R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list(10.65
+ ,NA
+ ,11.3447238275332
+ ,34.00466
+ ,0
+ ,34
+ ,10.65
+ ,34.0202876898303
+ ,34.00466
+ ,152
+ ,81.75
+ ,12.985
+ ,80.394008519981
+ ,34.00466
+ ,103
+ ,106.5
+ ,19.8615
+ ,104.461728571947
+ ,34.00466
+ ,98
+ ,0.525
+ ,28.52535
+ ,1.51024885747802
+ ,34.00466
+ ,24
+ ,24.025
+ ,25.725315
+ ,24.3449175147126
+ ,34.00466
+ ,24
+ ,5.25
+ ,25.5552835
+ ,6.10102813170674
+ ,34.00466
+ ,4
+ ,9
+ ,23.52475515
+ ,9.74297366894733
+ ,34.00466
+ ,0
+ ,12.8
+ ,22.072279635
+ ,13.4323962225627
+ ,34.00466
+ ,2
+ ,25.05
+ ,21.1450516715
+ ,25.3271480416495
+ ,34.00466
+ ,2
+ ,0.3
+ ,21.53554650435
+ ,1.29132499835047
+ ,34.00466
+ ,82
+ ,75.75
+ ,19.411991853915
+ ,74.5430992988187
+ ,34.00466
+ ,70
+ ,54.75
+ ,25.0457926685235
+ ,54.1692693680278
+ ,34.00466
+ ,76
+ ,1.526
+ ,28.0162134016712
+ ,2.48213334115502
+ ,34.00466
+ ,51
+ ,1.02
+ ,25.3671920615040
+ ,1.99046641401920
+ ,34.00466
+ ,NA
+ ,3.752
+ ,22.9324728553536
+ ,4.64256354643977
+ ,34.00466
+ ,0
+ ,17.25
+ ,21.0144255698183
+ ,17.7434661387314
+ ,34.00466
+ ,9
+ ,9.2
+ ,20.6379830128364
+ ,9.92884171115339
+ ,34.00466
+ ,12
+ ,50.25
+ ,19.4941847115528
+ ,49.7607775635948
+ ,34.00466
+ ,2
+ ,2.25
+ ,22.5697662403975
+ ,3.18356297838536
+ ,34.00466
+ ,51
+ ,3.95
+ ,20.5377896163578
+ ,4.83254096458096
+ ,34.00466
+ ,55
+ ,60
+ ,18.879010654722
+ ,59.2038839531516
+ ,34.00466
+ ,53
+ ,55.8
+ ,22.9911095892498
+ ,55.1395593527327
+ ,34.00466
+ ,17
+ ,6.75
+ ,26.2719986303248
+ ,7.55013353908689
+ ,34.00466
+ ,38
+ ,61.95
+ ,24.3197987672923
+ ,61.1045586779287
+ ,34.00466
+ ,29
+ ,7.025
+ ,28.0828188905631
+ ,7.817053763127
+ ,34.00466
+ ,32
+ ,85.75
+ ,25.9770370015068
+ ,84.1965045872622
+ ,34.00466
+ ,78
+ ,18.525
+ ,31.9543333013561
+ ,18.9797298623388
+ ,34.00466
+ ,26
+ ,6
+ ,30.6113999712205
+ ,6.8227878984193
+ ,34.00466
+ ,117
+ ,25.35
+ ,28.1502599740985
+ ,25.5966143213555
+ ,34.00466
+ ,29
+ ,46.775
+ ,27.8702339766886
+ ,46.3822925793737
+ ,34.00466
+ ,5
+ ,51.025
+ ,29.7607105790198
+ ,50.5102268038572
+ ,34.00466
+ ,45
+ ,30
+ ,31.8871395211178
+ ,30.1128301008900
+ ,34.00466
+ ,13
+ ,3
+ ,31.698425569006
+ ,3.91120762158714
+ ,34.00466
+ ,56
+ ,30
+ ,28.8285830121054
+ ,30.1059458610932
+ ,34.00466
+ ,55
+ ,44
+ ,28.9457247108949
+ ,43.6876743593134
+ ,34.00466
+ ,13
+ ,80.75
+ ,30.4511522398054
+ ,79.3472312750332
+ ,34.00466
+ ,65
+ ,27.5
+ ,35.4810370158248
+ ,27.6902669964837
+ ,34.00466
+ ,78
+ ,39.725
+ ,34.6829333142424
+ ,39.5536267539573
+ ,34.00466
+ ,49
+ ,29.25
+ ,35.1871399828181
+ ,29.3886144748858
+ ,34.00466
+ ,90
+ ,32.725
+ ,34.5934259845363
+ ,32.7602726524212
+ ,34.00466
+ ,52
+ ,56.25
+ ,34.4065833860827
+ ,55.591319459741
+ ,34.00466
+ ,28
+ ,28.65
+ ,36.5909250474744
+ ,28.8093454557490
+ ,34.00466
+ ,82
+ ,51.75
+ ,35.796832542727
+ ,51.2297172974473
+ ,34.00466
+ ,31
+ ,32.26
+ ,37.3921492884543
+ ,32.3159796143125
