R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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.
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(6.3,1.0,3.0,2.1,2547.0,4.0,9.1,10.55,4.0,15.8,0.023,1.0,5.2,160.0,4.0,10.9,3.3,1.0,8.3,52.16,1.0,11.0,0.425,4.0,3.2,465.0,5.0,6.3,0.075,1.0,6.6,0.785,2.0,9.5,0.2,2.0,3.3,27.66,5.0,11.0,0.12,2.0,4.7,85.0,1.0,10.4,0.101,3.0,7.4,1.04,4.0,2.1,521.0,5.0,17.9,0.01,1.0,6.1,62.0,1.0,11.9,0.023,3.0,13.8,1.7,1.0,14.3,3.5,1.0,15.2,0.48,2.0,10.0,10.0,4.0,11.9,1.62,2.0,6.5,192.0,4.0,7.5,2.5,5.0,10.6,0.28,3.0,7.4,4.235,1.0,8.4,6.8,2.0,5.7,0.75,2.0,4.9,3.6,3.0,3.2,55.5,5.0,11.0,0.9,2.0,4.9,2.0,3.0,13.2,0.104,2.0,9.7,4.19,4.0,12.8,3.5,1.0),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
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
SWS Wb D
1 6.3 1.000 3
2 2.1 2547.000 4
3 9.1 10.550 4
4 15.8 0.023 1
5 5.2 160.000 4
6 10.9 3.300 1
7 8.3 52.160 1
8 11.0 0.425 4
9 3.2 465.000 5
10 6.3 0.075 1
11 6.6 0.785 2
12 9.5 0.200 2
13 3.3 27.660 5
14 11.0 0.120 2
15 4.7 85.000 1
16 10.4 0.101 3
17 7.4 1.040 4
18 2.1 521.000 5
19 17.9 0.010 1
20 6.1 62.000 1
21 11.9 0.023 3
22 13.8 1.700 1
23 14.3 3.500 1
24 15.2 0.480 2
25 10.0 10.000 4
26 11.9 1.620 2
27 6.5 192.000 4
28 7.5 2.500 5
29 10.6 0.280 3
30 7.4 4.235 1
31 8.4 6.800 2
32 5.7 0.750 2
33 4.9 3.600 3
34 3.2 55.500 5
35 11.0 0.900 2
36 4.9 2.000 3
37 13.2 0.104 2
38 9.7 4.190 4
39 12.8 3.500 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Wb D
12.500291 -0.002559 -1.313307
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-6.2695 -2.5774 0.1556 2.2520 6.7130
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.500291 1.129376 11.068 3.85e-13 ***
Wb -0.002559 0.001317 -1.943 0.05992 .
D -1.313307 0.386405 -3.399 0.00167 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.259 on 36 degrees of freedom
Multiple R-squared: 0.361, Adjusted R-squared: 0.3255
F-statistic: 10.17 on 2 and 36 DF, p-value: 0.0003159
> 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,] 0.5002208 0.9995584 0.4997792
[2,] 0.5326913 0.9346174 0.4673087
[3,] 0.5448524 0.9102953 0.4551476
[4,] 0.4554766 0.9109533 0.5445234
[5,] 0.5768844 0.8462313 0.4231156
[6,] 0.5431086 0.9137828 0.4568914
[7,] 0.4299244 0.8598488 0.5700756
[8,] 0.3928490 0.7856980 0.6071510
[9,] 0.3169933 0.6339867 0.6830067
[10,] 0.5037665 0.9924670 0.4962335
[11,] 0.4454270 0.8908540 0.5545730
[12,] 0.3478950 0.6957899 0.6521050
[13,] 0.3095810 0.6191619 0.6904190
[14,] 0.6294432 0.7411135 0.3705568
[15,] 0.7018189 0.5963622 0.2981811
[16,] 0.6938431 0.6123139 0.3061569
[17,] 0.6508381 0.6983237 0.3491619
[18,] 0.6316133 0.7367735 0.3683867
[19,] 0.7718534 0.4562933 0.2281466
[20,] 0.7423071 0.5153858 0.2576929
[21,] 0.6986165 0.6027669 0.3013835
[22,] 0.6721624 0.6556752 0.3278376
[23,] 0.5653642 0.8692716 0.4346358
[24,] 0.4960303 0.9920606 0.5039697
[25,] 0.4836860 0.9673720 0.5163140
