x <- array(list(24 ,14 ,11 ,12 ,24 ,26 ,25 ,11 ,7 ,8 ,25 ,23 ,17 ,6 ,17 ,8 ,30 ,25 ,18 ,12 ,10 ,8 ,19 ,23 ,18 ,8 ,12 ,9 ,22 ,19 ,16 ,10 ,12 ,7 ,22 ,29 ,20 ,10 ,11 ,4 ,25 ,25 ,16 ,11 ,11 ,11 ,23 ,21 ,18 ,16 ,12 ,7 ,17 ,22 ,17 ,11 ,13 ,7 ,21 ,25 ,23 ,13 ,14 ,12 ,19 ,24 ,30 ,12 ,16 ,10 ,19 ,18 ,23 ,8 ,11 ,10 ,15 ,22 ,18 ,12 ,10 ,8 ,16 ,15 ,15 ,11 ,11 ,8 ,23 ,22 ,12 ,4 ,15 ,4 ,27 ,28 ,21 ,9 ,9 ,9 ,22 ,20 ,15 ,8 ,11 ,8 ,14 ,12 ,20 ,8 ,17 ,7 ,22 ,24 ,31 ,14 ,17 ,11 ,23 ,20 ,27 ,15 ,11 ,9 ,23 ,21 ,34 ,16 ,18 ,11 ,21 ,20 ,21 ,9 ,14 ,13 ,19 ,21 ,31 ,14 ,10 ,8 ,18 ,23 ,19 ,11 ,11 ,8 ,20 ,28 ,16 ,8 ,15 ,9 ,23 ,24 ,20 ,9 ,15 ,6 ,25 ,24 ,21 ,9 ,13 ,9 ,19 ,24 ,22 ,9 ,16 ,9 ,24 ,23 ,17 ,9 ,13 ,6 ,22 ,23 ,24 ,10 ,9 ,6 ,25 ,29 ,25 ,16 ,18 ,16 ,26 ,24 ,26 ,11 ,18 ,5 ,29 ,18 ,25 ,8 ,12 ,7 ,32 ,25 ,17 ,9 ,17 ,9 ,25 ,21 ,32 ,16 ,9 ,6 ,29 ,26 ,33 ,11 ,9 ,6 ,28 ,22 ,13 ,16 ,12 ,5 ,17 ,22 ,32 ,12 ,18 ,12 ,28 ,22 ,25 ,12 ,12 ,7 ,29 ,23 ,29 ,14 ,18 ,10 ,26 ,30 ,22 ,9 ,14 ,9 ,25 ,23 ,18 ,10 ,15 ,8 ,14 ,17 ,17 ,9 ,16 ,5 ,25 ,23 ,20 ,10 ,10 ,8 ,26 ,23 ,15 ,12 ,11 ,8 ,20 ,25 ,20 ,14 ,14 ,10 ,18 ,24 ,33 ,14 ,9 ,6 ,32 ,24 ,29 ,10 ,12 ,8 ,25 ,23 ,23 ,14 ,17 ,7 ,25 ,21 ,26 ,16 ,5 ,4 ,23 ,24 ,18 ,9 ,12 ,8 ,21 ,24 ,20 ,10 ,12 ,8 ,20 ,28 ,11 ,6 ,6 ,4 ,15 ,16 ,28 ,8 ,24 ,20 ,30 ,20 ,26 ,13 ,12 ,8 ,24 ,29 ,22 ,10 ,12 ,8 ,26 ,27 ,17 ,8 ,14 ,6 ,24 ,22 ,12 ,7 ,7 ,4 ,22 ,28 ,14 ,15 ,13 ,8 ,14 ,16 ,17 ,9 ,12 ,9 ,24 ,25 ,21 ,10 ,13 ,6 ,24 ,24 ,19 ,12 ,14 ,7 ,24 ,28 ,18 ,13 ,8 ,9 ,24 ,24 ,10 ,10 ,11 ,5 ,19 ,23 ,29 ,11 ,9 ,5 ,31 ,30 ,31 ,8 ,11 ,8 ,22 ,24 ,19 ,9 ,13 ,8 ,27 ,21 ,9 ,13 ,10 ,6 ,19 ,25 ,20 ,11 ,11 ,8 ,25 ,25 ,28 ,8 ,12 ,7 ,20 ,22 ,19 ,9 ,9 ,7 ,21 ,23 ,30 ,9 ,15 ,9 ,27 ,26 ,29 ,15 ,18 ,11 ,23 ,23 ,26 ,9 ,15 ,6 ,25 ,25 ,23 ,10 ,12 ,8 ,20 ,21 ,13 ,14 ,13 ,6 ,21 ,25 ,21 ,12 ,14 ,9 ,22 ,24 ,19 ,12 ,10 ,8 ,23 ,29 ,28 ,11 ,13 ,6 ,25 ,22 ,23 ,14 ,13 ,10 ,25 ,27 ,18 ,6 ,11 ,8 ,17 ,26 ,21 ,12 ,13 ,8 ,19 ,22 ,20 ,8 ,16 ,10 ,25 ,24 ,23 ,14 ,8 ,5 ,19 ,27 ,21 ,11 ,16 ,7 ,20 ,24 ,21 ,10 ,11 ,5 ,26 ,24 ,15 ,14 ,9 ,8 ,23 ,29 ,28 ,12 ,16 ,14 ,27 ,22 ,19 ,10 ,12 ,7 ,17 ,21 ,26 ,14 ,14 ,8 ,17 ,24 ,10 ,5 ,8 ,6 ,19 ,24 ,16 ,11 ,9 ,5 ,17 ,23 ,22 ,10 ,15 ,6 ,22 ,20 ,19 ,9 ,11 ,10 ,21 ,27 ,31 ,10 ,21 ,12 ,32 ,26 ,31 ,16 ,14 ,9 ,21 ,25 ,29 ,13 ,18 ,12 ,21 ,21 ,19 ,9 ,12 ,7 ,18 ,21 ,22 ,10 ,13 ,8 ,18 ,19 ,23 ,10 ,15 ,10 ,23 ,21 ,15 ,7 ,12 ,6 ,19 ,21 ,20 ,9 ,19 ,10 ,20 ,16 ,18 ,8 ,15 ,10 ,21 ,22 ,23 ,14 ,11 ,10 ,20 ,29 ,25 ,14 ,11 ,5 ,17 ,15 ,21 ,8 ,10 ,7 ,18 ,17 ,24 ,9 ,13 ,10 ,19 ,15 ,25 ,14 ,15 ,11 ,22 ,21 ,17 ,14 ,12 ,6 ,15 ,21 ,13 ,8 ,12 ,7 ,14 ,19 ,28 ,8 ,16 ,12 ,18 ,24 ,21 ,8 ,9 ,11 ,24 ,20 ,25 ,7 ,18 ,11 ,35 ,17 ,9 ,6 ,8 ,11 ,29 ,23 ,16 ,8 ,13 ,5 ,21 ,24 ,19 ,6 ,17 ,8 ,25 ,14 ,17 ,11 ,9 ,6 ,20 ,19 ,25 ,14 ,15 ,9 ,22 ,24 ,20 ,11 ,8 ,4 ,13 ,13 ,29 ,11 ,7 ,4 ,26 ,22 ,14 ,11 ,12 ,7 ,17 ,16 ,22 ,14 ,14 ,11 ,25 ,19 ,15 ,8 ,6 ,6 ,20 ,25 ,19 ,20 ,8 ,7 ,19 ,25 ,20 ,11 ,17 ,8 ,21 ,23 ,15 ,8 ,10 ,4 ,22 ,24 ,20 ,11 ,11 ,8 ,24 ,26 ,18 ,10 ,14 ,9 ,21 ,26 ,33 ,14 ,11 ,8 ,26 ,25 ,22 ,11 ,13 ,11 ,24 ,18 ,16 ,9 ,12 ,8 ,16 ,21 ,17 ,9 ,11 ,5 ,23 ,26 ,16 ,8 ,9 ,4 ,18 ,23 ,21 ,10 ,12 ,8 ,16 ,23 ,26 ,13 ,20 ,10 ,26 ,22 ,18 ,13 ,12 ,6 ,19 ,20 ,18 ,12 ,13 ,9 ,21 ,13 ,17 ,8 ,12 ,9 ,21 ,24 ,22 ,13 ,12 ,13 ,22 ,15 ,30 ,14 ,9 ,9 ,23 ,14 ,30 ,12 ,15 ,10 ,29 ,22 ,24 ,14 ,24 ,20 ,21 ,10 ,21 ,15 ,7 ,5 ,21 ,24 ,21 ,13 ,17 ,11 ,23 ,22 ,29 ,16 ,11 ,6 ,27 ,24 ,31 ,9 ,17 ,9 ,25 ,19 ,20 ,9 ,11 ,7 ,21 ,20 ,16 ,9 ,12 ,9 ,10 ,13 ,22 ,8 ,14 ,10 ,20 ,20 ,20 ,7 ,11 ,9 ,26 ,22 ,28 ,16 ,16 ,8 ,24 ,24 ,38 ,11 ,21 ,7 ,29 ,29 ,22 ,9 ,14 ,6 ,19 ,12 ,20 ,11 ,20 ,13 ,24 ,20 ,17 ,9 ,13 ,6 ,19 ,21 ,28 ,14 ,11 ,8 ,24 ,24 ,22 ,13 ,15 ,10 ,22 ,22 ,31 ,16 ,19 ,16 ,17 ,20) ,dim=c(6 ,159) ,dimnames=list(c('Intercept twijfels' ,'over' ,'acties verwachtingen' ,'ouders kritiek' ,'ouders persoonlijke' ,'normen organisatie' ,'student maand') ,1:159)) y <- array(NA,dim=c(6,159),dimnames=list(c('Intercept twijfels','over','acties verwachtingen','ouders kritiek','ouders persoonlijke','normen organisatie','student maand'),1:159)) for (i in 1:dim(x)[1]) { for (j in 1:dim(x)[2]) { y[i,j] <- as.numeric(x[i,j]) } } par3 = 'No Linear Trend' par2 = 'Do not include Seasonal Dummies' par1 = '1' par3 <- 'No Linear Trend' par2 <- 'Do not include Seasonal Dummies' par1 <- '1' #'GNU S' R Code compiled by R2WASP v. 1.0.44 () #Author: Prof. Dr. P. Wessa #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ #Source of accompanying publication: Office for Research, Development, and Education #Technical description: Write here your technical program description (don't use hard returns!) library(lattice) library(lmtest) n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test par1 <- as.numeric(par1) x <- t(y) k <- length(x[1,]) n <- length(x[,1]) x1 <- cbind(x[,par1], x[,1:k!=par1]) mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) colnames(x1) <- mycolnames #colnames(x)[par1] x <- x1 if (par3 == 'First Differences'){ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) for (i in 1:n-1) { for (j in 1:k) { x2[i,j] <- x[i+1,j] - x[i,j] } } x <- x2 } if (par2 == 'Include Monthly Dummies'){ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) for (i in 1:11){ x2[seq(i,n,12),i] <- 1 } x <- cbind(x, x2) } if (par2 == 'Include Quarterly Dummies'){ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) for (i in 1:3){ x2[seq(i,n,4),i] <- 1 } x <- cbind(x, x2) } k <- length(x[1,]) if (par3 == 'Linear Trend'){ x <- cbind(x, c(1:n)) colnames(x)[k+1] <- 't' } x k <- length(x[1,]) df <- as.data.frame(x) (mylm <- lm(df)) (mysum <- summary(mylm)) if (n > n25) { kp3 <- k + 3 nmkm3 <- n - k - 3 gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) numgqtests <- 0 numsignificant1 <- 0 numsignificant5 <- 0 numsignificant10 <- 0 for (mypoint in kp3:nmkm3) { j <- 0 numgqtests <- numgqtests + 1 for (myalt in c('greater', 'two.sided', 'less')) { j <- j + 1 gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value } if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 } gqarr } postscript(file="/var/fisher/rcomp/tmp/17u601352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') points(x[,1]-mysum$resid) grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/2xomt1352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/3aumc1352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/4ihhb1352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') dev.off() postscript(file="/var/fisher/rcomp/tmp/566011352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') qqline(mysum$resid) grid() dev.off() (myerror <- as.ts(mysum$resid)) postscript(file="/var/fisher/rcomp/tmp/6xe9q1352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) dum <- cbind(lag(myerror,k=1),myerror) dum dum1 <- dum[2:length(myerror),] dum1 z <- as.data.frame(dum1) z plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') lines(lowess(z)) abline(lm(z)) grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/7gro91352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/8yuhw1352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') grid() dev.off() postscript(file="/var/fisher/rcomp/tmp/9r65p1352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) plot(mylm, las = 1, sub='Residual Diagnostics') par(opar) dev.off() if (n > n25) { postscript(file="/var/fisher/rcomp/tmp/105cc41352155286.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') grid() dev.off() } #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab load(file="/var/fisher/rcomp/createtable") a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) a<-table.row.end(a) myeq <- colnames(x)[1] myeq <- paste(myeq, '[t] = ', sep='') for (i in 1:k){ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') if (rownames(mysum$coefficients)[i] != '(Intercept)') { myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') } } myeq <- paste(myeq, ' + e[t]') a<-table.row.start(a) a<-table.element(a, myeq) a<-table.row.end(a) a<-table.end(a) table.save(a,file="/var/fisher/rcomp/tmp/117fs21352155286.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',header=TRUE) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) a<-table.element(a,'2-tail p-value',header=TRUE) a<-table.element(a,'1-tail p-value',header=TRUE) a<-table.row.end(a) for (i in 1:k){ a<-table.row.start(a) a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) a<-table.element(a,mysum$coefficients[i,1]) a<-table.element(a, round(mysum$coefficients[i,2],6)) a<-table.element(a, round(mysum$coefficients[i,3],4)) a<-table.element(a, round(mysum$coefficients[i,4],6)) a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file="/var/fisher/rcomp/tmp/12apxh1352155286.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple R',1,TRUE) a<-table.element(a, sqrt(mysum$r.squared)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'R-squared',1,TRUE) a<-table.element(a, mysum$r.squared) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Adjusted R-squared',1,TRUE) a<-table.element(a, mysum$adj.r.squared) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (value)',1,TRUE) a<-table.element(a, mysum$fstatistic[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) a<-table.element(a, mysum$fstatistic[2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) a<-table.element(a, mysum$fstatistic[3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'p-value',1,TRUE) a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residual Standard Deviation',1,TRUE) a<-table.element(a, mysum$sigma) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Sum Squared Residuals',1,TRUE) a<-table.element(a, sum(myerror*myerror)) a<-table.row.end(a) a<-table.end(a) table.save(a,file="/var/fisher/rcomp/tmp/137emb1352155286.