R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
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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
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> x <- array(list(0,467,0,460,0,448,0,443,0,436,0,431,0,484,0,510,1,513,1,503,1,471,1,471,1,476,1,475,1,470,1,461,1,455,1,456,1,517,1,525,1,523,1,519,1,509,1,512,1,519,1,517,1,510,1,509,1,501,1,507,1,569,1,580,1,578,1,565,1,547,1,555),dim=c(2,36),dimnames=list(c('Dummy','Werkloosheid'),1:36))
> y <- array(NA,dim=c(2,36),dimnames=list(c('Dummy','Werkloosheid'),1:36))
> 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'
> #'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
Werkloosheid Dummy
1 467 0
2 460 0
3 448 0
4 443 0
5 436 0
6 431 0
7 484 0
8 510 0
9 513 1
10 503 1
11 471 1
12 471 1
13 476 1
14 475 1
15 470 1
16 461 1
17 455 1
18 456 1
19 517 1
20 525 1
21 523 1
22 519 1
23 509 1
24 512 1
25 519 1
26 517 1
27 510 1
28 509 1
29 501 1
30 507 1
31 569 1
32 580 1
33 578 1
34 565 1
35 547 1
36 555 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy
459.9 51.3
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-56.1786 -25.1250 -0.5268 12.3214 68.8214
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 459.87 12.21 37.672 < 2e-16 ***
Dummy 51.30 13.84 3.706 0.000745 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 34.53 on 34 degrees of freedom
Multiple R-squared: 0.2878, Adjusted R-squared: 0.2668
F-statistic: 13.74 on 1 and 34 DF, p-value: 0.0007446
> 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,] 0.07643545 0.15287090 0.9235645
[2,] 0.05705904 0.11411808 0.9429410
[3,] 0.10310712 0.20621424 0.8968929
[4,] 0.27708092 0.55416183 0.7229191
[5,] 0.17427493 0.34854986 0.8257251
[6,] 0.10543275 0.21086550 0.8945673
[7,] 0.10672155 0.21344309 0.8932785
[8,] 0.08995626 0.17991251 0.9100437
[9,] 0.06503202 0.13006404 0.9349680
[10,] 0.04781843 0.09563685 0.9521816
[11,] 0.04077703 0.08155406 0.9592230
[12,] 0.05108069 0.10216137 0.9489193
[13,] 0.09695126 0.19390252 0.9030487
[14,] 0.22536647 0.45073294 0.7746335
[15,] 0.26492449 0.52984898 0.7350755
[16,] 0.30135499 0.60270998 0.6986450
[17,] 0.29865847 0.59731694 0.7013415
[18,] 0.27131130 0.54262261 0.7286887
[19,] 0.24144423 0.48288846 0.7585558
[20,] 0.21288337 0.42576673 0.7871166
[21,] 0.18207765 0.36415531 0.8179223
[22,] 0.15501827 0.31003654 0.8449817
[23,] 0.14841012 0.29682024 0.8515899
[24,] 0.16528106 0.33056211 0.8347189
[25,] 0.33230541 0.66461082 0.6676946
[26,] 0.84745468 0.30509065 0.1525453
[27,] 0.78366934 0.43266132 0.2163307
> postscript(file="/var/www/html/rcomp/tmp/19wj21230054740.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/28o0c1230054740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3saff1230054740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4yx3v1230054740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5lbo51230054740.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 = 36
Frequency = 1
1 2 3 4 5 6
7.1250000 0.1250000 -11.8750000 -16.8750000 -23.8750000 -28.8750000
7 8 9 10 11 12
24.1250000 50.1250000 1.8214286 -8.1785714 -40.1785714 -40.1785714
13 14 15 16 17 18
-35.1785714 -36.1785714 -41.1785714 -50.1785714 -56.1785714 -55.1785714
19 20 21 22 23 24
5.8214286 13.8214286 11.8214286 7.8214286 -2.1785714 0.8214286
25 26 27 28 29 30
7.8214286 5.8214286 -1.1785714 -2.1785714 -10.1785714 -4.1785714
31 32 33 34 35 36
57.8214286 68.8214286 66.8214286 53.8214286 35.8214286 43.8214286
> postscript(file="/var/www/html/rcomp/tmp/6etvq1230054740.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 = 36
Frequency = 1
lag(myerror, k = 1) myerror
0 7.1250000 NA
1 0.1250000 7.1250000
2 -11.8750000 0.1250000
3 -16.8750000 -11.8750000
4 -23.8750000 -16.8750000
5 -28.8750000 -23.8750000
6 24.1250000 -28.8750000
7 50.1250000 24.1250000
8 1.8214286 50.1250000
9 -8.1785714 1.8214286
10 -40.1785714 -8.1785714
11 -40.1785714 -40.1785714
12 -35.1785714 -40.1785714
13 -36.1785714 -35.1785714