[26,] 0.3634966 0.7269933 0.6365034
[27,] 0.4400410 0.8800821 0.5599590
[28,] 0.4802282 0.9604565 0.5197718
> postscript(file="/var/www/html/rcomp/tmp/1ve4o1292277545.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/25ol91292277545.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/rcomp/tmp/35ol91292277545.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/45ol91292277545.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5gxkc1292277545.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
-2.2578126 1.3707169 1.8799324 4.6130741 -1.6376245 -0.2785401 -2.7535072
8 9 10 11 12 13 14
3.7540225 -1.5438218 -4.8867929 -3.2716694 -0.3731664 -2.5629764 1.1266289
15 16 17 18 19 20 21
-6.2694695 1.8398868 0.1555963 -2.5005177 6.7130408 -4.9283266 3.3396872
22 23 24 25 26 27 28
2.6173655 3.1219717 5.3275501 2.7785250 2.0304674 -0.2557364 1.5726390
29 30 31 32 33 34 35
2.0403449 -3.7761474 -1.4562770 -4.1717590 -3.6511592 -2.5917338 1.1286249
36 37 38 39
-3.6552536 3.3265879 2.4636572 1.6219717
> postscript(file="/var/www/html/rcomp/tmp/6gxkc1292277545.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 -2.2578126 NA
1 1.3707169 -2.2578126
2 1.8799324 1.3707169
3 4.6130741 1.8799324
4 -1.6376245 4.6130741
5 -0.2785401 -1.6376245
6 -2.7535072 -0.2785401
7 3.7540225 -2.7535072
8 -1.5438218 3.7540225
9 -4.8867929 -1.5438218
10 -3.2716694 -4.8867929
11 -0.3731664 -3.2716694
12 -2.5629764 -0.3731664
13 1.1266289 -2.5629764
14 -6.2694695 1.1266289
15 1.8398868 -6.2694695
16 0.1555963 1.8398868
17 -2.5005177 0.1555963
18 6.7130408 -2.5005177
19 -4.9283266 6.7130408
20 3.3396872 -4.9283266
21 2.6173655 3.3396872
22 3.1219717 2.6173655
23 5.3275501 3.1219717
24 2.7785250 5.3275501
25 2.0304674 2.7785250
26 -0.2557364 2.0304674
27 1.5726390 -0.2557364
28 2.0403449 1.5726390
29 -3.7761474 2.0403449
30 -1.4562770 -3.7761474
31 -4.1717590 -1.4562770
32 -3.6511592 -4.1717590
33 -2.5917338 -3.6511592
34 1.1286249 -2.5917338
35 -3.6552536 1.1286249
36 3.3265879 -3.6552536
37 2.4636572 3.3265879
38 1.6219717 2.4636572
39 NA 1.6219717
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.3707169 -2.2578126
[2,] 1.8799324 1.3707169
[3,] 4.6130741 1.8799324
[4,] -1.6376245 4.6130741
[5,] -0.2785401 -1.6376245
[6,] -2.7535072 -0.2785401
[7,] 3.7540225 -2.7535072
[8,] -1.5438218 3.7540225
[9,] -4.8867929 -1.5438218
[10,] -3.2716694 -4.8867929
[11,] -0.3731664 -3.2716694
[12,] -2.5629764 -0.3731664
[13,] 1.1266289 -2.5629764
[14,] -6.2694695 1.1266289
[15,] 1.8398868 -6.2694695
[16,] 0.1555963 1.8398868
[17,] -2.5005177 0.1555963
[18,] 6.7130408 -2.5005177
[19,] -4.9283266 6.7130408
[20,] 3.3396872 -4.9283266
[21,] 2.6173655 3.3396872
[22,] 3.1219717 2.6173655
[23,] 5.3275501 3.1219717
[24,] 2.7785250 5.3275501
[25,] 2.0304674 2.7785250
[26,] -0.2557364 2.0304674
[27,] 1.5726390 -0.2557364
[28,] 2.0403449 1.5726390
[29,] -3.7761474 2.0403449
[30,] -1.4562770 -3.7761474
