417 131.067 103.370 0.00784
58 1 117.274 129.916 110.402 0.00752
59 1 116.879 131.897 108.153 0.00788
60 1 114.847 271.314 104.680 0.00867
61 0 209.144 237.494 109.379 0.00282
62 0 223.365 238.987 98.664 0.00264
63 0 222.236 231.345 205.495 0.00266
64 0 228.832 234.619 223.634 0.00296
65 0 229.401 252.221 221.156 0.00205
66 0 228.969 239.541 113.201 0.00238
67 1 140.341 159.774 67.021 0.00817
68 1 136.969 166.607 66.004 0.00923
69 1 143.533 162.215 65.809 0.01101
70 1 148.090 162.824 67.343 0.00762
71 1 142.729 162.408 65.476 0.00831
72 1 136.358 176.595 65.750 0.00971
73 1 120.080 139.710 111.208 0.00405
74 1 112.014 588.518 107.024 0.00533
75 1 110.793 128.101 107.316 0.00494
76 1 110.707 122.611 105.007 0.00516
77 1 112.876 148.826 106.981 0.00500
78 1 110.568 125.394 106.821 0.00462
79 1 95.385 102.145 90.264 0.00608
80 1 100.770 115.697 85.545 0.01038
81 1 96.106 108.664 84.510 0.00694
82 1 95.605 107.715 87.549 0.00702
83 1 100.960 110.019 95.628 0.00606
84 1 98.804 102.305 87.804 0.00432
85 1 176.858 205.560 75.344 0.00747
86 1 180.978 200.125 155.495 0.00406
87 1 178.222 202.450 141.047 0.00321
88 1 176.281 227.381 125.610 0.00520
89 1 173.898 211.350 74.677 0.00448
90 1 179.711 225.930 144.878 0.00709
91 1 166.605 206.008 78.032 0.00742
92 1 151.955 163.335 147.226 0.00419
93 1 148.272 164.989 142.299 0.00459
94 1 152.125 161.469 76.596 0.00382
95 1 157.821 172.975 68.401 0.00358
96 1 157.447 163.267 149.605 0.00369
97 1 159.116 168.913 144.811 0.00342
98 1 125.036 143.946 116.187 0.01280
99 1 125.791 140.557 96.206 0.01378
100 1 126.512 141.756 99.770 0.01936
101 1 125.641 141.068 116.346 0.03316
102 1 128.451 150.449 75.632 0.01551
103 1 139.224 586.567 66.157 0.03011
104 1 150.258 154.609 75.349 0.00248
105 1 154.003 160.267 128.621 0.00183
106 1 149.689 160.368 133.608 0.00257
107 1 155.078 163.736 144.148 0.00168
108 1 151.884 157.765 133.751 0.00258
109 1 151.989 157.339 132.857 0.00174
110 1 193.030 208.900 80.297 0.00766
111 1 200.714 223.982 89.686 0.00621
112 1 208.519 220.315 199.020 0.00609
113 1 204.664 221.300 189.621 0.00841
114 1 210.141 232.706 185.258 0.00534
115 1 206.327 226.355 92.020 0.00495
116 1 151.872 492.892 69.085 0.00856
117 1 158.219 442.557 71.948 0.00476
118 1 170.756 450.247 79.032 0.00555
119 1 178.285 442.824 82.063 0.00462
120 1 217.116 233.481 93.978 0.00404
121 1 128.940 479.697 88.251 0.00581
122 1 176.824 215.293 83.961 0.00460
123 1 138.190 203.522 83.340 0.00704
124 1 182.018 197.173 79.187 0.00842
125 1 156.239 195.107 79.820 0.00694
126 1 145.174 198.109 80.637 0.00733
127 1 138.145 197.238 81.114 0.00544
128 1 166.888 198.966 79.512 0.00638
129 1 119.031 127.533 109.216 0.00440
130 1 120.078 126.632 105.667 0.00270
131 1 120.289 128.143 100.209 0.00492
132 1 120.256 125.306 104.773 0.00407
133 1 119.056 125.213 86.795 0.00346
134 1 118.747 123.723 109.836 0.00331
135 1 106.516 112.777 93.105 0.00589
136 1 110.453 127.611 105.554 0.00494
137 1 113.400 133.344 107.816 0.00451
138 1 113.166 130.270 100.673 0.00502
139 1 112.239 126.609 104.095 0.00472
140 1 116.150 131.731 109.815 0.00381
141 1 170.368 268.796 79.543 0.00571
142 1 208.083 253.792 91.802 0.00757
143 1 198.458 219.290 148.691 0.00376
144 1 202.805 231.508 86.232 0.00370
145 1 202.544 241.350 164.168 0.00254
146 1 223.361 263.872 87.638 0.00352
147 1 169.774 191.759 151.451 0.01568
148 1 183.520 216.814 161.340 0.01466
149 1 188.620 216.302 165.982 0.01719
150 1 202.632 565.740 177.258 0.01627
151 1 186.695 211.961 149.442 0.01872
152 1 192.818 224.429 168.793 0.03107
153 1 198.116 233.099 174.478 0.02714
154 1 121.345 139.644 98.250 0.00684
155 1 119.100 128.442 88.833 0.00692
156 1 117.870 127.349 95.654 0.00647
157 1 122.336 142.369 94.794 0.00727
158 1 117.963 134.209 100.757 0.01813
159 1 126.144 154.284 97.543 0.00975
160 1 127.930 138.752 112.173 0.00605
161 1 114.238 124.393 77.022 0.00581
162 1 115.322 135.738 107.802 0.00619
163 1 114.554 126.778 91.121 0.00651
164 1 112.150 131.669 97.527 0.00519
165 1 102.273 142.830 85.902 0.00907
166 0 236.200 244.663 102.137 0.00277
167 0 237.323 243.709 229.256 0.00303
168 0 260.105 264.919 237.303 0.00339
169 0 197.569 217.627 90.794 0.00803
170 0 240.301 245.135 219.783 0.00517
171 0 244.990 272.210 239.170 0.00451
172 0 112.547 133.374 105.715 0.00355
173 0 110.739 113.597 100.139 0.00356
174 0 113.715 116.443 96.913 0.00349
175 0 117.004 144.466 99.923 0.00353
176 0 115.380 123.109 108.634 0.00332
177 0 116.388 129.038 108.970 0.00346
178 1 151.737 190.204 129.859 0.00314
179 1 148.790 158.359 138.990 0.00309
180 1 148.143 155.982 135.041 0.00392
181 1 150.440 163.441 144.736 0.00396
182 1 148.462 161.078 141.998 0.00397
183 1 149.818 163.417 144.786 0.00336
184 0 117.226 123.925 106.656 0.00417
185 0 116.848 217.552 99.503 0.00531
186 0 116.286 177.291 96.983 0.00314
187 0 116.556 592.030 86.228 0.00496
188 0 116.342 581.289 94.246 0.00267
189 0 114.563 119.167 86.647 0.00327
190 0 201.774 262.707 78.228 0.00694
191 0 174.188 230.978 94.261 0.00459
192 0 209.516 253.017 89.488 0.00564
193 0 174.688 240.005 74.287 0.01360
194 0 198.764 396.961 74.904 0.00740
195 0 214.289 260.277 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 HNR RPDE DFA
1 0.02182 0.03130 0.02971 0.06545 21.033 0.414783 0.815285
2 0.03134 0.04518 0.04368 0.09403 19.085 0.458359 0.819521
3 0.02757 0.03858 0.03590 0.08270 20.651 0.429895 0.825288
4 0.02924 0.04005 0.03772 0.08771 20.644 0.434969 0.819235
5 0.03490 0.04825 0.04465 0.10470 19.649 0.417356 0.823484
6 0.02328 0.03526 0.03243 0.06985 21.378 0.415564 0.825069
7 0.00779 0.00937 0.01351 0.02337 24.886 0.596040 0.764112
8 0.00829 0.00946 0.01256 0.02487 26.892 0.637420 0.763262
9 0.01073 0.01277 0.01717 0.03218 21.812 0.615551 0.773587
10 0.01441 0.01725 0.02444 0.04324 21.862 0.547037 0.798463
11 0.01079 0.01342 0.01892 0.03237 21.118 0.611137 0.776156
12 0.01424 0.01641 0.02214 0.04272 21.414 0.583390 0.792520
13 0.00656 0.00717 0.01140 0.01968 25.703 0.460600 0.646846
14 0.00728 0.00932 0.01797 0.02184 24.889 0.430166 0.665833
15 0.01064 0.00972 0.01246 0.03191 24.922 0.474791 0.654027
16 0.00772 0.00888 0.01359 0.02316 25.175 0.565924 0.658245
17 0.00969 0.01200 0.02074 0.02908 22.333 0.567380 0.644692
18 0.01441 0.01893 0.03430 0.04322 20.376 0.631099 0.605417
19 0.02471 0.03572 0.05767 0.07413 17.280 0.665318 0.719467
20 0.01721 0.02374 0.04310 0.05164 17.153 0.649554 0.686080
21 0.01667 0.02383 0.04055 0.05000 17.536 0.660125 0.704087
22 0.02021 0.02591 0.04525 0.06062 19.493 0.629017 0.698951
23 0.02228 0.02540 0.04246 0.06685 22.468 0.619060 0.679834
24 0.02187 0.02470 0.03772 0.06562 20.422 0.537264 0.686894
25 0.00738 0.00948 0.01497 0.02214 23.831 0.397937 0.732479
26 0.01732 0.02245 0.03780 0.05197 22.066 0.522746 0.737948
27 0.00889 0.01169 0.01872 0.02666 25.908 0.418622 0.720916
28 0.00883 0.01144 0.01826 0.02650 25.119 0.358773 0.726652
29 0.00769 0.01012 0.01661 0.02307 25.970 0.470478 0.676258
30 0.00793 0.01057 0.01799 0.02380 25.678 0.427785 0.723797
31 0.00563 0.00680 0.00802 0.01689 26.775 0.422229 0.741367
32 0.00504 0.00641 0.00762 0.01513 30.940 0.432439 0.742055
33 0.00640 0.00825 0.00951 0.01919 30.775 0.465946 0.738703
