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(85,0,0,82,1,1,97,1,2,132,1,2,120,1,1,95,0,0,100,1,1,106,0,0,108,0,0,140,0,2,141,1,0,123,1,1,115,0,0,103,0,2,96,1,2,91,0,1,85,0,1,89,1,0,109,1,2,111,1,0,93,0,1,94,0,0,98,1,1,108,1,2,118,0,0,117,1,1,94,0,0,102,1,1,114,1,2,99,1,2,87,0,0,90,1,0,125,0,1,143,0,0,141,1,2,133,1,2,126,0,0,124,1,1,97,0,2,100,1,1),dim=c(3,40),dimnames=list(c('IQ','Geslacht','Gewest'),1:40))
> y <- array(NA,dim=c(3,40),dimnames=list(c('IQ','Geslacht','Gewest'),1:40))
> 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
IQ Geslacht Gewest
1 85 0 0
2 82 1 1
3 97 1 2
4 132 1 2
5 120 1 1
6 95 0 0
7 100 1 1
8 106 0 0
9 108 0 0
10 140 0 2
11 141 1 0
12 123 1 1
13 115 0 0
14 103 0 2
15 96 1 2
16 91 0 1
17 85 0 1
18 89 1 0
19 109 1 2
20 111 1 0
21 93 0 1
22 94 0 0
23 98 1 1
24 108 1 2
25 118 0 0
26 117 1 1
27 94 0 0
28 102 1 1
29 114 1 2
30 99 1 2
31 87 0 0
32 90 1 0
33 125 0 1
34 143 0 0
35 141 1 2
36 133 1 2
37 126 0 0
38 124 1 1
39 97 0 2
40 100 1 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Geslacht Gewest
104.282 2.563 2.793
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-27.638 -13.592 -5.649 13.451 38.718
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 104.282 4.637 22.489 <2e-16 ***
Geslacht 2.563 6.129 0.418 0.678
Gewest 2.793 3.727 0.749 0.458
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 17.6 on 37 degrees of freedom
Multiple R-squared: 0.03119, Adjusted R-squared: -0.02118
F-statistic: 0.5956 on 2 and 37 DF, p-value: 0.5564
> 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,] 0.77066141 0.4586772 0.2293386
[2,] 0.63274122 0.7345176 0.3672588
[3,] 0.54742547 0.9051491 0.4525745
[4,] 0.45067051 0.9013410 0.5493295
[5,] 0.40971624 0.8194325 0.5902838
[6,] 0.87334833 0.2533033 0.1266517
[7,] 0.83537951 0.3292410 0.1646205
[8,] 0.78304433 0.4339113 0.2169557
[9,] 0.72253553 0.5549289 0.2774645
[10,] 0.70851247 0.5829751 0.2914875
[11,] 0.68381306 0.6323739 0.3161869
[12,] 0.71737633 0.5652473 0.2826237
[13,] 0.70977104 0.5804579 0.2902290
[14,] 0.62307843 0.7538431 0.3769216
[15,] 0.53208817 0.9358237 0.4679118
[16,] 0.50448924 0.9910215 0.4955108
[17,] 0.44961847 0.8992369 0.5503815
[18,] 0.39105755 0.7821151 0.6089425
[19,] 0.30804693 0.6160939 0.6919531
[20,] 0.26224250 0.5244850 0.7377575
[21,] 0.19563176 0.3912635 0.8043682
[22,] 0.16454619 0.3290924 0.8354538
[23,] 0.11745824 0.2349165 0.8825418
[24,] 0.07277066 0.1455413 0.9272293
[25,] 0.06643685 0.1328737 0.9335631
[26,] 0.09656626 0.1931325 0.9034337
[27,] 0.20407366 0.4081473 0.7959263
[28,] 0.14279942 0.2855988 0.8572006
[29,] 0.22340785 0.4468157 0.7765922
> postscript(file="/var/wessaorg/rcomp/tmp/19ik91356222236.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2caa31356222236.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3t4r41356222236.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/49zv61356222236.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5o17m1356222236.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 = 40
Frequency = 1
1 2 3 4 5 6 7
-19.281752 -27.637990 -15.430835 19.569165 10.362010 -9.281752 -9.637990
8 9 10 11 12 13 14
1.718248 3.718248 30.132556 34.154856 13.362010 10.718248 -6.867444
15 16 17 18 19 20 21
-16.430835 -16.074598 -22.074598 -17.845144 -3.430835 4.154856 -14.074598
22 23 24 25 26 27 28
-10.281752 -11.637990 -4.430835 13.718248 7.362010 -10.281752 -7.637990
29 30 31 32 33 34 35
1.569165 -13.430835 -17.281752 -16.845144 17.925402 38.718248 28.569165
36 37 38 39 40
20.569165 21.718248 14.362010 -12.867444 -9.637990
> postscript(file="/var/wessaorg/rcomp/tmp/6ajey1356222236.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 = 40
Frequency = 1
lag(myerror, k = 1) myerror
0 -19.281752 NA
1 -27.637990 -19.281752
2 -15.430835 -27.637990
3 19.569165 -15.430835
4 10.362010 19.569165
5 -9.281752 10.362010
6 -9.637990 -9.281752
7 1.718248 -9.637990
8 3.718248 1.718248
9 30.132556 3.718248
10 34.154856 30.132556
11 13.362010 34.154856
12 10.718248 13.362010
13 -6.867444 10.718248
14 -16.430835 -6.867444
15 -16.074598 -16.430835
16 -22.074598 -16.074598
17 -17.845144 -22.074598
18 -3.430835 -17.845144
19 4.154856 -3.430835
20 -14.074598 4.154856
21 -10.281752 -14.074598