+ ,34.00466
+ ,4
+ ,72
+ ,36.8789343596088
+ ,70.8921850090827
+ ,34.00466
+ ,31
+ ,65.4
+ ,40.391040923648
+ ,64.5012300391254
+ ,34.00466
+ ,84
+ ,33.75
+ ,42.8919368312832
+ ,33.7767127288168
+ ,34.00466
+ ,56
+ ,77.85
+ ,41.9777431481549
+ ,76.6044993211423
+ ,34.00466
+ ,54
+ ,10.875
+ ,45.5649688333394
+ ,11.5642347595514
+ ,34.00466
+ ,84)
+ ,dim=c(5
+ ,50)
+ ,dimnames=list(c('Actuals'
+ ,'Croston'
+ ,'ETS'
+ ,'Arima'
+ ,'Kaneka')
+ ,1:50))
>  y <- array(NA,dim=c(5,50),dimnames=list(c('Actuals','Croston','ETS','Arima','Kaneka'),1:50))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par2 = 'No'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> library(rpart)
> library(partykit)
Loading required package: grid
Loading required package: mvtnorm
> par1 <- as.numeric(par1)
> autoprune <- function ( tree, method='Minimum CV'){
+ xerr <- tree$cptable[,'xerror']
+ cpmin.id <- which.min(xerr)
+ if (method == 'Minimum CV Error plus 1 SD'){
+ xstd <- tree$cptable[,'xstd']
+ errt <- xerr[cpmin.id] + xstd[cpmin.id]
+ cpSE1.min <- which.min( errt < xerr )
+ mycp <- (tree$cptable[,'CP'])[cpSE1.min]
+ }
+ if (method == 'Minimum CV') {
+ mycp <- (tree$cptable[,'CP'])[cpmin.id]
+ }
+ return (mycp)
+ }
> conf.multi.mat <- function(true, new)
+ {
+ if ( all( is.na(match( levels(true),levels(new) ) )) )
+ stop ( 'conflict of vector levels')
+ multi.t <- list()
+ for (mylev in levels(true) ) {
+ true.tmp <- true
+ new.tmp <- new
+ left.lev <- levels (true.tmp)[- match(mylev,levels(true) ) ]
+ levels(true.tmp) <- list ( mylev = mylev, all = left.lev )
+ levels(new.tmp)  <- list ( mylev = mylev, all = left.lev )
+ curr.t <- conf.mat ( true.tmp , new.tmp )
+ multi.t[[mylev]] <- curr.t
+ multi.t[[mylev]]$precision <-
+ round( curr.t$conf[1,1] / sum( curr.t$conf[1,] ), 2 )
+ }
+ return (multi.t)
+ }
> 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]
> m <- rpart(as.data.frame(x1))
> par2
[1] "No"
> if (par2 != 'No') {
+ mincp <- autoprune(m,method=par2)
+ print(mincp)
+ m <- prune(m,cp=mincp)
+ }
> m$cptable
         CP nsplit rel error    xerror       xstd
1 0.7429401      0 1.0000000 1.0297414 0.17446995
2 0.1128618      1 0.2570599 0.2954922 0.05220124
3 0.0100000      2 0.1441981 0.1760371 0.05472036
> postscript(file="/var/www/html/freestat/rcomp/tmp/1zpcn1274871078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(as.party(m),tp_args=list(id=FALSE))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/freestat/rcomp/tmp/2zpcn1274871078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plotcp(m)
> dev.off()
null device 
          1 
> cbind(y=m$y,pred=predict(m),res=residuals(m))
         y     pred          res
1   10.650  6.17350   4.47650000
2   34.000 29.34357   4.65642857
3   81.750 65.46111  16.28888889
4  106.500 65.46111  41.03888889
5    0.525  6.17350  -5.64850000
6   24.025 29.34357  -5.31857143
7    5.250  6.17350  -0.92350000
8    9.000  6.17350   2.82650000