34 0.00469 0.00606 0.00719 0.01407 32.684 0.368535 0.742133
35 0.00468 0.00610 0.00726 0.01403 33.047 0.340068 0.741899
36 0.00586 0.00760 0.00957 0.01758 31.732 0.344252 0.742737
37 0.01154 0.01347 0.01612 0.03463 23.216 0.360148 0.778834
38 0.00938 0.01160 0.01491 0.02814 24.951 0.341435 0.783626
39 0.00726 0.00885 0.01190 0.02177 26.738 0.403884 0.766209
40 0.00829 0.01003 0.01366 0.02488 26.310 0.396793 0.758324
41 0.00774 0.00941 0.01233 0.02321 26.822 0.326480 0.765623
42 0.00742 0.00901 0.01234 0.02226 26.453 0.306443 0.759203
43 0.01035 0.01024 0.01133 0.03104 22.736 0.305062 0.654172
44 0.01006 0.01038 0.01251 0.03017 23.145 0.457702 0.634267
45 0.00777 0.00898 0.01033 0.02330 25.368 0.438296 0.635285
46 0.00847 0.00879 0.01014 0.02542 25.032 0.431285 0.638928
47 0.00906 0.00977 0.01149 0.02719 24.602 0.467489 0.631653
48 0.00614 0.00730 0.00860 0.01841 26.805 0.610367 0.635204
49 0.00855 0.00776 0.01433 0.02566 23.162 0.579597 0.733659
50 0.00930 0.00802 0.01400 0.02789 24.971 0.538688 0.754073
51 0.01241 0.01024 0.01685 0.03724 25.135 0.553134 0.775933
52 0.01143 0.00959 0.01614 0.03429 25.030 0.507504 0.760361
53 0.01323 0.01072 0.01677 0.03969 24.692 0.459766 0.766204
54 0.01396 0.01219 0.01947 0.04188 25.429 0.420383 0.785714
55 0.01483 0.01609 0.02067 0.04450 21.028 0.536009 0.819032
56 0.01789 0.01992 0.02454 0.05368 20.767 0.558586 0.811843
57 0.02032 0.02302 0.02802 0.06097 21.422 0.541781 0.821364
58 0.01189 0.01459 0.01948 0.03568 22.817 0.530529 0.817756
59 0.01394 0.01625 0.02137 0.04183 22.603 0.540049 0.813432
60 0.01805 0.01974 0.02519 0.05414 21.660 0.547975 0.817396
61 0.00975 0.01258 0.01382 0.02925 25.554 0.341788 0.678874
62 0.01013 0.01296 0.01340 0.03039 26.138 0.447979 0.686264
63 0.00867 0.01108 0.01200 0.02602 25.856 0.364867 0.694399
64 0.00882 0.01075 0.01179 0.02647 25.964 0.256570 0.683296
65 0.00769 0.00957 0.01016 0.02308 26.415 0.276850 0.673636
66 0.00942 0.01160 0.01234 0.02827 24.547 0.305429 0.681811
67 0.01830 0.01810 0.02428 0.05490 19.560 0.460139 0.720908
68 0.01638 0.01759 0.02603 0.04914 19.979 0.498133 0.729067
69 0.03152 0.02422 0.03392 0.09455 20.338 0.513237 0.731444
70 0.03357 0.02494 0.03635 0.10070 21.718 0.487407 0.727313
71 0.01868 0.01906 0.02949 0.05605 20.264 0.489345 0.730387
72 0.02749 0.02466 0.03736 0.08247 18.570 0.543299 0.733232
73 0.00974 0.00925 0.01345 0.02921 25.742 0.495954 0.762959
74 0.01373 0.01375 0.01956 0.04120 24.178 0.509127 0.789532
75 0.01432 0.01325 0.01831 0.04295 25.438 0.437031 0.815908
76 0.01284 0.01219 0.01715 0.03851 25.197 0.463514 0.807217
77 0.02413 0.02231 0.02704 0.07238 23.370 0.489538 0.789977
78 0.01284 0.01199 0.01636 0.03852 25.820 0.429484 0.816340
79 0.01803 0.01886 0.02455 0.05408 21.875 0.644954 0.779612
80 0.01773 0.01783 0.02139 0.05320 19.200 0.594387 0.790117
81 0.02266 0.02451 0.02876 0.06799 19.055 0.544805 0.770466
82 0.01792 0.01841 0.02190 0.05377 19.659 0.576084 0.778747
83 0.01371 0.01421 0.01751 0.04114 20.536 0.554610 0.787896
84 0.01277 0.01343 0.01552 0.03831 22.244 0.576644 0.772416
85 0.02679 0.03022 0.03510 0.08037 13.893 0.556494 0.729586
86 0.02107 0.02493 0.02877 0.06321 16.176 0.583574 0.727747
87 0.02073 0.02415 0.02784 0.06219 15.924 0.598714 0.712199
88 0.03671 0.04159 0.04683 0.11012 13.922 0.602874 0.740837
89 0.03788 0.04254 0.04802 0.11363 14.739 0.599371 0.743937
90 0.02297 0.02768 0.03455 0.06892 11.866 0.590951 0.745526
91 0.03650 0.04282 0.05114 0.10949 11.744 0.653410 0.733165
92 0.04421 0.04962 0.05690 0.13262 19.664 0.501037 0.714360
93 0.02383 0.02521 0.03051 0.07150 18.780 0.454444 0.734504
94 0.03341 0.03794 0.04398 0.10024 20.969 0.447456 0.697790
95 0.02062 0.02321 0.02764 0.06185 22.219 0.502380 0.712170
96 0.01813 0.01909 0.02571 0.05439 21.693 0.447285 0.705658
97 0.01806 0.02024 0.02809 0.05417 22.663 0.366329 0.693429
98 0.02135 0.02174 0.03088 0.06406 15.338 0.629574 0.714485
99 0.02542 0.02630 0.03908 0.07625 15.433 0.571010 0.690892
100 0.03611 0.03963 0.05783 0.10833 12.435 0.638545 0.674953
101 0.05358 0.04791 0.06196 0.16074 8.867 0.671299 0.656846
102 0.03223 0.03672 0.05174 0.09669 15.060 0.639808 0.643327
103 0.05551 0.05005 0.06023 0.16654 10.489 0.596362 0.641418
104 0.00522 0.00659 0.01009 0.01567 26.759 0.296888 0.722356
105 0.00469 0.00582 0.00871 0.01406 28.409 0.263654 0.691483
106 0.00660 0.00818 0.01059 0.01979 27.421 0.365488 0.719974
107 0.00522 0.00632 0.00928 0.01567 29.746 0.334171 0.677930
108 0.00633 0.00788 0.01267 0.01898 26.833 0.393563 0.700246
109 0.00455 0.00576 0.00993 0.01364 29.928 0.311369 0.676066
110 0.01771 0.01815 0.02084 0.05312 21.934 0.497554 0.740539
111 0.01192 0.01439 0.01852 0.03576 23.239 0.436084 0.727863
112 0.00952 0.01058 0.01307 0.02855 22.407 0.338097 0.712466
113 0.01277 0.01483 0.01767 0.03831 21.305 0.498877 0.722085
114 0.00861 0.01017 0.01301 0.02583 23.671 0.441097 0.722254
115 0.01107 0.01284 0.01604 0.03320 21.864 0.331508 0.715121
116 0.00796 0.00832 0.01271 0.02389 23.693 0.407701 0.662668
117 0.00606 0.00747 0.01312 0.01818 26.356 0.450798 0.653823
118 0.00757 0.00971 0.01652 0.02270 25.690 0.486738 0.676023
119 0.00617 0.00744 0.01151 0.01851 25.020 0.470422 0.655239
120 0.00679 0.00631 0.01075 0.02038 24.581 0.462516 0.582710
121 0.00849 0.01117 0.01734 0.02548 24.743 0.487756 0.684130
122 0.00534 0.00630 0.01104 0.01603 27.166 0.400088 0.656182
123 0.02587 0.02567 0.03220 0.07761 18.305 0.538016 0.741480
124 0.01372 0.01580 0.01931 0.04115 18.784 0.589956 0.732903
125 0.01289 0.01420 0.01720 0.03867 19.196 0.618663 0.728421
126 0.01235 0.01495 0.01944 0.03706 18.857 0.637518 0.735546
127 0.01484 0.01805 0.02259 0.04451 18.178 0.623209 0.738245
128 0.01547 0.01859 0.02301 0.04641 18.330 0.585169 0.736964
129 0.00538 0.00570 0.00811 0.01614 26.842 0.457541 0.699787
130 0.00476 0.00588 0.00903 0.01428 26.369 0.491345 0.718839
131 0.00703 0.00820 0.01194 0.02110 23.949 0.467160 0.724045
132 0.00721 0.00815 0.01310 0.02164 26.017 0.468621 0.735136
133 0.00633 0.00701 0.00915 0.01898 23.389 0.470972 0.721308
134 0.00490 0.00621 0.00903 0.01471 25.619 0.482296 0.723096
135 0.02683 0.03112 0.03651 0.08050 17.060 0.637814 0.744064
136 0.02229 0.02592 0.03316 0.06688 17.707 0.653427 0.706687
137 0.02385 0.02973 0.04370 0.07154 19.013 0.647900 0.708144
138 0.02896 0.03347 0.04134 0.08689 16.747 0.625362 0.708617
139 0.03070 0.03530 0.04451 0.09211 17.366 0.640945 0.701404
140 0.01514 0.01812 0.02770 0.04543 18.801 0.624811 0.696049
141 0.01713 0.01964 0.02824 0.05139 18.540 0.677131 0.685057
142 0.04016 0.04003 0.04464 0.12047 15.648 0.606344 0.665945
143 0.02055 0.02076 0.02530 0.06165 18.702 0.606273 0.661735
144 0.01117 0.01177 0.01506 0.03350 18.687 0.536102 0.632631
145 0.01475 0.01558 0.02006 0.04426 20.680 0.497480 0.630409
146 0.01379 0.01478 0.01909 0.04137 20.366 0.566849 0.574282
147 0.03804 0.05426 0.08808 0.11411 12.359 0.561610 0.793509
148 0.02865 0.04101 0.06359 0.08595 14.367 0.478024 0.768974
149 0.03474 0.04580 0.06824 0.10422 12.298 0.552870 0.764036
150 0.03515 0.04265 0.06460 0.10546 14.989 0.427627 0.775708
151 0.02699 0.03714 0.06259 0.08096 12.529 0.507826 0.762726
152 0.05647 0.07940 0.13778 0.16942 8.441 0.625866 0.768320