22 -11.637990 -10.281752
23 -4.430835 -11.637990
24 13.718248 -4.430835
25 7.362010 13.718248
26 -10.281752 7.362010
27 -7.637990 -10.281752
28 1.569165 -7.637990
29 -13.430835 1.569165
30 -17.281752 -13.430835
31 -16.845144 -17.281752
32 17.925402 -16.845144
33 38.718248 17.925402
34 28.569165 38.718248
35 20.569165 28.569165
36 21.718248 20.569165
37 14.362010 21.718248
38 -12.867444 14.362010
39 -9.637990 -12.867444
40 NA -9.637990
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -27.637990 -19.281752
[2,] -15.430835 -27.637990
[3,] 19.569165 -15.430835
[4,] 10.362010 19.569165
[5,] -9.281752 10.362010
[6,] -9.637990 -9.281752
[7,] 1.718248 -9.637990
[8,] 3.718248 1.718248
[9,] 30.132556 3.718248
[10,] 34.154856 30.132556
[11,] 13.362010 34.154856
[12,] 10.718248 13.362010
[13,] -6.867444 10.718248
[14,] -16.430835 -6.867444
[15,] -16.074598 -16.430835
[16,] -22.074598 -16.074598
[17,] -17.845144 -22.074598
[18,] -3.430835 -17.845144
[19,] 4.154856 -3.430835
[20,] -14.074598 4.154856
[21,] -10.281752 -14.074598
[22,] -11.637990 -10.281752
[23,] -4.430835 -11.637990
[24,] 13.718248 -4.430835
[25,] 7.362010 13.718248
[26,] -10.281752 7.362010
[27,] -7.637990 -10.281752
[28,] 1.569165 -7.637990
[29,] -13.430835 1.569165
[30,] -17.281752 -13.430835
[31,] -16.845144 -17.281752
[32,] 17.925402 -16.845144
[33,] 38.718248 17.925402
[34,] 28.569165 38.718248
[35,] 20.569165 28.569165
[36,] 21.718248 20.569165
[37,] 14.362010 21.718248
[38,] -12.867444 14.362010
[39,] -9.637990 -12.867444
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -27.637990 -19.281752
2 -15.430835 -27.637990
3 19.569165 -15.430835
4 10.362010 19.569165
5 -9.281752 10.362010
6 -9.637990 -9.281752
7 1.718248 -9.637990
8 3.718248 1.718248
9 30.132556 3.718248
10 34.154856 30.132556
11 13.362010 34.154856
12 10.718248 13.362010
13 -6.867444 10.718248
14 -16.430835 -6.867444
15 -16.074598 -16.430835
16 -22.074598 -16.074598
17 -17.845144 -22.074598
18 -3.430835 -17.845144
19 4.154856 -3.430835
20 -14.074598 4.154856
21 -10.281752 -14.074598
22 -11.637990 -10.281752
23 -4.430835 -11.637990
24 13.718248 -4.430835
25 7.362010 13.718248
26 -10.281752 7.362010
27 -7.637990 -10.281752
28 1.569165 -7.637990
29 -13.430835 1.569165
30 -17.281752 -13.430835
31 -16.845144 -17.281752
32 17.925402 -16.845144
33 38.718248 17.925402
34 28.569165 38.718248
35 20.569165 28.569165
36 21.718248 20.569165
37 14.362010 21.718248
38 -12.867444 14.362010
39 -9.637990 -12.867444
> 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/wessaorg/rcomp/tmp/73gcs1356222236.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8wns51356222236.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9fxj41356222237.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10ipb41356222237.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1114b71356222237.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/12r4we1356222237.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/13omnr1356222237.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/1473ms1356222237.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/1518g01356222237.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/16l9ko1356222237.tab")
+ }
>
> try(system("convert tmp/19ik91356222236.ps tmp/19ik91356222236.png",intern=TRUE))
character(0)
> try(system("convert tmp/2caa31356222236.ps tmp/2caa31356222236.png",intern=TRUE))
character(0)
> try(system("convert tmp/3t4r41356222236.ps tmp/3t4r41356222236.png",intern=TRUE))
character(0)
> try(system("convert tmp/49zv61356222236.ps tmp/49zv61356222236.png",intern=TRUE))
character(0)
> try(system("convert tmp/5o17m1356222236.ps tmp/5o17m1356222236.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ajey1356222236.ps tmp/6ajey1356222236.png",intern=TRUE))
character(0)
> try(system("convert tmp/73gcs1356222236.ps tmp/73gcs1356222236.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wns51356222236.ps tmp/8wns51356222236.png",intern=TRUE))
character(0)
> try(system("convert tmp/9fxj41356222237.ps tmp/9fxj41356222237.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ipb41356222237.ps tmp/10ipb41356222237.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.955 1.146 7.218