R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-redhat-linux-gnu (64-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
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Type 'q()' to quit R.
> x <- array(list(-6,-18,5,-3,-14,0,-3,-12,-2,-7,-17,6,-9,-23,11,-11,-28,9,-13,-31,17,-11,-21,21,-9,-19,21,-17,-22,41,-22,-22,57,-25,-25,65,-20,-16,68,-24,-22,73,-24,-21,71,-22,-10,71,-19,-7,70,-18,-5,69,-17,-4,65,-11,7,57,-11,6,57,-12,3,57,-10,10,55,-15,0,65,-15,-2,65,-15,-1,64,-13,2,60,-8,8,43,-13,-6,47,-9,-4,40,-7,4,31,-4,7,27,-4,3,24,-2,3,23,0,8,17,-2,3,16),dim=c(3,36),dimnames=list(c('IndVertr','EcoSit','werkl
'),1:36))
> y <- array(NA,dim=c(3,36),dimnames=list(c('IndVertr','EcoSit','werkl
'),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 = '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
IndVertr EcoSit werkl\r
1 -6 -18 5
2 -3 -14 0
3 -3 -12 -2
4 -7 -17 6
5 -9 -23 11
6 -11 -28 9
7 -13 -31 17
8 -11 -21 21
9 -9 -19 21
10 -17 -22 41
11 -22 -22 57
12 -25 -25 65
13 -20 -16 68
14 -24 -22 73
15 -24 -21 71
16 -22 -10 71
17 -19 -7 70
18 -18 -5 69
19 -17 -4 65
20 -11 7 57
21 -11 6 57
22 -12 3 57
23 -10 10 55
24 -15 0 65
25 -15 -2 65
26 -15 -1 64
27 -13 2 60
28 -8 8 43
29 -13 -6 47
30 -9 -4 40
31 -7 4 31
32 -4 7 27
33 -4 3 24
34 -2 3 23
35 0 8 17
36 -2 3 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) EcoSit `werkl\r`
1.2368 0.3364 -0.2553
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.74925 -0.53122 0.02241 0.41804 1.62524
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.236846 0.320265 3.862 0.000497 ***
EcoSit 0.336359 0.012263 27.430 < 2e-16 ***
`werkl\r` -0.255268 0.006086 -41.941 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.8689 on 33 degrees of freedom
Multiple R-squared: 0.985, Adjusted R-squared: 0.9841
F-statistic: 1081 on 2 and 33 DF, p-value: < 2.2e-16
> 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,] 0.4436280 0.8872560 0.5563720
[2,] 0.3078783 0.6157567 0.6921217
[3,] 0.1832465 0.3664931 0.8167535
[4,] 0.2334427 0.4668854 0.7665573
[5,] 0.3684797 0.7369594 0.6315203
[6,] 0.4415845 0.8831690 0.5584155
[7,] 0.4478647 0.8957294 0.5521353
[8,] 0.7510429 0.4979143 0.2489571
[9,] 0.7125905 0.5748190 0.2874095
[10,] 0.6168560 0.7662879 0.3831440
[11,] 0.8698129 0.2603743 0.1301871
[12,] 0.8252340 0.3495319 0.1747660
[13,] 0.7664634 0.4670732 0.2335366
[14,] 0.7348598 0.5302804 0.2651402
[15,] 0.6445230 0.7109540 0.3554770
[16,] 0.5683449 0.8633102 0.4316551
[17,] 0.4721045 0.9442089 0.5278955
[18,] 0.3773026 0.7546052 0.6226974
[19,] 0.2853321 0.5706643 0.7146679
[20,] 0.2710749 0.5421498 0.7289251
[21,] 0.1981431 0.3962861 0.8018569
[22,] 0.2027865 0.4055730 0.7972135
[23,] 0.1754563 0.3509125 0.8245437
[24,] 0.1239029 0.2478058 0.8760971
[25,] 0.1475480 0.2950961 0.8524520
> postscript(file="/var/www/wessaorg/rcomp/tmp/14o941294765872.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/2f1wu1294765872.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/wessaorg/rcomp/tmp/3a3w71294765872.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/4vk101294765872.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/5rb9v1294765872.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 = 36
Frequency = 1
1 2 3 4 5 6
0.09394946 0.47217588 -0.71107703 -0.98714151 0.30734949 -0.52139244
7 8 9 10 11 12
0.52982566 0.18730950 1.51459207 -0.37097690 -1.28669300 -1.23547490
13 14 15 16 17 18
1.50309991 0.79759091 -0.04930329 -1.74924914 -0.01359302 0.05842181
19 20 21 22 23 24
-0.29900788 -0.04109568 0.29526303 0.30433917 -0.56070731 0.35555726
25 26 27 28 29 30
1.02827469 0.43664823 0.40650112 -0.95120281 -0.22110985 1.31929851
31 32 33 34 35 36
-1.66898089 -0.69912801 -0.11949639 1.62523587 0.41183584 -0.16163834
> postscript(file="/var/www/wessaorg/rcomp/tmp/6f4pp1294765872.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 = 36
Frequency = 1
lag(myerror, k = 1) myerror
0 0.09394946 NA
1 0.47217588 0.09394946
2 -0.71107703 0.47217588
3 -0.98714151 -0.71107703
4 0.30734949 -0.98714151
5 -0.52139244 0.30734949
6 0.52982566 -0.52139244
7 0.18730950 0.52982566
8 1.51459207 0.18730950
9 -0.37097690 1.51459207
10 -1.28669300 -0.37097690
11 -1.23547490 -1.28669300
12 1.50309991 -1.23547490
13 0.79759091 1.50309991
14 -0.04930329 0.79759091
15 -1.74924914 -0.04930329
16 -0.01359302 -1.74924914
17 0.05842181 -0.01359302