9   12.800  6.17350   6.62650000
10  25.050 29.34357  -4.29357143
11   0.300  6.17350  -5.87350000
12  75.750 65.46111  10.28888889
13  54.750 65.46111 -10.71111111
14   1.526  6.17350  -4.64750000
15   1.020  6.17350  -5.15350000
16   3.752  6.17350  -2.42150000
17  17.250  6.17350  11.07650000
18   9.200  6.17350   3.02650000
19  50.250 65.46111 -15.21111111
20   2.250  6.17350  -3.92350000
21   3.950  6.17350  -2.22350000
22  60.000 65.46111  -5.46111111
23  55.800 65.46111  -9.66111111
24   6.750  6.17350   0.57650000
25  61.950 65.46111  -3.51111111
26   7.025  6.17350   0.85150000
27  85.750 65.46111  20.28888889
28  18.525 29.34357 -10.81857143
29   6.000  6.17350  -0.17350000
30  25.350 29.34357  -3.99357143
31  46.775 65.46111 -18.68611111
32  51.025 65.46111 -14.43611111
33  30.000 29.34357   0.65642857
34   3.000  6.17350  -3.17350000
35  30.000 29.34357   0.65642857
36  44.000 65.46111 -21.46111111
37  80.750 65.46111  15.28888889
38  27.500 29.34357  -1.84357143
39  39.725 29.34357  10.38142857
40  29.250 29.34357  -0.09357143
41  32.725 29.34357   3.38142857
42  56.250 65.46111  -9.21111111
43  28.650 29.34357  -0.69357143
44  51.750 65.46111 -13.71111111
45  32.260 29.34357   2.91642857
46  72.000 65.46111   6.53888889
47  65.400 65.46111  -0.06111111
48  33.750 29.34357   4.40642857
49  77.850 65.46111  12.38888889
50  10.875  6.17350   4.70150000
> myr <- residuals(m)
> myp <- predict(m)
> postscript(file="/var/www/html/freestat/rcomp/tmp/3zpcn1274871078.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(2,2))
> plot(myr,ylab='residuals')
> plot(density(myr),main='Residual Kernel Density')
> plot(myp,myr,xlab='predicted',ylab='residuals',main='Predicted vs Residuals')
> plot(density(myp),main='Prediction Kernel Density')
> par(op)
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Model Performance',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'#',header=TRUE)
> a<-table.element(a,'Complexity',header=TRUE)
> a<-table.element(a,'split',header=TRUE)
> a<-table.element(a,'relative error',header=TRUE)
> a<-table.element(a,'CV error',header=TRUE)
> a<-table.element(a,'CV S.D.',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:length(m$cptable[,1])) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,round(m$cptable[i,'CP'],3))
+ a<-table.element(a,m$cptable[i,'nsplit'])
+ a<-table.element(a,round(m$cptable[i,'rel error'],3))
+ a<-table.element(a,round(m$cptable[i,'xerror'],3))
+ a<-table.element(a,round(m$cptable[i,'xstd'],3))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/4qd281274871078.tab") 
> 
> try(system("convert tmp/1zpcn1274871078.ps tmp/1zpcn1274871078.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zpcn1274871078.ps tmp/2zpcn1274871078.png",intern=TRUE))
character(0)
> try(system("convert tmp/3zpcn1274871078.ps tmp/3zpcn1274871078.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.504   0.707   1.677