x <- array(list(87.28
,255
,87.28
,280.2
,87.09
,299.9
,86.92
,339.2
,87.59
,374.2
,90.72
,393.5
,90.69
,389.2
,90.3
,381.7
,89.55
,375.2
,88.94
,369
,88.41
,357.4
,87.82
,352.1
,87.07
,346.5
,86.82
,342.9
,86.4
,340.3
,86.02
,328.3
,85.66
,322.9
,85.32
,314.3
,85
,308.9
,84.67
,294
,83.94
,285.6
,82.83
,281.2
,81.95
,280.3
,81.19
,278.8
,80.48
,274.5
,78.86
,270.4
,69.47
,263.4
,68.77
,259.9
,70.06
,258
,73.95
,262.7
,75.8
,284.7
,77.79
,311.3
,81.57
,322.1
,83.07
,327
,84.34
,331.3
,85.1
,333.3
,85.25
,321.4
,84.26
,327
,83.63
,320
,86.44
,314.7
,85.3
,316.7
,84.1
,314.4
,83.36
,321.3
,82.48
,318.2
,81.58
,307.2
,80.47
,301.3
,79.34
,287.5
,82.13
,277.7
,81.69
,274.4
,80.7
,258.8
,79.88
,253.3
,79.16
,251
,78.38
,248.4
,77.42
,249.5
,76.47
,246.1
,75.46
,244.5
,74.48
,243.6
,78.27
,244
,80.7
,240.8
,79.91
,249.8
,78.75
,248
,77.78
,259.4
,81.14
,260.5
,81.08
,260.8
,80.03
,261.3
,78.91
,259.5
,78.01
,256.6
,76.9
,257.9
,75.97
,256.5
,81.93
,254.2
,80.27
,253.3
,78.67
,253.8
,77.42
,255.5
,76.16
,257.1
,74.7
,257.3
,76.39
,253.2
,76.04
,252.8
,74.65
,252
,73.29
,250.7
,71.79
,252.2
,74.39
,250
,74.91
,251
,74.54
,253.4
,73.08
,251.2
,72.75
,255.6
,71.32
,261.1
,70.38
,258.9
,70.35
,259.9
,70.01
,261.2
,69.36
,264.7
,67.77
,267.1
,69.26
,266.4
,69.8
,267.7
,68.38
,268.6
,67.62
,267.5
,68.39
,268.5
,66.95
,268.5
,65.21
,270.5
,66.64
,270.9
,63.45
,270.1
,60.66
,269.3
,62.34
,269.8
,60.32
,270.1
,58.64
,264.9
,60.46
,263.7
,58.59
,264.8
,61.87
,263.7
,61.85
,255.9
,67.44
,276.2
,77.06
,360.1
,91.74
,380.5
,93.15
,373.7
,94.15
,369.8
,93.11
,366.6
,91.51
,359.3
,89.96
,345.8
,88.16
,326.2
,86.98
,324.5
,88.03
,328.1
,86.24
,327.5
,84.65
,324.4
,83.23
,316.5
,81.7
,310.9
,80.25
,301.5
,78.8
,291.7
,77.51
,290.4
,76.2
,287.4
,75.04
,277.7
,74
,281.6
,75.49
,288
,77.14
,276
,76.15
,272.9
,76.27
,283
,78.19
,283.3
,76.49
,276.8
,77.31
,284.5
,76.65
,282.7
,74.99
,281.2
,73.51
,287.4
,72.07
,283.1
,70.59
,284
,71.96
,285.5
,76.29
,289.2
,74.86
,292.5
,74.93
,296.4
,71.9
,305.2
,71.01
,303.9
,77.47
,311.5
,75.78
,316.3
,76.6
,316.7
,76.07
,322.5
,74.57
,317.1
,73.02
,309.8
,72.65
,303.8
,73.16
,290.3
,71.53
,293.7
,69.78
,291.7
,67.98
,296.5
,69.96
,289.1
,72.16
,288.5
,70.47
,293.8
,68.86
,297.7
,67.37
,305.4
,65.87
,302.7
,72.16
,302.5
,71.34
,303
,69.93
,294.5
,68.44
,294.1
,67.16
,294.5
,66.01
,297.1
,67.25
,289.4
,70.91
,292.4
,69.75
,287.9
,68.59
,286.6
,67.48
,280.5
,66.31
,272.4
,64.81
,269.2
,66.58
,270.6
,65.97
,267.3
,64.7
,262.5
,64.7
,266.8
,60.94
,268.8
,59.08
,263.1
,58.42
,261.2
,57.77
,266
,57.11
,262.5
,53.31
,265.2
,49.96
,261.3
,49.4
,253.7
,48.84
,249.2
,48.3
,239.1
,47.74
,236.4
,47.24
,235.2
,46.76
,245.2
,46.29
,246.2
,48.9
,247.7
,49.23
,251.4
,48.53
,253.3
,48.03
,254.8
,54.34
,250
,53.79
,249.3
,53.24
,241.5
,52.96
,243.3
,52.17
,248
,51.7
,253
,58.55
,252.9
,78.2
,251.5
,77.03
,251.6
,76.19
,253.5
,77.15
,259.8
,75.87
,334.1
,95.47
,448
,109.67
,445.8
,112.28
,445
,112.01
,448.2
,107.93
,438.2
,105.96
,439.8
,105.06
,423.4
,102.98
,410.8
,102.2
,408.4
,105.23
,406.7
,101.85
,405.9
,99.89
,402.7
,96.23
,405.1
,94.76
,399.6
,91.51
,386.5
,91.63
,381.4
,91.54
,375.2
,85.23
,357.7
,87.83
,359
,87.38
,355
,84.44
,352.7
,85.19
,344.4
,84.03
,343.8
,86.73
,338
,102.52
,339
,104.45
,333.3
,106.98
,334.4
,107.02
,328.3
,99.26
,330.7
,94.45
,330
,113.44
,331.6
,157.33
,351.2
,147.38
,389.4
,171.89
,410.9
,171.95
,442.8
,132.71
,462.8
,126.02
,466.9
,121.18
,461.7
,115.45
,439.2
,110.48
,430.3
,117.85
,416.1
,117.63
,402.5
,124.65
,397.3
,109.59
,403.3
,111.27
,395.9
,99.78
,387.8
,98.21
,378.6
,99.2
,377.1
,97.97
,370.4
,89.55
,362
,87.91
,350.3
,93.34
,348.2
,94.42
,344.6
,93.2
,343.5
,90.29
,342.8
,91.46
,347.6
,89.98
,346.6
,88.35
,349.5
,88.41
,342.1
,82.44
,342
,79.89
,342.8
,75.69
,339.3
,75.66
,348.2
,84.5
,333.7
,96.73
,334.7
,87.48
,354
,82.39
,367.7
,83.48
,363.3
,79.31
,358.4
,78.16
,353.1
,72.77
,343.1
,72.45
,344.6
,68.46
,344.4
,67.62
,333.9
,68.76
,331.7
,70.07
,324.3
,68.55
,321.2
,65.3
,322.4
,58.96
,321.7
,59.17
,320.5
,62.37