153 0.04284 0.05556 0.08318 0.12851 9.449 0.584164 0.754449
154 0.01340 0.01399 0.02056 0.04019 21.520 0.566867 0.670475
155 0.01484 0.01405 0.02018 0.04451 21.824 0.651680 0.659333
156 0.01659 0.01804 0.02402 0.04977 22.431 0.628300 0.652025
157 0.01205 0.01289 0.01771 0.03615 22.953 0.611679 0.623731
158 0.02610 0.02161 0.02916 0.07830 19.075 0.630547 0.646786
159 0.01500 0.01581 0.02157 0.04499 21.534 0.635015 0.627337
160 0.01360 0.01650 0.03105 0.04079 19.651 0.654945 0.675865
161 0.01579 0.01994 0.04114 0.04736 20.437 0.653139 0.694571
162 0.01644 0.01722 0.02931 0.04933 19.388 0.577802 0.684373
163 0.01864 0.01940 0.03091 0.05592 18.954 0.685151 0.719576
164 0.00967 0.01033 0.01363 0.02902 21.219 0.557045 0.673086
165 0.01579 0.01553 0.02073 0.04736 18.447 0.671378 0.674562
166 0.01410 0.01426 0.01621 0.04231 24.078 0.469928 0.628232
167 0.00696 0.00747 0.00882 0.02089 24.679 0.384868 0.626710
168 0.01186 0.01230 0.01367 0.03557 21.083 0.440988 0.628058
169 0.01279 0.01272 0.01439 0.03836 19.269 0.372222 0.725216
170 0.01176 0.01191 0.01344 0.03529 21.020 0.371837 0.646167
171 0.01084 0.01121 0.01255 0.03253 21.528 0.522812 0.646818
172 0.00664 0.00786 0.01140 0.01992 26.436 0.413295 0.756700
173 0.00754 0.00950 0.01285 0.02261 26.550 0.369090 0.776158
174 0.00748 0.00905 0.01148 0.02245 26.547 0.380253 0.766700
175 0.00881 0.01062 0.01318 0.02643 25.445 0.387482 0.756482
176 0.00812 0.00933 0.01133 0.02436 26.005 0.405991 0.761255
177 0.00874 0.01021 0.01331 0.02623 26.143 0.361232 0.763242
178 0.00728 0.00886 0.01230 0.02184 24.151 0.396610 0.745957
179 0.00839 0.00956 0.01309 0.02518 24.412 0.402591 0.762508
180 0.00725 0.00876 0.01263 0.02175 23.683 0.398499 0.778349
181 0.01321 0.01574 0.02148 0.03964 23.133 0.352396 0.759320
182 0.00950 0.01103 0.01559 0.02849 22.866 0.408598 0.768845
183 0.01155 0.01341 0.01666 0.03464 23.008 0.329577 0.757180
184 0.00864 0.01223 0.01949 0.02592 23.079 0.603515 0.669565
185 0.00810 0.01144 0.01756 0.02429 22.085 0.663842 0.656516
186 0.00667 0.00990 0.01691 0.02001 24.199 0.598515 0.654331
187 0.00820 0.00972 0.01491 0.02460 23.958 0.566424 0.667654
188 0.00631 0.00789 0.01144 0.01892 25.023 0.528485 0.663884
189 0.00557 0.00721 0.01095 0.01672 24.775 0.555303 0.659132
190 0.01454 0.01582 0.01758 0.04363 19.368 0.508479 0.683761
191 0.02336 0.02498 0.02745 0.07008 19.517 0.448439 0.657899
192 0.01604 0.01657 0.01879 0.04812 19.147 0.431674 0.683244
193 0.01268 0.01365 0.01667 0.03804 17.883 0.407567 0.655683
194 0.01265 0.01321 0.01588 0.03794 19.020 0.451221 0.643956
195 0.01026 0.01161 0.01373 0.03078 21.209 0.462803 0.664357
spread1 spread2 D2 PPE t
1 -4.813031 0.266482 2.301442 0.284654 1
2 -4.075192 0.335590 2.486855 0.368674 2
3 -4.443179 0.311173 2.342259 0.332634 3
4 -4.117501 0.334147 2.405554 0.368975 4
5 -3.747787 0.234513 2.332180 0.410335 5
6 -4.242867 0.299111 2.187560 0.357775 6
7 -5.634322 0.257682 1.854785 0.211756 7
8 -6.167603 0.183721 2.064693 0.163755 8
9 -5.498678 0.327769 2.322511 0.231571 9
10 -5.011879 0.325996 2.432792 0.271362 10
11 -5.249770 0.391002 2.407313 0.249740 11
12 -4.960234 0.363566 2.642476 0.275931 12
13 -6.547148 0.152813 2.041277 0.138512 13
14 -5.660217 0.254989 2.519422 0.199889 14
15 -6.105098 0.203653 2.125618 0.170100 15
16 -5.340115 0.210185 2.205546 0.234589 16
17 -5.440040 0.239764 2.264501 0.218164 17
18 -2.931070 0.434326 3.007463 0.430788 18
19 -3.949079 0.357870 3.109010 0.377429 19
20 -4.554466 0.340176 2.856676 0.322111 20
21 -4.095442 0.262564 2.739710 0.365391 21
22 -5.186960 0.237622 2.557536 0.259765 22
23 -4.330956 0.262384 2.916777 0.285695 23
24 -5.248776 0.210279 2.547508 0.253556 24
25 -5.557447 0.220890 2.692176 0.215961 25
26 -5.571843 0.236853 2.846369 0.219514 26
27 -6.183590 0.226278 2.589702 0.147403 27
28 -6.271690 0.196102 2.314209 0.162999 28
29 -7.120925 0.279789 2.241742 0.108514 29
30 -6.635729 0.209866 1.957961 0.135242 30
31 -7.348300 0.177551 1.743867 0.085569 31
32 -7.682587 0.173319 2.103106 0.068501 32
33 -7.067931 0.175181 1.512275 0.096320 33
34 -7.695734 0.178540 1.544609 0.056141 34
35 -7.964984 0.163519 1.423287 0.044539 35
36 -7.777685 0.170183 2.447064 0.057610 36
37 -6.149653 0.218037 2.477082 0.165827 37
38 -6.006414 0.196371 2.536527 0.173218 38
39 -6.452058 0.212294 2.269398 0.141929 39
40 -6.006647 0.266892 2.382544 0.160691 40
41 -6.647379 0.201095 2.374073 0.130554 41
42 -7.044105 0.063412 2.361532 0.115730 42
43 -7.310550 0.098648 2.416838 0.095032 43
44 -6.793547 0.158266 2.256699 0.117399 44
45 -7.057869 0.091608 2.330716 0.091470 45
46 -6.995820 0.102083 2.365800 0.102706 46
47 -7.156076 0.127642 2.392122 0.097336 47
48 -7.319510 0.200873 2.028612 0.086398 48
49 -6.439398 0.266392 2.079922 0.133867 49
50 -6.482096 0.264967 2.054419 0.128872 50
51 -6.650471 0.254498 1.840198 0.103561 51
52 -6.689151 0.291954 2.431854 0.105993 52
53 -7.072419 0.220434 1.972297 0.119308 53
54 -6.836811 0.269866 2.223719 0.147491 54
55 -4.649573 0.205558 1.986899 0.316700 55
56 -4.333543 0.221727 2.014606 0.344834 56
57 -4.438453 0.238298 1.922940 0.335041 57
58 -4.608260 0.290024 2.021591 0.314464 58
59 -4.476755 0.262633 1.827012 0.326197 59
60 -4.609161 0.221711 1.831691 0.316395 60
61 -7.040508 0.066994 2.460791 0.101516 61
62 -7.293801 0.086372 2.321560 0.098555 62
63 -6.966321 0.095882 2.278687 0.103224 63
64 -7.245620 0.018689 2.498224 0.093534 64
65 -7.496264 0.056844 2.003032 0.073581 65
66 -7.314237 0.006274 2.118596 0.091546 66
67 -5.409423 0.226850 2.359973 0.226156 67
68 -5.324574 0.205660 2.291558 0.226247 68
69 -5.869750 0.151814 2.118496 0.185580 69
70 -6.261141 0.120956 2.137075 0.141958 70
71 -5.720868 0.158830 2.277927 0.180828 71
72 -5.207985 0.224852 2.642276 0.242981 72
73 -5.791820 0.329066 2.205024 0.188180 73
74 -5.389129 0.306636 1.928708 0.225461 74
75 -5.313360 0.201861 2.225815 0.244512 75
76 -5.477592 0.315074 1.862092 0.228624 76
77 -5.775966 0.341169 2.007923 0.193918 77
78 -5.391029 0.250572 1.777901 0.232744 78
79 -5.115212 0.249494 2.017753 0.260015 79
80 -4.913885 0.265699 2.398422 0.277948 80
81 -4.441519 0.155097 2.645959 0.327978 81
82 -5.132032 0.210458 2.232576 0.260633 82
83 -5.022288 0.146948 2.428306 0.264666 83
84 -6.025367 0.078202 2.053601 0.177275 84
85 -5.288912 0.343073 3.099301 0.242119 85
86 -5.657899 0.315903 3.098256 0.200423 86
87 -6.366916 0.335753 2.654271 0.144614 87
88 -5.515071 0.299549 3.136550 0.220968 88
89 -5.783272 0.299793 3.007096 0.194052 89
90 -4.379411 0.375531 3.671155 0.332086 90
91 -4.508984 0.389232 3.317586 0.301952 91
92 -6.411497 0.207156 2.344876 0.134120 92
93 -5.952058 0.087840 2.344336 0.186489 93
94 -6.152551 0.173520 2.080121 0.160809 94
95 -6.251425 0.188056 2.143851 0.160812 95
96 -6.247076 0.180528 2.344348 0.164916 96
97 -6.417440 0.194627 2.473239 0.151709 97
98 -4.020042 0.265315 2.671825 0.340623 98
99 -5.159169 0.202146 2.441612 0.260375 99
100 -3.760348 0.242861 2.634633 0.378483 100
101 -3.700544 0.260481 2.991063 0.370961 101
102 -4.202730 0.310163 2.638279 0.356881 102
103 -3.269487 0.270641 2.690917 0.444774 103
104 -6.878393 0.089267 2.004055 0.113942 104
105 -7.111576 0.144780 2.065477 0.093193 105
106 -6.997403 0.210279 1.994387 0.112878 106
