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(0.3010,3,1.62,0.2553,4,2.8,-0.1549,4,2.26,0.5911,1,1.54,0.0000,4,2.59,0.5563,1,1.8,0.1461,1,2.36,0.1761,4,2.05,-0.1549,5,2.45,0.3222,1,1.62,0.6128,2,1.62,0.0792,2,2.08,-0.3010,5,2.17,0.5315,2,1.2,0.1761,1,2.49,0.5315,3,1.45,-0.0969,4,1.83,-0.0969,5,2.53,0.3010,1,1.7,0.2788,1,2.43,0.1139,3,1.28,0.7482,1,1.08,0.4914,1,2.08,0.2553,2,2.15,-0.0458,4,2.23,0.2553,2,1.23,0.2788,4,2.06,-0.0458,5,1.49,0.4150,3,1.32,0.3802,1,1.72,0.0792,2,2.21,-0.0458,2,2.35,-0.3010,3,2.35,-0.2218,5,2.18,0.3617,2,1.78,-0.3010,3,2.3,0.4150,2,1.66,-0.2218,4,2.32,0.8195,1,1.15),dim=c(3,39),dimnames=list(c('PS','D','Tg
'),1:39))
> y <- array(NA,dim=c(3,39),dimnames=list(c('PS','D','Tg
'),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
PS D Tg\r\r\r\r
1 0.3010 3 1.62
2 0.2553 4 2.80
3 -0.1549 4 2.26
4 0.5911 1 1.54
5 0.0000 4 2.59
6 0.5563 1 1.80
7 0.1461 1 2.36
8 0.1761 4 2.05
9 -0.1549 5 2.45
10 0.3222 1 1.62
11 0.6128 2 1.62
12 0.0792 2 2.08
13 -0.3010 5 2.17
14 0.5315 2 1.20
15 0.1761 1 2.49
16 0.5315 3 1.45
17 -0.0969 4 1.83
18 -0.0969 5 2.53
19 0.3010 1 1.70
20 0.2788 1 2.43
21 0.1139 3 1.28
22 0.7482 1 1.08
23 0.4914 1 2.08
24 0.2553 2 2.15
25 -0.0458 4 2.23
26 0.2553 2 1.23
27 0.2788 4 2.06
28 -0.0458 5 1.49
29 0.4150 3 1.32
30 0.3802 1 1.72
31 0.0792 2 2.21
32 -0.0458 2 2.35
33 -0.3010 3 2.35
34 -0.2218 5 2.18
35 0.3617 2 1.78
36 -0.3010 3 2.30
37 0.4150 2 1.66
38 -0.2218 4 2.32
39 0.8195 1 1.15
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D `Tg\r\r\r\r`
1.0727 -0.1106 -0.3026
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.34613 -0.14495 0.04298 0.12576 0.47202
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.07274 0.12881 8.328 6.47e-10 ***
D -0.11058 0.02222 -4.976 1.62e-05 ***
`Tg\r\r\r\r` -0.30255 0.06894 -4.389 9.55e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.182 on 36 degrees of freedom
Multiple R-squared: 0.6537, Adjusted R-squared: 0.6345
F-statistic: 33.98 on 2 and 36 DF, p-value: 5.125e-09
> 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,] 0.5967498 0.80650048 0.40325024
[2,] 0.8046720 0.39065596 0.19532798
[3,] 0.7195588 0.56088239 0.28044120
[4,] 0.6482107 0.70357860 0.35178930
[5,] 0.6115657 0.77686853 0.38843426
[6,] 0.6878204 0.62435913 0.31217957
[7,] 0.6883808 0.62323836 0.31161918
[8,] 0.7353465 0.52930693 0.26465347
[9,] 0.6487973 0.70240549 0.35120274
[10,] 0.5635451 0.87290974 0.43645487
[11,] 0.5930287 0.81394261 0.40697131
[12,] 0.6095474 0.78090526 0.39045263
[13,] 0.6129386 0.77412284 0.38706142
[14,] 0.5881626 0.82367473 0.41183736
[15,] 0.5026241 0.99475178 0.49737589
[16,] 0.5890280 0.82194391 0.41097196
[17,] 0.5242408 0.95151848 0.47575924
[18,] 0.5320114 0.93597721 0.46798860
[19,] 0.4816921 0.96338414 0.51830793
[20,] 0.4133406 0.82668115 0.58665943
[21,] 0.6021739 0.79565222 0.39782611
[22,] 0.9605754 0.07884915 0.03942458
[23,] 0.9708793 0.05824141 0.02912071
[24,] 0.9634193 0.07316135 0.03658068
[25,] 0.9343513 0.13129744 0.06564872
[26,] 0.9144518 0.17109644 0.08554822
[27,] 0.9380395 0.12392096 0.06196048
[28,] 0.8828252 0.23434969 0.11717485
> postscript(file="/var/www/html/rcomp/tmp/1pa4d1291989682.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/202ly1291989682.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/302ly1291989682.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4tb2j1291989682.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5tb2j1291989682.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
0.050130293 0.472023205 -0.101556075 0.094868096 0.153186819 0.138732194
7 8 9 10 11 12
-0.102037442 0.165907539 0.066508157 -0.149827566 0.251351364 -0.143073694
13 14 15 16 17 18
-0.164307025 0.042978590 -0.032705393 0.229196076 -0.173654390 0.148712495
19 20 21 22 23 24
-0.146823228 0.051841354 -0.239838142 0.112793154 0.158547376 0.054205101
25 26 27 28 29 30
-0.001532701 -0.224144783 0.271633081 -0.114843896 0.073364027 -0.061572144
31 32 33 34 35 36
-0.103741645 -0.186384054 -0.331005124 -0.082081483 0.048660039 -0.346132835
37 38 39
0.065653533 -0.150302821 0.205271949
> postscript(file="/var/www/html/rcomp/tmp/6tb2j1291989682.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 0.050130293 NA
1 0.472023205 0.050130293
2 -0.101556075 0.472023205
3 0.094868096 -0.101556075
4 0.153186819 0.094868096
