R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-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(94
+ ,112285
+ ,24188
+ ,146283
+ ,145
+ ,56
+ ,103
+ ,84786
+ ,18273
+ ,98364
+ ,101
+ ,56
+ ,93
+ ,83123
+ ,14130
+ ,86146
+ ,98
+ ,54
+ ,103
+ ,101193
+ ,32287
+ ,96933
+ ,132
+ ,89
+ ,51
+ ,38361
+ ,8654
+ ,79234
+ ,60
+ ,40
+ ,70
+ ,68504
+ ,9245
+ ,42551
+ ,38
+ ,25
+ ,91
+ ,119182
+ ,33251
+ ,195663
+ ,144
+ ,92
+ ,22
+ ,22807
+ ,1271
+ ,6853
+ ,5
+ ,18
+ ,38
+ ,17140
+ ,5279
+ ,21529
+ ,28
+ ,63
+ ,93
+ ,116174
+ ,27101
+ ,95757
+ ,84
+ ,44
+ ,60
+ ,57635
+ ,16373
+ ,85584
+ ,79
+ ,33
+ ,123
+ ,66198
+ ,19716
+ ,143983
+ ,127
+ ,84
+ ,148
+ ,71701
+ ,17753
+ ,75851
+ ,78
+ ,88
+ ,90
+ ,57793
+ ,9028
+ ,59238
+ ,60
+ ,55
+ ,124
+ ,80444
+ ,18653
+ ,93163
+ ,131
+ ,60
+ ,70
+ ,53855
+ ,8828
+ ,96037
+ ,84
+ ,66
+ ,168
+ ,97668
+ ,29498
+ ,151511
+ ,133
+ ,154
+ ,115
+ ,133824
+ ,27563
+ ,136368
+ ,150
+ ,53
+ ,71
+ ,101481
+ ,18293
+ ,112642
+ ,91
+ ,119
+ ,66
+ ,99645
+ ,22530
+ ,94728
+ ,132
+ ,41
+ ,134
+ ,114789
+ ,15977
+ ,105499
+ ,136
+ ,61
+ ,117
+ ,99052
+ ,35082
+ ,121527
+ ,124
+ ,58
+ ,108
+ ,67654
+ ,16116
+ ,127766
+ ,118
+ ,75
+ ,84
+ ,65553
+ ,15849
+ ,98958
+ ,70
+ ,33
+ ,156
+ ,97500
+ ,16026
+ ,77900
+ ,107
+ ,40
+ ,120
+ ,69112
+ ,26569
+ ,85646
+ ,119
+ ,92
+ ,114
+ ,82753
+ ,24785
+ ,98579
+ ,89
+ ,100
+ ,94
+ ,85323
+ ,17569
+ ,130767
+ ,112
+ ,112
+ ,120
+ ,72654
+ ,23825
+ ,131741
+ ,108
+ ,73
+ ,81
+ ,30727
+ ,7869
+ ,53907
+ ,52
+ ,40
+ ,110
+ ,77873
+ ,14975
+ ,178812
+ ,112
+ ,45
+ ,133
+ ,117478
+ ,37791
+ ,146761
+ ,116
+ ,60
+ ,122
+ ,74007
+ ,9605
+ ,82036
+ ,123
+ ,62
+ ,158
+ ,90183
+ ,27295
+ ,163253
+ ,125
+ ,75
+ ,109
+ ,61542
+ ,2746
+ ,27032
+ ,27
+ ,31
+ ,124
+ ,101494
+ ,34461
+ ,171975
+ ,162
+ ,77
+ ,39
+ ,27570
+ ,8098
+ ,65990
+ ,32
+ ,34
+ ,92
+ ,55813
+ ,4787
+ ,86572
+ ,64
+ ,46
+ ,126
+ ,79215
+ ,24919
+ ,159676
+ ,92
+ ,99
+ ,0
+ ,1423
+ ,603
+ ,1929
+ ,0
+ ,17
+ ,70
+ ,55461
+ ,16329
+ ,85371
+ ,83
+ ,66
+ ,37
+ ,31081
+ ,12558
+ ,58391
+ ,41
+ ,30
+ ,38
+ ,22996
+ ,7784
+ ,31580
+ ,47
+ ,76
+ ,120
+ ,83122
+ ,28522
+ ,136815
+ ,120
+ ,146
+ ,93
+ ,70106
+ ,22265
+ ,120642
+ ,105
+ ,67
+ ,95
+ ,60578
+ ,14459
+ ,69107
+ ,79
+ ,56
+ ,77
+ ,39992
+ ,14526
+ ,50495
+ ,65
+ ,107
+ ,90
+ ,79892
+ ,22240
+ ,108016
+ ,70
+ ,58
+ ,80
+ ,49810
+ ,11802
+ ,46341
+ ,55
+ ,34
+ ,31
+ ,71570
+ ,7623
+ ,78348
+ ,39
+ ,61
+ ,110
+ ,100708
+ ,11912
+ ,79336
+ ,67
+ ,119
+ ,66
+ ,33032
+ ,7935
+ ,56968
+ ,21
+ ,42
+ ,138
+ ,82875
+ ,18220
+ ,93176
+ ,127
+ ,66
+ ,133
+ ,139077
+ ,19199
+ ,161632
+ ,152
+ ,89
+ ,113
+ ,71595
+ ,19918
+ ,87850
+ ,113
+ ,44
+ ,100
+ ,72260
+ ,21884
+ ,127969
+ ,99
+ ,66
+ ,7
+ ,5950
+ ,2694
+ ,15049
+ ,7
+ ,24
+ ,140
+ ,115762
+ ,15808
+ ,155135
+ ,141
+ ,259
+ ,61
+ ,32551
+ ,3597
+ ,25109
+ ,21
+ ,17
+ ,41
+ ,31701
+ ,5296
+ ,45824
+ ,35
+ ,64
+ ,96
+ ,80670
+ ,25239
+ ,102996
+ ,109
+ ,41
+ ,164
+ ,143558
+ ,29801
+ ,160604
+ ,133
+ ,68
+ ,78
+ ,117105
+ ,18450
+ ,158051
+ ,123
+ ,168
+ ,49
+ ,23789
+ ,7132
+ ,44547
+ ,26
+ ,43
+ ,102
+ ,120733
+ ,34861
+ ,162647
+ ,230
+ ,132
+ ,124
+ ,105195
+ ,35940
+ ,174141
+ ,166
+ ,105
+ ,99
+ ,73107
+ ,16688
+ ,60622
+ ,68
+ ,71
+ ,129
+ ,132068
+ ,24683
+ ,179566
+ ,147
+ ,112
+ ,62
+ ,149193
+ ,46230
+ ,184301
+ ,179
+ ,94
+ ,73
+ ,46821
+ ,10387
+ ,75661
+ ,61
+ ,82
+ ,114
+ ,87011
+ ,21436
+ ,96144
+ ,101
+ ,70
+ ,99
+ ,95260
+ ,30546
+ ,129847
+ ,108
+ ,57
+ ,70
+ ,55183
+ ,19746
+ ,117286
+ ,90
+ ,53
+ ,104
+ ,106671
+ ,15977
+ ,71180
+ ,114
+ ,103
+ ,116
+ ,73511
+ ,22583
+ ,109377
+ ,103
+ ,121
+ ,91
+ ,92945
+ ,17274
+ ,85298
+ ,142
+ ,62
+ ,74
+ ,78664
+ ,16469
+ ,73631
+ ,79
+ ,52
+ ,138
+ ,70054
+ ,14251
+ ,86767
+ ,88
+ ,52
+ ,67
+ ,22618
+ ,3007
+ ,23824
+ ,25
+ ,32
+ ,151
+ ,74011
+ ,16851
+ ,93487
+ ,83
+ ,62
+ ,72
+ ,83737
+ ,21113
+ ,82981
+ ,113
