R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(39,144,45,138,47,145,65,162,46,142,67,170,42,124,67,158,56,154,64,162,56,150,59,140,34,110,42,128,48,130,45,135,17,114,20,116,19,124,36,136,50,142,39,120,21,120,44,160,53,158,63,144,29,130,25,125,69,175),dim=c(2,29),dimnames=list(c('leeftijd','bloeddruk'),1:29))
> y <- array(NA,dim=c(2,29),dimnames=list(c('leeftijd','bloeddruk'),1:29))
> 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 = '2'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '2'
> #'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)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> 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
bloeddruk leeftijd
1 144 39
2 138 45
3 145 47
4 162 65
5 142 46
6 170 67
7 124 42
8 158 67
9 154 56
10 162 64
11 150 56
12 140 59
13 110 34
14 128 42
15 130 48
16 135 45
17 114 17
18 116 20
19 124 19
20 136 36
21 142 50
22 120 39
23 120 21
24 160 44
25 158 53
26 144 63
27 130 29
28 125 25
29 175 69
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) leeftijd
97.0771 0.9493
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-19.354 -4.797 1.254 4.747 21.153
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 97.0771 5.5276 17.562 2.67e-16 ***
leeftijd 0.9493 0.1161 8.174 8.88e-09 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 9.563 on 27 degrees of freedom
Multiple R-squared: 0.7122, Adjusted R-squared: 0.7015
F-statistic: 66.81 on 1 and 27 DF, p-value: 8.876e-09
> 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
+ }
[,1] [,2] [,3]
[1,] 0.11674439 0.23348879 0.8832556
[2,] 0.08650142 0.17300284 0.9134986
[3,] 0.29454601 0.58909201 0.7054540
[4,] 0.23414384 0.46828768 0.7658562
[5,] 0.14590754 0.29181509 0.8540925
[6,] 0.08613568 0.17227136 0.9138643
[7,] 0.04686843 0.09373686 0.9531316
[8,] 0.11155866 0.22311733 0.8884413
[9,] 0.27502612 0.55005223 0.7249739
[10,] 0.23027095 0.46054189 0.7697291
[11,] 0.27987734 0.55975468 0.7201227
[12,] 0.21533548 0.43067096 0.7846645
[13,] 0.20364391 0.40728781 0.7963561
[14,] 0.15122776 0.30245551 0.8487722
[15,] 0.14539272 0.29078543 0.8546073
[16,] 0.09567053 0.19134105 0.9043295
[17,] 0.05854586 0.11709171 0.9414541
[18,] 0.15240363 0.30480727 0.8475964
[19,] 0.09484989 0.18969978 0.9051501
[20,] 0.24763566 0.49527132 0.7523643
> postscript(file="/var/fisher/rcomp/tmp/1d48o1354573546.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/2en2d1354573546.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/3kvsu1354573546.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4q0011354573546.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5s16t1354573546.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()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 29
Frequency = 1
1 2 3 4 5 6
9.89933678 -1.79659845 3.30475648 3.21695081 1.25407902 9.31830573
7 8 9 10 11 12
-12.94863083 -2.68169427 3.76085364 4.16627334 -0.23914636 -13.08711397
13 14 15 16 17 18
-19.35405054 -8.94863083 -12.64456606 -4.79659845 0.78443260 -0.06353501
19 20 21 22 23 24
8.88578752 4.74730439 -2.54321113 -14.10066322 2.98714245 21.15272409
25 26 27 28 29
10.60882126 -12.88440412 5.39256215 4.18985230 12.41966066
> postscript(file="/var/fisher/rcomp/tmp/6hktp1354573546.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 29
Frequency = 1
lag(myerror, k = 1) myerror
0 9.89933678 NA
1 -1.79659845 9.89933678
2 3.30475648 -1.79659845
3 3.21695081 3.30475648
4 1.25407902 3.21695081
5 9.31830573 1.25407902
6 -12.94863083 9.31830573
7 -2.68169427 -12.94863083
8 3.76085364 -2.68169427
9 4.16627334 3.76085364
10 -0.23914636 4.16627334
11 -13.08711397 -0.23914636
12 -19.35405054 -13.08711397
13 -8.94863083 -19.35405054
14 -12.64456606 -8.94863083
15 -4.79659845 -12.64456606
16 0.78443260 -4.79659845