14 -41.1785714 -36.1785714
15 -50.1785714 -41.1785714
16 -56.1785714 -50.1785714
17 -55.1785714 -56.1785714
18 5.8214286 -55.1785714
19 13.8214286 5.8214286
20 11.8214286 13.8214286
21 7.8214286 11.8214286
22 -2.1785714 7.8214286
23 0.8214286 -2.1785714
24 7.8214286 0.8214286
25 5.8214286 7.8214286
26 -1.1785714 5.8214286
27 -2.1785714 -1.1785714
28 -10.1785714 -2.1785714
29 -4.1785714 -10.1785714
30 57.8214286 -4.1785714
31 68.8214286 57.8214286
32 66.8214286 68.8214286
33 53.8214286 66.8214286
34 35.8214286 53.8214286
35 43.8214286 35.8214286
36 NA 43.8214286
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.1250000 7.1250000
[2,] -11.8750000 0.1250000
[3,] -16.8750000 -11.8750000
[4,] -23.8750000 -16.8750000
[5,] -28.8750000 -23.8750000
[6,] 24.1250000 -28.8750000
[7,] 50.1250000 24.1250000
[8,] 1.8214286 50.1250000
[9,] -8.1785714 1.8214286
[10,] -40.1785714 -8.1785714
[11,] -40.1785714 -40.1785714
[12,] -35.1785714 -40.1785714
[13,] -36.1785714 -35.1785714
[14,] -41.1785714 -36.1785714
[15,] -50.1785714 -41.1785714
[16,] -56.1785714 -50.1785714
[17,] -55.1785714 -56.1785714
[18,] 5.8214286 -55.1785714
[19,] 13.8214286 5.8214286
[20,] 11.8214286 13.8214286
[21,] 7.8214286 11.8214286
[22,] -2.1785714 7.8214286
[23,] 0.8214286 -2.1785714
[24,] 7.8214286 0.8214286
[25,] 5.8214286 7.8214286
[26,] -1.1785714 5.8214286
[27,] -2.1785714 -1.1785714
[28,] -10.1785714 -2.1785714
[29,] -4.1785714 -10.1785714
[30,] 57.8214286 -4.1785714
[31,] 68.8214286 57.8214286
[32,] 66.8214286 68.8214286
[33,] 53.8214286 66.8214286
[34,] 35.8214286 53.8214286
[35,] 43.8214286 35.8214286
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.1250000 7.1250000
2 -11.8750000 0.1250000
3 -16.8750000 -11.8750000
4 -23.8750000 -16.8750000
5 -28.8750000 -23.8750000
6 24.1250000 -28.8750000
7 50.1250000 24.1250000
8 1.8214286 50.1250000
9 -8.1785714 1.8214286
10 -40.1785714 -8.1785714
11 -40.1785714 -40.1785714
12 -35.1785714 -40.1785714
13 -36.1785714 -35.1785714
14 -41.1785714 -36.1785714
15 -50.1785714 -41.1785714
16 -56.1785714 -50.1785714
17 -55.1785714 -56.1785714
18 5.8214286 -55.1785714
19 13.8214286 5.8214286
20 11.8214286 13.8214286
21 7.8214286 11.8214286
22 -2.1785714 7.8214286
23 0.8214286 -2.1785714
24 7.8214286 0.8214286
25 5.8214286 7.8214286
26 -1.1785714 5.8214286
27 -2.1785714 -1.1785714
28 -10.1785714 -2.1785714
29 -4.1785714 -10.1785714
30 57.8214286 -4.1785714
31 68.8214286 57.8214286
32 66.8214286 68.8214286
33 53.8214286 66.8214286
34 35.8214286 53.8214286
35 43.8214286 35.8214286
> 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/77agh1230054740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8b4qg1230054740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9bde51230054740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10tmz71230054740.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11h0o01230054740.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/12pb3r1230054740.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/13pp0x1230054740.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/140br41230054741.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/15nrsc1230054741.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/1677i11230054741.tab")
+ }
>
> system("convert tmp/19wj21230054740.ps tmp/19wj21230054740.png")
> system("convert tmp/28o0c1230054740.ps tmp/28o0c1230054740.png")
> system("convert tmp/3saff1230054740.ps tmp/3saff1230054740.png")
> system("convert tmp/4yx3v1230054740.ps tmp/4yx3v1230054740.png")
> system("convert tmp/5lbo51230054740.ps tmp/5lbo51230054740.png")
> system("convert tmp/6etvq1230054740.ps tmp/6etvq1230054740.png")
> system("convert tmp/77agh1230054740.ps tmp/77agh1230054740.png")
> system("convert tmp/8b4qg1230054740.ps tmp/8b4qg1230054740.png")
> system("convert tmp/9bde51230054740.ps tmp/9bde51230054740.png")
> system("convert tmp/10tmz71230054740.ps tmp/10tmz71230054740.png")
>
>
> proc.time()
user system elapsed
2.248 1.564 3.163