+ ,45
+ ,120
+ ,69094
+ ,17401
+ ,73815
+ ,118
+ ,46
+ ,115
+ ,93133
+ ,23958
+ ,94552
+ ,110
+ ,63
+ ,105
+ ,95536
+ ,23567
+ ,132190
+ ,129
+ ,75
+ ,104
+ ,225920
+ ,13065
+ ,128754
+ ,51
+ ,88
+ ,108
+ ,62133
+ ,15358
+ ,66363
+ ,93
+ ,46
+ ,98
+ ,61370
+ ,14587
+ ,67808
+ ,76
+ ,53
+ ,69
+ ,43836
+ ,12770
+ ,61724
+ ,49
+ ,37
+ ,111
+ ,106117
+ ,24021
+ ,131722
+ ,118
+ ,90
+ ,99
+ ,38692
+ ,9648
+ ,68580
+ ,38
+ ,63
+ ,71
+ ,84651
+ ,20537
+ ,106175
+ ,141
+ ,78
+ ,27
+ ,56622
+ ,7905
+ ,55792
+ ,58
+ ,25
+ ,69
+ ,15986
+ ,4527
+ ,25157
+ ,27
+ ,45
+ ,107
+ ,95364
+ ,30495
+ ,76669
+ ,91
+ ,46
+ ,73
+ ,26706
+ ,7117
+ ,57283
+ ,48
+ ,41
+ ,107
+ ,89691
+ ,17719
+ ,105805
+ ,63
+ ,144
+ ,93
+ ,67267
+ ,27056
+ ,129484
+ ,56
+ ,82
+ ,129
+ ,126846
+ ,33473
+ ,72413
+ ,144
+ ,91
+ ,69
+ ,41140
+ ,9758
+ ,87831
+ ,73
+ ,71
+ ,118
+ ,102860
+ ,21115
+ ,96971
+ ,168
+ ,63
+ ,73
+ ,51715
+ ,7236
+ ,71299
+ ,64
+ ,53
+ ,119
+ ,55801
+ ,13790
+ ,77494
+ ,97
+ ,62
+ ,104
+ ,111813
+ ,32902
+ ,120336
+ ,117
+ ,63
+ ,107
+ ,120293
+ ,25131
+ ,93913
+ ,100
+ ,32
+ ,99
+ ,138599
+ ,30910
+ ,136048
+ ,149
+ ,39
+ ,90
+ ,161647
+ ,35947
+ ,181248
+ ,187
+ ,62
+ ,197
+ ,115929
+ ,29848
+ ,146123
+ ,127
+ ,117
+ ,36
+ ,24266
+ ,6943
+ ,32036
+ ,37
+ ,34
+ ,85
+ ,162901
+ ,42705
+ ,186646
+ ,245
+ ,92
+ ,139
+ ,109825
+ ,31808
+ ,102255
+ ,87
+ ,93
+ ,106
+ ,129838
+ ,26675
+ ,168237
+ ,177
+ ,54
+ ,50
+ ,37510
+ ,8435
+ ,64219
+ ,49
+ ,144
+ ,64
+ ,43750
+ ,7409
+ ,19630
+ ,49
+ ,14
+ ,31
+ ,40652
+ ,14993
+ ,76825
+ ,73
+ ,61
+ ,63
+ ,87771
+ ,36867
+ ,115338
+ ,177
+ ,109
+ ,92
+ ,85872
+ ,33835
+ ,109427
+ ,94
+ ,38
+ ,106
+ ,89275
+ ,24164
+ ,118168
+ ,117
+ ,73
+ ,63
+ ,44418
+ ,12607
+ ,84845
+ ,60
+ ,75
+ ,69
+ ,192565
+ ,22609
+ ,153197
+ ,55
+ ,50
+ ,41
+ ,35232
+ ,5892
+ ,29877
+ ,39
+ ,61
+ ,56
+ ,40909
+ ,17014
+ ,63506
+ ,64
+ ,55
+ ,25
+ ,13294
+ ,5394
+ ,22445
+ ,26
+ ,77
+ ,65
+ ,32387
+ ,9178
+ ,47695
+ ,64
+ ,75
+ ,93
+ ,140867
+ ,6440
+ ,68370
+ ,58
+ ,72
+ ,114
+ ,120662
+ ,21916
+ ,146304
+ ,95
+ ,50
+ ,38
+ ,21233
+ ,4011
+ ,38233
+ ,25
+ ,32
+ ,44
+ ,44332
+ ,5818
+ ,42071
+ ,26
+ ,53
+ ,87
+ ,61056
+ ,18647
+ ,50517
+ ,76
+ ,42
+ ,110
+ ,101338
+ ,20556
+ ,103950
+ ,129
+ ,71
+ ,0
+ ,1168
+ ,238
+ ,5841
+ ,11
+ ,10
+ ,27
+ ,13497
+ ,70
+ ,2341
+ ,2
+ ,35
+ ,83
+ ,65567
+ ,22392
+ ,84396
+ ,101
+ ,65
+ ,30
+ ,25162
+ ,3913
+ ,24610
+ ,28
+ ,25
+ ,80
+ ,32334
+ ,12237
+ ,35753
+ ,36
+ ,66
+ ,98
+ ,40735
+ ,8388
+ ,55515
+ ,89
+ ,41
+ ,82
+ ,91413
+ ,22120
+ ,209056
+ ,193
+ ,86
+ ,0
+ ,855
+ ,338
+ ,6622
+ ,4
+ ,16
+ ,60
+ ,97068
+ ,11727
+ ,115814
+ ,84
+ ,42
+ ,28
+ ,44339
+ ,3704
+ ,11609
+ ,23
+ ,19
+ ,9
+ ,14116
+ ,3988
+ ,13155
+ ,39
+ ,19
+ ,33
+ ,10288
+ ,3030
+ ,18274
+ ,14
+ ,45
+ ,59
+ ,65622
+ ,13520
+ ,72875
+ ,78
+ ,65
+ ,49
+ ,16563
+ ,1421
+ ,10112
+ ,14
+ ,35
+ ,115
+ ,76643
+ ,20923
+ ,142775
+ ,101
+ ,95
+ ,140
+ ,110681
+ ,20237
+ ,68847
+ ,82
+ ,49
+ ,49
+ ,29011
+ ,3219
+ ,17659
+ ,24
+ ,37
+ ,120
+ ,92696
+ ,3769
+ ,20112
+ ,36
+ ,64
+ ,66
+ ,94785
+ ,12252
+ ,61023
+ ,75
+ ,38
+ ,21
+ ,8773
+ ,1888
+ ,13983
+ ,16
+ ,34
+ ,124
+ ,83209
+ ,14497
+ ,65176
+ ,55
+ ,32
+ ,152
+ ,93815
+ ,28864
+ ,132432
+ ,131
+ ,65
+ ,139
+ ,86687
+ ,21721
+ ,112494
+ ,131
+ ,52
+ ,38
+ ,34553
+ ,4821
+ ,45109
+ ,39
+ ,62
+ ,144
+ ,105547
+ ,33644
+ ,170875
+ ,144
+ ,65
+ ,120
+ ,103487
+ ,15923
+ ,180759
+ ,139
+ ,83
+ ,160
+ ,213688
+ ,42935
+ ,214921
+ ,211
+ ,95
+ ,114
+ ,71220
+ ,18864
+ ,100226
+ ,78
+ ,29
+ ,39
+ ,23517
+ ,4977
+ ,32043
+ ,50
+ ,18
+ ,78
+ ,56926
+ ,7785
+ ,54454
+ ,39
+ ,33
+ ,119
+ ,91721
+ ,17939
+ ,78876
+ ,90
+ ,247
+ ,141
+ ,115168
+ ,23436
+ ,170745
+ ,166
+ ,139
+ ,101
+ ,111194
+ ,325
+ ,6940
+ ,12
+ ,29
+ ,56
+ ,51009
+ ,13539
+ ,49025
+ ,57
+ ,118
+ ,133
+ ,135777
+ ,34538
+ ,122037
+ ,133
+ ,110
+ ,83
+ ,51513
+ ,12198
+ ,53782
+ ,69
+ ,67
