R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-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.
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> x <- array(list(12,408,187,-3,5,2,-24,2,1,-11,250,133,1,16,10,17,159,55,10,336,70,28,138,46,-16,97,105,1,1272,321,5,88,17,5,201,104,9,102,35,11,127,76,7,209,103,7,247,178,47,145,31,10,3517,1347,21,27,14,9,101,91,10,2,1,101,5,2,45,100,65,11,34,9,38,1418,418,39,206,82,44,130,117,14,865,137,-5,229,162,-24,1,1,6,229,87,0,17,3,-3,92,16),dim=c(3,33),dimnames=list(c('nr','omzet','Personeel
'),1:33))
> y <- array(NA,dim=c(3,33),dimnames=list(c('nr','omzet','Personeel
'),1:33))
> 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
> 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
nr omzet Personeel\r
1 12 408 187
2 -3 5 2
3 -24 2 1
4 -11 250 133
5 1 16 10
6 17 159 55
7 10 336 70
8 28 138 46
9 -16 97 105
10 1 1272 321
11 5 88 17
12 5 201 104
13 9 102 35
14 11 127 76
15 7 209 103
16 7 247 178
17 47 145 31
18 10 3517 1347
19 21 27 14
20 9 101 91
21 10 2 1
22 101 5 2
23 45 100 65
24 11 34 9
25 38 1418 418
26 39 206 82
27 44 130 117
28 14 865 137
29 -5 229 162
30 -24 1 1
31 6 229 87
32 0 17 3
33 -3 92 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) omzet `Personeel\r`
12.84601 0.01356 -0.03678
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-36.836 -12.966 -3.942 4.020 88.160
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.84601 4.82008 2.665 0.0123 *
omzet 0.01356 0.02800 0.484 0.6316
`Personeel\r` -0.03678 0.07766 -0.474 0.6392
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 24.57 on 30 degrees of freedom
Multiple R-squared: 0.007768, Adjusted R-squared: -0.05838
F-statistic: 0.1174 on 2 and 30 DF, p-value: 0.8896
> 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,] 0.1049850278 0.209970056 0.8950150
[2,] 0.1199183482 0.239836696 0.8800817
[3,] 0.1706523213 0.341304643 0.8293477
[4,] 0.1053255073 0.210651015 0.8946745
[5,] 0.1320015829 0.264003166 0.8679984
[6,] 0.0754231178 0.150846236 0.9245769
[7,] 0.0417861699 0.083572340 0.9582138
[8,] 0.0220851975 0.044170395 0.9779148
[9,] 0.0120974378 0.024194876 0.9879026
[10,] 0.0058021216 0.011604243 0.9941979
[11,] 0.0027182359 0.005436472 0.9972818
[12,] 0.0154945729 0.030989146 0.9845054
[13,] 0.0088506089 0.017701218 0.9911494
[14,] 0.0050661826 0.010132365 0.9949338
[15,] 0.0023734707 0.004746941 0.9976265
[16,] 0.0009759063 0.001951813 0.9990241
[17,] 0.6097782284 0.780443543 0.3902218
[18,] 0.7098933434 0.580213313 0.2901067
[19,] 0.5981188084 0.803762383 0.4018812
[20,] 0.4904736810 0.980947362 0.5095263
[21,] 0.5569168008 0.886166398 0.4430832
[22,] 0.8957134302 0.208573140 0.1042866
> postscript(file="/var/www/rcomp/tmp/19eyj1322149591.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2gpub1322149591.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3jjt31322149591.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4xok11322149591.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5wko61322149591.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 = 33
Frequency = 1
1 2 3 4 5 6
0.4974808 -15.8402767 -36.8363632 -22.3454486 -11.6952506 4.0201304
7 8 9 10 11 12
-4.8290375 14.9739667 -26.2999462 -17.2935540 -8.4144158 -6.7473952
13 14 15 16 17 18
-3.9422927 -0.7734596 -4.8926872 -2.6497038 33.3273337 -1.0098445
19 20 21 22 23 24
8.3026596 -1.8691079 -2.8363632 88.1597233 33.1882037 -1.9761840
25 26 27 28 29 30
21.2936395 26.3756474 33.6937846 -5.5402760 -14.9940125 -36.8227991
31 32 33
-6.7524330 -12.9662673 -16.5054513
> postscript(file="/var/www/rcomp/tmp/673g81322149591.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 = 33
Frequency = 1
lag(myerror, k = 1) myerror
0 0.4974808 NA
1 -15.8402767 0.4974808
2 -36.8363632 -15.8402767
3 -22.3454486 -36.8363632
4 -11.6952506 -22.3454486
5 4.0201304 -11.6952506
6 -4.8290375 4.0201304
7 14.9739667 -4.8290375
8 -26.2999462 14.9739667
9 -17.2935540 -26.2999462
10 -8.4144158 -17.2935540
11 -6.7473952 -8.4144158
12 -3.9422927 -6.7473952
13 -0.7734596 -3.9422927
14 -4.8926872 -0.7734596
