R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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(31.53,1.70,48.86,58.68,2.00,38.94,1.64,50.81,60.54,2.78,31.51,1.49,50.30,60.45,3.19,29.54,1.77,48.45,57.82,2.69,25.20,2.12,45.71,55.26,2.50,22.90,1.92,43.66,51.77,2.35,23.95,1.69,47.58,54.47,2.39,28.26,2.76,49.54,56.68,2.46,25.52,2.53,45.53,55.51,2.64,16.74,2.08,40.51,50.76,2.32,23.14,2.27,35.74,42.83,1.88,35.50,4.23,34.58,39.69,2.89,29.61,4.07,37.96,41.33,3.66,29.84,3.33,36.90,42.01,3.23,33.62,5.63,34.74,41.57,4.06,43.46,5.85,51.34,60.96,4.32,59.89,8.79,62.91,89.33,5.88,69.32,6.76,63.04,93.46,7.85,74.90,6.95,69.86,88.24,8.03,96.91,8.85,122.81,179.03,11.56,61.67,3.89,110.11,167.82,8.52),dim=c(5,21),dimnames=list(c('Crudeoilnnected','Naturalgas','steamcoal','cokingcoal','LNG'),1:21))
> y <- array(NA,dim=c(5,21),dimnames=list(c('Crudeoilnnected','Naturalgas','steamcoal','cokingcoal','LNG'),1:21))
> 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'
> #'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.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
Crudeoilnnected Naturalgas steamcoal cokingcoal LNG
1 31.53 1.70 48.86 58.68 2.00
2 38.94 1.64 50.81 60.54 2.78
3 31.51 1.49 50.30 60.45 3.19
4 29.54 1.77 48.45 57.82 2.69
5 25.20 2.12 45.71 55.26 2.50
6 22.90 1.92 43.66 51.77 2.35
7 23.95 1.69 47.58 54.47 2.39
8 28.26 2.76 49.54 56.68 2.46
9 25.52 2.53 45.53 55.51 2.64
10 16.74 2.08 40.51 50.76 2.32
11 23.14 2.27 35.74 42.83 1.88
12 35.50 4.23 34.58 39.69 2.89
13 29.61 4.07 37.96 41.33 3.66
14 29.84 3.33 36.90 42.01 3.23
15 33.62 5.63 34.74 41.57 4.06
16 43.46 5.85 51.34 60.96 4.32
17 59.89 8.79 62.91 89.33 5.88
18 69.32 6.76 63.04 93.46 7.85
19 74.90 6.95 69.86 88.24 8.03
20 96.91 8.85 122.81 179.03 11.56
21 61.67 3.89 110.11 167.82 8.52
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Naturalgas steamcoal cokingcoal LNG
-4.8475 1.9439 0.8603 -0.4785 5.7066
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7.221 -2.716 -1.404 2.593 9.991
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -4.8475 6.7810 -0.715 0.4850
Naturalgas 1.9439 1.0847 1.792 0.0920 .
steamcoal 0.8603 0.4618 1.863 0.0809 .