18 -0.29900788 0.05842181
19 -0.04109568 -0.29900788
20 0.29526303 -0.04109568
21 0.30433917 0.29526303
22 -0.56070731 0.30433917
23 0.35555726 -0.56070731
24 1.02827469 0.35555726
25 0.43664823 1.02827469
26 0.40650112 0.43664823
27 -0.95120281 0.40650112
28 -0.22110985 -0.95120281
29 1.31929851 -0.22110985
30 -1.66898089 1.31929851
31 -0.69912801 -1.66898089
32 -0.11949639 -0.69912801
33 1.62523587 -0.11949639
34 0.41183584 1.62523587
35 -0.16163834 0.41183584
36 NA -0.16163834
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.47217588 0.09394946
[2,] -0.71107703 0.47217588
[3,] -0.98714151 -0.71107703
[4,] 0.30734949 -0.98714151
[5,] -0.52139244 0.30734949
[6,] 0.52982566 -0.52139244
[7,] 0.18730950 0.52982566
[8,] 1.51459207 0.18730950
[9,] -0.37097690 1.51459207
[10,] -1.28669300 -0.37097690
[11,] -1.23547490 -1.28669300
[12,] 1.50309991 -1.23547490
[13,] 0.79759091 1.50309991
[14,] -0.04930329 0.79759091
[15,] -1.74924914 -0.04930329
[16,] -0.01359302 -1.74924914
[17,] 0.05842181 -0.01359302
[18,] -0.29900788 0.05842181
[19,] -0.04109568 -0.29900788
[20,] 0.29526303 -0.04109568
[21,] 0.30433917 0.29526303
[22,] -0.56070731 0.30433917
[23,] 0.35555726 -0.56070731
[24,] 1.02827469 0.35555726
[25,] 0.43664823 1.02827469
[26,] 0.40650112 0.43664823
[27,] -0.95120281 0.40650112
[28,] -0.22110985 -0.95120281
[29,] 1.31929851 -0.22110985
[30,] -1.66898089 1.31929851
[31,] -0.69912801 -1.66898089
[32,] -0.11949639 -0.69912801
[33,] 1.62523587 -0.11949639
[34,] 0.41183584 1.62523587
[35,] -0.16163834 0.41183584
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.47217588 0.09394946
2 -0.71107703 0.47217588
3 -0.98714151 -0.71107703
4 0.30734949 -0.98714151
5 -0.52139244 0.30734949
6 0.52982566 -0.52139244
7 0.18730950 0.52982566
8 1.51459207 0.18730950
9 -0.37097690 1.51459207
10 -1.28669300 -0.37097690
11 -1.23547490 -1.28669300
12 1.50309991 -1.23547490
13 0.79759091 1.50309991
14 -0.04930329 0.79759091
15 -1.74924914 -0.04930329
16 -0.01359302 -1.74924914
17 0.05842181 -0.01359302
18 -0.29900788 0.05842181
19 -0.04109568 -0.29900788
20 0.29526303 -0.04109568
21 0.30433917 0.29526303
22 -0.56070731 0.30433917
23 0.35555726 -0.56070731
24 1.02827469 0.35555726
25 0.43664823 1.02827469
26 0.40650112 0.43664823
27 -0.95120281 0.40650112
28 -0.22110985 -0.95120281
29 1.31929851 -0.22110985
30 -1.66898089 1.31929851
31 -0.69912801 -1.66898089
32 -0.11949639 -0.69912801
33 1.62523587 -0.11949639
34 0.41183584 1.62523587
35 -0.16163834 0.41183584
> 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/wessaorg/rcomp/tmp/7r0ee1294765872.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/8lova1294765872.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/9ldc21294765872.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/wessaorg/rcomp/tmp/107b0d1294765872.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/www/wessaorg/rcomp/tmp/118vf11294765872.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/wessaorg/rcomp/tmp/12on8q1294765872.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/wessaorg/rcomp/tmp/13dh771294765872.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/wessaorg/rcomp/tmp/14k9gx1294765872.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/wessaorg/rcomp/tmp/154s5m1294765872.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/wessaorg/rcomp/tmp/16oowl1294765872.tab")
+ }
>
> try(system("convert tmp/14o941294765872.ps tmp/14o941294765872.png",intern=TRUE))
character(0)
> try(system("convert tmp/2f1wu1294765872.ps tmp/2f1wu1294765872.png",intern=TRUE))
character(0)
> try(system("convert tmp/3a3w71294765872.ps tmp/3a3w71294765872.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vk101294765872.ps tmp/4vk101294765872.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rb9v1294765872.ps tmp/5rb9v1294765872.png",intern=TRUE))
character(0)
> try(system("convert tmp/6f4pp1294765872.ps tmp/6f4pp1294765872.png",intern=TRUE))
character(0)
> try(system("convert tmp/7r0ee1294765872.ps tmp/7r0ee1294765872.png",intern=TRUE))
character(0)
> try(system("convert tmp/8lova1294765872.ps tmp/8lova1294765872.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ldc21294765872.ps tmp/9ldc21294765872.png",intern=TRUE))
character(0)
> try(system("convert tmp/107b0d1294765872.ps tmp/107b0d1294765872.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.980 0.330 3.494