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.
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
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Type 'q()' to quit R.
> x <- array(list(6.3,0.00000,3,2.1,3.40603,4,9.1,1.02325,4,15.8,-1.63827,1,5.2,2.20412,4,10.9,0.51851,1,8.3,1.71734,1,11.0,-0.37161,4,3.2,2.66745,5,6.3,-1.12494,1,6.6,-0.10513,2,9.5,-0.69897,2,3.3,1.44185,5,11.0,-0.92082,2,4.7,1.92942,1,10.4,-0.99568,3,7.4,0.01703,4,2.1,2.71684,5,17.9,-2.00000,1,6.1,1.79239,1,11.9,-1.63827,3,13.8,0.23045,1,14.3,0.54407,1,15.2,-0.31876,2,10.0,1.00000,4,11.9,0.20952,2,6.5,2.28330,4,7.5,0.39794,5,10.6,-0.55284,3,7.4,0.62685,1,8.4,0.83251,2,5.7,-0.12494,2,4.9,0.55630,3,3.2,1.74429,5,11.0,-0.04576,2,4.9,0.30103,3,13.2,-0.98297,2,9.7,0.62221,4,12.8,0.54407,1),dim=c(3,39),dimnames=list(c('SWS','LOGWb','D'),1:39))
> y <- array(NA,dim=c(3,39),dimnames=list(c('SWS','LOGWb','D'),1:39))
> 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
SWS LOGWb D
1 6.3 0.00000 3
2 2.1 3.40603 4
3 9.1 1.02325 4
4 15.8 -1.63827 1
5 5.2 2.20412 4
6 10.9 0.51851 1
7 8.3 1.71734 1
8 11.0 -0.37161 4
9 3.2 2.66745 5
10 6.3 -1.12494 1
11 6.6 -0.10513 2
12 9.5 -0.69897 2
13 3.3 1.44185 5
14 11.0 -0.92082 2
15 4.7 1.92942 1
16 10.4 -0.99568 3
17 7.4 0.01703 4
18 2.1 2.71684 5
19 17.9 -2.00000 1
20 6.1 1.79239 1
21 11.9 -1.63827 3
22 13.8 0.23045 1
23 14.3 0.54407 1
24 15.2 -0.31876 2
25 10.0 1.00000 4
26 11.9 0.20952 2
27 6.5 2.28330 4
28 7.5 0.39794 5
29 10.6 -0.55284 3
30 7.4 0.62685 1
31 8.4 0.83251 2
32 5.7 -0.12494 2
33 4.9 0.55630 3
34 3.2 1.74429 5
35 11.0 -0.04576 2
36 4.9 0.30103 3
37 13.2 -0.98297 2
38 9.7 0.62221 4
39 12.8 0.54407 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) LOGWb D
11.6991 -1.8149 -0.8062
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-6.6345 -1.6456 0.3162 2.0518 4.5348
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11.6991 0.9411 12.431 1.37e-14 ***
LOGWb -1.8149 0.3729 -4.866 2.26e-05 ***
D -0.8062 0.3370 -2.393 0.0221 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.661 on 36 degrees of freedom
Multiple R-squared: 0.5741, Adjusted R-squared: 0.5505
F-statistic: 24.27 on 2 and 36 DF, p-value: 2.124e-07
> 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,] 0.4874170 0.9748339 0.5125830
[2,] 0.3145216 0.6290433 0.6854784
[3,] 0.2118512 0.4237024 0.7881488
[4,] 0.1186432 0.2372864 0.8813568
[5,] 0.6866981 0.6266037 0.3133019
[6,] 0.7152212 0.5695576 0.2847788
[7,] 0.6410255 0.7179489 0.3589745
[8,] 0.5852068 0.8295864 0.4147932
[9,] 0.4931096 0.9862192 0.5068904
[10,] 0.4659541 0.9319082 0.5340459
[11,] 0.3727588 0.7455177 0.6272412
[12,] 0.2914920 0.5829839 0.7085080
[13,] 0.2167443 0.4334885 0.7832557
[14,] 0.3077380 0.6154759 0.6922620
[15,] 0.2636946 0.5273892 0.7363054
[16,] 0.1882600 0.3765200 0.8117400
[17,] 0.2275899 0.4551798 0.7724101
[18,] 0.3396930 0.6793860 0.6603070
[19,] 0.5035271 0.9929457 0.4964729
[20,] 0.5394322 0.9211357 0.4605678
[21,] 0.5129441 0.9741118 0.4870559
