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(3111
+ ,5140
+ ,17153
+ ,2.5
+ ,766
+ ,332
+ ,2.4
+ ,3995
+ ,4749
+ ,15579
+ ,1.8
+ ,294
+ ,369
+ ,2.4
+ ,5245
+ ,3635
+ ,16755
+ ,7.3
+ ,235
+ ,384
+ ,2.4
+ ,5588
+ ,4305
+ ,16585
+ ,9.9
+ ,462
+ ,373
+ ,2.1
+ ,10681
+ ,5805
+ ,16572
+ ,13.2
+ ,919
+ ,378
+ ,2
+ ,10516
+ ,4260
+ ,16325
+ ,17.8
+ ,346
+ ,426
+ ,2
+ ,7496
+ ,3869
+ ,17913
+ ,18.8
+ ,298
+ ,423
+ ,2.1
+ ,9935
+ ,7325
+ ,17572
+ ,19.3
+ ,92
+ ,397
+ ,2.1
+ ,10249
+ ,9280
+ ,17338
+ ,13.9
+ ,516
+ ,422
+ ,2
+ ,6271
+ ,6222
+ ,17087
+ ,7.5
+ ,843
+ ,409
+ ,2
+ ,3616
+ ,3272
+ ,15864
+ ,8
+ ,395
+ ,430
+ ,2
+ ,3724
+ ,7598
+ ,15554
+ ,4
+ ,961
+ ,412
+ ,1.7
+ ,2886
+ ,1345
+ ,16229
+ ,3.6
+ ,1231
+ ,470
+ ,1.3
+ ,3318
+ ,1900
+ ,15180
+ ,4.8
+ ,794
+ ,491
+ ,1.2
+ ,4166
+ ,1480
+ ,16215
+ ,5.9
+ ,420
+ ,504
+ ,1.1
+ ,6401
+ ,1472
+ ,15801
+ ,10.4
+ ,331
+ ,484
+ ,1.4
+ ,9209
+ ,3823
+ ,15751
+ ,12.3
+ ,312
+ ,474
+ ,1.5
+ ,9820
+ ,4454
+ ,16477
+ ,15.5
+ ,692
+ ,508
+ ,1.4
+ ,7470
+ ,3357
+ ,17324
+ ,16.7
+ ,1221
+ ,492
+ ,1.1
+ ,8207
+ ,5393
+ ,16919
+ ,18.8
+ ,1272
+ ,452
+ ,1.1
+ ,9564
+ ,8329
+ ,16438
+ ,15.2
+ ,622
+ ,457
+ ,1
+ ,5309
+ ,4152
+ ,16239
+ ,11.3
+ ,479
+ ,457
+ ,1.4
+ ,3385
+ ,4042
+ ,15613
+ ,6.3
+ ,757
+ ,471
+ ,1.3
+ ,3706
+ ,7747
+ ,15821
+ ,3.2
+ ,463
+ ,451
+ ,1.2
+ ,2733
+ ,1451
+ ,15678
+ ,5.3
+ ,534
+ ,493
+ ,1.5
+ ,3045
+ ,911
+ ,14671
+ ,2.4
+ ,731
+ ,514
+ ,1.6
+ ,3449
+ ,406
+ ,15876
+ ,6.5
+ ,498
+ ,522
+ ,1.8
+ ,5542
+ ,1387
+ ,15563
+ ,10.4
+ ,629
+ ,490
+ ,1.5
+ ,10072
+ ,2150
+ ,15711
+ ,12.6
+ ,542
+ ,484
+ ,1.3
+ ,9418
+ ,1577
+ ,15583
+ ,16.8
+ ,519
+ ,506
+ ,1.6
+ ,7516
+ ,2642
+ ,16405
+ ,17.7
+ ,1585
+ ,501
+ ,1.6
+ ,7840
+ ,4273
+ ,16701
+ ,16.2
+ ,956
+ ,462
+ ,1.8
+ ,10081
+ ,8064
+ ,16194
+ ,15.7
+ ,633
+ ,465
+ ,1.8
+ ,4956
+ ,3243
+ ,16024
+ ,13.3
+ ,561
+ ,454
+ ,1.6
+ ,3641
+ ,1112
+ ,14728
+ ,6.9
+ ,976
+ ,464
+ ,1.8
+ ,3970
+ ,2280
+ ,14776
+ ,4
+ ,565
+ ,427
+ ,2
+ ,2931
+ ,505
+ ,15399
+ ,1.5
+ ,151
+ ,460
+ ,1.3
+ ,3170
+ ,744
+ ,14286
+ ,2.9
+ ,588
+ ,473
+ ,1.1
+ ,3889
+ ,1369
+ ,15646
+ ,3.9
+ ,1043
+ ,465
+ ,1
+ ,4850
+ ,531
+ ,14543
+ ,9
+ ,398
+ ,422
+ ,1.2
+ ,8037
+ ,1041
+ ,15673
+ ,14.5
+ ,902
+ ,415
+ ,1.2
+ ,12370
+ ,2076
+ ,15171
+ ,16.7
+ ,180
+ ,413
+ ,1.3
+ ,6712
+ ,577
+ ,15999
+ ,22.3
+ ,150
+ ,420
+ ,1.3
+ ,7297
+ ,5080
+ ,1626
+ ,16.4
+ ,1805
+ ,363
+ ,1.4
+ ,10613
+ ,6584
+ ,16123
+ ,17.9
+ ,86
+ ,376
+ ,1.1
