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
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(6.3000,0.0000,3,2.1000,3.4060,4,9.1000,1.0233,4,15.8000,-1.6383,1,5.2000,2.2041,4,10.9000,0.5185,1,8.3000,1.7173,1,11.0000,-0.3716,4,3.2000,2.6675,5,6.3000,-1.1249,1,6.6000,-0.1051,2,9.5000,-0.6990,2,3.3000,1.4419,5,11.0000,-0.9208,2,4.7000,1.9294,1,10.4000,-0.9957,3,7.4000,0.0170,4,2.1000,2.7168,5,17.9000,-2.0000,1,6.1000,1.7924,1,11.9000,-1.6383,3,13.8000,0.2304,1,14.3000,0.5441,1,15.2000,-0.3188,2,10.0000,1.0000,4,11.9000,0.2095,2,6.5000,2.2833,4,7.5000,0.3979,5,10.6000,-0.5528,3,7.4000,0.6269,1,8.4000,0.8325,2,5.7000,-0.1249,2,4.9000,0.5563,3,3.2000,1.7443,5,11.0000,-0.0458,2,4.9000,0.3010,3,13.2000,-0.9830,2,9.7000,0.6222,4,12.8000,0.5441,1),dim=c(3,39),dimnames=list(c('SWS','Wb','D'),1:39))
> y <- array(NA,dim=c(3,39),dimnames=list(c('SWS','Wb','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 Wb D
1 6.3 0.0000 3
2 2.1 3.4060 4
3 9.1 1.0233 4
4 15.8 -1.6383 1
5 5.2 2.2041 4
6 10.9 0.5185 1
7 8.3 1.7173 1
8 11.0 -0.3716 4
9 3.2 2.6675 5
10 6.3 -1.1249 1
11 6.6 -0.1051 2
12 9.5 -0.6990 2
13 3.3 1.4419 5
14 11.0 -0.9208 2
15 4.7 1.9294 1
16 10.4 -0.9957 3
17 7.4 0.0170 4
18 2.1 2.7168 5
19 17.9 -2.0000 1
20 6.1 1.7924 1
21 11.9 -1.6383 3
22 13.8 0.2304 1
23 14.3 0.5441 1
24 15.2 -0.3188 2
25 10.0 1.0000 4
26 11.9 0.2095 2
27 6.5 2.2833 4
28 7.5 0.3979 5
29 10.6 -0.5528 3
30 7.4 0.6269 1
31 8.4 0.8325 2
32 5.7 -0.1249 2
33 4.9 0.5563 3
34 3.2 1.7443 5
35 11.0 -0.0458 2
36 4.9 0.3010 3
37 13.2 -0.9830 2
38 9.7 0.6222 4
39 12.8 0.5441 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Wb D
11.6991 -1.8149 -0.8062
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-6.6344 -1.6455 0.3163 2.0517 4.5347
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11.6991 0.9411 12.431 1.37e-14 ***
Wb -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,] 0.4874291 0.9748581 0.5125709
[2,] 0.3145330 0.6290659 0.6854670
[3,] 0.2118603 0.4237206 0.7881397
[4,] 0.1186498 0.2372996 0.8813502
[5,] 0.6866966 0.6266069 0.3133034
[6,] 0.7152175 0.5695649 0.2847825
[7,] 0.6410240 0.7179520 0.3589760
[8,] 0.5852035 0.8295930 0.4147965
[9,] 0.4931056 0.9862111 0.5068944
[10,] 0.4659501 0.9319002 0.5340499
[11,] 0.3727551 0.7455102 0.6272449
[12,] 0.2914903 0.5829806 0.7085097
[13,] 0.2167439 0.4334878 0.7832561
[14,] 0.3077383 0.6154766 0.6922617
[15,] 0.2636939 0.5273879 0.7363061
[16,] 0.1882597 0.3765193 0.8117403
[17,] 0.2275863 0.4551725 0.7724137
[18,] 0.3396979 0.6793958 0.6603021
[19,] 0.5035258 0.9929484 0.4964742
[20,] 0.5394331 0.9211338 0.4605669
[21,] 0.5129433 0.9741134 0.4870567
[22,] 0.4907668 0.9815335 0.5092332
[23,] 0.3908129 0.7816259 0.6091871
[24,] 0.2888090 0.5776181 0.7111910
[25,] 0.2474784 0.4949568 0.7525216
[26,] 0.1555106 0.3110212 0.8444894
[27,] 0.2939779 0.5879558 0.7060221
[28,] 0.3338069 0.6676137 0.6661931
> postscript(file="/var/www/rcomp/tmp/126gp1291990628.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/226gp1291990628.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vffs1291990628.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4vffs1291990628.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5vffs1291990628.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
-2.9804590 -0.1928015 2.4829088 1.9338167 0.7259068 0.9481274 0.5237930
8 9 10 11 12 13 14
1.8513473 0.3731291 -6.6344293 -3.6774135 -1.8552645 -1.7511750 -0.7578026
15 16 17 18 19 20 21
-2.6912732 -0.6875246 -1.0433944 -0.6373978 3.3773784 -1.5399103 -0.3537598
22 23 24 25 26 27 28
3.3252634 4.3945880 4.5347489 3.3406224 2.1935444 2.1696445 0.5541012
29 30 31 32 33 34 35
0.3162811 -2.3551408 -0.1757918 -4.6133479 -3.3708470 -1.3023585 0.8302082
36 37 38 39
-3.8341832 1.3293125 2.3549646 2.8945880
> postscript(file="/var/www/rcomp/tmp/6n6ed1291990628.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 -2.9804590 NA
1 -0.1928015 -2.9804590
2 2.4829088 -0.1928015
3 1.9338167 2.4829088
4 0.7259068 1.9338167
5 0.9481274 0.7259068
6 0.5237930 0.9481274
7 1.8513473 0.5237930
8 0.3731291 1.8513473
9 -6.6344293 0.3731291
10 -3.6774135 -6.6344293
11 -1.8552645 -3.6774135
12 -1.7511750 -1.8552645
13 -0.7578026 -1.7511750
14 -2.6912732 -0.7578026
15 -0.6875246 -2.6912732
16 -1.0433944 -0.6875246