[22,] 0.4907646 0.9815291 0.5092354
[23,] 0.3908123 0.7816246 0.6091877
[24,] 0.2888071 0.5776142 0.7111929
[25,] 0.2474810 0.4949619 0.7525190
[26,] 0.1555125 0.3110249 0.8444875
[27,] 0.2939882 0.5879763 0.7060118
[28,] 0.3338179 0.6676359 0.6661821
> postscript(file="/var/www/rcomp/tmp/1tur81292256803.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/243qt1292256803.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/343qt1292256803.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/443qt1292256803.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5wupe1292256803.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 = 39
Frequency = 1
1 2 3 4 5 6 7
-2.9804564 -0.1927805 2.4828141 1.9338818 0.7259245 0.9481295 0.5238347
8 9 10 11 12 13 14
1.8513424 0.3730201 -6.6344976 -3.6774702 -1.8552050 -1.7512689 -0.7578311
15 16 17 18 19 20 21
-2.6912704 -0.6874734 -1.0433315 -0.6373441 3.3773935 -1.5399602 -0.3536825
22 23 24 25 26 27 28
3.3253417 4.3945172 4.5348219 3.3406186 2.1935746 2.1696249 0.5541836
29 30 31 32 33 34 35
0.3162179 -2.3552489 -0.1757875 -4.6134225 -3.3708514 -1.3023834 0.8302779
36 37 38 39
-3.8341299 1.3293756 2.3549837 2.8945172
> postscript(file="/var/www/rcomp/tmp/6wupe1292256803.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 = 39
Frequency = 1
lag(myerror, k = 1) myerror
0 -2.9804564 NA
1 -0.1927805 -2.9804564
2 2.4828141 -0.1927805
3 1.9338818 2.4828141
4 0.7259245 1.9338818
5 0.9481295 0.7259245
6 0.5238347 0.9481295
7 1.8513424 0.5238347
8 0.3730201 1.8513424
9 -6.6344976 0.3730201
10 -3.6774702 -6.6344976
11 -1.8552050 -3.6774702
12 -1.7512689 -1.8552050
13 -0.7578311 -1.7512689
14 -2.6912704 -0.7578311
15 -0.6874734 -2.6912704
16 -1.0433315 -0.6874734
17 -0.6373441 -1.0433315
18 3.3773935 -0.6373441
19 -1.5399602 3.3773935
20 -0.3536825 -1.5399602
21 3.3253417 -0.3536825
22 4.3945172 3.3253417
23 4.5348219 4.3945172
24 3.3406186 4.5348219
25 2.1935746 3.3406186
26 2.1696249 2.1935746
27 0.5541836 2.1696249
28 0.3162179 0.5541836
29 -2.3552489 0.3162179
30 -0.1757875 -2.3552489
31 -4.6134225 -0.1757875
32 -3.3708514 -4.6134225
33 -1.3023834 -3.3708514
34 0.8302779 -1.3023834
35 -3.8341299 0.8302779
36 1.3293756 -3.8341299
37 2.3549837 1.3293756
38 2.8945172 2.3549837
39 NA 2.8945172
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.1927805 -2.9804564
[2,] 2.4828141 -0.1927805
[3,] 1.9338818 2.4828141
[4,] 0.7259245 1.9338818
[5,] 0.9481295 0.7259245
[6,] 0.5238347 0.9481295
[7,] 1.8513424 0.5238347
[8,] 0.3730201 1.8513424
[9,] -6.6344976 0.3730201
[10,] -3.6774702 -6.6344976
[11,] -1.8552050 -3.6774702
[12,] -1.7512689 -1.8552050
[13,] -0.7578311 -1.7512689
[14,] -2.6912704 -0.7578311
[15,] -0.6874734 -2.6912704
[16,] -1.0433315 -0.6874734
[17,] -0.6373441 -1.0433315
[18,] 3.3773935 -0.6373441
[19,] -1.5399602 3.3773935
[20,] -0.3536825 -1.5399602
[21,] 3.3253417 -0.3536825
[22,] 4.3945172 3.3253417
[23,] 4.5348219 4.3945172
[24,] 3.3406186 4.5348219
[25,] 2.1935746 3.3406186
[26,] 2.1696249 2.1935746