107 -6.981201 0.184550 2.129924 0.106802 107
108 -6.600023 0.249172 2.499148 0.105306 108
109 -6.739151 0.160686 2.296873 0.115130 109
110 -5.845099 0.278679 2.608749 0.185668 110
111 -5.258320 0.256454 2.550961 0.232520 111
112 -6.471427 0.184378 2.502336 0.136390 112
113 -4.876336 0.212054 2.376749 0.268144 113
114 -5.963040 0.250283 2.489191 0.177807 114
115 -6.729713 0.181701 2.938114 0.115515 115
116 -4.673241 0.261549 2.702355 0.274407 116
117 -6.051233 0.273280 2.640798 0.170106 117
118 -4.597834 0.372114 2.975889 0.282780 118
119 -4.913137 0.393056 2.816781 0.251972 119
120 -5.517173 0.389295 2.925862 0.220657 120
121 -6.186128 0.279933 2.686240 0.152428 121
122 -4.711007 0.281618 2.655744 0.234809 122
123 -5.418787 0.160267 2.090438 0.229892 123
124 -5.445140 0.142466 2.174306 0.215558 124
125 -5.944191 0.143359 1.929715 0.181988 125
126 -5.594275 0.127950 1.765957 0.222716 126
127 -5.540351 0.087165 1.821297 0.214075 127
128 -5.825257 0.115697 1.996146 0.196535 128
129 -6.890021 0.152941 2.328513 0.112856 129
130 -5.892061 0.195976 2.108873 0.183572 130
131 -6.135296 0.203630 2.539724 0.169923 131
132 -6.112667 0.217013 2.527742 0.170633 132
133 -5.436135 0.254909 2.516320 0.232209 133
134 -6.448134 0.178713 2.034827 0.141422 134
135 -5.301321 0.320385 2.375138 0.243080 135
136 -5.333619 0.322044 2.631793 0.228319 136
137 -4.378916 0.300067 2.445502 0.259451 137
138 -4.654894 0.304107 2.672362 0.274387 138
139 -5.634576 0.306014 2.419253 0.209191 139
140 -5.866357 0.233070 2.445646 0.184985 140
141 -4.796845 0.397749 2.963799 0.277227 141
142 -5.410336 0.288917 2.665133 0.231723 142
143 -5.585259 0.310746 2.465528 0.209863 143
144 -5.898673 0.213353 2.470746 0.189032 144
145 -6.132663 0.220617 2.576563 0.159777 145
146 -5.456811 0.345238 2.840556 0.232861 146
147 -3.297668 0.414758 3.413649 0.457533 147
148 -4.276605 0.355736 3.142364 0.336085 148
149 -3.377325 0.335357 3.274865 0.418646 149
150 -4.892495 0.262281 2.910213 0.270173 150
151 -4.484303 0.340256 2.958815 0.301487 151
152 -2.434031 0.450493 3.079221 0.527367 152
153 -2.839756 0.356224 3.184027 0.454721 153
154 -4.865194 0.246404 2.013530 0.168581 154
155 -4.239028 0.175691 2.451130 0.247455 155
156 -3.583722 0.207914 2.439597 0.206256 156
157 -5.435100 0.230532 2.699645 0.220546 157
158 -3.444478 0.303214 2.964568 0.261305 158
159 -5.070096 0.280091 2.892300 0.249703 159
160 -5.498456 0.234196 2.103014 0.216638 160
161 -5.185987 0.259229 2.151121 0.244948 161
162 -5.283009 0.226528 2.442906 0.238281 162
163 -5.529833 0.242750 2.408689 0.220520 163
164 -5.617124 0.184896 1.871871 0.212386 164
165 -2.929379 0.396746 2.560422 0.367233 165
166 -6.816086 0.172270 2.235197 0.119652 166
167 -7.018057 0.176316 1.852402 0.091604 167
168 -7.517934 0.160414 1.881767 0.075587 168
169 -5.736781 0.164529 2.882450 0.202879 169
170 -7.169701 0.073298 2.266432 0.100881 170
171 -7.304500 0.171088 2.095237 0.096220 171
172 -6.323531 0.218885 2.193412 0.160376 172
173 -6.085567 0.192375 1.889002 0.174152 173
174 -5.943501 0.192150 1.852542 0.179677 174
175 -6.012559 0.229298 1.872946 0.163118 175
176 -5.966779 0.197938 1.974857 0.184067 176
177 -6.016891 0.109256 2.004719 0.174429 177
178 -6.486822 0.197919 2.449763 0.132703 178
179 -6.311987 0.182459 2.251553 0.160306 179
180 -5.711205 0.240875 2.845109 0.192730 180
181 -6.261446 0.183218 2.264226 0.144105 181
182 -5.704053 0.216204 2.679185 0.197710 182
183 -6.277170 0.109397 2.209021 0.156368 183
184 -5.619070 0.191576 2.027228 0.215724 184
185 -5.198864 0.206768 2.120412 0.252404 185
186 -5.592584 0.133917 2.058658 0.214346 186
187 -6.431119 0.153310 2.161936 0.120605 187
188 -6.359018 0.116636 2.152083 0.138868 188
189 -6.710219 0.149694 1.913990 0.121777 189
190 -6.934474 0.159890 2.316346 0.112838 190
191 -6.538586 0.121952 2.657476 0.133050 191
192 -6.195325 0.129303 2.784312 0.168895 192
193 -6.787197 0.158453 2.679772 0.131728 193
194 -6.744577 0.207454 2.138608 0.123306 194
195 -5.724056 0.190667 2.555477 0.148569 195
> 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)`
5.123e+00 -4.594e-03 -3.023e-05 -1.297e-03
`MDVP:Jitter(%)` `MDVP:Jitter(Abs)` `MDVP:RAP` `MDVP:PPQ`
-1.808e+02 -9.327e+03 -2.298e+02 -4.231e+01
`Jitter:DDP` `MDVP:Shimmer` `MDVP:Shimmer(dB)` `Shimmer:APQ3`
1.995e+02 1.669e+01 1.184e+00 -4.002e+02
`Shimmer:APQ5` `MDVP:APQ` `Shimmer:DDA` HNR
-1.953e+01 -5.850e+00 1.263e+02 -3.820e-02
RPDE DFA spread1 spread2
-1.338e+00 -2.806e-01 2.358e-01 1.216e+00
D2 PPE t
-3.409e-02 1.891e-01 -2.391e-03
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.80740 -0.15166 0.02418 0.21658 0.65727
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.123e+00 1.282e+00 3.996 9.52e-05 ***
`MDVP:Fo(Hz)` -4.594e-03 1.520e-03 -3.022 0.00290 **
`MDVP:Fhi(Hz)` -3.023e-05 3.044e-04 -0.099 0.92101
`MDVP:Flo(Hz)` -1.297e-03 7.633e-04 -1.699 0.09106 .
`MDVP:Jitter(%)` -1.808e+02 6.304e+01 -2.868 0.00465 **
`MDVP:Jitter(Abs)` -9.327e+03 4.576e+03 -2.038 0.04308 *
`MDVP:RAP` -2.298e+02 8.842e+03 -0.026 0.97929
`MDVP:PPQ` -4.231e+01 8.312e+01 -0.509 0.61142
`Jitter:DDP` 1.995e+02 2.948e+03 0.068 0.94612
`MDVP:Shimmer` 1.669e+01 3.254e+01 0.513 0.60873
`MDVP:Shimmer(dB)` 1.184e+00 1.147e+00 1.032 0.30355
`Shimmer:APQ3` -4.002e+02 8.517e+03 -0.047 0.96257
`Shimmer:APQ5` -1.953e+01 1.914e+01 -1.020 0.30904
`MDVP:APQ` -5.850e+00 1.029e+01 -0.569 0.57024
`Shimmer:DDA` 1.263e+02 2.838e+03 0.044 0.96457
HNR -3.820e-02 1.458e-02 -2.620 0.00959 **
RPDE -1.338e+00 4.240e-01 -3.157 0.00188 **
DFA -2.806e-01 6.852e-01 -0.409 0.68269
spread1 2.358e-01 9.331e-02 2.527 0.01241 *
spread2 1.216e+00 4.478e-01 2.716 0.00729 **
D2 -3.409e-02 1.094e-01 -0.312 0.75563
PPE 1.891e-01 1.334e+00 0.142 0.88743
t -2.391e-03 5.277e-04 -4.530 1.10e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.3102 on 172 degrees of freedom
Multiple R-squared: 0.5425, Adjusted R-squared: 0.484
F-statistic: 9.272 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,] 1.687526e-53 3.375052e-53 1.0000000
[2,] 3.481776e-65 6.963551e-65 1.0000000
[3,] 1.353602e-77 2.707204e-77 1.0000000
[4,] 5.161079e-94 1.032216e-93 1.0000000
[5,] 6.527937e-110 1.305587e-109 1.0000000
[6,] 2.841222e-03 5.682444e-03 0.9971588
[7,] 1.048840e-03 2.097680e-03 0.9989512
[8,] 3.533547e-04 7.067093e-04 0.9996466
[9,] 1.139259e-04 2.278519e-04 0.9998861
[10,] 5.832220e-05 1.166444e-04 0.9999417
[11,] 2.154847e-05 4.309694e-05 0.9999785
[12,] 2.219280e-04 4.438560e-04 0.9997781
[13,] 1.795027e-04 3.590053e-04 0.9998205
[14,] 1.143357e-03 2.286713e-03 0.9988566
[15,] 5.599214e-04 1.119843e-03 0.9994401
[16,] 7.475448e-04 1.495090e-03 0.9992525
[17,] 5.069383e-04 1.013877e-03 0.9994931
[18,] 2.610895e-04 5.221789e-04 0.9997389
[19,] 1.431325e-04 2.862650e-04 0.9998569
[20,] 7.155214e-05 1.431043e-04 0.9999284
[21,] 3.346559e-05 6.693117e-05 0.9999665
[22,] 1.707688e-05 3.415375e-05 0.9999829
[23,] 7.769542e-06 1.553908e-05 0.9999922
[24,] 9.025912e-04 1.805182e-03 0.9990974
[25,] 9.298931e-04 1.859786e-03 0.9990701
[26,] 7.561790e-04 1.512358e-03 0.9992438
[27,] 6.498189e-04 1.299638e-03 0.9993502
[28,] 6.930147e-04 1.386029e-03 0.9993070
[29,] 9.578615e-04 1.915723e-03 0.9990421
[30,] 7.364401e-04 1.472880e-03 0.9992636
[31,] 7.012749e-04 1.402550e-03 0.9992987