cokingcoal -0.4785 0.2845 -1.682 0.1120
LNG 5.7066 1.7841 3.198 0.0056 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.172 on 16 degrees of freedom
Multiple R-squared: 0.9506, Adjusted R-squared: 0.9382
F-statistic: 76.92 on 4 and 16 DF, p-value: 3.066e-10
> 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/www/html/rcomp/tmp/1hmfm1290537302.ps",horizontal=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2hmfm1290537302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3hmfm1290537302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4sde71290537302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5sde71290537302.ps",horizontal=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 = 21
Frequency = 1
1 2 3 4 5 6 7
7.7030327 9.9909627 0.9085465 1.5806688 -1.2231681 -2.1846884 -2.9962877
8 9 10 11 12 13 14
-1.7944689 -2.2246215 -6.2578811 2.5929267 4.8747619 -7.2213208 -1.8617443
15 16 17 18 19 20 21
-5.6415023 -2.7160031 2.7174377 6.7159348 2.5346505 -1.4044525 -4.0927839
> postscript(file="/var/www/html/rcomp/tmp/62nea1290537302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 21
Frequency = 1
lag(myerror, k = 1) myerror
0 7.7030327 NA
1 9.9909627 7.7030327
2 0.9085465 9.9909627
3 1.5806688 0.9085465
4 -1.2231681 1.5806688
5 -2.1846884 -1.2231681
6 -2.9962877 -2.1846884
7 -1.7944689 -2.9962877
8 -2.2246215 -1.7944689
9 -6.2578811 -2.2246215
10 2.5929267 -6.2578811
11 4.8747619 2.5929267
12 -7.2213208 4.8747619
13 -1.8617443 -7.2213208
14 -5.6415023 -1.8617443
15 -2.7160031 -5.6415023
16 2.7174377 -2.7160031
17 6.7159348 2.7174377
18 2.5346505 6.7159348
19 -1.4044525 2.5346505
20 -4.0927839 -1.4044525
21 NA -4.0927839
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 9.9909627 7.7030327
[2,] 0.9085465 9.9909627
[3,] 1.5806688 0.9085465
[4,] -1.2231681 1.5806688
[5,] -2.1846884 -1.2231681
[6,] -2.9962877 -2.1846884
[7,] -1.7944689 -2.9962877
[8,] -2.2246215 -1.7944689
[9,] -6.2578811 -2.2246215
[10,] 2.5929267 -6.2578811
[11,] 4.8747619 2.5929267
[12,] -7.2213208 4.8747619
[13,] -1.8617443 -7.2213208
[14,] -5.6415023 -1.8617443
[15,] -2.7160031 -5.6415023
[16,] 2.7174377 -2.7160031
[17,] 6.7159348 2.7174377
[18,] 2.5346505 6.7159348
[19,] -1.4044525 2.5346505
[20,] -4.0927839 -1.4044525
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 9.9909627 7.7030327
2 0.9085465 9.9909627
3 1.5806688 0.9085465
4 -1.2231681 1.5806688
5 -2.1846884 -1.2231681
6 -2.9962877 -2.1846884
7 -1.7944689 -2.9962877
8 -2.2246215 -1.7944689
9 -6.2578811 -2.2246215
10 2.5929267 -6.2578811
11 4.8747619 2.5929267
12 -7.2213208 4.8747619
13 -1.8617443 -7.2213208
14 -5.6415023 -1.8617443
15 -2.7160031 -5.6415023
16 2.7174377 -2.7160031
17 6.7159348 2.7174377
18 2.5346505 6.7159348
19 -1.4044525 2.5346505
20 -4.0927839 -1.4044525
> 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/www/html/rcomp/tmp/7dwvd1290537302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8dwvd1290537302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9dwvd1290537302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/106nuf1290537302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/www/html/rcomp/tmp/119ob31290537302.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/www/html/rcomp/tmp/12do9r1290537302.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/www/html/rcomp/tmp/139y7i1290537302.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/www/html/rcomp/tmp/14chno1290537302.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/www/html/rcomp/tmp/15yhmu1290537302.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/www/html/rcomp/tmp/16trj21290537302.tab")
+ }
>
> try(system("convert tmp/1hmfm1290537302.ps tmp/1hmfm1290537302.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hmfm1290537302.ps tmp/2hmfm1290537302.png",intern=TRUE))
character(0)
> try(system("convert tmp/3hmfm1290537302.ps tmp/3hmfm1290537302.png",intern=TRUE))
character(0)
> try(system("convert tmp/4sde71290537302.ps tmp/4sde71290537302.png",intern=TRUE))
character(0)
> try(system("convert tmp/5sde71290537302.ps tmp/5sde71290537302.png",intern=TRUE))
character(0)
> try(system("convert tmp/62nea1290537302.ps tmp/62nea1290537302.png",intern=TRUE))
character(0)
> try(system("convert tmp/7dwvd1290537302.ps tmp/7dwvd1290537302.png",intern=TRUE))
character(0)
> try(system("convert tmp/8dwvd1290537302.ps tmp/8dwvd1290537302.png",intern=TRUE))
character(0)
> try(system("convert tmp/9dwvd1290537302.ps tmp/9dwvd1290537302.png",intern=TRUE))
character(0)
> try(system("convert tmp/106nuf1290537302.ps tmp/106nuf1290537302.png",intern=TRUE))
convert: unable to open image `tmp/106nuf1290537302.ps': No such file or directory.
convert: missing an image filename `tmp/106nuf1290537302.png'.
character(0)
>
>
> proc.time()
user system elapsed
1.988 1.425 5.114