+ ,116
+ ,74163
+ ,26924
+ ,127748
+ ,119
+ ,42
+ ,90
+ ,51633
+ ,12716
+ ,86839
+ ,119
+ ,65
+ ,36
+ ,75345
+ ,8172
+ ,44830
+ ,65
+ ,94
+ ,50
+ ,33416
+ ,10855
+ ,77395
+ ,61
+ ,64
+ ,61
+ ,83305
+ ,11932
+ ,89324
+ ,49
+ ,81
+ ,97
+ ,98952
+ ,14300
+ ,103300
+ ,101
+ ,95
+ ,98
+ ,102372
+ ,25515
+ ,112283
+ ,196
+ ,67
+ ,78
+ ,37238
+ ,2805
+ ,10901
+ ,15
+ ,63
+ ,117
+ ,103772
+ ,29402
+ ,120691
+ ,136
+ ,83
+ ,148
+ ,123969
+ ,16440
+ ,58106
+ ,89
+ ,45
+ ,41
+ ,27142
+ ,11221
+ ,57140
+ ,40
+ ,30
+ ,105
+ ,135400
+ ,28732
+ ,122422
+ ,123
+ ,70
+ ,55
+ ,21399
+ ,5250
+ ,25899
+ ,21
+ ,32
+ ,132
+ ,130115
+ ,28608
+ ,139296
+ ,163
+ ,83
+ ,44
+ ,24874
+ ,8092
+ ,52678
+ ,29
+ ,31
+ ,21
+ ,34988
+ ,4473
+ ,23853
+ ,35
+ ,67
+ ,50
+ ,45549
+ ,1572
+ ,17306
+ ,13
+ ,66
+ ,0
+ ,6023
+ ,2065
+ ,7953
+ ,5
+ ,10
+ ,73
+ ,64466
+ ,14817
+ ,89455
+ ,96
+ ,70
+ ,86
+ ,54990
+ ,16714
+ ,147866
+ ,151
+ ,103
+ ,0
+ ,1644
+ ,556
+ ,4245
+ ,6
+ ,5
+ ,13
+ ,6179
+ ,2089
+ ,21509
+ ,13
+ ,20
+ ,4
+ ,3926
+ ,2658
+ ,7670
+ ,3
+ ,5
+ ,57
+ ,32755
+ ,10695
+ ,66675
+ ,56
+ ,36
+ ,48
+ ,34777
+ ,1669
+ ,14336
+ ,23
+ ,34
+ ,46
+ ,73224
+ ,16267
+ ,53608
+ ,57
+ ,48
+ ,48
+ ,27114
+ ,7768
+ ,30059
+ ,14
+ ,40
+ ,32
+ ,20760
+ ,7252
+ ,29668
+ ,43
+ ,43
+ ,68
+ ,37636
+ ,6387
+ ,22097
+ ,20
+ ,31
+ ,87
+ ,65461
+ ,18715
+ ,96841
+ ,72
+ ,42
+ ,43
+ ,30080
+ ,7936
+ ,41907
+ ,87
+ ,46
+ ,67
+ ,24094
+ ,8643
+ ,27080
+ ,21
+ ,33
+ ,46
+ ,69008
+ ,7294
+ ,35885
+ ,56
+ ,18
+ ,46
+ ,54968
+ ,4570
+ ,41247
+ ,59
+ ,55
+ ,56
+ ,46090
+ ,7185
+ ,28313
+ ,82
+ ,35
+ ,48
+ ,27507
+ ,10058
+ ,36845
+ ,43
+ ,59
+ ,44
+ ,10672
+ ,2342
+ ,16548
+ ,25
+ ,19
+ ,60
+ ,34029
+ ,8509
+ ,36134
+ ,38
+ ,66
+ ,65
+ ,46300
+ ,13275
+ ,55764
+ ,25
+ ,60
+ ,55
+ ,24760
+ ,6816
+ ,28910
+ ,38
+ ,36
+ ,38
+ ,18779
+ ,1930
+ ,13339
+ ,12
+ ,25
+ ,52
+ ,21280
+ ,8086
+ ,25319
+ ,29
+ ,47
+ ,60
+ ,40662
+ ,10737
+ ,66956
+ ,47
+ ,54
+ ,54
+ ,28987
+ ,8033
+ ,47487
+ ,45
+ ,53
+ ,86
+ ,22827
+ ,7058
+ ,52785
+ ,40
+ ,40
+ ,24
+ ,18513
+ ,6782
+ ,44683
+ ,30
+ ,40
+ ,52
+ ,30594
+ ,5401
+ ,35619
+ ,41
+ ,39
+ ,49
+ ,24006
+ ,6521
+ ,21920
+ ,25
+ ,14
+ ,61
+ ,27913
+ ,10856
+ ,45608
+ ,23
+ ,45
+ ,61
+ ,42744
+ ,2154
+ ,7721
+ ,14
+ ,36
+ ,81
+ ,12934
+ ,6117
+ ,20634
+ ,16
+ ,28
+ ,43
+ ,22574
+ ,5238
+ ,29788
+ ,26
+ ,44
+ ,40
+ ,41385
+ ,4820
+ ,31931
+ ,21
+ ,30
+ ,40
+ ,18653
+ ,5615
+ ,37754
+ ,27
+ ,22
+ ,56
+ ,18472
+ ,4272
+ ,32505
+ ,9
+ ,17
+ ,68
+ ,30976
+ ,8702
+ ,40557
+ ,33
+ ,31
+ ,79
+ ,63339
+ ,15340
+ ,94238
+ ,42
+ ,55
+ ,47
+ ,25568
+ ,8030
+ ,44197
+ ,68
+ ,54
+ ,57
+ ,33747
+ ,9526
+ ,43228
+ ,32
+ ,21
+ ,41
+ ,4154
+ ,1278
+ ,4103
+ ,6
+ ,14
+ ,29
+ ,19474
+ ,4236
+ ,44144
+ ,67
+ ,81
+ ,3
+ ,35130
+ ,3023
+ ,32868
+ ,33
+ ,35
+ ,60
+ ,39067
+ ,7196
+ ,27640
+ ,77
+ ,43
+ ,30
+ ,13310
+ ,3394
+ ,14063
+ ,46
+ ,46
+ ,79
+ ,65892
+ ,6371
+ ,28990
+ ,30
+ ,30
+ ,47
+ ,4143
+ ,1574
+ ,4694
+ ,0
+ ,23
+ ,40
+ ,28579
+ ,9620
+ ,42648
+ ,36
+ ,38
+ ,48
+ ,51776
+ ,6978
+ ,64329
+ ,46
+ ,54
+ ,36
+ ,21152
+ ,4911
+ ,21928
+ ,18
+ ,20
+ ,42
+ ,38084
+ ,8645
+ ,25836
+ ,48
+ ,53
+ ,49
+ ,27717
+ ,8987
+ ,22779
+ ,29
+ ,45
+ ,57
+ ,32928
+ ,5544
+ ,40820
+ ,28
+ ,39
+ ,12
+ ,11342
+ ,3083
+ ,27530
+ ,34
+ ,20
+ ,40
+ ,19499
+ ,6909
+ ,32378
+ ,33
+ ,24
+ ,43
+ ,16380
+ ,3189
+ ,10824
+ ,34
+ ,31
+ ,33
+ ,36874
+ ,6745
+ ,39613
+ ,33
+ ,35
+ ,77
+ ,48259
+ ,16724
+ ,60865
+ ,80
+ ,151
+ ,43
+ ,16734
+ ,4850
+ ,19787
+ ,32
+ ,52
+ ,45
+ ,28207
+ ,7025
+ ,20107
+ ,30
+ ,30
+ ,47
+ ,30143
+ ,6047
+ ,36605
+ ,41
+ ,31
+ ,43
+ ,41369
+ ,7377
+ ,40961
+ ,41
+ ,29
+ ,45
+ ,45833
+ ,9078
+ ,48231
+ ,51
+ ,57
+ ,50
+ ,29156
+ ,4605
+ ,39725
+ ,18
+ ,40
+ ,35
+ ,35944
+ ,3238
+ ,21455
+ ,34
+ ,44
+ ,7
+ ,36278
+ ,8100
+ ,23430
+ ,31
+ ,25
+ ,71
+ ,45588
+ ,9653
+ ,62991
+ ,39
+ ,77
+ ,67
+ ,45097
+ ,8914
+ ,49363
+ ,54
+ ,35
+ ,0