+ ,5184
+ ,3761
+ ,16144
+ ,13.6
+ ,1093
+ ,380
+ ,0.9
+ ,3506
+ ,294
+ ,15005
+ ,9.2
+ ,925
+ ,384
+ ,1
+ ,3810
+ ,5020
+ ,14806
+ ,6.5
+ ,750
+ ,346
+ ,1.1
+ ,2692
+ ,1141
+ ,15019
+ ,7.1
+ ,1038
+ ,389
+ ,1.4
+ ,3073
+ ,3805
+ ,13909
+ ,6
+ ,679
+ ,407
+ ,1.5
+ ,3713
+ ,2127
+ ,15211
+ ,8
+ ,848
+ ,393
+ ,1.8
+ ,4555
+ ,2531
+ ,14385
+ ,13.1
+ ,300
+ ,346
+ ,1.8
+ ,7807
+ ,3682
+ ,15144
+ ,14.1
+ ,1379
+ ,348
+ ,1.8
+ ,10869
+ ,3263
+ ,14659
+ ,17.5
+ ,901
+ ,353
+ ,1.7
+ ,9682
+ ,2798
+ ,15989
+ ,17
+ ,1606
+ ,364
+ ,1.5
+ ,7704
+ ,5936
+ ,16262
+ ,17.1
+ ,422
+ ,305
+ ,1.1
+ ,9826
+ ,10568
+ ,16021
+ ,13.8
+ ,968
+ ,307
+ ,1.3
+ ,5456
+ ,5296
+ ,15662
+ ,10.1
+ ,319
+ ,312
+ ,1.6
+ ,3677
+ ,1870
+ ,14531
+ ,6.9
+ ,583
+ ,312
+ ,1.9
+ ,3431
+ ,4390
+ ,14544
+ ,2.4
+ ,765
+ ,286
+ ,1.9
+ ,2765
+ ,3707
+ ,15071
+ ,6.5
+ ,963
+ ,324
+ ,2
+ ,3483
+ ,5201
+ ,14236
+ ,5.1
+ ,392
+ ,336
+ ,2.2
+ ,3445
+ ,3748
+ ,14771
+ ,5.9
+ ,919
+ ,327
+ ,2.2
+ ,6081
+ ,5282
+ ,14804
+ ,8.9
+ ,339
+ ,302
+ ,2
+ ,8767
+ ,5349
+ ,15597
+ ,15.7
+ ,327
+ ,299
+ ,2.3
+ ,9407
+ ,6249
+ ,15418
+ ,16.5
+ ,397
+ ,311
+ ,2.6
+ ,6551
+ ,5517
+ ,16903
+ ,18.1
+ ,1268
+ ,315
+ ,3.2
+ ,12480
+ ,8640
+ ,16350
+ ,17.4
+ ,1137
+ ,264
+ ,3.2
+ ,9530
+ ,15767
+ ,16393
+ ,13.6
+ ,1000
+ ,278
+ ,3.1
+ ,5960
+ ,8850
+ ,15685
+ ,10.1
+ ,915
+ ,278
+ ,2.8
+ ,3252
+ ,5582
+ ,14556
+ ,6.9
+ ,905
+ ,287
+ ,2.3
+ ,3717
+ ,6496
+ ,14850
+ ,2.4
+ ,243
+ ,279
+ ,1.9
+ ,2642
+ ,3255
+ ,15391
+ ,0.8
+ ,537
+ ,324
+ ,1.9
+ ,2989
+ ,6189
+ ,13704
+ ,3.3
+ ,551
+ ,354
+ ,2
+ ,3607
+ ,6452
+ ,15409
+ ,6.3
+ ,482
+ ,354
+ ,2
+ ,5366
+ ,5099
+ ,15098
+ ,12.2
+ ,199
+ ,360
+ ,1.8
+ ,8898
+ ,6833
+ ,15254
+ ,13.9
+ ,650
+ ,363
+ ,1.6
+ ,9435
+ ,7046
+ ,15522
+ ,15.6
+ ,533
+ ,385
+ ,1.4
+ ,7328
+ ,7739
+ ,16669
+ ,18.1
+ ,1071
+ ,412
+ ,0.2
+ ,8594
+ ,10142
+ ,16238
+ ,18.5
+ ,469
+ ,370
+ ,0.3
+ ,11349
+ ,16054
+ ,16246
+ ,15
+ ,335
+ ,389
+ ,0.4
+ ,5797
+ ,7721
+ ,15424
+ ,10.7
+ ,598
+ ,395
+ ,0.7
+ ,3621
+ ,6182
+ ,14952
+ ,9.5
+ ,1200
+ ,417
+ ,1
+ ,3851
+ ,6490
+ ,15008
+ ,2.2
+ ,844
+ ,404
+ ,1.1)
+ ,dim=c(7
+ ,84)
+ ,dimnames=list(c('Huwelijken'
+ ,'Bevolkingsgroei'
+ ,'Geborenen'
+ ,'Temperatuur'
+ ,'Neerslag'
+ ,'Werkloosheid'
+ ,'Inflatie')
+ ,1:84))
>  y <- array(NA,dim=c(7,84),dimnames=list(c('Huwelijken','Bevolkingsgroei','Geborenen','Temperatuur','Neerslag','Werkloosheid','Inflatie'),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 = '2'
