R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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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(631.923
+ ,21.454
+ ,97.06
+ ,130.678
+ ,654.294
+ ,23.899
+ ,97.73
+ ,120.877
+ ,671.833
+ ,24.939
+ ,98
+ ,137.114
+ ,586.840
+ ,23.580
+ ,97.76
+ ,134.406
+ ,600.969
+ ,24.562
+ ,97.48
+ ,120.262
+ ,625.568
+ ,24.696
+ ,97.77
+ ,130.846
+ ,558.110
+ ,23.785
+ ,97.96
+ ,120.343
+ ,630.577
+ ,23.812
+ ,98.22
+ ,98.881
+ ,628.654
+ ,21.917
+ ,98.51
+ ,115.678
+ ,603.184
+ ,19.713
+ ,98.19
+ ,120.796
+ ,656.255
+ ,19.282
+ ,98.37
+ ,94.261
+ ,600.730
+ ,18.788
+ ,98.31
+ ,89.151
+ ,670.326
+ ,21.453
+ ,98.6
+ ,119.880
+ ,678.423
+ ,24.482
+ ,98.96
+ ,131.468
+ ,641.502
+ ,27.474
+ ,99.11
+ ,155.089
+ ,625.311
+ ,27.264
+ ,99.64
+ ,149.581
+ ,628.177
+ ,27.349
+ ,100.02
+ ,122.788
+ ,589.767
+ ,30.632
+ ,99.98
+ ,143.900
+ ,582.471
+ ,29.429
+ ,100.32
+ ,112.115
+ ,636.248
+ ,30.084
+ ,100.44
+ ,109.600
+ ,599.885
+ ,26.290
+ ,100.51
+ ,117.446
+ ,621.694
+ ,24.379
+ ,101
+ ,118.456
+ ,637.406
+ ,23.335
+ ,100.88
+ ,101.901
+ ,595.994
+ ,21.346
+ ,100.55
+ ,89.940
+ ,696.308
+ ,21.106
+ ,100.82
+ ,129.143
+ ,674.201
+ ,24.514
+ ,101.5
+ ,126.102
+ ,648.861
+ ,28.353
+ ,102.15
+ ,143.048
+ ,649.605
+ ,30.805
+ ,102.39
+ ,142.258
+ ,672.392
+ ,31.348
+ ,102.54
+ ,131.011
+ ,598.396
+ ,34.556
+ ,102.85
+ ,146.471
+ ,613.177
+ ,33.855
+ ,103.47
+ ,114.073
+ ,638.104
+ ,34.787
+ ,103.56
+ ,114.642
+ ,615.632
+ ,32.529
+ ,103.69
+ ,118.226
+ ,634.465
+ ,29.998
+ ,103.49
+ ,111.338
+ ,638.686
+ ,29.257
+ ,103.47
+ ,108.701
+ ,604.243
+ ,28.155
+ ,103.45
+ ,80.512
+ ,706.669
+ ,30.466
+ ,103.48
+ ,146.865
+ ,677.185
+ ,35.704
+ ,103.93
+ ,137.179
+ ,644.328
+ ,39.327
+ ,103.89
+ ,166.536
+ ,664.825
+ ,39.351
+ ,104.4
+ ,137.070
+ ,605.707
+ ,42.234
+ ,104.79
+ ,127.090
+ ,600.136
+ ,43.630
+ ,104.77
+ ,139.966
+ ,612.166
+ ,43.722
+ ,105.13
+ ,122.243
+ ,599.659
+ ,43.121
+ ,105.26
+ ,109.097
+ ,634.210
+ ,37.985
+ ,104.96
+ ,116.591
+ ,618.234
+ ,37.135
+ ,104.75
+ ,111.964
+ ,613.576
+ ,34.646
+ ,105.01
+ ,109.754
+ ,627.200
+ ,33.026
+ ,105.15
+ ,77.609
+ ,668.973
+ ,35.087
+ ,105.2
+ ,138.445
+ ,651.479
+ ,38.846
+ ,105.77
+ ,127.901
+ ,619.661
+ ,42.013
+ ,105.78
+ ,156.615
+ ,644.260
+ ,43.908
+ ,106.26
+ ,133.264
+ ,579.936
+ ,42.868
+ ,106.13
+ ,143.521
+ ,601.752
+ ,44.423
+ ,106.12
+ ,152.139
+ ,595.376
+ ,44.167
+ ,106.57
+ ,131.523
+ ,588.902
+ ,43.636
+ ,106.44
+ ,113.925
+ ,634.341
+ ,44.382
+ ,106.54
+ ,86.495
+ ,594.305
+ ,42.142
+ ,107.1
+ ,127.877
+ ,606.200
+ ,43.452
+ ,108.1
+ ,107.017
+ ,610.926
+ ,36.912
+ ,108.4
+ ,78.716
+ ,633.685
+ ,42.413
+ ,108.84
+ ,138.278
+ ,639.696
+ ,45.344
+ ,109.62
+ ,144.238
+ ,659.451
+ ,44.873
+ ,110.42
+ ,143.679
+ ,593.248
+ ,47.510
+ ,110.67
+ ,159.932
+ ,606.677
+ ,49.554
+ ,111.66
+ ,136.781
+ ,599.434
+ ,47.369
+ ,112.28
+ ,148.173
+ ,569.578
+ ,45.998
+ ,112.87
+ ,125.673
+ ,629.873
+ ,48.140
+ ,112.18
+ ,105.573
+ ,613.438
+ ,48.441
+ ,112.36
+ ,122.405
+ ,604.172
+ ,44.928
+ ,112.16
+ ,128.045
+ ,658.328
+ ,40.454
+ ,111.49
+ ,94.467
+ ,612.633
+ ,38.661
+ ,111.25
+ ,85.573
+ ,707.372
+ ,37.246
+ ,111.36
+ ,121.501
+ ,739.770
+ ,36.843
+ ,111.74
+ ,125.074
+ ,777.535
+ ,36.424
+ ,111.1
+ ,144.979
+ ,685.030
+ ,37.594
+ ,111.33
+ ,142.120
+ ,730.234
+ ,38.144
+ ,111.25
+ ,124.213
+ ,714.154
+ ,38.737
+ ,111.04
+ ,144.407
+ ,630.872
+ ,34.560
+ ,110.97
+ ,125.170
+ ,719.492
+ ,36.080
+ ,111.31
+ ,109.267
+ ,677.023
+ ,33.508
+ ,111.02
+ ,122.354
+ ,679.272
+ ,35.462
+ ,111.07
+ ,122.589
+ ,718.317
+ ,33.374
+ ,111.36
+ ,104.982
+ ,645.672
+ ,32.110
+ ,111.54
+ ,90.542)
+ ,dim=c(4
+ ,84)
+ ,dimnames=list(c('werkloosheid'
+ ,'vacatures'
+ ,'consumentprijsindex'
+ ,'inschrijvingen')
+ ,1:84))
>  y <- array(NA,dim=c(4,84),dimnames=list(c('werkloosheid','vacatures','consumentprijsindex','inschrijvingen'),1:84))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par4 = 'no'
> par3 = '4'
> par2 = 'none'
> par1 = '2'
> 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