+ ,3895
+ ,786
+ ,9604
+ ,14
+ ,11
+ ,62
+ ,28394
+ ,6700
+ ,24552
+ ,24
+ ,63
+ ,54
+ ,18632
+ ,5788
+ ,31493
+ ,24
+ ,44
+ ,4
+ ,2325
+ ,593
+ ,3439
+ ,8
+ ,19
+ ,25
+ ,25139
+ ,4506
+ ,19555
+ ,26
+ ,13
+ ,40
+ ,27975
+ ,6382
+ ,21228
+ ,19
+ ,42
+ ,38
+ ,14483
+ ,5621
+ ,23177
+ ,11
+ ,38
+ ,19
+ ,13127
+ ,3997
+ ,22094
+ ,14
+ ,29
+ ,17
+ ,5839
+ ,520
+ ,2342
+ ,1
+ ,20
+ ,67
+ ,24069
+ ,8891
+ ,38798
+ ,39
+ ,27
+ ,14
+ ,3738
+ ,999
+ ,3255
+ ,5
+ ,20
+ ,30
+ ,18625
+ ,7067
+ ,24261
+ ,37
+ ,19
+ ,54
+ ,36341
+ ,4639
+ ,18511
+ ,32
+ ,37
+ ,35
+ ,24548
+ ,5654
+ ,40798
+ ,38
+ ,26
+ ,59
+ ,21792
+ ,6928
+ ,28893
+ ,47
+ ,42
+ ,24
+ ,26263
+ ,1514
+ ,21425
+ ,47
+ ,49
+ ,58
+ ,23686
+ ,9238
+ ,50276
+ ,37
+ ,30
+ ,42
+ ,49303
+ ,8204
+ ,37643
+ ,51
+ ,49
+ ,46
+ ,25659
+ ,5926
+ ,30377
+ ,45
+ ,67
+ ,61
+ ,28904
+ ,5785
+ ,27126
+ ,21
+ ,28
+ ,3
+ ,2781
+ ,4
+ ,13
+ ,1
+ ,19
+ ,52
+ ,29236
+ ,5930
+ ,42097
+ ,42
+ ,49
+ ,25
+ ,19546
+ ,3710
+ ,24451
+ ,26
+ ,27
+ ,40
+ ,22818
+ ,705
+ ,14335
+ ,21
+ ,30
+ ,32
+ ,32689
+ ,443
+ ,5084
+ ,4
+ ,22
+ ,4
+ ,5752
+ ,2416
+ ,9927
+ ,10
+ ,12
+ ,49
+ ,22197
+ ,7747
+ ,43527
+ ,43
+ ,31
+ ,63
+ ,20055
+ ,5432
+ ,27184
+ ,34
+ ,20
+ ,67
+ ,25272
+ ,4913
+ ,21610
+ ,31
+ ,20
+ ,32
+ ,82206
+ ,2650
+ ,20484
+ ,19
+ ,39
+ ,23
+ ,32073
+ ,2370
+ ,20156
+ ,34
+ ,29
+ ,7
+ ,5444
+ ,775
+ ,6012
+ ,6
+ ,16
+ ,54
+ ,20154
+ ,5576
+ ,18475
+ ,11
+ ,27
+ ,37
+ ,36944
+ ,1352
+ ,12645
+ ,24
+ ,21
+ ,35
+ ,8019
+ ,3080
+ ,11017
+ ,16
+ ,19
+ ,51
+ ,30884
+ ,10205
+ ,37623
+ ,72
+ ,35
+ ,39
+ ,19540
+ ,6095
+ ,35873
+ ,21
+ ,14)
+ ,dim=c(6
+ ,289)
+ ,dimnames=list(c('feedback_messages_p120'
+ ,'totsize'
+ ,'totrevisions'
+ ,'totseconds'
+ ,'totblogs'
+ ,'logins')
+ ,1:289))
>  y <- array(NA,dim=c(6,289),dimnames=list(c('feedback_messages_p120','totsize','totrevisions','totseconds','totblogs','logins'),1:289))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par4 = 'yes'
> par3 = '2'
> par2 = 'quantiles'
> par1 = '1'
> library(party)
Loading required package: survival
Loading required package: splines
Loading required package: grid
Loading required package: modeltools
Loading required package: stats4
Loading required package: coin
Loading required package: mvtnorm
Loading required package: zoo
Loading required package: sandwich
Loading required package: strucchange
Loading required package: vcd
Loading required package: MASS
Loading required package: colorspace
> library(Hmisc)

Attaching package: 'Hmisc'

The following object(s) are masked from 'package:survival':

    untangle.specials

The following object(s) are masked from 'package:base':

    format.pval, round.POSIXt, trunc.POSIXt, units

> par1 <- as.numeric(par1)
> par3 <- as.numeric(par3)
> x <- data.frame(t(y))
> is.data.frame(x)
[1] TRUE
> x <- x[!is.na(x[,par1]),]
> k <- length(x[1,])
> n <- length(x[,1])
> colnames(x)[par1]
[1] "feedback_messages_p120"
> x[,par1]
  [1]  94 103  93 103  51  70  91  22  38  93  60 123 148  90 124  70 168 115
 [19]  71  66 134 117 108  84 156 120 114  94 120  81 110 133 122 158 109 124
 [37]  39  92 126   0  70  37  38 120  93  95  77  90  80  31 110  66 138 133
 [55] 113 100   7 140  61  41  96 164  78  49 102 124  99 129  62  73 114  99
 [73]  70 104 116  91  74 138  67 151  72 120 115 105 104 108  98  69 111  99
 [91]  71  27  69 107  73 107  93 129  69 118  73 119 104 107  99  90 197  36
[109]  85 139 106  50  64  31  63  92 106  63  69  41  56  25  65  93 114  38
[127]  44  87 110   0  27  83  30  80  98  82   0  60  28   9  33  59  49 115
[145] 140  49 120  66  21 124 152 139  38 144 120 160 114  39  78 119 141 101
[163]  56 133  83 116  90  36  50  61  97  98  78 117 148  41 105  55 132  44
[181]  21  50   0  73  86   0  13   4  57  48  46  48  32  68  87  43  67  46
[199]  46  56  48  44  60  65  55  38  52  60  54  86  24  52  49  61  61  81