> par2 = 'quantiles'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> 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] "Huwelijken"
> x[,par1]
 [1]  3111  3995  5245  5588 10681 10516  7496  9935 10249  6271  3616  3724
[13]  2886  3318  4166  6401  9209  9820  7470  8207  9564  5309  3385  3706
[25]  2733  3045  3449  5542 10072  9418  7516  7840 10081  4956  3641  3970
[37]  2931  3170  3889  4850  8037 12370  6712  7297 10613  5184  3506  3810
[49]  2692  3073  3713  4555  7807 10869  9682  7704  9826  5456  3677  3431
[61]  2765  3483  3445  6081  8767  9407  6551 12480  9530  5960  3252  3717
[73]  2642  2989  3607  5366  8898  9435  7328  8594 11349  5797  3621  3851
> 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])

[2642, 5542) [5542,12480] 
          42           42 
> colnames(x)
[1] "Huwelijken"      "Bevolkingsgroei" "Geborenen"       "Temperatuur"    
[5] "Neerslag"        "Werkloosheid"    "Inflatie"       
> colnames(x)[par1]
[1] "Huwelijken"
> x[,par1]
 [1] [2642, 5542) [2642, 5542) [2642, 5542) [5542,12480] [5542,12480]
 [6] [5542,12480] [5542,12480] [5542,12480] [5542,12480] [5542,12480]
[11] [2642, 5542) [2642, 5542) [2642, 5542) [2642, 5542) [2642, 5542)
[16] [5542,12480] [5542,12480] [5542,12480] [5542,12480] [5542,12480]
[21] [5542,12480] [2642, 5542) [2642, 5542) [2642, 5542) [2642, 5542)
[26] [2642, 5542) [2642, 5542) [5542,12480] [5542,12480] [5542,12480]
[31] [5542,12480] [5542,12480] [5542,12480] [2642, 5542) [2642, 5542)
[36] [2642, 5542) [2642, 5542) [2642, 5542) [2642, 5542) [2642, 5542)
[41] [5542,12480] [5542,12480] [5542,12480] [5542,12480] [5542,12480]
[46] [2642, 5542) [2642, 5542) [2642, 5542) [2642, 5542) [2642, 5542)
[51] [2642, 5542) [2642, 5542) [5542,12480] [5542,12480] [5542,12480]
[56] [5542,12480] [5542,12480] [2642, 5542) [2642, 5542) [2642, 5542)
[61] [2642, 5542) [2642, 5542) [2642, 5542) [5542,12480] [5542,12480]
[66] [5542,12480] [5542,12480] [5542,12480] [5542,12480] [5542,12480]
[71] [2642, 5542) [2642, 5542) [2642, 5542) [2642, 5542) [2642, 5542)
[76] [2642, 5542) [5542,12480] [5542,12480] [5542,12480] [5542,12480]
[81] [5542,12480] [5542,12480] [2642, 5542) [2642, 5542)
Levels: [2642, 5542) [5542,12480]
> 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/1hin51292700257.tab") 
+ }
+ }
> m

	 Conditional inference tree with 2 terminal nodes

Response:  as.factor(Huwelijken) 
Inputs:  Bevolkingsgroei, Geborenen, Temperatuur, Neerslag, Werkloosheid, Inflatie 
