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Type 'q()' to quit R. > x <- array(list(6.3,0.819543936,3,2.1,3.663040975,4,9.1,2.254064453,4,15.8,-0.522878745,1,5.2,2.227886705,4,10.9,1.408239965,1,8.3,2.643452676,1,11,0.806179974,4,3.2,2.626340367,5,6.3,0.079181246,1,6.6,0.544068044,2,9.5,0.698970004,2,3.3,2.06069784,5,11,0,2,4.7,2.511883361,1,10.4,0.602059991,3,7.4,0.740362689,4,2.1,2.8162413,5,17.9,-0.602059991,1,6.1,3.120573931,1,11.9,-0.397940009,3,13.8,0.799340549,1,14.3,1.033423755,1,15.2,1.190331698,2,10,2.06069784,4,6.5,1.056904851,4,7.5,2.255272505,5,10.6,1.08278537,3,7.4,0.278753601,1,8.4,1.702430536,2,5.7,2.252853031,2,4.9,1.089905111,3,3.2,1.322219295,5,11,2.243038049,2,4.9,0.414973348,3,13.2,1.089905111,2,9.7,0.397940009,4,12.8,1.763427994,1,11.9,0.591064607,2),dim=c(3,39),dimnames=list(c('SWS','logWbr','ODI '),1:39)) > y <- array(NA,dim=c(3,39),dimnames=list(c('SWS','logWbr','ODI '),1:39)) > 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 = '3' > par2 = 'none' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "SWS" > x[,par1] [1] 6.3 2.1 9.1 15.8 5.2 10.9 8.3 11.0 3.2 6.3 6.6 9.5 3.3 11.0 4.7 [16] 10.4 7.4 2.1 17.9 6.1 11.9 13.8 14.3 15.2 10.0 6.5 7.5 10.6 7.4 8.4 [31] 5.7 4.9 3.2 11.0 4.9 13.2 9.7 12.8 11.9 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 2.1 3.2 3.3 4.7 4.9 5.2 5.7 6.1 6.3 6.5 6.6 7.4 7.5 8.3 8.4 9.1 2 2 1 1 2 1 1 1 2 1 1 2 1 1 1 1 9.5 9.7 10 10.4 10.6 10.9 11 11.9 12.8 13.2 13.8 14.3 15.2 15.8 17.9 1 1 1 1 1 1 3 2 1 1 1 1 1 1 1 > colnames(x) [1] "SWS" "logWbr" "ODI." > colnames(x)[par1] [1] "SWS" > x[,par1] [1] 6.3 2.1 9.1 15.8 5.2 10.9 8.3 11.0 3.2 6.3 6.6 9.5 3.3 11.0 4.7 [16] 10.4 7.4 2.1 17.9 6.1 11.9 13.8 14.3 15.2 10.0 6.5 7.5 10.6 7.4 8.4 [31] 5.7 4.9 3.2 11.0 4.9 13.2 9.7 12.8 11.9 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/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/html/rcomp/tmp/1lbcm1292848819.tab") + } + } > m Conditional inference tree with 3 terminal nodes Response: SWS Inputs: logWbr, ODI. Number of observations: 39 1) logWbr <= 1.763428; criterion = 0.999, statistic = 11.812 2) ODI. <= 2; criterion = 0.989, statistic = 7.649 3)* weights = 15 2) ODI. > 2 4)* weights = 11 1) logWbr > 1.763428 5)* weights = 13 > postscript(file="/var/www/html/rcomp/tmp/2ekb81292848819.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/html/rcomp/tmp/3ekb81292848819.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 6.3 7.890909 -1.59090909 2 2.1 6.023077 -3.92307692 3 9.1 6.023077 3.07692308 4 15.8 11.666667 4.13333333 5 5.2 6.023077 -0.82307692 6 10.9 11.666667 -0.76666667 7 8.3 6.023077 2.27692308 8 11.0 7.890909 3.10909091 9 3.2 6.023077 -2.82307692 10 6.3 11.666667 -5.36666667 11 6.6 11.666667 -5.06666667 12 9.5 11.666667 -2.16666667 13 3.3 6.023077 -2.72307692 14 11.0 11.666667 -0.66666667 15 4.7 6.023077 -1.32307692 16 10.4 7.890909 2.50909091 17 7.4 7.890909 -0.49090909 18 2.1 6.023077 -3.92307692 19 17.9 11.666667 6.23333333 20 6.1 6.023077 0.07692308 21 11.9 7.890909 4.00909091 22 13.8 11.666667 2.13333333 23 14.3 11.666667 2.63333333 24 15.2 11.666667 3.53333333 25 10.0 6.023077 3.97692308 26 6.5 7.890909 -1.39090909 27 7.5 6.023077 1.47692308 28 10.6 7.890909 2.70909091 29 7.4 11.666667 -4.26666667 30 8.4 11.666667 -3.26666667 31 5.7 6.023077 -0.32307692 32 4.9 7.890909 -2.99090909 33 3.2 7.890909 -4.69090909 34 11.0 6.023077 4.97692308 35 4.9 7.890909 -2.99090909 36 13.2 11.666667 1.53333333 37 9.7 7.890909 1.80909091 38 12.8 11.666667 1.13333333 39 11.9 11.666667 0.23333333 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/www/html/rcomp/tmp/4ptaa1292848819.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/html/rcomp/tmp/53l811292848819.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/html/rcomp/tmp/6wc741292848819.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/html/rcomp/tmp/7zd6a1292848819.tab") + } > > try(system("convert tmp/2ekb81292848819.ps tmp/2ekb81292848819.png",intern=TRUE)) character(0) > try(system("convert tmp/3ekb81292848819.ps tmp/3ekb81292848819.png",intern=TRUE)) character(0) > try(system("convert tmp/4ptaa1292848819.ps tmp/4ptaa1292848819.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.148 0.572 5.352