[31,] -4.1717590 -1.4562770
[32,] -3.6511592 -4.1717590
[33,] -2.5917338 -3.6511592
[34,] 1.1286249 -2.5917338
[35,] -3.6552536 1.1286249
[36,] 3.3265879 -3.6552536
[37,] 2.4636572 3.3265879
[38,] 1.6219717 2.4636572
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.3707169 -2.2578126
2 1.8799324 1.3707169
3 4.6130741 1.8799324
4 -1.6376245 4.6130741
5 -0.2785401 -1.6376245
6 -2.7535072 -0.2785401
7 3.7540225 -2.7535072
8 -1.5438218 3.7540225
9 -4.8867929 -1.5438218
10 -3.2716694 -4.8867929
11 -0.3731664 -3.2716694
12 -2.5629764 -0.3731664
13 1.1266289 -2.5629764
14 -6.2694695 1.1266289
15 1.8398868 -6.2694695
16 0.1555963 1.8398868
17 -2.5005177 0.1555963
18 6.7130408 -2.5005177
19 -4.9283266 6.7130408
20 3.3396872 -4.9283266
21 2.6173655 3.3396872
22 3.1219717 2.6173655
23 5.3275501 3.1219717
24 2.7785250 5.3275501
25 2.0304674 2.7785250
26 -0.2557364 2.0304674
27 1.5726390 -0.2557364
28 2.0403449 1.5726390
29 -3.7761474 2.0403449
30 -1.4562770 -3.7761474
31 -4.1717590 -1.4562770
32 -3.6511592 -4.1717590
33 -2.5917338 -3.6511592
34 1.1286249 -2.5917338
35 -3.6552536 1.1286249
36 3.3265879 -3.6552536
37 2.4636572 3.3265879
38 1.6219717 2.4636572
> 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/7962x1292277545.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8962x1292277545.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ky101292277545.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ky101292277545.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/115yzo1292277545.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/128hgc1292277545.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/13n8el1292277545.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/14q9u81292277545.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/15t9bw1292277545.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/16pj851292277545.tab")
+ }
>
> try(system("convert tmp/1ve4o1292277545.ps tmp/1ve4o1292277545.png",intern=TRUE))
character(0)
> try(system("convert tmp/25ol91292277545.ps tmp/25ol91292277545.png",intern=TRUE))
character(0)
> try(system("convert tmp/35ol91292277545.ps tmp/35ol91292277545.png",intern=TRUE))
character(0)
> try(system("convert tmp/45ol91292277545.ps tmp/45ol91292277545.png",intern=TRUE))
character(0)
> try(system("convert tmp/5gxkc1292277545.ps tmp/5gxkc1292277545.png",intern=TRUE))
character(0)
> try(system("convert tmp/6gxkc1292277545.ps tmp/6gxkc1292277545.png",intern=TRUE))
character(0)
> try(system("convert tmp/7962x1292277545.ps tmp/7962x1292277545.png",intern=TRUE))
character(0)
> try(system("convert tmp/8962x1292277545.ps tmp/8962x1292277545.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ky101292277545.ps tmp/9ky101292277545.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ky101292277545.ps tmp/10ky101292277545.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.263 1.598 5.213