17 -0.06353501 0.78443260
18 8.88578752 -0.06353501
19 4.74730439 8.88578752
20 -2.54321113 4.74730439
21 -14.10066322 -2.54321113
22 2.98714245 -14.10066322
23 21.15272409 2.98714245
24 10.60882126 21.15272409
25 -12.88440412 10.60882126
26 5.39256215 -12.88440412
27 4.18985230 5.39256215
28 12.41966066 4.18985230
29 NA 12.41966066
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.79659845 9.89933678
[2,] 3.30475648 -1.79659845
[3,] 3.21695081 3.30475648
[4,] 1.25407902 3.21695081
[5,] 9.31830573 1.25407902
[6,] -12.94863083 9.31830573
[7,] -2.68169427 -12.94863083
[8,] 3.76085364 -2.68169427
[9,] 4.16627334 3.76085364
[10,] -0.23914636 4.16627334
[11,] -13.08711397 -0.23914636
[12,] -19.35405054 -13.08711397
[13,] -8.94863083 -19.35405054
[14,] -12.64456606 -8.94863083
[15,] -4.79659845 -12.64456606
[16,] 0.78443260 -4.79659845
[17,] -0.06353501 0.78443260
[18,] 8.88578752 -0.06353501
[19,] 4.74730439 8.88578752
[20,] -2.54321113 4.74730439
[21,] -14.10066322 -2.54321113
[22,] 2.98714245 -14.10066322
[23,] 21.15272409 2.98714245
[24,] 10.60882126 21.15272409
[25,] -12.88440412 10.60882126
[26,] 5.39256215 -12.88440412
[27,] 4.18985230 5.39256215
[28,] 12.41966066 4.18985230
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.79659845 9.89933678
2 3.30475648 -1.79659845
3 3.21695081 3.30475648
4 1.25407902 3.21695081
5 9.31830573 1.25407902
6 -12.94863083 9.31830573
7 -2.68169427 -12.94863083
8 3.76085364 -2.68169427
9 4.16627334 3.76085364
10 -0.23914636 4.16627334
11 -13.08711397 -0.23914636
12 -19.35405054 -13.08711397
13 -8.94863083 -19.35405054
14 -12.64456606 -8.94863083
15 -4.79659845 -12.64456606
16 0.78443260 -4.79659845
17 -0.06353501 0.78443260
18 8.88578752 -0.06353501
19 4.74730439 8.88578752
20 -2.54321113 4.74730439
21 -14.10066322 -2.54321113
22 2.98714245 -14.10066322
23 21.15272409 2.98714245
24 10.60882126 21.15272409
25 -12.88440412 10.60882126
26 5.39256215 -12.88440412
27 4.18985230 5.39256215
28 12.41966066 4.18985230
> 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()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/7dd3i1354573546.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8l65f1354573546.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/9u1081354573546.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10xrm81354573546.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/115pdc1354573546.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/12udk61354573546.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/1339qe1354573546.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/14xqzc1354573546.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/15fofk1354573546.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/164j5m1354573546.tab")
+ }
>
> try(system("convert tmp/1d48o1354573546.ps tmp/1d48o1354573546.png",intern=TRUE))
character(0)
> try(system("convert tmp/2en2d1354573546.ps tmp/2en2d1354573546.png",intern=TRUE))
character(0)
> try(system("convert tmp/3kvsu1354573546.ps tmp/3kvsu1354573546.png",intern=TRUE))
character(0)
> try(system("convert tmp/4q0011354573546.ps tmp/4q0011354573546.png",intern=TRUE))
character(0)
> try(system("convert tmp/5s16t1354573546.ps tmp/5s16t1354573546.png",intern=TRUE))
character(0)
> try(system("convert tmp/6hktp1354573546.ps tmp/6hktp1354573546.png",intern=TRUE))
character(0)
> try(system("convert tmp/7dd3i1354573546.ps tmp/7dd3i1354573546.png",intern=TRUE))
character(0)
> try(system("convert tmp/8l65f1354573546.ps tmp/8l65f1354573546.png",intern=TRUE))
character(0)
> try(system("convert tmp/9u1081354573546.ps tmp/9u1081354573546.png",intern=TRUE))
character(0)
> try(system("convert tmp/10xrm81354573546.ps tmp/10xrm81354573546.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.716 1.435 7.163