[32,] 4.184344e-04 8.368687e-04 0.9995816
[33,] 2.821224e-04 5.642448e-04 0.9997179
[34,] 1.910951e-04 3.821902e-04 0.9998089
[35,] 1.631716e-04 3.263431e-04 0.9998368
[36,] 1.217404e-02 2.434807e-02 0.9878260
[37,] 1.170623e-02 2.341246e-02 0.9882938
[38,] 1.439868e-02 2.879737e-02 0.9856013
[39,] 1.642194e-02 3.284388e-02 0.9835781
[40,] 1.800722e-02 3.601443e-02 0.9819928
[41,] 3.336607e-02 6.673214e-02 0.9666339
[42,] 2.799986e-02 5.599973e-02 0.9720001
[43,] 2.378143e-02 4.756286e-02 0.9762186
[44,] 2.731882e-02 5.463764e-02 0.9726812
[45,] 2.307559e-02 4.615118e-02 0.9769244
[46,] 1.878804e-02 3.757608e-02 0.9812120
[47,] 1.903380e-02 3.806759e-02 0.9809662
[48,] 1.663946e-02 3.327892e-02 0.9833605
[49,] 2.278489e-02 4.556977e-02 0.9772151
[50,] 2.248173e-02 4.496345e-02 0.9775183
[51,] 1.760961e-02 3.521921e-02 0.9823904
[52,] 1.663990e-02 3.327980e-02 0.9833601
[53,] 1.499667e-02 2.999334e-02 0.9850033
[54,] 1.450620e-02 2.901241e-02 0.9854938
[55,] 1.263992e-02 2.527983e-02 0.9873601
[56,] 9.871066e-03 1.974213e-02 0.9901289
[57,] 7.865994e-03 1.573199e-02 0.9921340
[58,] 7.168759e-03 1.433752e-02 0.9928312
[59,] 6.714809e-03 1.342962e-02 0.9932852
[60,] 7.080673e-03 1.416135e-02 0.9929193
[61,] 1.413676e-02 2.827353e-02 0.9858632
[62,] 3.096437e-02 6.192874e-02 0.9690356
[63,] 3.149311e-02 6.298622e-02 0.9685069
[64,] 3.328741e-02 6.657481e-02 0.9667126
[65,] 5.914711e-02 1.182942e-01 0.9408529
[66,] 8.936494e-02 1.787299e-01 0.9106351
[67,] 1.128488e-01 2.256976e-01 0.8871512
[68,] 1.106441e-01 2.212883e-01 0.8893559
[69,] 9.166615e-02 1.833323e-01 0.9083339
[70,] 7.785117e-02 1.557023e-01 0.9221488
[71,] 8.119240e-02 1.623848e-01 0.9188076
[72,] 7.643974e-02 1.528795e-01 0.9235603
[73,] 1.128160e-01 2.256319e-01 0.8871840
[74,] 1.183861e-01 2.367722e-01 0.8816139
[75,] 1.350306e-01 2.700612e-01 0.8649694
[76,] 1.511352e-01 3.022704e-01 0.8488648
[77,] 1.392498e-01 2.784995e-01 0.8607502
[78,] 1.269404e-01 2.538808e-01 0.8730596
[79,] 1.214807e-01 2.429614e-01 0.8785193
[80,] 1.105215e-01 2.210431e-01 0.8894785
[81,] 1.179841e-01 2.359682e-01 0.8820159
[82,] 1.221078e-01 2.442155e-01 0.8778922
[83,] 1.066393e-01 2.132786e-01 0.8933607
[84,] 8.717777e-02 1.743555e-01 0.9128222
[85,] 7.712075e-02 1.542415e-01 0.9228792
[86,] 6.288322e-02 1.257664e-01 0.9371168
[87,] 5.773914e-02 1.154783e-01 0.9422609
[88,] 4.555887e-02 9.111774e-02 0.9544411
[89,] 4.286637e-02 8.573274e-02 0.9571336
[90,] 3.810277e-02 7.620555e-02 0.9618972
[91,] 2.947238e-02 5.894476e-02 0.9705276
[92,] 2.409353e-02 4.818706e-02 0.9759065
[93,] 1.891160e-02 3.782320e-02 0.9810884
[94,] 1.497187e-02 2.994375e-02 0.9850281
[95,] 2.076829e-02 4.153657e-02 0.9792317
[96,] 1.714385e-02 3.428769e-02 0.9828562
[97,] 1.664296e-02 3.328591e-02 0.9833570
[98,] 1.659264e-02 3.318528e-02 0.9834074
[99,] 1.229730e-02 2.459460e-02 0.9877027
[100,] 9.185699e-03 1.837140e-02 0.9908143
[101,] 7.249918e-03 1.449984e-02 0.9927501
[102,] 5.712609e-03 1.142522e-02 0.9942874
[103,] 6.619972e-03 1.323994e-02 0.9933800
[104,] 6.285678e-03 1.257136e-02 0.9937143
[105,] 5.807830e-03 1.161566e-02 0.9941922
[106,] 4.091631e-03 8.183262e-03 0.9959084
[107,] 3.046091e-03 6.092182e-03 0.9969539
[108,] 2.651835e-03 5.303670e-03 0.9973482
[109,] 2.601604e-03 5.203207e-03 0.9973984
[110,] 2.051583e-03 4.103165e-03 0.9979484
[111,] 2.501019e-03 5.002038e-03 0.9974990
[112,] 3.713909e-03 7.427817e-03 0.9962861
[113,] 3.592239e-03 7.184479e-03 0.9964078
[114,] 2.521215e-03 5.042429e-03 0.9974788
[115,] 6.698604e-03 1.339721e-02 0.9933014
[116,] 5.229718e-03 1.045944e-02 0.9947703
[117,] 4.541781e-03 9.083561e-03 0.9954582
[118,] 3.872636e-03 7.745272e-03 0.9961274
[119,] 4.828122e-03 9.656244e-03 0.9951719
[120,] 4.370874e-03 8.741748e-03 0.9956291
[121,] 2.971093e-03 5.942186e-03 0.9970289
[122,] 2.523844e-03 5.047689e-03 0.9974762
[123,] 1.697305e-03 3.394610e-03 0.9983027
[124,] 2.725385e-03 5.450771e-03 0.9972746
[125,] 2.372525e-03 4.745050e-03 0.9976275
[126,] 2.725265e-03 5.450530e-03 0.9972747
[127,] 3.678496e-03 7.356991e-03 0.9963215
[128,] 5.833130e-02 1.166626e-01 0.9416687
[129,] 4.925415e-02 9.850830e-02 0.9507459
[130,] 5.717086e-02 1.143417e-01 0.9428291
[131,] 5.602709e-02 1.120542e-01 0.9439729
[132,] 1.305153e-01 2.610305e-01 0.8694847
[133,] 9.551138e-02 1.910228e-01 0.9044886
[134,] 4.715913e-01 9.431825e-01 0.5284087
[135,] 3.914055e-01 7.828109e-01 0.6085945
[136,] 3.575127e-01 7.150253e-01 0.6424873
[137,] 2.925026e-01 5.850052e-01 0.7074974
[138,] 4.276639e-01 8.553279e-01 0.5723361
[139,] 3.429380e-01 6.858761e-01 0.6570620
[140,] 3.980283e-01 7.960565e-01 0.6019717
[141,] 6.049439e-01 7.901121e-01 0.3950561
[142,] 8.697970e-01 2.604060e-01 0.1302030
[143,] 8.022515e-01 3.954970e-01 0.1977485
[144,] 8.591760e-01 2.816480e-01 0.1408240
> postscript(file="/var/wessaorg/rcomp/tmp/10ua51386503857.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2cq4c1386503857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3fs131386503857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4sc0e1386503857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5wo7g1386503857.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
-8.139766e-02 -1.404468e-01 2.418141e-02 -5.968792e-02 2.142088e-01
6 7 8 9 10
5.765841e-03 -1.037641e-02 2.611564e-01 -1.110044e-01 -2.437811e-01
11 12 13 14 15
-2.513120e-01 -3.282571e-01 2.422688e-01 -1.097170e-01 5.485340e-02
16 17 18 19 20
9.376001e-02 2.162846e-01 -5.228663e-01 -3.453451e-01 -9.428203e-02
21 22 23 24 25
-2.208477e-01 -1.940485e-02 -1.436090e-01 3.925288e-02 6.757218e-02
26 27 28 29 30
5.234900e-03 8.852325e-02 7.072204e-05 1.969079e-01 1.525131e-01
31 32 33 34 35
-4.547635e-01 -1.520358e-01 -2.520411e-01 -1.458821e-01 -9.510626e-02
36 37 38 39 40
-1.512904e-01 2.768186e-02 5.163773e-02 3.321081e-01 1.688417e-01
41 42 43 44 45
3.251674e-01 4.545683e-01 -4.129927e-01 -3.460864e-01 -1.014621e-01
46 47 48 49 50
-1.708513e-01 -1.055823e-01 7.025157e-02 -4.215741e-01 -5.108792e-01
51 52 53 54 55
-4.750132e-01 -3.937176e-01 -4.351603e-01 -4.624199e-01 1.968834e-01
56 57 58 59 60
2.846791e-01 2.145732e-01 2.779635e-01 2.885988e-01 4.276058e-01
61 62 63 64 65
-4.523825e-01 -2.432817e-01 -3.244868e-01 -2.735955e-01 -2.014436e-01
66 67 68 69 70
-3.419692e-01 4.674060e-05 4.868686e-02 1.311184e-01 7.963769e-02
71 72 73 74 75
6.654824e-02 -6.120279e-02 6.453214e-02 5.216203e-02 -3.029881e-02
76 77 78 79 80
-5.261769e-02 -9.334860e-02 -1.201746e-02 9.577863e-02 -7.246528e-02
81 82 83 84 85
-1.381160e-01 -1.522754e-01 -2.653037e-02 2.168757e-01 -2.176455e-01
86 87 88 89 90
3.013598e-02 1.735192e-01 8.982107e-03 -9.805716e-03 -4.115398e-01
91 92 93 94 95
-3.168878e-01 2.450656e-01 1.678001e-01 1.118230e-01 2.035157e-01
96 97 98 99 100
1.856864e-01 1.609034e-01 -9.610796e-02 1.292704e-01 -9.738371e-03
101 102 103 104 105
-1.204071e-01 2.212859e-02 -1.108410e-01 3.891463e-01 3.605770e-01
106 107 108 109 110
4.449014e-01 4.664214e-01 3.176604e-01 3.733047e-01 2.278023e-01
111 112 113 114 115
3.228161e-02 4.140415e-01 2.162026e-01 3.935814e-01 2.087073e-01
116 117 118 119 120
2.071825e-02 3.095271e-01 1.291722e-02 1.938043e-01 3.672834e-01
121 122 123 124 125