[217]  43  40  40  56  68  79  47  57  41  29   3  60  30  79  47  40  48  36
[235]  42  49  57  12  40  43  33  77  43  45  47  43  45  50  35   7  71  67
[253]   0  62  54   4  25  40  38  19  17  67  14  30  54  35  59  24  58  42
[271]  46  61   3  52  25  40  32   4  49  63  67  32  23   7  54  37  35  51
[289]  39
> if (par2 == 'kmeans') {
+ cl <- kmeans(x[,par1], par3)
+ print(cl)
+ clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
+ clm <- clm[sort.list(clm[,1]),]
+ for (i in 1:par3) {
+ cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
+ }
+ cl$cluster <- as.factor(cl$cluster)
+ print(cl$cluster)
+ x[,par1] <- cl$cluster
+ }
> if (par2 == 'quantiles') {
+ x[,par1] <- cut2(x[,par1],g=par3)
+ }
> if (par2 == 'hclust') {
+ hc <- hclust(dist(x[,par1])^2, 'cen')
+ print(hc)
+ memb <- cutree(hc, k = par3)
+ dum <- c(mean(x[memb==1,par1]))
+ for (i in 2:par3) {
+ dum <- c(dum, mean(x[memb==i,par1]))
+ }
+ hcm <- matrix(cbind(dum,1:par3),ncol=2)
+ hcm <- hcm[sort.list(hcm[,1]),]
+ for (i in 1:par3) {
+ memb[memb==hcm[i,2]] <- paste('C',i,sep='')
+ }
+ memb <- as.factor(memb)
+ print(memb)
+ x[,par1] <- memb
+ }
> if (par2=='equal') {
+ ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
+ x[,par1] <- as.factor(ed)
+ }
> table(x[,par1])

[ 0, 67) [67,197] 
     145      144 
> colnames(x)
[1] "feedback_messages_p120" "totsize"                "totrevisions"          
[4] "totseconds"             "totblogs"               "logins"                
> colnames(x)[par1]
[1] "feedback_messages_p120"
> x[,par1]
  [1] [67,197] [67,197] [67,197] [67,197] [ 0, 67) [67,197] [67,197] [ 0, 67)
  [9] [ 0, 67) [67,197] [ 0, 67) [67,197] [67,197] [67,197] [67,197] [67,197]
 [17] [67,197] [67,197] [67,197] [ 0, 67) [67,197] [67,197] [67,197] [67,197]
 [25] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197]
 [33] [67,197] [67,197] [67,197] [67,197] [ 0, 67) [67,197] [67,197] [ 0, 67)
 [41] [67,197] [ 0, 67) [ 0, 67) [67,197] [67,197] [67,197] [67,197] [67,197]
 [49] [67,197] [ 0, 67) [67,197] [ 0, 67) [67,197] [67,197] [67,197] [67,197]
 [57] [ 0, 67) [67,197] [ 0, 67) [ 0, 67) [67,197] [67,197] [67,197] [ 0, 67)
 [65] [67,197] [67,197] [67,197] [67,197] [ 0, 67) [67,197] [67,197] [67,197]
 [73] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197]
 [81] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197]
 [89] [67,197] [67,197] [67,197] [ 0, 67) [67,197] [67,197] [67,197] [67,197]
 [97] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197] [67,197]
[105] [67,197] [67,197] [67,197] [ 0, 67) [67,197] [67,197] [67,197] [ 0, 67)
[113] [ 0, 67) [ 0, 67) [ 0, 67) [67,197] [67,197] [ 0, 67) [67,197] [ 0, 67)
[121] [ 0, 67) [ 0, 67) [ 0, 67) [67,197] [67,197] [ 0, 67) [ 0, 67) [67,197]
[129] [67,197] [ 0, 67) [ 0, 67) [67,197] [ 0, 67) [67,197] [67,197] [67,197]
[137] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [67,197]
[145] [67,197] [ 0, 67) [67,197] [ 0, 67) [ 0, 67) [67,197] [67,197] [67,197]
[153] [ 0, 67) [67,197] [67,197] [67,197] [67,197] [ 0, 67) [67,197] [67,197]
[161] [67,197] [67,197] [ 0, 67) [67,197] [67,197] [67,197] [67,197] [ 0, 67)
[169] [ 0, 67) [ 0, 67) [67,197] [67,197] [67,197] [67,197] [67,197] [ 0, 67)
[177] [67,197] [ 0, 67) [67,197] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [67,197]
[185] [67,197] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67)
[193] [ 0, 67) [67,197] [67,197] [ 0, 67) [67,197] [ 0, 67) [ 0, 67) [ 0, 67)
[201] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67)
[209] [ 0, 67) [67,197] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [67,197]
[217] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [67,197] [67,197] [ 0, 67) [ 0, 67)
[225] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [67,197] [ 0, 67) [ 0, 67)
[233] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67)
