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Type 'q()' to quit R. > x <- array(list(4.031636 + ,0.5215052 + ,9.166456 + ,1.303763 + ,3.702076 + ,0.4248284 + ,7.970589 + ,1.416094 + ,3.056176 + ,0.4250311 + ,7.104091 + ,1.052458 + ,3.280707 + ,0.4771938 + ,6.621064 + ,1.312283 + ,2.984728 + ,0.8280212 + ,7.529215 + ,1.309429 + ,3.693712 + ,0.6156186 + ,8.170938 + ,1.492409 + ,3.226317 + ,0.366627 + ,8.15745 + ,1.026556 + ,2.190349 + ,0.4308883 + ,7.378962 + ,1.005406 + ,2.599515 + ,0.2810287 + ,7.921496 + ,1.334886 + ,3.080288 + ,0.4646245 + ,8.15674 + ,1.393873 + ,2.929672 + ,0.2693951 + ,8.856365 + ,1.128092 + ,2.922548 + ,0.5779049 + ,8.817177 + ,1.122787 + ,3.234943 + ,0.5661151 + ,8.734347 + ,1.213104 + ,2.983081 + ,0.5077584 + ,9.345927 + ,1.253528 + ,3.284389 + ,0.7507175 + ,8.99297 + ,1.094796 + ,3.806511 + ,0.6808395 + ,10.78512 + ,0.9129438 + ,3.784579 + ,0.7661091 + ,8.886867 + ,1.19513 + ,2.645654 + ,0.4561473 + ,8.818847 + ,0.9274994 + ,3.092081 + ,0.4977496 + ,8.823744 + ,0.9653326 + ,3.204859 + ,0.4193273 + ,9.165298 + ,1.198078 + ,3.107225 + ,0.6095514 + ,8.652657 + ,0.966362 + ,3.466909 + ,0.457337 + ,8.173054 + ,0.9736851 + ,2.984404 + ,0.5705478 + ,7.563416 + ,0.9948013 + ,3.218072 + ,0.3478996 + ,7.595809 + ,0.8262616 + ,2.82731 + ,0.3874993 + ,8.381467 + ,0.6888877 + ,3.182049 + ,0.5824285 + ,7.216432 + ,0.7813066 + ,2.236319 + ,0.2391033 + ,6.540178 + ,0.6047907 + ,2.033218 + ,0.2367445 + ,6.238914 + ,1.08624 + ,1.644804 + ,0.2626158 + ,5.487288 + ,0.7740255 + ,1.627971 + ,0.4240934 + ,5.759462 + ,1.026032 + ,1.677559 + ,0.365275 + ,5.993215 + ,0.6764351 + ,2.330828 + ,0.3750758 + ,7.474726 + ,0.830525 + ,2.493615 + ,0.4090056 + ,7.348907 + ,0.7916238 + ,2.257172 + ,0.3891676 + ,7.303379 + ,0.7523907 + ,2.655517 + ,0.240261 + ,7.119314 + ,0.6702018 + ,2.298655 + ,0.1589496 + ,6.99378 + ,0.8803359 + ,2.600402 + ,0.4393373 + ,6.958153 + ,0.9142966 + ,3.04523 + ,0.5094681 + ,7.595706 + ,0.9610421 + ,2.790583 + ,0.3743465 + ,8.088153 + ,0.9301944 + ,3.227052 + ,0.4339828 + ,7.555753 + ,0.8679657 + ,2.967479 + ,0.4130557 + ,7.315433 + ,0.9891596 + ,2.938817 + ,0.3288928 + ,7.893427 + ,0.9972879 + ,3.277961 + ,0.5186648 + ,8.858794 + ,0.7987437 + ,3.423985 + ,0.5486504 + ,8.839367 + ,0.9753785 + ,3.072646 + ,0.5469111 + ,8.014733 + ,0.9347208 + ,2.754253 + ,0.4963494 + ,7.873465 + ,0.9732341 + ,2.910431 + ,0.5308929 + ,8.930377 + ,0.8152998 + ,3.174369 + ,0.5957761 + ,10.50055 + ,0.9402092 + ,3.068387 + ,0.5570584 + ,12.61144 + ,0.794493 + ,3.089543 + ,0.5731325 + ,11.41787 + ,0.9313403 + ,2.906654 + ,0.5005416 + ,11.87249 + ,0.9220503 + ,2.931161 + ,0.5431269 + ,11.06082 + ,0.7845167 + ,3.02566 + ,0.5593657 + ,12.04331 + ,0.8220981 + ,2.939551 + ,0.6911693 + ,9.776299 + ,0.8910255 + ,2.691019 + ,0.4403485 + ,9.557194 + ,0.8073056 + ,3.19812 + ,0.5676662 + ,9.20259 + ,0.9514406 + ,3.07639 + ,0.5969114 + ,10.22402 + ,1.147907 + ,2.863873 + ,0.4735537 + ,9.350807 + ,1.172609 + ,3.013802 + ,0.5923935 + ,8.300913 + ,1.281051 + ,3.053364 + ,0.5975556 + ,8.365779 + ,1.165962 + ,2.864753 + ,0.6334127 + ,8.133595 + ,0.9789106 + ,3.057062 + ,0.6057115 + ,7.66047 + ,1.410951 + ,2.959365 + ,0.7046107 + ,8.074839 + ,1.197838 + ,3.252258 + ,0.4805263 + ,7.848597 + ,1.288368 + ,3.602988 + ,0.702686 + ,7.99822 + ,1.102253 + ,3.497704 + ,0.7009017 + ,7.396895 + ,1.197657 + ,3.296867 + ,0.6030854 + ,7.900419 + ,1.299984 + ,3.602417 + ,0.6980919 + ,8.1005 + ,1.198611 + ,3.3001 + ,0.597656 + ,7.899453 + ,1.299252 + ,3.40193 + ,0.8023421 + ,7.599783 + ,1.097604 + ,3.502591 + ,0.6017109 + ,8.100929 + ,1.39977 + ,3.402348 + ,0.5993127 + ,9.002175 + ,1.398396 + ,3.498551 + ,0.6025625 + ,10.2989 + ,1.40188 + ,3.199823 + ,0.7016625 + ,10.10152 + ,1.699717 + ,2.700064 + ,0.4995714 + ,10.69915 + ,1.39761 + ,2.801034 + ,0.4980918 + ,9.69814 + ,1.500135 + ,2.898628 + ,0.497569 + ,9.800951 + ,1.400136 + ,2.800854 + ,0.600183 + ,10.90047 + ,1.400427 + ,2.399942 + ,0.3339542 + ,10.69785 + ,1.341477 + ,2.402724 + ,0.274437 + ,9.297252 + ,1.33858 + ,2.202331 + ,0.3209428 + ,10.39744 + ,1.482977 + ,2.102594 + ,0.5406671 + ,10.90072 + ,1.163253 + ,1.798293 + ,0.4050209 + ,12.90127 + ,1.328468 + ,1.202484 + ,0.2885961 + ,13.09906 + ,1.23455 + ,1.400201 + ,0.3275942 + ,11.69828 + ,1.484741 + ,1.200832 + ,0.3132606 + ,11.09987 + ,1.336579 + ,1.298083 + ,0.2575562 + ,11.30157 + ,1.339292 + ,1.099742 + ,0.2138386 + ,10.70211 + ,1.405225 + ,1.001377 + ,0.1861856 + ,10.09931 + ,1.333491 + ,0.8361743 + ,0.1592713 + ,9.591119 + ,1.14974) + ,dim=c(4 + ,90) + ,dimnames=list(c('firearmsuicide' + ,'firearmhomicide' + ,'nonfirearmsuicide' + ,'nonfirearmhomicide') + ,1:90)) > y <- array(NA,dim=c(4,90),dimnames=list(c('firearmsuicide','firearmhomicide','nonfirearmsuicide','nonfirearmhomicide'),1:90)) > 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 = '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 