5.235498e-01 6.813797e-02 4.435500e-02 3.164805e-01 3.350632e-01
126 127 128 129 130
3.607335e-01 3.406820e-01 3.798857e-01 6.572674e-01 2.300680e-01
131 132 133 134 135
2.390540e-01 1.949462e-01 -4.785061e-02 3.799285e-01 1.603081e-01
136 137 138 139 140
5.392337e-02 -1.126784e-01 -1.615206e-01 1.046363e-01 2.098251e-01
141 142 143 144 145
2.190706e-01 3.174885e-01 3.657434e-01 3.192340e-01 5.033766e-01
146 147 148 149 150
2.794661e-01 -8.505259e-02 -2.469489e-02 -1.246261e-01 1.493283e-01
151 152 153 154 155
-3.098577e-02 9.791844e-02 -1.342836e-02 6.804324e-02 1.014813e-01
156 157 158 159 160
-1.039055e-01 3.165178e-01 -1.421438e-01 2.068134e-01 2.254780e-01
161 162 163 164 165
4.556479e-02 5.908650e-03 2.527320e-01 2.463688e-01 -2.963313e-01
166 167 168 169 170
-2.245439e-01 -1.372292e-01 1.979330e-02 -8.074020e-01 -1.299318e-01
171 172 173 174 175
6.743164e-02 -6.374800e-01 -7.088205e-01 -7.558772e-01 -7.715007e-01
176 177 178 179 180
-6.942355e-01 -6.376750e-01 5.067659e-01 4.466471e-01 2.762689e-01
181 182 183 184 185
4.074148e-01 3.228826e-01 3.752913e-01 -4.320713e-01 -4.698918e-01
186 187 188 189 190
-4.721673e-01 -3.307528e-01 -4.348466e-01 -3.032843e-01 -3.454584e-01
191 192 193 194 195
-5.116999e-01 -5.021667e-01 2.204149e-01 -2.690004e-01 -4.310476e-01
> postscript(file="/var/wessaorg/rcomp/tmp/629241386503857.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 -8.139766e-02 NA
1 -1.404468e-01 -8.139766e-02
2 2.418141e-02 -1.404468e-01
3 -5.968792e-02 2.418141e-02
4 2.142088e-01 -5.968792e-02
5 5.765841e-03 2.142088e-01
6 -1.037641e-02 5.765841e-03
7 2.611564e-01 -1.037641e-02
8 -1.110044e-01 2.611564e-01
9 -2.437811e-01 -1.110044e-01
10 -2.513120e-01 -2.437811e-01
11 -3.282571e-01 -2.513120e-01
12 2.422688e-01 -3.282571e-01
13 -1.097170e-01 2.422688e-01
14 5.485340e-02 -1.097170e-01
15 9.376001e-02 5.485340e-02
16 2.162846e-01 9.376001e-02
17 -5.228663e-01 2.162846e-01
18 -3.453451e-01 -5.228663e-01
19 -9.428203e-02 -3.453451e-01
20 -2.208477e-01 -9.428203e-02
21 -1.940485e-02 -2.208477e-01
22 -1.436090e-01 -1.940485e-02
23 3.925288e-02 -1.436090e-01
24 6.757218e-02 3.925288e-02
25 5.234900e-03 6.757218e-02
26 8.852325e-02 5.234900e-03
27 7.072204e-05 8.852325e-02
28 1.969079e-01 7.072204e-05
29 1.525131e-01 1.969079e-01
30 -4.547635e-01 1.525131e-01
31 -1.520358e-01 -4.547635e-01
32 -2.520411e-01 -1.520358e-01
33 -1.458821e-01 -2.520411e-01
34 -9.510626e-02 -1.458821e-01
35 -1.512904e-01 -9.510626e-02
36 2.768186e-02 -1.512904e-01
37 5.163773e-02 2.768186e-02
38 3.321081e-01 5.163773e-02
39 1.688417e-01 3.321081e-01
40 3.251674e-01 1.688417e-01
41 4.545683e-01 3.251674e-01
42 -4.129927e-01 4.545683e-01
43 -3.460864e-01 -4.129927e-01
44 -1.014621e-01 -3.460864e-01
45 -1.708513e-01 -1.014621e-01
46 -1.055823e-01 -1.708513e-01
47 7.025157e-02 -1.055823e-01
48 -4.215741e-01 7.025157e-02
49 -5.108792e-01 -4.215741e-01
50 -4.750132e-01 -5.108792e-01
51 -3.937176e-01 -4.750132e-01
52 -4.351603e-01 -3.937176e-01
53 -4.624199e-01 -4.351603e-01
54 1.968834e-01 -4.624199e-01
55 2.846791e-01 1.968834e-01
56 2.145732e-01 2.846791e-01
57 2.779635e-01 2.145732e-01
58 2.885988e-01 2.779635e-01
59 4.276058e-01 2.885988e-01
60 -4.523825e-01 4.276058e-01
61 -2.432817e-01 -4.523825e-01
62 -3.244868e-01 -2.432817e-01
63 -2.735955e-01 -3.244868e-01
64 -2.014436e-01 -2.735955e-01
65 -3.419692e-01 -2.014436e-01
66 4.674060e-05 -3.419692e-01
67 4.868686e-02 4.674060e-05
68 1.311184e-01 4.868686e-02
69 7.963769e-02 1.311184e-01
70 6.654824e-02 7.963769e-02
71 -6.120279e-02 6.654824e-02
72 6.453214e-02 -6.120279e-02
73 5.216203e-02 6.453214e-02
74 -3.029881e-02 5.216203e-02
75 -5.261769e-02 -3.029881e-02
76 -9.334860e-02 -5.261769e-02
77 -1.201746e-02 -9.334860e-02
78 9.577863e-02 -1.201746e-02
79 -7.246528e-02 9.577863e-02
80 -1.381160e-01 -7.246528e-02
81 -1.522754e-01 -1.381160e-01
82 -2.653037e-02 -1.522754e-01
83 2.168757e-01 -2.653037e-02
84 -2.176455e-01 2.168757e-01
85 3.013598e-02 -2.176455e-01
86 1.735192e-01 3.013598e-02
87 8.982107e-03 1.735192e-01
88 -9.805716e-03 8.982107e-03
89 -4.115398e-01 -9.805716e-03
90 -3.168878e-01 -4.115398e-01
91 2.450656e-01 -3.168878e-01
92 1.678001e-01 2.450656e-01
93 1.118230e-01 1.678001e-01
94 2.035157e-01 1.118230e-01
95 1.856864e-01 2.035157e-01
96 1.609034e-01 1.856864e-01
97 -9.610796e-02 1.609034e-01
98 1.292704e-01 -9.610796e-02
99 -9.738371e-03 1.292704e-01
100 -1.204071e-01 -9.738371e-03
101 2.212859e-02 -1.204071e-01
102 -1.108410e-01 2.212859e-02
103 3.891463e-01 -1.108410e-01
104 3.605770e-01 3.891463e-01
105 4.449014e-01 3.605770e-01
106 4.664214e-01 4.449014e-01
107 3.176604e-01 4.664214e-01
108 3.733047e-01 3.176604e-01
109 2.278023e-01 3.733047e-01
110 3.228161e-02 2.278023e-01
111 4.140415e-01 3.228161e-02
112 2.162026e-01 4.140415e-01
113 3.935814e-01 2.162026e-01
114 2.087073e-01 3.935814e-01
115 2.071825e-02 2.087073e-01
116 3.095271e-01 2.071825e-02
117 1.291722e-02 3.095271e-01
118 1.938043e-01 1.291722e-02
119 3.672834e-01 1.938043e-01
120 5.235498e-01 3.672834e-01
121 6.813797e-02 5.235498e-01
122 4.435500e-02 6.813797e-02
123 3.164805e-01 4.435500e-02
124 3.350632e-01 3.164805e-01
125 3.607335e-01 3.350632e-01
126 3.406820e-01 3.607335e-01
127 3.798857e-01 3.406820e-01
128 6.572674e-01 3.798857e-01
129 2.300680e-01 6.572674e-01
130 2.390540e-01 2.300680e-01
131 1.949462e-01 2.390540e-01
132 -4.785061e-02 1.949462e-01
133 3.799285e-01 -4.785061e-02
134 1.603081e-01 3.799285e-01
135 5.392337e-02 1.603081e-01
136 -1.126784e-01 5.392337e-02
137 -1.615206e-01 -1.126784e-01
138 1.046363e-01 -1.615206e-01
139 2.098251e-01 1.046363e-01
140 2.190706e-01 2.098251e-01
141 3.174885e-01 2.190706e-01
142 3.657434e-01 3.174885e-01
143 3.192340e-01 3.657434e-01
144 5.033766e-01 3.192340e-01
145 2.794661e-01 5.033766e-01
146 -8.505259e-02 2.794661e-01
147 -2.469489e-02 -8.505259e-02
148 -1.246261e-01 -2.469489e-02
149 1.493283e-01 -1.246261e-01
150 -3.098577e-02 1.493283e-01
151 9.791844e-02 -3.098577e-02
152 -1.342836e-02 9.791844e-02
153 6.804324e-02 -1.342836e-02
154 1.014813e-01 6.804324e-02
155 -1.039055e-01 1.014813e-01
156 3.165178e-01 -1.039055e-01
157 -1.421438e-01 3.165178e-01
158 2.068134e-01 -1.421438e-01
159 2.254780e-01 2.068134e-01
160 4.556479e-02 2.254780e-01
161 5.908650e-03 4.556479e-02
162 2.527320e-01 5.908650e-03
163 2.463688e-01 2.527320e-01
164 -2.963313e-01 2.463688e-01
165 -2.245439e-01 -2.963313e-01
166 -1.372292e-01 -2.245439e-01
167 1.979330e-02 -1.372292e-01
168 -8.074020e-01 1.979330e-02
169 -1.299318e-01 -8.074020e-01
170 6.743164e-02 -1.299318e-01
171 -6.374800e-01 6.743164e-02
172 -7.088205e-01 -6.374800e-01
173 -7.558772e-01 -7.088205e-01
174 -7.715007e-01 -7.558772e-01
175 -6.942355e-01 -7.715007e-01
176 -6.376750e-01 -6.942355e-01
177 5.067659e-01 -6.376750e-01
178 4.466471e-01 5.067659e-01
179 2.762689e-01 4.466471e-01
180 4.074148e-01 2.762689e-01
181 3.228826e-01 4.074148e-01
182 3.752913e-01 3.228826e-01
183 -4.320713e-01 3.752913e-01
184 -4.698918e-01 -4.320713e-01
185 -4.721673e-01 -4.698918e-01
186 -3.307528e-01 -4.721673e-01
187 -4.348466e-01 -3.307528e-01
188 -3.032843e-01 -4.348466e-01
189 -3.454584e-01 -3.032843e-01
190 -5.116999e-01 -3.454584e-01
191 -5.021667e-01 -5.116999e-01