15 -2.6497038 -4.8926872
16 33.3273337 -2.6497038
17 -1.0098445 33.3273337
18 8.3026596 -1.0098445
19 -1.8691079 8.3026596
20 -2.8363632 -1.8691079
21 88.1597233 -2.8363632
22 33.1882037 88.1597233
23 -1.9761840 33.1882037
24 21.2936395 -1.9761840
25 26.3756474 21.2936395
26 33.6937846 26.3756474
27 -5.5402760 33.6937846
28 -14.9940125 -5.5402760
29 -36.8227991 -14.9940125
30 -6.7524330 -36.8227991
31 -12.9662673 -6.7524330
32 -16.5054513 -12.9662673
33 NA -16.5054513
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -15.8402767 0.4974808
[2,] -36.8363632 -15.8402767
[3,] -22.3454486 -36.8363632
[4,] -11.6952506 -22.3454486
[5,] 4.0201304 -11.6952506
[6,] -4.8290375 4.0201304
[7,] 14.9739667 -4.8290375
[8,] -26.2999462 14.9739667
[9,] -17.2935540 -26.2999462
[10,] -8.4144158 -17.2935540
[11,] -6.7473952 -8.4144158
[12,] -3.9422927 -6.7473952
[13,] -0.7734596 -3.9422927
[14,] -4.8926872 -0.7734596
[15,] -2.6497038 -4.8926872
[16,] 33.3273337 -2.6497038
[17,] -1.0098445 33.3273337
[18,] 8.3026596 -1.0098445
[19,] -1.8691079 8.3026596
[20,] -2.8363632 -1.8691079
[21,] 88.1597233 -2.8363632
[22,] 33.1882037 88.1597233
[23,] -1.9761840 33.1882037
[24,] 21.2936395 -1.9761840
[25,] 26.3756474 21.2936395
[26,] 33.6937846 26.3756474
[27,] -5.5402760 33.6937846
[28,] -14.9940125 -5.5402760
[29,] -36.8227991 -14.9940125
[30,] -6.7524330 -36.8227991
[31,] -12.9662673 -6.7524330
[32,] -16.5054513 -12.9662673
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -15.8402767 0.4974808
2 -36.8363632 -15.8402767
3 -22.3454486 -36.8363632
4 -11.6952506 -22.3454486
5 4.0201304 -11.6952506
6 -4.8290375 4.0201304
7 14.9739667 -4.8290375
8 -26.2999462 14.9739667
9 -17.2935540 -26.2999462
10 -8.4144158 -17.2935540
11 -6.7473952 -8.4144158
12 -3.9422927 -6.7473952
13 -0.7734596 -3.9422927
14 -4.8926872 -0.7734596
15 -2.6497038 -4.8926872
16 33.3273337 -2.6497038
17 -1.0098445 33.3273337
18 8.3026596 -1.0098445
19 -1.8691079 8.3026596
20 -2.8363632 -1.8691079
21 88.1597233 -2.8363632
22 33.1882037 88.1597233
23 -1.9761840 33.1882037
24 21.2936395 -1.9761840
25 26.3756474 21.2936395
26 33.6937846 26.3756474
27 -5.5402760 33.6937846
28 -14.9940125 -5.5402760
29 -36.8227991 -14.9940125
30 -6.7524330 -36.8227991
31 -12.9662673 -6.7524330
32 -16.5054513 -12.9662673
> 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/rcomp/tmp/72viy1322149591.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/87cyh1322149591.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9rw081322149591.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10mvj61322149591.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11ec9b1322149591.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/rcomp/tmp/120udw1322149591.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/rcomp/tmp/13e13m1322149591.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/rcomp/tmp/145ju81322149591.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/rcomp/tmp/15fc6n1322149591.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/rcomp/tmp/16p54g1322149591.tab")
+ }
>
> try(system("convert tmp/19eyj1322149591.ps tmp/19eyj1322149591.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gpub1322149591.ps tmp/2gpub1322149591.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jjt31322149591.ps tmp/3jjt31322149591.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xok11322149591.ps tmp/4xok11322149591.png",intern=TRUE))
character(0)
> try(system("convert tmp/5wko61322149591.ps tmp/5wko61322149591.png",intern=TRUE))
character(0)
> try(system("convert tmp/673g81322149591.ps tmp/673g81322149591.png",intern=TRUE))
character(0)
> try(system("convert tmp/72viy1322149591.ps tmp/72viy1322149591.png",intern=TRUE))
character(0)
> try(system("convert tmp/87cyh1322149591.ps tmp/87cyh1322149591.png",intern=TRUE))
character(0)
> try(system("convert tmp/9rw081322149591.ps tmp/9rw081322149591.png",intern=TRUE))
character(0)
> try(system("convert tmp/10mvj61322149591.ps tmp/10mvj61322149591.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.420 0.380 4.779