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.
R is a collaborative project with many contributors.
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(95,2768,252,22,324,8760219,438465.0625,150,4108,333,29,308,8760195,438474.0625,4,4045,62,5,249,8760168,438480.0625,0,4572,85,8,14,8760135,438489.0625,0,4614,115,10,63,8760105,438495.0625,80,4321,176,16,130,8760072,438498.0625,95,3886,72,6,199,8760039,438504.0625,20,4206,57,5,32,8760012,438507.0625,90,4192,266,23,197,8759985,438513.0625,10,4051,69,6,113,8759955,4385190625,10,3746,62,5,149,8759922,438519.0625,50,3789,42,3,218,8759895,438525.0625,45,3771,44,4,53,8759865,438531.0625,60,3796,48,4,101,8759838,438534.0625,55,3885,77,7,332,8759811,438537.0625,3,4295,113,10,18,8759787,438540.0625,33,4467,147,13,50,8759760,438546.0625,0,4764,12,1,276,8759730,438552.0625,35,4313,38,3,350,8759703,438552.0625,45,4387,40,3,46,8759673,438558.0625),dim=c(7,20),dimnames=list(c('Sneeuwhoogte','hoogte(berg)','ruwheid','helling','Orientering','breedtegraad','lengte'),1:20))
> y <- array(NA,dim=c(7,20),dimnames=list(c('Sneeuwhoogte','hoogte(berg)','ruwheid','helling','Orientering','breedtegraad','lengte'),1:20))
> 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)
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
Sneeuwhoogte hoogte(berg) ruwheid helling Orientering breedtegraad
1 95 2768 252 22 324 8760219
2 150 4108 333 29 308 8760195
3 4 4045 62 5 249 8760168
4 0 4572 85 8 14 8760135
5 0 4614 115 10 63 8760105
6 80 4321 176 16 130 8760072
7 95 3886 72 6 199 8760039
8 20 4206 57 5 32 8760012
9 90 4192 266 23 197 8759985
10 10 4051 69 6 113 8759955
11 10 3746 62 5 149 8759922
12 50 3789 42 3 218 8759895
13 45 3771 44 4 53 8759865
14 60 3796 48 4 101 8759838
15 55 3885 77 7 332 8759811
16 3 4295 113 10 18 8759787
17 33 4467 147 13 50 8759760
18 0 4764 12 1 276 8759730
19 35 4313 38 3 350 8759703
20 45 4387 40 3 46 8759673
lengte
1 438465.1
2 438474.1
3 438480.1
4 438489.1
5 438495.1
6 438498.1
7 438504.1
8 438507.1
9 438513.1
10 4385190625.0
11 438519.1
12 438525.1
13 438531.1
14 438534.1
15 438537.1
16 438540.1
17 438546.1
18 438552.1
19 438552.1
20 438558.1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `hoogte(berg)` ruwheid helling Orientering
3.336e+05 -2.437e-02 9.202e-01 -6.776e+00 6.229e-02
breedtegraad lengte
-3.807e-02 -4.678e-09
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-35.430 -17.212 -2.643 18.689 55.548
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.336e+05 4.384e+05 0.761 0.460
`hoogte(berg)` -2.437e-02 1.802e-02 -1.352 0.199
ruwheid 9.202e-01 2.037e+00 0.452 0.659
helling -6.776e+00 2.304e+01 -0.294 0.773
Orientering 6.229e-02 6.746e-02 0.923 0.373
breedtegraad -3.807e-02 5.005e-02 -0.761 0.460
lengte -4.678e-09 7.017e-09 -0.667 0.517
Residual standard error: 29.58 on 13 degrees of freedom
Multiple R-squared: 0.6493, Adjusted R-squared: 0.4874
F-statistic: 4.011 on 6 and 13 DF, p-value: 0.01707
> 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/1941e1352109808.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/23lcz1352109808.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3se5l1352109808.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/4lqoo1352109808.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/5af9b1352109808.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 = 20
Frequency = 1
1 2 3 4 5
-2.984654e+01 3.078608e+01 -2.735458e+01 -5.968316e+00 -2.319273e+01
6 7 8 9 10
2.876236e+01 5.554799e+01 4.746320e+00 -7.251667e+00 -7.798778e-08
11 12 13 14 15
-3.177778e+01 8.796240e+00 1.742815e+01 2.533896e+01 7.344221e-01
16 17 18 19 20
-3.542975e+01 -1.521798e+01 -1.328551e+01 -5.285513e+00 2.246984e+01
> postscript(file="/var/fisher/rcomp/tmp/673ez1352109808.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 = 20
Frequency = 1
lag(myerror, k = 1) myerror
0 -2.984654e+01 NA
1 3.078608e+01 -2.984654e+01
2 -2.735458e+01 3.078608e+01
3 -5.968316e+00 -2.735458e+01
4 -2.319273e+01 -5.968316e+00