192 2.204149e-01 -5.021667e-01
193 -2.690004e-01 2.204149e-01
194 -4.310476e-01 -2.690004e-01
195 NA -4.310476e-01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.404468e-01 -8.139766e-02
[2,] 2.418141e-02 -1.404468e-01
[3,] -5.968792e-02 2.418141e-02
[4,] 2.142088e-01 -5.968792e-02
[5,] 5.765841e-03 2.142088e-01
[6,] -1.037641e-02 5.765841e-03
[7,] 2.611564e-01 -1.037641e-02
[8,] -1.110044e-01 2.611564e-01
[9,] -2.437811e-01 -1.110044e-01
[10,] -2.513120e-01 -2.437811e-01
[11,] -3.282571e-01 -2.513120e-01
[12,] 2.422688e-01 -3.282571e-01
[13,] -1.097170e-01 2.422688e-01
[14,] 5.485340e-02 -1.097170e-01
[15,] 9.376001e-02 5.485340e-02
[16,] 2.162846e-01 9.376001e-02
[17,] -5.228663e-01 2.162846e-01
[18,] -3.453451e-01 -5.228663e-01
[19,] -9.428203e-02 -3.453451e-01
[20,] -2.208477e-01 -9.428203e-02
[21,] -1.940485e-02 -2.208477e-01
[22,] -1.436090e-01 -1.940485e-02
[23,] 3.925288e-02 -1.436090e-01
[24,] 6.757218e-02 3.925288e-02
[25,] 5.234900e-03 6.757218e-02
[26,] 8.852325e-02 5.234900e-03
[27,] 7.072204e-05 8.852325e-02
[28,] 1.969079e-01 7.072204e-05
[29,] 1.525131e-01 1.969079e-01
[30,] -4.547635e-01 1.525131e-01
[31,] -1.520358e-01 -4.547635e-01
[32,] -2.520411e-01 -1.520358e-01
[33,] -1.458821e-01 -2.520411e-01
[34,] -9.510626e-02 -1.458821e-01
[35,] -1.512904e-01 -9.510626e-02
[36,] 2.768186e-02 -1.512904e-01
[37,] 5.163773e-02 2.768186e-02
[38,] 3.321081e-01 5.163773e-02
[39,] 1.688417e-01 3.321081e-01
[40,] 3.251674e-01 1.688417e-01
[41,] 4.545683e-01 3.251674e-01
[42,] -4.129927e-01 4.545683e-01
[43,] -3.460864e-01 -4.129927e-01
[44,] -1.014621e-01 -3.460864e-01
[45,] -1.708513e-01 -1.014621e-01
[46,] -1.055823e-01 -1.708513e-01
[47,] 7.025157e-02 -1.055823e-01
[48,] -4.215741e-01 7.025157e-02
[49,] -5.108792e-01 -4.215741e-01
[50,] -4.750132e-01 -5.108792e-01
[51,] -3.937176e-01 -4.750132e-01
[52,] -4.351603e-01 -3.937176e-01
[53,] -4.624199e-01 -4.351603e-01
[54,] 1.968834e-01 -4.624199e-01
[55,] 2.846791e-01 1.968834e-01
[56,] 2.145732e-01 2.846791e-01
[57,] 2.779635e-01 2.145732e-01
[58,] 2.885988e-01 2.779635e-01
[59,] 4.276058e-01 2.885988e-01
[60,] -4.523825e-01 4.276058e-01
[61,] -2.432817e-01 -4.523825e-01
[62,] -3.244868e-01 -2.432817e-01
[63,] -2.735955e-01 -3.244868e-01
[64,] -2.014436e-01 -2.735955e-01
[65,] -3.419692e-01 -2.014436e-01
[66,] 4.674060e-05 -3.419692e-01
[67,] 4.868686e-02 4.674060e-05
[68,] 1.311184e-01 4.868686e-02
[69,] 7.963769e-02 1.311184e-01
[70,] 6.654824e-02 7.963769e-02
[71,] -6.120279e-02 6.654824e-02
[72,] 6.453214e-02 -6.120279e-02
[73,] 5.216203e-02 6.453214e-02
[74,] -3.029881e-02 5.216203e-02
[75,] -5.261769e-02 -3.029881e-02
[76,] -9.334860e-02 -5.261769e-02
[77,] -1.201746e-02 -9.334860e-02
[78,] 9.577863e-02 -1.201746e-02
[79,] -7.246528e-02 9.577863e-02
[80,] -1.381160e-01 -7.246528e-02
[81,] -1.522754e-01 -1.381160e-01
[82,] -2.653037e-02 -1.522754e-01
[83,] 2.168757e-01 -2.653037e-02
[84,] -2.176455e-01 2.168757e-01
[85,] 3.013598e-02 -2.176455e-01
[86,] 1.735192e-01 3.013598e-02
[87,] 8.982107e-03 1.735192e-01
[88,] -9.805716e-03 8.982107e-03
[89,] -4.115398e-01 -9.805716e-03
[90,] -3.168878e-01 -4.115398e-01
[91,] 2.450656e-01 -3.168878e-01
[92,] 1.678001e-01 2.450656e-01
[93,] 1.118230e-01 1.678001e-01
[94,] 2.035157e-01 1.118230e-01
[95,] 1.856864e-01 2.035157e-01
[96,] 1.609034e-01 1.856864e-01
[97,] -9.610796e-02 1.609034e-01
[98,] 1.292704e-01 -9.610796e-02
[99,] -9.738371e-03 1.292704e-01
[100,] -1.204071e-01 -9.738371e-03
[101,] 2.212859e-02 -1.204071e-01
[102,] -1.108410e-01 2.212859e-02
[103,] 3.891463e-01 -1.108410e-01
[104,] 3.605770e-01 3.891463e-01
[105,] 4.449014e-01 3.605770e-01
[106,] 4.664214e-01 4.449014e-01
[107,] 3.176604e-01 4.664214e-01
[108,] 3.733047e-01 3.176604e-01
[109,] 2.278023e-01 3.733047e-01
[110,] 3.228161e-02 2.278023e-01
[111,] 4.140415e-01 3.228161e-02
[112,] 2.162026e-01 4.140415e-01
[113,] 3.935814e-01 2.162026e-01
[114,] 2.087073e-01 3.935814e-01
[115,] 2.071825e-02 2.087073e-01
[116,] 3.095271e-01 2.071825e-02
[117,] 1.291722e-02 3.095271e-01
[118,] 1.938043e-01 1.291722e-02
[119,] 3.672834e-01 1.938043e-01
[120,] 5.235498e-01 3.672834e-01
[121,] 6.813797e-02 5.235498e-01
[122,] 4.435500e-02 6.813797e-02
[123,] 3.164805e-01 4.435500e-02
[124,] 3.350632e-01 3.164805e-01
[125,] 3.607335e-01 3.350632e-01
[126,] 3.406820e-01 3.607335e-01
[127,] 3.798857e-01 3.406820e-01
[128,] 6.572674e-01 3.798857e-01
[129,] 2.300680e-01 6.572674e-01
[130,] 2.390540e-01 2.300680e-01
[131,] 1.949462e-01 2.390540e-01
[132,] -4.785061e-02 1.949462e-01
[133,] 3.799285e-01 -4.785061e-02
[134,] 1.603081e-01 3.799285e-01
[135,] 5.392337e-02 1.603081e-01
[136,] -1.126784e-01 5.392337e-02
[137,] -1.615206e-01 -1.126784e-01
[138,] 1.046363e-01 -1.615206e-01
[139,] 2.098251e-01 1.046363e-01
[140,] 2.190706e-01 2.098251e-01
[141,] 3.174885e-01 2.190706e-01
[142,] 3.657434e-01 3.174885e-01
[143,] 3.192340e-01 3.657434e-01
[144,] 5.033766e-01 3.192340e-01
[145,] 2.794661e-01 5.033766e-01
[146,] -8.505259e-02 2.794661e-01
[147,] -2.469489e-02 -8.505259e-02
[148,] -1.246261e-01 -2.469489e-02
[149,] 1.493283e-01 -1.246261e-01
[150,] -3.098577e-02 1.493283e-01
[151,] 9.791844e-02 -3.098577e-02
[152,] -1.342836e-02 9.791844e-02
[153,] 6.804324e-02 -1.342836e-02
[154,] 1.014813e-01 6.804324e-02
[155,] -1.039055e-01 1.014813e-01
[156,] 3.165178e-01 -1.039055e-01
[157,] -1.421438e-01 3.165178e-01
[158,] 2.068134e-01 -1.421438e-01
[159,] 2.254780e-01 2.068134e-01
[160,] 4.556479e-02 2.254780e-01
[161,] 5.908650e-03 4.556479e-02
[162,] 2.527320e-01 5.908650e-03
[163,] 2.463688e-01 2.527320e-01
[164,] -2.963313e-01 2.463688e-01
[165,] -2.245439e-01 -2.963313e-01
[166,] -1.372292e-01 -2.245439e-01
[167,] 1.979330e-02 -1.372292e-01
[168,] -8.074020e-01 1.979330e-02
[169,] -1.299318e-01 -8.074020e-01
[170,] 6.743164e-02 -1.299318e-01
[171,] -6.374800e-01 6.743164e-02
[172,] -7.088205e-01 -6.374800e-01
[173,] -7.558772e-01 -7.088205e-01
[174,] -7.715007e-01 -7.558772e-01
[175,] -6.942355e-01 -7.715007e-01
[176,] -6.376750e-01 -6.942355e-01
[177,] 5.067659e-01 -6.376750e-01
[178,] 4.466471e-01 5.067659e-01
[179,] 2.762689e-01 4.466471e-01
[180,] 4.074148e-01 2.762689e-01
[181,] 3.228826e-01 4.074148e-01
[182,] 3.752913e-01 3.228826e-01
[183,] -4.320713e-01 3.752913e-01
[184,] -4.698918e-01 -4.320713e-01
[185,] -4.721673e-01 -4.698918e-01
[186,] -3.307528e-01 -4.721673e-01
[187,] -4.348466e-01 -3.307528e-01
[188,] -3.032843e-01 -4.348466e-01
[189,] -3.454584e-01 -3.032843e-01
[190,] -5.116999e-01 -3.454584e-01
[191,] -5.021667e-01 -5.116999e-01
[192,] 2.204149e-01 -5.021667e-01
[193,] -2.690004e-01 2.204149e-01
[194,] -4.310476e-01 -2.690004e-01
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.404468e-01 -8.139766e-02
2 2.418141e-02 -1.404468e-01
3 -5.968792e-02 2.418141e-02
4 2.142088e-01 -5.968792e-02
5 5.765841e-03 2.142088e-01
6 -1.037641e-02 5.765841e-03
7 2.611564e-01 -1.037641e-02
8 -1.110044e-01 2.611564e-01
9 -2.437811e-01 -1.110044e-01
10 -2.513120e-01 -2.437811e-01
11 -3.282571e-01 -2.513120e-01
12 2.422688e-01 -3.282571e-01
13 -1.097170e-01 2.422688e-01
14 5.485340e-02 -1.097170e-01
15 9.376001e-02 5.485340e-02
16 2.162846e-01 9.376001e-02
17 -5.228663e-01 2.162846e-01
18 -3.453451e-01 -5.228663e-01