,312.8
,66.28
,309.7
,55.62
,315.6
,55.23
,309.7
,55.85
,304.6
,56.75
,302.5
,50.89
,301.5
,53.88
,298.8
,52.95
,291.3
,55.08
,293.6
,53.61
,294.6
,58.78
,285.9
,61.85
,297.6
,55.91
,301.1
,53.32
,293.8
,46.41
,297.7
,44.57
,292.9
,50
,292.1
,50
,287.2
,53.36
,288.2
,46.23
,283.8
,50.45
,299.9
,49.07
,292.4
,45.85
,293.3
,48.45
,300.8
,49.96
,293.7
,46.53
,293.1
,50.51
,294.4
,47.58
,292.1
,48.05
,291.9
,46.84
,282.5
,47.67
,277.9
,49.16
,287.5
,55.54
,289.2
,55.82
,285.6
,58.22
,293.2
,56.19
,290.8
,57.77
,283.1
,63.19
,275
,54.76
,287.8
,55.74
,287.8
,62.54
,287.4
,61.39
,284
,69.6
,277.8
,79.23
,277.6
,80
,304.9
,93.68
,294
,107.63
,300.9
,100.18
,324
,97.3
,332.9
,90.45
,341.6
,80.64
,333.4
,80.58
,348.2
,75.82
,344.7
,85.59
,344.7
,89.35
,329.3
,89.42
,323.5
,104.73
,323.2
,95.32
,317.4
,89.27
,330.1
,90.44
,329.2
,86.97
,334.9
,79.98
,315.8
,81.22
,315.4
,87.35
,319.6
,83.64
,317.3
,82.22
,313.8
,94.4
,315.8
,102.18
,311.3)
,dim=c(2
,360)
,dimnames=list(c('Colombia'
,'USA')
,1:360))
y <- array(NA,dim=c(2,360),dimnames=list(c('Colombia','USA'),1:360))
for (i in 1:dim(x)[1])
{
for (j in 1:dim(x)[2])
{
y[i,j] <- as.numeric(x[i,j])
}
}
par3 = 'Linear Trend'
par2 = 'Do not include Seasonal Dummies'
par1 = '2'
par3 <- '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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
#Source of accompanying publication: Office for Research, Development, and Education
#Technical description: Write here your technical program description (don't use hard returns!)
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$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/wessaorg/rcomp/tmp/1abne1353408305.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$resid)
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/2b3gx1353408305.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/3g5gs1353408305.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/4ekel1353408305.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/515ut1353408305.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$resid))
postscript(file="/var/wessaorg/rcomp/tmp/6c4jw1353408305.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/7pa121353408305.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/8v5t71353408305.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/9zsnl1353408305.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
postscript(file="/var/wessaorg/rcomp/tmp/10cx5u1353408305.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
#Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
load(file="/var/wessaorg/rcomp/createtable")
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$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/wessaorg/rcomp/tmp/11rcsm1353408305.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/wessaorg/rcomp/tmp/12udxm1353408305.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/wessaorg/rcomp/tmp/13qczi1353408305.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/wessaorg/rcomp/tmp/14rqqe1353408305.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/wessaorg/rcomp/tmp/15630s1353408305.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/wessaorg/rcomp/tmp/16fmna1353408305.tab")
}
try(system("convert tmp/1abne1353408305.ps tmp/1abne1353408305.png",intern=TRUE))
try(system("convert tmp/2b3gx1353408305.ps tmp/2b3gx1353408305.png",intern=TRUE))
try(system("convert tmp/3g5gs1353408305.ps tmp/3g5gs1353408305.png",intern=TRUE))
try(system("convert tmp/4ekel1353408305.ps tmp/4ekel1353408305.png",intern=TRUE))
try(system("convert tmp/515ut1353408305.ps tmp/515ut1353408305.png",intern=TRUE))
try(system("convert tmp/6c4jw1353408305.ps tmp/6c4jw1353408305.png",intern=TRUE))
try(system("convert tmp/7pa121353408305.ps tmp/7pa121353408305.png",intern=TRUE))
try(system("convert tmp/8v5t71353408305.ps tmp/8v5t71353408305.png",intern=TRUE))
try(system("convert tmp/9zsnl1353408305.ps tmp/9zsnl1353408305.png",intern=TRUE))
try(system("convert tmp/10cx5u1353408305.ps tmp/10cx5u1353408305.png",intern=TRUE))