[241] [ 0, 67) [67,197] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67)
[249] [ 0, 67) [ 0, 67) [67,197] [67,197] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67)
[257] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [67,197] [ 0, 67) [ 0, 67)
[265] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67)
[273] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67)
[281] [67,197] [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67) [ 0, 67)
[289] [ 0, 67)
Levels: [ 0, 67) [67,197]
> if (par2 == 'none') {
+ m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
+ }
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
> 
> if (par2 != 'none') {
+ m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
+ if (par4=='yes') {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'',1,TRUE)
+ a<-table.element(a,'Prediction (training)',par3+1,TRUE)
+ a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Actual',1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
+ a<-table.element(a,'CV',1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
+ a<-table.element(a,'CV',1,TRUE)
+ a<-table.row.end(a)
+ for (i in 1:10) {
+ ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
+ m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
+ if (i==1) {
+ m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
+ m.ct.i.actu <- x[ind==1,par1]
+ m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
+ m.ct.x.actu <- x[ind==2,par1]
+ } else {
+ m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
+ m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
+ m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
+ m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
+ }
+ }
+ print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
+ numer <- 0
+ for (i in 1:par3) {
+ print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
+ numer <- numer + m.ct.i.tab[i,i]
+ }
+ print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
+ print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
+ numer <- 0
+ for (i in 1:par3) {
+ print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
+ numer <- numer + m.ct.x.tab[i,i]
+ }
+ print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
+ for (i in 1:par3) {
+ a<-table.row.start(a)
+ a<-table.element(a,paste('C',i,sep=''),1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
+ a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
+ for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
+ a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
+ a<-table.row.end(a)
+ }
+ a<-table.row.start(a)
+ a<-table.element(a,'Overall',1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,'-')
+ a<-table.element(a,round(m.ct.i.cp,4))
+ for (jjj in 1:par3) a<-table.element(a,'-')
+ a<-table.element(a,round(m.ct.x.cp,4))
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/1xgve1324660062.tab") 
+ }
+ }
           m.ct.i.pred
m.ct.i.actu    1    2
          1 1172  124
          2  217 1087
[1] 0.904321
[1] 0.833589
[1] 0.8688462
           m.ct.x.pred
m.ct.x.actu   1   2
          1 129  25
          2  21 115
[1] 0.8376623
[1] 0.8455882
[1] 0.8413793
> m

	 Conditional inference tree with 4 terminal nodes

Response:  as.factor(feedback_messages_p120) 
Inputs:  totsize, totrevisions, totseconds, totblogs, logins 
Number of observations:  289 

1) totseconds <= 49025; criterion = 1, statistic = 128.631
  2) totsize <= 49303; criterion = 1, statistic = 16.29
    3)*  weights = 123 
  2) totsize > 49303
    4)*  weights = 11 
1) totseconds > 49025
  5) totblogs <= 61; criterion = 1, statistic = 22.253
    6)*  weights = 34 
  5) totblogs > 61
    7)*  weights = 121 
> postscript(file="/var/www/rcomp/tmp/2mh6e1324660062.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m)
> dev.off()
null device 
          1 
> postscript(file="/var/www/rcomp/tmp/3klzr1324660062.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