Attaching package: 'zoo'

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

    as.Date, as.Date.numeric

Loading required package: sandwich
Loading required package: strucchange
Loading required package: vcd
Loading required package: MASS
Loading required package: colorspace
> library(Hmisc)
Hmisc library by Frank E Harrell Jr

Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview')
to see overall documentation.

NOTE:Hmisc no longer redefines [.factor to drop unused levels when
subsetting.  To get the old behavior of Hmisc type dropUnusedLevels().


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] "vacatures"
> x[,par1]
 [1] 21.454 23.899 24.939 23.580 24.562 24.696 23.785 23.812 21.917 19.713
[11] 19.282 18.788 21.453 24.482 27.474 27.264 27.349 30.632 29.429 30.084
[21] 26.290 24.379 23.335 21.346 21.106 24.514 28.353 30.805 31.348 34.556
[31] 33.855 34.787 32.529 29.998 29.257 28.155 30.466 35.704 39.327 39.351
[41] 42.234 43.630 43.722 43.121 37.985 37.135 34.646 33.026 35.087 38.846
[51] 42.013 43.908 42.868 44.423 44.167 43.636 44.382 42.142 43.452 36.912
[61] 42.413 45.344 44.873 47.510 49.554 47.369 45.998 48.140 48.441 44.928
[71] 40.454 38.661 37.246 36.843 36.424 37.594 38.144 38.737 34.560 36.080
[81] 33.508 35.462 33.374 32.110
> 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])

