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Type 'q()' to quit R. > x <- array(list(5 + ,15 + ,8 + ,12 + ,3 + ,8 + ,11 + ,10 + ,12 + ,4 + ,11 + ,11 + ,8 + ,12 + ,6 + ,16 + ,11 + ,13 + ,14 + ,7 + ,17 + ,11 + ,15 + ,14 + ,5 + ,9 + ,15 + ,6 + ,8 + ,4 + ,9 + ,11 + ,12 + ,13 + ,5 + ,13 + ,12 + ,16 + ,16 + ,6 + ,10 + ,12 + ,5 + ,13 + ,6 + ,6 + ,9 + ,15 + ,11 + ,6 + ,12 + ,12 + ,12 + ,14 + ,5 + ,8 + ,12 + ,8 + ,13 + ,4 + ,14 + ,13 + ,13 + ,13 + ,5 + ,12 + ,11 + ,14 + ,13 + ,5 + ,11 + ,9 + ,12 + ,12 + ,4 + ,16 + ,9 + ,16 + ,16 + ,6 + ,8 + ,11 + ,10 + ,15 + ,2 + ,15 + ,11 + ,15 + ,15 + ,8 + ,7 + ,12 + ,8 + ,12 + ,3 + ,16 + ,12 + ,16 + ,14 + ,6 + ,14 + ,9 + ,19 + ,12 + ,6 + ,16 + ,11 + ,14 + ,15 + ,6 + ,9 + ,9 + ,6 + ,12 + ,5 + ,14 + ,12 + ,13 + ,13 + ,5 + ,11 + ,12 + ,15 + ,12 + ,6 + ,13 + ,12 + ,7 + ,12 + ,5 + ,15 + ,12 + ,13 + ,13 + ,6 + ,5 + ,14 + ,4 + ,5 + ,2 + ,15 + ,11 + ,14 + ,13 + ,5 + ,13 + ,12 + ,13 + ,13 + ,5 + ,11 + ,11 + ,11 + ,14 + ,5 + ,11 + ,6 + ,14 + ,17 + ,6 + ,12 + ,10 + ,12 + ,13 + ,6 + ,12 + ,12 + ,15 + ,13 + ,6 + ,12 + ,13 + ,14 + ,12 + ,5 + ,12 + ,8 + ,13 + ,13 + ,5 + ,14 + ,12 + ,8 + ,14 + ,4 + ,6 + ,12 + ,6 + ,11 + ,2 + ,7 + ,12 + ,7 + ,12 + ,4 + ,14 + ,6 + ,13 + ,12 + ,6 + ,14 + ,11 + ,13 + ,16 + ,6 + ,10 + ,10 + ,11 + ,12 + ,5 + ,13 + ,12 + ,5 + ,12 + ,3 + ,12 + ,13 + ,12 + ,12 + ,6 + ,9 + ,11 + ,8 + ,10 + ,4 + ,12 + ,7 + ,11 + ,15 + ,5 + ,16 + ,11 + ,14 + ,15 + ,8 + ,10 + ,11 + ,9 + ,12 + ,4 + ,14 + ,11 + ,10 + ,16 + ,6 + ,10 + ,11 + ,13 + ,15 + ,6 + ,16 + ,12 + ,16 + ,16 + ,7 + ,15 + ,10 + ,16 + ,13 + ,6 + ,12 + ,11 + ,11 + ,12 + ,5 + ,10 + ,12 + ,8 + ,11 + ,4 + ,8 + ,7 + ,4 + ,13 + ,6 + ,8 + ,13 + ,7 + ,10 + ,3 + ,11 + ,8 + ,14 + ,15 + ,5 + ,13 + ,12 + ,11 + ,13 + ,6 + ,16 + ,11 + ,17 + ,16 + ,7 + ,16 + ,12 + ,15 + ,15 + ,7 + ,14 + ,14 + ,17 + ,18 + ,6 + ,11 + ,10 + ,5 + ,13 + ,3 + ,4 + ,10 + ,4 + ,10 + ,2 + ,14 + ,13 + ,10 + ,16 + ,8 + ,9 + ,10 + ,11 + ,13 + ,3 + ,14 + ,11 + ,15 + ,15 + ,8 + ,8 + ,10 + ,10 + ,14 + ,3 + ,8 + ,7 + ,9 + ,15 + ,4 + ,11 + ,10 + ,12 + ,14 + ,5 + ,12 + ,8 + ,15 + ,13 + ,7 + ,11 + ,12 + ,7 + ,13 + ,6 + ,14 + ,12 + ,13 + ,15 + ,6 + ,15 + ,12 + ,12 + ,16 + ,7 + ,16 + ,11 + ,14 + ,14 + ,6 + ,16 + ,12 + ,14 + ,14 + ,6 + ,11 + ,12 + ,8 + ,16 + ,6 + ,14 + ,12 + ,15 + ,14 + ,6 + ,14 + ,11 + ,12 + ,12 + ,4 + ,12 + ,12 + ,12 + ,13 + ,4 + ,14 + ,11 + ,16 + ,12 + ,5 + ,8 + ,11 + ,9 + ,12 + ,4 + ,13 + ,13 + ,15 + ,14 + ,6 + ,16 + ,12 + ,15 + ,14 + ,6 + ,12 + ,12 + ,6 + ,14 + ,5 + ,16 + ,12 + ,14 + ,16 + ,8 + ,12 + ,12 + ,15 + ,13 + ,6 + ,11 + ,8 + ,10 + ,14 + ,5 + ,4 + ,8 + ,6 + ,4 + ,4 + ,16 + ,12 + ,14 + ,16 + ,8 + ,15 + ,11 + ,12 + ,13 + ,6 + ,10 + ,12 + ,8 + ,16 + ,4 + ,13 + ,13 + ,11 + ,15 + ,6 + ,15 + ,12 + ,13 + ,14 + ,6 + ,12 + ,12 + ,9 + ,13 + ,4 + ,14 + ,11 + ,15 + ,14 + ,6 + ,7 + ,12 + ,13 + ,12 + ,3 + ,19 + ,12 + ,15 + ,15 + ,6 + ,12 + ,10 + ,14 + ,14 + ,5 + ,12 + ,11 + ,16 + ,13 + ,4 + ,13 + ,12 + ,14 + ,14 + ,6 + ,15 + ,12 + ,14 + ,16 + ,4 + ,8 + ,10 + ,10 + ,6 + ,4 + ,12 + ,12 + ,10 + ,13 + ,4 + ,10 + ,13 + ,4 + ,13 + ,6 + ,8 + ,12 + ,8 + ,14 + ,5 + ,10 + ,15 + ,15 + ,15 + ,6 + ,15 + ,11 + ,16 + ,14 + ,6 + ,16 + ,12 + ,12 + ,15 + ,8 + ,13 + ,11 + ,12 + ,13 + ,7 + ,16 + ,12 + ,15 + ,16 + ,7 + ,9 + ,11 + ,9 + ,12 + ,4 + ,14 + ,10 + ,12 + ,15 + ,6 + ,14 + ,11 + ,14 + ,12 + ,6 + ,12 + ,11 + ,11 + ,14 + ,2) + ,dim=c(5 + ,114) + ,dimnames=list(c('Popularity' + ,'Findingfriends' + ,'Knowingpeople' + ,'Liked' + ,'Celebrity') + ,1:114)) > y <- array(NA,dim=c(5,114),dimnames=list(c('Popularity','Findingfriends','Knowingpeople','Liked','Celebrity'),1:114)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par20 = '' > par19 = '' > par18 = '' > par17 = '' > par16 = '' > par15 = '' > par14 = '' > par13 = '' > par12 = '' > par11 = '' > par10 = '' > par9 = '' > par8 = '' > par7 = '' > par6 = '' > par5 = '' > par4 = 'no' > par3 = '2' > par2 = 'quantiles' > par1 = '3' > 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 objects 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 is masked from 'package:survival': untangle.specials The following objects 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] "Knowingpeople" > x[,par1] [1] 8 10 8 13 15 6 12 16 5 15 12 8 13 14 12 16 10 15 8 16 19 14 6 13 15 [26] 7 13 4 14 13 11 14 12 15 14 13 8 6 7 13 13 11 5 12 8 11 14 9 10 13 [51] 16 16 11 8 4 7 14 11 17 15 17 5 4 10 11 15 10 9 12 15 7 13 12 14 14 [76] 8 15 12 12 16 9 15 15 6 14 15 10 6 14 12 8 11 13 9 15 13 15 14 16 14 [101] 14 10 10 4 8 15 16 12 12 15 9 12 14 11 > 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]) [ 4,13) [13,19] 60 54 > colnames(x) [1] "Popularity" "Findingfriends" "Knowingpeople" "Liked" [5] "Celebrity" > colnames(x)[par1] [1] "Knowingpeople" > x[,par1] [1] [ 4,13) [ 4,13) [ 4,13) [13,19] [13,19] [ 4,13) [ 4,13) [13,19] [ 4,13) [10] [13,19] [ 4,13) [ 4,13) [13,19] [13,19] [ 4,13) [13,19] [ 4,13) [13,19] [19] [ 4,13) [13,19] [13,19] [13,19] [ 4,13) [13,19] [13,19] [ 4,13) [13,19] [28] [ 4,13) [13,19] [13,19] [ 4,13) [13,19] [ 4,13) [13,19] [13,19] [13,19] [37] [ 4,13) [ 4,13) [ 4,13) [13,19] [13,19] [ 4,13) [ 4,13) [ 4,13) [ 4,13) [46] [ 4,13) [13,19] [ 4,13) [ 4,13) [13,19] [13,19] [13,19] [ 4,13) [ 4,13) [55] [ 4,13) [ 4,13) [13,19] [ 4,13) [13,19] [13,19] [13,19] [ 4,13) [ 4,13) [64] [ 4,13) [ 4,13) [13,19] [ 4,13) [ 4,13) [ 4,13) [13,19] [ 4,13) [13,19] [73] [ 4,13) [13,19] [13,19] [ 4,13) [13,19] [ 4,13) [ 4,13) [13,19] [ 4,13) [82] [13,19] [13,19] [ 4,13) [13,19] [13,19] [ 4,13) [ 4,13) [13,19] [ 