5 2.876236e+01 -2.319273e+01
6 5.554799e+01 2.876236e+01
7 4.746320e+00 5.554799e+01
8 -7.251667e+00 4.746320e+00
9 -7.798778e-08 -7.251667e+00
10 -3.177778e+01 -7.798778e-08
11 8.796240e+00 -3.177778e+01
12 1.742815e+01 8.796240e+00
13 2.533896e+01 1.742815e+01
14 7.344221e-01 2.533896e+01
15 -3.542975e+01 7.344221e-01
16 -1.521798e+01 -3.542975e+01
17 -1.328551e+01 -1.521798e+01
18 -5.285513e+00 -1.328551e+01
19 2.246984e+01 -5.285513e+00
20 NA 2.246984e+01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 3.078608e+01 -2.984654e+01
[2,] -2.735458e+01 3.078608e+01
[3,] -5.968316e+00 -2.735458e+01
[4,] -2.319273e+01 -5.968316e+00
[5,] 2.876236e+01 -2.319273e+01
[6,] 5.554799e+01 2.876236e+01
[7,] 4.746320e+00 5.554799e+01
[8,] -7.251667e+00 4.746320e+00
[9,] -7.798778e-08 -7.251667e+00
[10,] -3.177778e+01 -7.798778e-08
[11,] 8.796240e+00 -3.177778e+01
[12,] 1.742815e+01 8.796240e+00
[13,] 2.533896e+01 1.742815e+01
[14,] 7.344221e-01 2.533896e+01
[15,] -3.542975e+01 7.344221e-01
[16,] -1.521798e+01 -3.542975e+01
[17,] -1.328551e+01 -1.521798e+01
[18,] -5.285513e+00 -1.328551e+01
[19,] 2.246984e+01 -5.285513e+00
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 3.078608e+01 -2.984654e+01
2 -2.735458e+01 3.078608e+01
3 -5.968316e+00 -2.735458e+01
4 -2.319273e+01 -5.968316e+00
5 2.876236e+01 -2.319273e+01
6 5.554799e+01 2.876236e+01
7 4.746320e+00 5.554799e+01
8 -7.251667e+00 4.746320e+00
9 -7.798778e-08 -7.251667e+00
10 -3.177778e+01 -7.798778e-08
11 8.796240e+00 -3.177778e+01
12 1.742815e+01 8.796240e+00
13 2.533896e+01 1.742815e+01
14 7.344221e-01 2.533896e+01
15 -3.542975e+01 7.344221e-01
16 -1.521798e+01 -3.542975e+01
17 -1.328551e+01 -1.521798e+01
18 -5.285513e+00 -1.328551e+01
19 2.246984e+01 -5.285513e+00
> 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/7c8zf1352109808.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/8otrb1352109808.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/fisher/rcomp/tmp/9cbjh1352109808.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: Not plotting observations with leverage one:
10
2: Not plotting observations with leverage one:
10
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/fisher/rcomp/tmp/10sfcf1352109808.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1160ws1352109809.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/128eau1352109809.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/132ot21352109809.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/14rgzm1352109809.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/15luyg1352109809.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/16n17n1352109809.tab")
+ }
>
> try(system("convert tmp/1941e1352109808.ps tmp/1941e1352109808.png",intern=TRUE))
character(0)
> try(system("convert tmp/23lcz1352109808.ps tmp/23lcz1352109808.png",intern=TRUE))
character(0)
> try(system("convert tmp/3se5l1352109808.ps tmp/3se5l1352109808.png",intern=TRUE))
character(0)
> try(system("convert tmp/4lqoo1352109808.ps tmp/4lqoo1352109808.png",intern=TRUE))
character(0)
> try(system("convert tmp/5af9b1352109808.ps tmp/5af9b1352109808.png",intern=TRUE))
character(0)
> try(system("convert tmp/673ez1352109808.ps tmp/673ez1352109808.png",intern=TRUE))
character(0)
> try(system("convert tmp/7c8zf1352109808.ps tmp/7c8zf1352109808.png",intern=TRUE))
character(0)
> try(system("convert tmp/8otrb1352109808.ps tmp/8otrb1352109808.png",intern=TRUE))
character(0)
> try(system("convert tmp/9cbjh1352109808.ps tmp/9cbjh1352109808.png",intern=TRUE))
character(0)
> try(system("convert tmp/10sfcf1352109808.ps tmp/10sfcf1352109808.png",intern=TRUE))
convert: unable to open image `tmp/10sfcf1352109808.ps': @ error/blob.c/OpenBlob/2587.
convert: missing an image filename `tmp/10sfcf1352109808.png' @ error/convert.c/ConvertImageCommand/3011.
character(0)
attr(,"status")
[1] 1
Warning message:
running command 'convert tmp/10sfcf1352109808.ps tmp/10sfcf1352109808.png' had status 1
>
>
> proc.time()
user system elapsed
4.925 0.969 5.898