19 -9.428203e-02 -3.453451e-01
20 -2.208477e-01 -9.428203e-02
21 -1.940485e-02 -2.208477e-01
22 -1.436090e-01 -1.940485e-02
23 3.925288e-02 -1.436090e-01
24 6.757218e-02 3.925288e-02
25 5.234900e-03 6.757218e-02
26 8.852325e-02 5.234900e-03
27 7.072204e-05 8.852325e-02
28 1.969079e-01 7.072204e-05
29 1.525131e-01 1.969079e-01
30 -4.547635e-01 1.525131e-01
31 -1.520358e-01 -4.547635e-01
32 -2.520411e-01 -1.520358e-01
33 -1.458821e-01 -2.520411e-01
34 -9.510626e-02 -1.458821e-01
35 -1.512904e-01 -9.510626e-02
36 2.768186e-02 -1.512904e-01
37 5.163773e-02 2.768186e-02
38 3.321081e-01 5.163773e-02
39 1.688417e-01 3.321081e-01
40 3.251674e-01 1.688417e-01
41 4.545683e-01 3.251674e-01
42 -4.129927e-01 4.545683e-01
43 -3.460864e-01 -4.129927e-01
44 -1.014621e-01 -3.460864e-01
45 -1.708513e-01 -1.014621e-01
46 -1.055823e-01 -1.708513e-01
47 7.025157e-02 -1.055823e-01
48 -4.215741e-01 7.025157e-02
49 -5.108792e-01 -4.215741e-01
50 -4.750132e-01 -5.108792e-01
51 -3.937176e-01 -4.750132e-01
52 -4.351603e-01 -3.937176e-01
53 -4.624199e-01 -4.351603e-01
54 1.968834e-01 -4.624199e-01
55 2.846791e-01 1.968834e-01
56 2.145732e-01 2.846791e-01
57 2.779635e-01 2.145732e-01
58 2.885988e-01 2.779635e-01
59 4.276058e-01 2.885988e-01
60 -4.523825e-01 4.276058e-01
61 -2.432817e-01 -4.523825e-01
62 -3.244868e-01 -2.432817e-01
63 -2.735955e-01 -3.244868e-01
64 -2.014436e-01 -2.735955e-01
65 -3.419692e-01 -2.014436e-01
66 4.674060e-05 -3.419692e-01
67 4.868686e-02 4.674060e-05
68 1.311184e-01 4.868686e-02
69 7.963769e-02 1.311184e-01
70 6.654824e-02 7.963769e-02
71 -6.120279e-02 6.654824e-02
72 6.453214e-02 -6.120279e-02
73 5.216203e-02 6.453214e-02
74 -3.029881e-02 5.216203e-02
75 -5.261769e-02 -3.029881e-02
76 -9.334860e-02 -5.261769e-02
77 -1.201746e-02 -9.334860e-02
78 9.577863e-02 -1.201746e-02
79 -7.246528e-02 9.577863e-02
80 -1.381160e-01 -7.246528e-02
81 -1.522754e-01 -1.381160e-01
82 -2.653037e-02 -1.522754e-01
83 2.168757e-01 -2.653037e-02
84 -2.176455e-01 2.168757e-01
85 3.013598e-02 -2.176455e-01
86 1.735192e-01 3.013598e-02
87 8.982107e-03 1.735192e-01
88 -9.805716e-03 8.982107e-03
89 -4.115398e-01 -9.805716e-03
90 -3.168878e-01 -4.115398e-01
91 2.450656e-01 -3.168878e-01
92 1.678001e-01 2.450656e-01
93 1.118230e-01 1.678001e-01
94 2.035157e-01 1.118230e-01
95 1.856864e-01 2.035157e-01
96 1.609034e-01 1.856864e-01
97 -9.610796e-02 1.609034e-01
98 1.292704e-01 -9.610796e-02
99 -9.738371e-03 1.292704e-01
100 -1.204071e-01 -9.738371e-03
101 2.212859e-02 -1.204071e-01
102 -1.108410e-01 2.212859e-02
103 3.891463e-01 -1.108410e-01
104 3.605770e-01 3.891463e-01
105 4.449014e-01 3.605770e-01
106 4.664214e-01 4.449014e-01
107 3.176604e-01 4.664214e-01
108 3.733047e-01 3.176604e-01
109 2.278023e-01 3.733047e-01
110 3.228161e-02 2.278023e-01
111 4.140415e-01 3.228161e-02
112 2.162026e-01 4.140415e-01
113 3.935814e-01 2.162026e-01
114 2.087073e-01 3.935814e-01
115 2.071825e-02 2.087073e-01
116 3.095271e-01 2.071825e-02
117 1.291722e-02 3.095271e-01
118 1.938043e-01 1.291722e-02
119 3.672834e-01 1.938043e-01
120 5.235498e-01 3.672834e-01
121 6.813797e-02 5.235498e-01
122 4.435500e-02 6.813797e-02
123 3.164805e-01 4.435500e-02
124 3.350632e-01 3.164805e-01
125 3.607335e-01 3.350632e-01
126 3.406820e-01 3.607335e-01
127 3.798857e-01 3.406820e-01
128 6.572674e-01 3.798857e-01
129 2.300680e-01 6.572674e-01
130 2.390540e-01 2.300680e-01
131 1.949462e-01 2.390540e-01
132 -4.785061e-02 1.949462e-01
133 3.799285e-01 -4.785061e-02
134 1.603081e-01 3.799285e-01
135 5.392337e-02 1.603081e-01
136 -1.126784e-01 5.392337e-02
137 -1.615206e-01 -1.126784e-01
138 1.046363e-01 -1.615206e-01
139 2.098251e-01 1.046363e-01
140 2.190706e-01 2.098251e-01
141 3.174885e-01 2.190706e-01
142 3.657434e-01 3.174885e-01
143 3.192340e-01 3.657434e-01
144 5.033766e-01 3.192340e-01
145 2.794661e-01 5.033766e-01
146 -8.505259e-02 2.794661e-01
147 -2.469489e-02 -8.505259e-02
148 -1.246261e-01 -2.469489e-02
149 1.493283e-01 -1.246261e-01
150 -3.098577e-02 1.493283e-01
151 9.791844e-02 -3.098577e-02
152 -1.342836e-02 9.791844e-02
153 6.804324e-02 -1.342836e-02
154 1.014813e-01 6.804324e-02
155 -1.039055e-01 1.014813e-01
156 3.165178e-01 -1.039055e-01
157 -1.421438e-01 3.165178e-01
158 2.068134e-01 -1.421438e-01
159 2.254780e-01 2.068134e-01
160 4.556479e-02 2.254780e-01
161 5.908650e-03 4.556479e-02
162 2.527320e-01 5.908650e-03
163 2.463688e-01 2.527320e-01
164 -2.963313e-01 2.463688e-01
165 -2.245439e-01 -2.963313e-01
166 -1.372292e-01 -2.245439e-01
167 1.979330e-02 -1.372292e-01
168 -8.074020e-01 1.979330e-02
169 -1.299318e-01 -8.074020e-01
170 6.743164e-02 -1.299318e-01
171 -6.374800e-01 6.743164e-02
172 -7.088205e-01 -6.374800e-01
173 -7.558772e-01 -7.088205e-01
174 -7.715007e-01 -7.558772e-01
175 -6.942355e-01 -7.715007e-01
176 -6.376750e-01 -6.942355e-01
177 5.067659e-01 -6.376750e-01
178 4.466471e-01 5.067659e-01
179 2.762689e-01 4.466471e-01
180 4.074148e-01 2.762689e-01
181 3.228826e-01 4.074148e-01
182 3.752913e-01 3.228826e-01
183 -4.320713e-01 3.752913e-01
184 -4.698918e-01 -4.320713e-01
185 -4.721673e-01 -4.698918e-01
186 -3.307528e-01 -4.721673e-01
187 -4.348466e-01 -3.307528e-01
188 -3.032843e-01 -4.348466e-01
189 -3.454584e-01 -3.032843e-01
190 -5.116999e-01 -3.454584e-01
191 -5.021667e-01 -5.116999e-01
192 2.204149e-01 -5.021667e-01
193 -2.690004e-01 2.204149e-01
194 -4.310476e-01 -2.690004e-01
> 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/wessaorg/rcomp/tmp/74hvg1386503857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8jlf41386503857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9angh1386503857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10w1x31386503857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/118zt91386503857.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/wessaorg/rcomp/tmp/12mof11386503857.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/wessaorg/rcomp/tmp/13h9so1386503857.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/wessaorg/rcomp/tmp/1411z11386503857.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/wessaorg/rcomp/tmp/158rww1386503857.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/wessaorg/rcomp/tmp/16b6f81386503857.tab")
+ }
>
> try(system("convert tmp/10ua51386503857.ps tmp/10ua51386503857.png",intern=TRUE))
character(0)
> try(system("convert tmp/2cq4c1386503857.ps tmp/2cq4c1386503857.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fs131386503857.ps tmp/3fs131386503857.png",intern=TRUE))
character(0)
> try(system("convert tmp/4sc0e1386503857.ps tmp/4sc0e1386503857.png",intern=TRUE))
character(0)
> try(system("convert tmp/5wo7g1386503857.ps tmp/5wo7g1386503857.png",intern=TRUE))
character(0)
> try(system("convert tmp/629241386503857.ps tmp/629241386503857.png",intern=TRUE))
character(0)
> try(system("convert tmp/74hvg1386503857.ps tmp/74hvg1386503857.png",intern=TRUE))
character(0)
> try(system("convert tmp/8jlf41386503857.ps tmp/8jlf41386503857.png",intern=TRUE))
character(0)
> try(system("convert tmp/9angh1386503857.ps tmp/9angh1386503857.png",intern=TRUE))
character(0)
> try(system("convert tmp/10w1x31386503857.ps tmp/10w1x31386503857.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
29.021 5.077 34.419