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Time or Index', 1, TRUE) a<-table.element(a, 'Actuals', 1, TRUE) a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,i, 1, TRUE) a<-table.element(a,x[i]) a<-table.element(a,x[i]-mysum$resid[i]) a<-table.element(a,mysum$resid[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file="/var/fisher/rcomp/tmp/14ix2s1352155287.tab") if (n > n25) { a<-table.start() a<-table.row.start(a) a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-values',header=TRUE) a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'breakpoint index',header=TRUE) a<-table.element(a,'greater',header=TRUE) a<-table.element(a,'2-sided',header=TRUE) a<-table.element(a,'less',header=TRUE) a<-table.row.end(a) for (mypoint in kp3:nmkm3) { a<-table.row.start(a) a<-table.element(a,mypoint,header=TRUE) a<-table.element(a,gqarr[mypoint-kp3+1,1]) a<-table.element(a,gqarr[mypoint-kp3+1,2]) a<-table.element(a,gqarr[mypoint-kp3+1,3]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file="/var/fisher/rcomp/tmp/15esi81352155287.tab") a<-table.start() a<-table.row.start(a) a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Description',header=TRUE) a<-table.element(a,'# significant tests',header=TRUE) a<-table.element(a,'% significant tests',header=TRUE) a<-table.element(a,'OK/NOK',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'1% type I error level',header=TRUE) a<-table.element(a,numsignificant1) a<-table.element(a,numsignificant1/numgqtests) if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'5% type I error level',header=TRUE) a<-table.element(a,numsignificant5) a<-table.element(a,numsignificant5/numgqtests) if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'10% type I error level',header=TRUE) a<-table.element(a,numsignificant10) a<-table.element(a,numsignificant10/numgqtests) if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.end(a) table.save(a,file="/var/fisher/rcomp/tmp/16gyn51352155287.tab") } try(system("convert tmp/17u601352155286.ps tmp/17u601352155286.png",intern=TRUE)) try(system("convert tmp/2xomt1352155286.ps tmp/2xomt1352155286.png",intern=TRUE)) try(system("convert tmp/3aumc1352155286.ps tmp/3aumc1352155286.png",intern=TRUE)) try(system("convert tmp/4ihhb1352155286.ps tmp/4ihhb1352155286.png",intern=TRUE)) try(system("convert tmp/566011352155286.ps tmp/566011352155286.png",intern=TRUE)) try(system("convert tmp/6xe9q1352155286.ps tmp/6xe9q1352155286.png",intern=TRUE)) try(system("convert tmp/7gro91352155286.ps tmp/7gro91352155286.png",intern=TRUE)) try(system("convert tmp/8yuhw1352155286.ps tmp/8yuhw1352155286.png",intern=TRUE)) try(system("convert tmp/9r65p1352155286.ps tmp/9r65p1352155286.png",intern=TRUE)) try(system("convert tmp/105cc41352155286.ps tmp/105cc41352155286.png",intern=TRUE))