17 -0.6373978 -1.0433944
18 3.3773784 -0.6373978
19 -1.5399103 3.3773784
20 -0.3537598 -1.5399103
21 3.3252634 -0.3537598
22 4.3945880 3.3252634
23 4.5347489 4.3945880
24 3.3406224 4.5347489
25 2.1935444 3.3406224
26 2.1696445 2.1935444
27 0.5541012 2.1696445
28 0.3162811 0.5541012
29 -2.3551408 0.3162811
30 -0.1757918 -2.3551408
31 -4.6133479 -0.1757918
32 -3.3708470 -4.6133479
33 -1.3023585 -3.3708470
34 0.8302082 -1.3023585
35 -3.8341832 0.8302082
36 1.3293125 -3.8341832
37 2.3549646 1.3293125
38 2.8945880 2.3549646
39 NA 2.8945880
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.1928015 -2.9804590
[2,] 2.4829088 -0.1928015
[3,] 1.9338167 2.4829088
[4,] 0.7259068 1.9338167
[5,] 0.9481274 0.7259068
[6,] 0.5237930 0.9481274
[7,] 1.8513473 0.5237930
[8,] 0.3731291 1.8513473
[9,] -6.6344293 0.3731291
[10,] -3.6774135 -6.6344293
[11,] -1.8552645 -3.6774135
[12,] -1.7511750 -1.8552645
[13,] -0.7578026 -1.7511750
[14,] -2.6912732 -0.7578026
[15,] -0.6875246 -2.6912732
[16,] -1.0433944 -0.6875246
[17,] -0.6373978 -1.0433944
[18,] 3.3773784 -0.6373978
[19,] -1.5399103 3.3773784
[20,] -0.3537598 -1.5399103
[21,] 3.3252634 -0.3537598
[22,] 4.3945880 3.3252634
[23,] 4.5347489 4.3945880
[24,] 3.3406224 4.5347489
[25,] 2.1935444 3.3406224
[26,] 2.1696445 2.1935444
[27,] 0.5541012 2.1696445
[28,] 0.3162811 0.5541012
[29,] -2.3551408 0.3162811
[30,] -0.1757918 -2.3551408
[31,] -4.6133479 -0.1757918
[32,] -3.3708470 -4.6133479
[33,] -1.3023585 -3.3708470
[34,] 0.8302082 -1.3023585
[35,] -3.8341832 0.8302082
[36,] 1.3293125 -3.8341832
[37,] 2.3549646 1.3293125
[38,] 2.8945880 2.3549646
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.1928015 -2.9804590
2 2.4829088 -0.1928015
3 1.9338167 2.4829088
4 0.7259068 1.9338167
5 0.9481274 0.7259068
6 0.5237930 0.9481274
7 1.8513473 0.5237930
8 0.3731291 1.8513473
9 -6.6344293 0.3731291
10 -3.6774135 -6.6344293
11 -1.8552645 -3.6774135
12 -1.7511750 -1.8552645
13 -0.7578026 -1.7511750
14 -2.6912732 -0.7578026
15 -0.6875246 -2.6912732
16 -1.0433944 -0.6875246
17 -0.6373978 -1.0433944
18 3.3773784 -0.6373978
19 -1.5399103 3.3773784
20 -0.3537598 -1.5399103
21 3.3252634 -0.3537598
22 4.3945880 3.3252634
23 4.5347489 4.3945880
24 3.3406224 4.5347489
25 2.1935444 3.3406224
26 2.1696445 2.1935444
27 0.5541012 2.1696445
28 0.3162811 0.5541012
29 -2.3551408 0.3162811
30 -0.1757918 -2.3551408
31 -4.6133479 -0.1757918
32 -3.3708470 -4.6133479
33 -1.3023585 -3.3708470
34 0.8302082 -1.3023585
35 -3.8341832 0.8302082
36 1.3293125 -3.8341832
37 2.3549646 1.3293125
38 2.8945880 2.3549646
> 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/7ygdy1291990628.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8ygdy1291990628.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9ygdy1291990628.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/1097v11291990628.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11c7b71291990628.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/12yqav1291990628.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/1349761291990628.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/14x0691291990628.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/1511mf1291990628.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/16wa261291990628.tab")
+ }
> try(system("convert tmp/126gp1291990628.ps tmp/126gp1291990628.png",intern=TRUE))
character(0)
> try(system("convert tmp/226gp1291990628.ps tmp/226gp1291990628.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vffs1291990628.ps tmp/3vffs1291990628.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vffs1291990628.ps tmp/4vffs1291990628.png",intern=TRUE))
character(0)
> try(system("convert tmp/5vffs1291990628.ps tmp/5vffs1291990628.png",intern=TRUE))
character(0)
> try(system("convert tmp/6n6ed1291990628.ps tmp/6n6ed1291990628.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ygdy1291990628.ps tmp/7ygdy1291990628.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ygdy1291990628.ps tmp/8ygdy1291990628.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ygdy1291990628.ps tmp/9ygdy1291990628.png",intern=TRUE))
character(0)
> try(system("convert tmp/1097v11291990628.ps tmp/1097v11291990628.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.950 1.770 4.774