> dev.off()
null device 
          1 
> if (par2 == 'none') {
+ forec <- predict(m)
+ result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
+ colnames(result) <- c('Actuals','Forecasts','Residuals')
+ print(result)
+ }
> if (par2 != 'none') {
+ print(cbind(as.factor(x[,par1]),predict(m)))
+ myt <- table(as.factor(x[,par1]),predict(m))
+ print(myt)
+ }
       [,1] [,2]
  [1,]    2    2
  [2,]    2    2
  [3,]    2    2
  [4,]    2    2
  [5,]    1    1
  [6,]    2    2
  [7,]    2    2
  [8,]    1    1
  [9,]    1    1
 [10,]    2    2
 [11,]    1    2
 [12,]    2    2
 [13,]    2    2
 [14,]    2    1
 [15,]    2    2
 [16,]    2    2
 [17,]    2    2
 [18,]    2    2
 [19,]    2    2
 [20,]    1    2
 [21,]    2    2
 [22,]    2    2
 [23,]    2    2
 [24,]    2    2
 [25,]    2    2
 [26,]    2    2
 [27,]    2    2
 [28,]    2    2
 [29,]    2    2
 [30,]    2    1
 [31,]    2    2
 [32,]    2    2
 [33,]    2    2
 [34,]    2    2
 [35,]    2    2
 [36,]    2    2
 [37,]    1    1
 [38,]    2    2
 [39,]    2    2
 [40,]    1    1
 [41,]    2    2
 [42,]    1    1
 [43,]    1    1
 [44,]    2    2
 [45,]    2    2
 [46,]    2    2
 [47,]    2    2
 [48,]    2    2
 [49,]    2    2
 [50,]    1    1
 [51,]    2    2
 [52,]    1    1
 [53,]    2    2
 [54,]    2    2
 [55,]    2    2
 [56,]    2    2
 [57,]    1    1
 [58,]    2    2
 [59,]    1    1
 [60,]    1    1
 [61,]    2    2
 [62,]    2    2
 [63,]    2    2
 [64,]    1    1
 [65,]    2    2
 [66,]    2    2
 [67,]    2    2
 [68,]    2    2
 [69,]    1    2
 [70,]    2    1
 [71,]    2    2
 [72,]    2    2
 [73,]    2    2
 [74,]    2    2
 [75,]    2    2
 [76,]    2    2
 [77,]    2    2
 [78,]    2    2
 [79,]    2    1
 [80,]    2    2
 [81,]    2    2
 [82,]    2    2
 [83,]    2    2
 [84,]    2    2
 [85,]    2    1
 [86,]    2    2
 [87,]    2    2
 [88,]    2    1
 [89,]    2    2
 [90,]    2    1
 [91,]    2    2
 [92,]    1    1
 [93,]    2    1
 [94,]    2    2
 [95,]    2    1
 [96,]    2    2
 [97,]    2    1
 [98,]    2    2
 [99,]    2    2
[100,]    2    2
[101,]    2    2
[102,]    2    2
[103,]    2    2
[104,]    2    2
[105,]    2    2
[106,]    2    2
[107,]    2    2
[108,]    1    1
[109,]    2    2
[110,]    2    2
[111,]    2    2
[112,]    1    1
[113,]    1    1
[114,]    1    2
[115,]    1    2
[116,]    2    2
[117,]    2    2
[118,]    1    1
[119,]    2    1
[120,]    1    1
[121,]    1    2
[122,]    1    1
[123,]    1    1
[124,]    2    1
[125,]    2    2
[126,]    1    1
[127,]    1    1
[128,]    2    2
[129,]    2    2
[130,]    1    1
[131,]    1    1
[132,]    2    2
[133,]    1    1
[134,]    2    1
[135,]    2    2
[136,]    2    2
[137,]    1    1
[138,]    1    2
[139,]    1    1
[140,]    1    1
[141,]    1    1
[142,]    1    2
[143,]    1    1
[144,]    2    2
[145,]    2    2
[146,]    1    1
[147,]    2    2
[148,]    1    2
[149,]    1    1
[150,]    2    1
[151,]    2    2
[152,]    2    2
[153,]    1    1
[154,]    2    2
[155,]    2    2
[156,]    2    2
[157,]    2    2
[158,]    1    1
[159,]    2    1
[160,]    2    2
[161,]    2    2
[162,]    2    2
[163,]    1    2
[164,]    2    2
[165,]    2    2
[166,]    2    2
[167,]    2    2
[168,]    1    2
[169,]    1    1
[170,]    1    1
[171,]    2    2
[172,]    2    2
[173,]    2    1
[174,]    2    2
[175,]    2    2
[176,]    1    1
[177,]    2    2
[178,]    1    1
[179,]    2    2
[180,]    1    1
[181,]    1    1
[182,]    1    1
[183,]    1    1
[184,]    2    2
[185,]    2    2
[186,]    1    1
[187,]    1    1
[188,]    1    1
[189,]    1    1
[190,]    1    1
[191,]    1    1
[192,]    1    1
[193,]    1    1
[194,]    2    1
[195,]    2    2
[196,]    1    1
[197,]    2    1
[198,]    1    2
[199,]    1    2
[200,]    1    1
[201,]    1    1
[202,]    1    1
[203,]    1    1