Number of observations:  84 

1) Temperatuur <= 9.5; criterion = 1, statistic = 54.783
  2)*  weights = 38 
1) Temperatuur > 9.5
  3)*  weights = 46 
> postscript(file="/var/www/rcomp/tmp/2sr5q1292700257.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/3sr5q1292700257.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,]    1    1
 [2,]    1    1
 [3,]    1    1
 [4,]    2    2
 [5,]    2    2
 [6,]    2    2
 [7,]    2    2
 [8,]    2    2
 [9,]    2    2
[10,]    2    1
[11,]    1    1
[12,]    1    1
[13,]    1    1
[14,]    1    1
[15,]    1    1
[16,]    2    2
[17,]    2    2
[18,]    2    2
[19,]    2    2
[20,]    2    2
[21,]    2    2
[22,]    1    2
[23,]    1    1
[24,]    1    1
[25,]    1    1
[26,]    1    1
[27,]    1    1
[28,]    2    2
[29,]    2    2
[30,]    2    2
[31,]    2    2
[32,]    2    2
[33,]    2    2
[34,]    1    2
[35,]    1    1
[36,]    1    1
[37,]    1    1
[38,]    1    1
[39,]    1    1
[40,]    1    1
[41,]    2    2
[42,]    2    2
[43,]    2    2
[44,]    2    2
[45,]    2    2
[46,]    1    2
[47,]    1    1
[48,]    1    1
[49,]    1    1
[50,]    1    1
[51,]    1    1
[52,]    1    2
[53,]    2    2
[54,]    2    2
[55,]    2    2
[56,]    2    2
[57,]    2    2
[58,]    1    2
[59,]    1    1
[60,]    1    1
[61,]    1    1
[62,]    1    1
[63,]    1    1
[64,]    2    1
[65,]    2    2
[66,]    2    2
[67,]    2    2
[68,]    2    2
[69,]    2    2
[70,]    2    2
[71,]    1    1
[72,]    1    1
[73,]    1    1
[74,]    1    1
[75,]    1    1
[76,]    1    2
[77,]    2    2
[78,]    2    2
[79,]    2    2
[80,]    2    2
[81,]    2    2
[82,]    2    2
[83,]    1    1
[84,]    1    1
              
               [2642, 5542) [5542,12480]
  [2642, 5542)           36            6
  [5542,12480]            2           40
> postscript(file="/var/www/rcomp/tmp/4l0mb1292700257.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/56j3h1292700257.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/6a1151292700257.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/7d2ht1292700257.tab") 
+ }
> 
> try(system("convert tmp/2sr5q1292700257.ps tmp/2sr5q1292700257.png",intern=TRUE))
character(0)
> try(system("convert tmp/3sr5q1292700257.ps tmp/3sr5q1292700257.png",intern=TRUE))
character(0)
> try(system("convert tmp/4l0mb1292700257.ps tmp/4l0mb1292700257.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.020   0.300   2.286