18.788 19.282 19.713 21.106 21.346 21.453 21.454 21.917 23.335  23.58 23.785 
     1      1      1      1      1      1      1      1      1      1      1 
23.812 23.899 24.379 24.482 24.514 24.562 24.696 24.939  26.29 27.264 27.349 
     1      1      1      1      1      1      1      1      1      1      1 
27.474 28.155 28.353 29.257 29.429 29.998 30.084 30.466 30.632 30.805 31.348 
     1      1      1      1      1      1      1      1      1      1      1 
 32.11 32.529 33.026 33.374 33.508 33.855 34.556  34.56 34.646 34.787 35.087 
     1      1      1      1      1      1      1      1      1      1      1 
35.462 35.704  36.08 36.424 36.843 36.912 37.135 37.246 37.594 37.985 38.144 
     1      1      1      1      1      1      1      1      1      1      1 
38.661 38.737 38.846 39.327 39.351 40.454 42.013 42.142 42.234 42.413 42.868 
     1      1      1      1      1      1      1      1      1      1      1 
43.121 43.452  43.63 43.636 43.722 43.908 44.167 44.382 44.423 44.873 44.928 
     1      1      1      1      1      1      1      1      1      1      1 
45.344 45.998 47.369  47.51  48.14 48.441 49.554 
     1      1      1      1      1      1      1 
> colnames(x)
[1] "werkloosheid"        "vacatures"           "consumentprijsindex"
[4] "inschrijvingen"     
> colnames(x)[par1]
[1] "vacatures"
> x[,par1]
 [1] 21.454 23.899 24.939 23.580 24.562 24.696 23.785 23.812 21.917 19.713
[11] 19.282 18.788 21.453 24.482 27.474 27.264 27.349 30.632 29.429 30.084
[21] 26.290 24.379 23.335 21.346 21.106 24.514 28.353 30.805 31.348 34.556
[31] 33.855 34.787 32.529 29.998 29.257 28.155 30.466 35.704 39.327 39.351
[41] 42.234 43.630 43.722 43.121 37.985 37.135 34.646 33.026 35.087 38.846
[51] 42.013 43.908 42.868 44.423 44.167 43.636 44.382 42.142 43.452 36.912
[61] 42.413 45.344 44.873 47.510 49.554 47.369 45.998 48.140 48.441 44.928
[71] 40.454 38.661 37.246 36.843 36.424 37.594 38.144 38.737 34.560 36.080
[81] 33.508 35.462 33.374 32.110
> if (par2 == 'none') {
+ m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
+ }
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/1irxr1355227563.tab") 
+ }
+ }
> m

	 Conditional inference tree with 4 terminal nodes

Response:  vacatures 
Inputs:  werkloosheid, consumentprijsindex, inschrijvingen 
Number of observations:  84 