[204,]    1    1
[205,]    1    1
[206,]    1    1
[207,]    1    1
[208,]    1    1
[209,]    1    1
[210,]    2    1
[211,]    1    1
[212,]    1    1
[213,]    1    1
[214,]    1    1
[215,]    1    1
[216,]    2    1
[217,]    1    1
[218,]    1    1
[219,]    1    1
[220,]    1    1
[221,]    2    1
[222,]    2    1
[223,]    1    1
[224,]    1    1
[225,]    1    1
[226,]    1    1
[227,]    1    1
[228,]    1    1
[229,]    1    1
[230,]    2    2
[231,]    1    1
[232,]    1    1
[233,]    1    1
[234,]    1    1
[235,]    1    1
[236,]    1    1
[237,]    1    1
[238,]    1    1
[239,]    1    1
[240,]    1    1
[241,]    1    1
[242,]    2    2
[243,]    1    1
[244,]    1    1
[245,]    1    1
[246,]    1    1
[247,]    1    1
[248,]    1    1
[249,]    1    1
[250,]    1    1
[251,]    2    1
[252,]    2    1
[253,]    1    1
[254,]    1    1
[255,]    1    1
[256,]    1    1
[257,]    1    1
[258,]    1    1
[259,]    1    1
[260,]    1    1
[261,]    1    1
[262,]    2    1
[263,]    1    1
[264,]    1    1
[265,]    1    1
[266,]    1    1
[267,]    1    1
[268,]    1    1
[269,]    1    1
[270,]    1    1
[271,]    1    1
[272,]    1    1
[273,]    1    1
[274,]    1    1
[275,]    1    1
[276,]    1    1
[277,]    1    1
[278,]    1    1
[279,]    1    1
[280,]    1    1
[281,]    2    1
[282,]    1    2
[283,]    1    1
[284,]    1    1
[285,]    1    1
[286,]    1    1
[287,]    1    1
[288,]    1    1
[289,]    1    1
          
           [ 0, 67) [67,197]
  [ 0, 67)      131       14
  [67,197]       26      118
> postscript(file="/var/www/rcomp/tmp/4lbs71324660062.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if(par2=='none') {
+ op <- par(mfrow=c(2,2))
+ plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
+ plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
+ plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
+ plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
+ par(op)
+ }
> if(par2!='none') {
+ plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
+ }
> dev.off()
null device 
          1 
> if (par2 == 'none') {
+ detcoef <- cor(result$Forecasts,result$Actuals)
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goodness of Fit',2,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Correlation',1,TRUE)
+ a<-table.element(a,round(detcoef,4))
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'R-squared',1,TRUE)
+ a<-table.element(a,round(detcoef*detcoef,4))
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'RMSE',1,TRUE)
+ a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/575ux1324660062.tab") 
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'#',header=TRUE)
+ a<-table.element(a,'Actuals',header=TRUE)
+ a<-table.element(a,'Forecasts',header=TRUE)
+ a<-table.element(a,'Residuals',header=TRUE)
+ a<-table.row.end(a)
+ for (i in 1:length(result$Actuals)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,result$Actuals[i])
+ a<-table.element(a,result$Forecasts[i])
+ a<-table.element(a,result$Residuals[i])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/6hjrz1324660062.tab") 
+ }
> if (par2 != 'none') {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'',1,TRUE)
+ for (i in 1:par3) {
+ a<-table.element(a,paste('C',i,sep=''),1,TRUE)
+ }
+ a<-table.row.end(a)
+ for (i in 1:par3) {
+ a<-table.row.start(a)
+ a<-table.element(a,paste('C',i,sep=''),1,TRUE)
+ for (j in 1:par3) {
+ a<-table.element(a,myt[i,j])
+ }
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/7pwu51324660062.tab") 
+ }
> 
> try(system("convert tmp/2mh6e1324660062.ps tmp/2mh6e1324660062.png",intern=TRUE))
character(0)
> try(system("convert tmp/3klzr1324660062.ps tmp/3klzr1324660062.png",intern=TRUE))
character(0)
> try(system("convert tmp/4lbs71324660062.ps tmp/4lbs71324660062.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.850   0.100   2.927