[27,] 0.5541836 2.1696249
[28,] 0.3162179 0.5541836
[29,] -2.3552489 0.3162179
[30,] -0.1757875 -2.3552489
[31,] -4.6134225 -0.1757875
[32,] -3.3708514 -4.6134225
[33,] -1.3023834 -3.3708514
[34,] 0.8302779 -1.3023834
[35,] -3.8341299 0.8302779
[36,] 1.3293756 -3.8341299
[37,] 2.3549837 1.3293756
[38,] 2.8945172 2.3549837
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.1927805 -2.9804564
2 2.4828141 -0.1927805
3 1.9338818 2.4828141
4 0.7259245 1.9338818
5 0.9481295 0.7259245
6 0.5238347 0.9481295
7 1.8513424 0.5238347
8 0.3730201 1.8513424
9 -6.6344976 0.3730201
10 -3.6774702 -6.6344976
11 -1.8552050 -3.6774702
12 -1.7512689 -1.8552050
13 -0.7578311 -1.7512689
14 -2.6912704 -0.7578311
15 -0.6874734 -2.6912704
16 -1.0433315 -0.6874734
17 -0.6373441 -1.0433315
18 3.3773935 -0.6373441
19 -1.5399602 3.3773935
20 -0.3536825 -1.5399602
21 3.3253417 -0.3536825
22 4.3945172 3.3253417
23 4.5348219 4.3945172
24 3.3406186 4.5348219
25 2.1935746 3.3406186
26 2.1696249 2.1935746
27 0.5541836 2.1696249
28 0.3162179 0.5541836
29 -2.3552489 0.3162179
30 -0.1757875 -2.3552489
31 -4.6134225 -0.1757875
32 -3.3708514 -4.6134225
33 -1.3023834 -3.3708514
34 0.8302779 -1.3023834
35 -3.8341299 0.8302779
36 1.3293756 -3.8341299
37 2.3549837 1.3293756
38 2.8945172 2.3549837
> 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/774pz1292256803.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/874pz1292256803.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/90vok1292256803.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/100vok1292256803.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11lw481292256803.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/12pwle1292256803.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/13dx071292256803.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/1466zs1292256803.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/1597yg1292256803.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/165hd71292256803.tab")
+ }
>
> try(system("convert tmp/1tur81292256803.ps tmp/1tur81292256803.png",intern=TRUE))
character(0)
> try(system("convert tmp/243qt1292256803.ps tmp/243qt1292256803.png",intern=TRUE))
character(0)
> try(system("convert tmp/343qt1292256803.ps tmp/343qt1292256803.png",intern=TRUE))
character(0)
> try(system("convert tmp/443qt1292256803.ps tmp/443qt1292256803.png",intern=TRUE))
character(0)
> try(system("convert tmp/5wupe1292256803.ps tmp/5wupe1292256803.png",intern=TRUE))
character(0)
> try(system("convert tmp/6wupe1292256803.ps tmp/6wupe1292256803.png",intern=TRUE))
character(0)
> try(system("convert tmp/774pz1292256803.ps tmp/774pz1292256803.png",intern=TRUE))
character(0)
> try(system("convert tmp/874pz1292256803.ps tmp/874pz1292256803.png",intern=TRUE))
character(0)
> try(system("convert tmp/90vok1292256803.ps tmp/90vok1292256803.png",intern=TRUE))
character(0)
> try(system("convert tmp/100vok1292256803.ps tmp/100vok1292256803.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.870 1.660 4.529