4,13) [91] [ 4,13) [ 4,13) [13,19] [ 4,13) [13,19] [13,19] [13,19] [13,19] [13,19] [100] [13,19] [13,19] [ 4,13) [ 4,13) [ 4,13) [ 4,13) [13,19] [13,19] [ 4,13) [109] [ 4,13) [13,19] [ 4,13) [ 4,13) [13,19] [ 4,13) Levels: [ 4,13) [13,19] > 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/1ubzw1386626847.tab") + } + } > m Conditional inference tree with 3 terminal nodes Response: as.factor(Knowingpeople) Inputs: Popularity, Findingfriends, Liked, Celebrity Number of observations: 114 1) Popularity <= 13; criterion = 1, statistic = 35.361 2) Celebrity <= 4; criterion = 0.996, statistic = 10.844 3)* weights = 31 2) Celebrity > 4 4)* weights = 40 1) Popularity > 13 5)* weights = 43 > postscript(file="/var/wessaorg/rcomp/tmp/2wr6m1386626847.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/3rk341386626847.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,] 1 1 [7,] 1 1 [8,] 2 1 [9,] 1 1 [10,] 2 1 [11,] 1 1 [12,] 1 1 [13,] 2 2 [14,] 2 1 [15,] 1 1 [16,] 2 2 [17,] 1 1 [18,] 2 2 [19,] 1 1 [20,] 2 2 [21,] 2 2 [22,] 2 2 [23,] 1 1 [24,] 2 2 [25,] 2 1 [26,] 1 1 [27,] 2 2 [28,] 1 1 [29,] 2 2 [30,] 2 1 [31,] 1 1 [32,] 2 1 [33,] 1 1 [34,] 2 1 [35,] 2 1 [36,] 2 1 [37,] 1 2 [38,] 1 1 [39,] 1 1 [40,] 2 2 [41,] 2 2 [42,] 1 1 [43,] 1 1 [44,] 1 1 [45,] 1 1 [46,] 1 1 [47,] 2 2 [48,] 1 1 [49,] 1 2 [50,] 2 1 [51,] 2 2 [52,] 2 2 [53,] 1 1 [54,] 1 1 [55,] 1 1 [56,] 1 1 [57,] 2 1 [58,] 1 1 [59,] 2 2 [60,] 2 2 [61,] 2 2 [62,] 1 1 [63,] 1 1 [64,] 1 2 [65,] 1 1 [66,] 2 2 [67,] 1 1 [68,] 1 1 [69,] 1 1 [70,] 2 1 [71,] 1 1 [72,] 2 2 [73,] 1 2 [74,] 2 2 [75,] 2 2 [76,] 1 1 [77,] 2 2 [78,] 1 2 [79,] 1 1 [80,] 2 2 [81,] 1 1 [82,] 2 1 [83,] 2 2 [84,] 1 1 [85,] 2 2 [86,] 2 1 [87,] 1 1 [88,] 1 1 [89,] 2 2 [90,] 1 2 [91,] 1 1 [92,] 1 1 [93,] 2 2 [94,] 1 1 [95,] 2 2 [96,] 2 1 [97,] 2 2 [98,] 2 1 [99,] 2 1 [100,] 2 1 [101,] 2 2 [102,] 1 1 [103,] 1 1 [104,] 1 1 [105,] 1 1 [106,] 2 1 [107,] 2 2 [108,] 1 2 [109,] 1 1 [110,] 2 2 [111,] 1 1 [112,] 1 2 [113,] 2 2 [114,] 1 1 [ 4,13) [13,19] [ 4,13) 52 8 [13,19] 19 35 > postscript(file="/var/wessaorg/rcomp/tmp/4g8nx1386626847.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$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/5f0mo1386626847.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$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/6okjq1386626847.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/724ze1386626847.tab") + } > > try(system("convert tmp/2wr6m1386626847.ps tmp/2wr6m1386626847.png",intern=TRUE)) character(0) > try(system("convert tmp/3rk341386626847.ps tmp/3rk341386626847.png",intern=TRUE)) character(0) > try(system("convert tmp/4g8nx1386626847.ps tmp/4g8nx1386626847.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 7.025 1.278 8.278