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] "firearmsuicide" > x[,par1] [1] 4.0316360 3.7020760 3.0561760 3.2807070 2.9847280 3.6937120 3.2263170 [8] 2.1903490 2.5995150 3.0802880 2.9296720 2.9225480 3.2349430 2.9830810 [15] 3.2843890 3.8065110 3.7845790 2.6456540 3.0920810 3.2048590 3.1072250 [22] 3.4669090 2.9844040 3.2180720 2.8273100 3.1820490 2.2363190 2.0332180 [29] 1.6448040 1.6279710 1.6775590 2.3308280 2.4936150 2.2571720 2.6555170 [36] 2.2986550 2.6004020 3.0452300 2.7905830 3.2270520 2.9674790 2.9388170 [43] 3.2779610 3.4239850 3.0726460 2.7542530 2.9104310 3.1743690 3.0683870 [50] 3.0895430 2.9066540 2.9311610 3.0256600 2.9395510 2.6910190 3.1981200 [57] 3.0763900 2.8638730 3.0138020 3.0533640 2.8647530 3.0570620 2.9593650 [64] 3.2522580 3.6029880 3.4977040 3.2968670 3.6024170 3.3001000 3.4019300 [71] 3.5025910 3.4023480 3.4985510 3.1998230 2.7000640 2.8010340 2.8986280 [78] 2.8008540 2.3999420 2.4027240 2.2023310 2.1025940 1.7982930 1.2024840 [85] 1.4002010 1.2008320 1.2980830 1.0997420 1.0013770 0.8361743 > 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]) [0.836,2.60) [2.600,2.98) [2.983,3.23) [3.227,4.03] 23 22 23 22 > colnames(x) [1] "firearmsuicide" "firearmhomicide" "nonfirearmsuicide" [4] "nonfirearmhomicide" > colnames(x)[par1] [1] "firearmsuicide" > x[,par1] [1] [3.227,4.03] [3.227,4.03] [2.983,3.23) [3.227,4.03] [2.983,3.23) [6] [3.227,4.03] [2.983,3.23) [0.836,2.60) [0.836,2.60) [2.983,3.23) [11] [2.600,2.98) [2.600,2.98) [3.227,4.03] [2.983,3.23) [3.227,4.03] [16] [3.227,4.03] [3.227,4.03] [2.600,2.98) [2.983,3.23) [2.983,3.23) [21] [2.983,3.23) [3.227,4.03] [2.983,3.23) [2.983,3.23) [2.600,2.98) [26] [2.983,3.23) [0.836,2.60) [0.836,2.60) [0.836,2.60) [0.836,2.60) [31] [0.836,2.60) [0.836,2.60) [0.836,2.60) [0.836,2.60) [2.600,2.98) [36] [0.836,2.60) [2.600,2.98) [2.983,3.23) [2.600,2.98) [3.227,4.03] [41] [2.600,2.98) [2.600,2.98) [3.227,4.03] [3.227,4.03] [2.983,3.23) [46] [2.600,2.98) [2.600,2.98) [2.983,3.23) [2.983,3.23) [2.983,3.23) [51] [2.600,2.98) [2.600,2.98) [2.983,3.23) [2.600,2.98) [2.600,2.98) [56] [2.983,3.23) [2.983,3.23) [2.600,2.98) [2.983,3.23) [2.983,3.23) [61] [2.600,2.98) [2.983,3.23) [2.600,2.98) [3.227,4.03] [3.227,4.03] [66] [3.227,4.03] [3.227,4.03] [3.227,4.03] [3.227,4.03] [3.227,4.03] [71] [3.227,4.03] [3.227,4.03] [3.227,4.03] [2.983,3.23) [2.600,2.98) [76] [2.600,2.98) [2.600,2.98) [2.600,2.98) [0.836,2.60) [0.836,2.60) [81] [0.836,2.60) [0.836,2.60) [0.836,2.60) [0.836,2.60) [0.836,2.60) [86] [0.836,2.60) [0.836,2.60) [0.836,2.60) [0.836,2.60) [0.836,2.60) Levels: [0.836,2.60) [2.600,2.98) [2.983,3.23) [3.227,4.03] > 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/12h821292945615.tab") + } + } > m Conditional inference tree with 2 terminal nodes Response: as.factor(firearmsuicide) Inputs: firearmhomicide, nonfirearmsuicide, nonfirearmhomicide Number of observations: 90 1) firearmhomicide <= 0.4090056; criterion = 1, statistic = 45.782 2)* weights = 27 1) firearmhomicide > 0.4090056 3)* weights = 63 > postscript(file="/var/www/html/rcomp/tmp/2vq741292945615.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/3vq741292945615.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,] 4 4 [2,] 4 4 [3,] 3 4 [4,] 4 4 [5,] 3 4 [6,] 4 4 [7,] 3 1 [8,] 1 4 [9,] 1 1 [10,] 3 4 [11,] 2 1 [12,] 2 4 [13,] 4 4 [14,] 3 4 [15,] 4 4 [16,] 4 4 [17,] 4 4 [18,] 2 4 [19,] 3 4 [20,] 3 4 [21,] 3 4 [22,] 4 4 [23,] 3 4 [24,] 3 1 [25,] 2 1 [26,] 3 4 [27,] 1 1 [28,] 1 1 [29,] 1 1 [30,] 1 4 [31,] 1 1 [32,] 1 1 [33,] 1 1 [34,] 1 1 [35,] 2 1 [36,] 1 1 [37,] 2 4 [38,] 3 4 [39,] 2 1 [40,] 4 4 [41,] 2 4 [42,] 2 1 [43,] 4 4 [44,] 4 4 [45,] 3 4 [46,] 2 4 [47,] 2 4 [48,] 3 4 [49,] 3 4 [50,] 3 4 [51,] 2 4 [52,] 2 4 [53,] 3 4 [54,] 2 4 [55,] 2 4 [56,] 3 4 [57,] 3 4 [58,] 2 4 [59,] 3 4 [60,] 3 4 [61,] 2 4 [62,] 3 4 [63,] 2 4 [64,] 4 4 [65,] 4 4 [66,] 4 4 [67,] 4 4 [68,] 4 4 [69,] 4 4 [70,] 4 4 [71,] 4 4 [72,] 4 4 [73,] 4 4 [74,] 3 4 [75,] 2 4 [76,] 2 4 [77,] 2 4 [78,] 2 4 [79,] 1 1 [80,] 1 1 [81,] 1 1 [82,] 1 4 [83,] 1 1 [84,] 1 1 [85,] 1 1 [86,] 1 1 [87,] 1 1 [88,] 1 1 [89,] 1 1 [90,] 1 1 [0.836,2.60) [2.600,2.98) [2.983,3.23) [3.227,4.03] [0.836,2.60) 20 0 0 3 [2.600,2.98) 5 0 0 17 [2.983,3.23) 2 0 0 21 [3.227,4.03] 0 0 0 22 > postscript(file="/var/www/html/rcomp/tmp/45z671292945615.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/590nv1292945615.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/6ci3j1292945615.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/7f1271292945615.tab") + } > > try(system("convert tmp/2vq741292945615.ps tmp/2vq741292945615.png",intern=TRUE)) character(0) > try(system("convert tmp/3vq741292945615.ps tmp/3vq741292945615.png",intern=TRUE)) character(0) > try(system("convert tmp/45z671292945615.ps tmp/45z671292945615.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.973 0.477 5.311