1) consumentprijsindex <= 103.49; criterion = 1, statistic = 53.161
  2) consumentprijsindex <= 101.5; criterion = 1, statistic = 17.4
    3)*  weights = 26 
  2) consumentprijsindex > 101.5
    4)*  weights = 9 
1) consumentprijsindex > 103.49
  5) werkloosheid <= 613.438; criterion = 0.999, statistic = 13.164
    6)*  weights = 18 
  5) werkloosheid > 613.438
    7)*  weights = 31 
> postscript(file="/var/wessaorg/rcomp/tmp/2b2rw1355227563.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/wessaorg/rcomp/tmp/30wt41355227563.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)
+ }
   Actuals Forecasts   Residuals
1   21.454  24.21400 -2.76000000
2   23.899  24.21400 -0.31500000
3   24.939  24.21400  0.72500000
4   23.580  24.21400 -0.63400000
5   24.562  24.21400  0.34800000
6   24.696  24.21400  0.48200000
7   23.785  24.21400 -0.42900000
8   23.812  24.21400 -0.40200000
9   21.917  24.21400 -2.29700000
10  19.713  24.21400 -4.50100000
11  19.282  24.21400 -4.93200000
12  18.788  24.21400 -5.42600000
13  21.453  24.21400 -2.76100000
14  24.482  24.21400  0.26800000
15  27.474  24.21400  3.26000000
16  27.264  24.21400  3.05000000
17  27.349  24.21400  3.13500000
18  30.632  24.21400  6.41800000
19  29.429  24.21400  5.21500000
20  30.084  24.21400  5.87000000
21  26.290  24.21400  2.07600000
22  24.379  24.21400  0.16500000
23  23.335  24.21400 -0.87900000
24  21.346  24.21400 -2.86800000
25  21.106  24.21400 -3.10800000
26  24.514  24.21400  0.30000000
27  28.353  30.75478 -2.40177778
28  30.805  30.75478  0.05022222
29  31.348  30.75478  0.59322222
30  34.556  30.75478  3.80122222
31  33.855  30.75478  3.10022222
32  34.787  38.06555 -3.27854839
33  32.529  38.06555 -5.53654839
34  29.998  30.75478 -0.75677778
35  29.257  30.75478 -1.49777778
36  28.155  30.75478 -2.59977778
37  30.466  30.75478 -0.28877778
38  35.704  38.06555 -2.36154839
39  39.327  38.06555  1.26145161
40  39.351  38.06555  1.28545161
41  42.234  44.04267 -1.80866667
42  43.630  44.04267 -0.41266667
43  43.722  44.04267 -0.32066667
44  43.121  44.04267 -0.92166667
45  37.985  38.06555 -0.08054839
46  37.135  38.06555 -0.93054839
47  34.646  38.06555 -3.41954839
48  33.026  38.06555 -5.03954839
49  35.087  38.06555 -2.97854839
50  38.846  38.06555  0.78045161
51  42.013  38.06555  3.94745161
52  43.908  38.06555  5.84245161
53  42.868  44.04267 -1.17466667
54  44.423  44.04267  0.38033333
55  44.167  44.04267  0.12433333
56  43.636  44.04267 -0.40666667
57  44.382  38.06555  6.31645161
58  42.142  44.04267 -1.90066667
59  43.452  44.04267 -0.59066667
60  36.912  44.04267 -7.13066667
61  42.413  38.06555  4.34745161
62  45.344  38.06555  7.27845161
63  44.873  38.06555  6.80745161
64  47.510  44.04267  3.46733333
65  49.554  44.04267  5.51133333
66  47.369  44.04267  3.32633333
67  45.998  44.04267  1.95533333
68  48.140  38.06555 10.07445161
69  48.441  44.04267  4.39833333
70  44.928  44.04267  0.88533333
71  40.454  38.06555  2.38845161
72  38.661  44.04267 -5.38166667
73  37.246  38.06555 -0.81954839
74  36.843  38.06555 -1.22254839
75  36.424  38.06555 -1.64154839
76  37.594  38.06555 -0.47154839
77  38.144  38.06555  0.07845161
78  38.737  38.06555  0.67145161
79  34.560  38.06555 -3.50554839
80  36.080  38.06555 -1.98554839
81  33.508  38.06555 -4.55754839
82  35.462  38.06555 -2.60354839
83  33.374  38.06555 -4.69154839
84  32.110  38.06555 -5.95554839
> if (par2 != 'none') {
+ print(cbind(as.factor(x[,par1]),predict(m)))
+ myt <- table(as.factor(x[,par1]),predict(m))
+ print(myt)
+ }
> postscript(file="/var/wessaorg/rcomp/tmp/4roim1355227563.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/wessaorg/rcomp/tmp/5q0rd1355227563.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/wessaorg/rcomp/tmp/6iblp1355227563.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/wessaorg/rcomp/tmp/747xm1355227563.tab") 
+ }
> 
> try(system("convert tmp/2b2rw1355227563.ps tmp/2b2rw1355227563.png",intern=TRUE))
character(0)
> try(system("convert tmp/30wt41355227563.ps tmp/30wt41355227563.png",intern=TRUE))
character(0)
> try(system("convert tmp/4roim1355227563.ps tmp/4roim1355227563.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  4.615   0.549   5.141