5 0.138732194 0.153186819
6 -0.102037442 0.138732194
7 0.165907539 -0.102037442
8 0.066508157 0.165907539
9 -0.149827566 0.066508157
10 0.251351364 -0.149827566
11 -0.143073694 0.251351364
12 -0.164307025 -0.143073694
13 0.042978590 -0.164307025
14 -0.032705393 0.042978590
15 0.229196076 -0.032705393
16 -0.173654390 0.229196076
17 0.148712495 -0.173654390
18 -0.146823228 0.148712495
19 0.051841354 -0.146823228
20 -0.239838142 0.051841354
21 0.112793154 -0.239838142
22 0.158547376 0.112793154
23 0.054205101 0.158547376
24 -0.001532701 0.054205101
25 -0.224144783 -0.001532701
26 0.271633081 -0.224144783
27 -0.114843896 0.271633081
28 0.073364027 -0.114843896
29 -0.061572144 0.073364027
30 -0.103741645 -0.061572144
31 -0.186384054 -0.103741645
32 -0.331005124 -0.186384054
33 -0.082081483 -0.331005124
34 0.048660039 -0.082081483
35 -0.346132835 0.048660039
36 0.065653533 -0.346132835
37 -0.150302821 0.065653533
38 0.205271949 -0.150302821
39 NA 0.205271949
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.472023205 0.050130293
[2,] -0.101556075 0.472023205
[3,] 0.094868096 -0.101556075
[4,] 0.153186819 0.094868096
[5,] 0.138732194 0.153186819
[6,] -0.102037442 0.138732194
[7,] 0.165907539 -0.102037442
[8,] 0.066508157 0.165907539
[9,] -0.149827566 0.066508157
[10,] 0.251351364 -0.149827566
[11,] -0.143073694 0.251351364
[12,] -0.164307025 -0.143073694
[13,] 0.042978590 -0.164307025
[14,] -0.032705393 0.042978590
[15,] 0.229196076 -0.032705393
[16,] -0.173654390 0.229196076
[17,] 0.148712495 -0.173654390
[18,] -0.146823228 0.148712495
[19,] 0.051841354 -0.146823228
[20,] -0.239838142 0.051841354
[21,] 0.112793154 -0.239838142
[22,] 0.158547376 0.112793154
[23,] 0.054205101 0.158547376
[24,] -0.001532701 0.054205101
[25,] -0.224144783 -0.001532701
[26,] 0.271633081 -0.224144783
[27,] -0.114843896 0.271633081
[28,] 0.073364027 -0.114843896
[29,] -0.061572144 0.073364027
[30,] -0.103741645 -0.061572144
[31,] -0.186384054 -0.103741645
[32,] -0.331005124 -0.186384054
[33,] -0.082081483 -0.331005124
[34,] 0.048660039 -0.082081483
[35,] -0.346132835 0.048660039
[36,] 0.065653533 -0.346132835
[37,] -0.150302821 0.065653533
[38,] 0.205271949 -0.150302821
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.472023205 0.050130293
2 -0.101556075 0.472023205
3 0.094868096 -0.101556075
4 0.153186819 0.094868096
5 0.138732194 0.153186819
6 -0.102037442 0.138732194
7 0.165907539 -0.102037442
8 0.066508157 0.165907539
9 -0.149827566 0.066508157
10 0.251351364 -0.149827566
11 -0.143073694 0.251351364
12 -0.164307025 -0.143073694
13 0.042978590 -0.164307025
14 -0.032705393 0.042978590
15 0.229196076 -0.032705393
16 -0.173654390 0.229196076
17 0.148712495 -0.173654390
18 -0.146823228 0.148712495
19 0.051841354 -0.146823228
20 -0.239838142 0.051841354
21 0.112793154 -0.239838142
22 0.158547376 0.112793154
23 0.054205101 0.158547376
24 -0.001532701 0.054205101
25 -0.224144783 -0.001532701
26 0.271633081 -0.224144783
27 -0.114843896 0.271633081
28 0.073364027 -0.114843896
29 -0.061572144 0.073364027
30 -0.103741645 -0.061572144
31 -0.186384054 -0.103741645
32 -0.331005124 -0.186384054
33 -0.082081483 -0.331005124
34 0.048660039 -0.082081483
35 -0.346132835 0.048660039
36 0.065653533 -0.346132835
37 -0.150302821 0.065653533
38 0.205271949 -0.150302821
> 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/7lkkm1291989682.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8lkkm1291989682.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9wb171291989682.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10wb171291989682.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11s3hg1291989682.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/12luy11291989682.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/1326gp1291989683.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/14n6ed1291989683.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/15ygdy1291989683.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/16c7b71291989683.tab")
+ }
>
> try(system("convert tmp/1pa4d1291989682.ps tmp/1pa4d1291989682.png",intern=TRUE))
character(0)
> try(system("convert tmp/202ly1291989682.ps tmp/202ly1291989682.png",intern=TRUE))
character(0)
> try(system("convert tmp/302ly1291989682.ps tmp/302ly1291989682.png",intern=TRUE))
character(0)
> try(system("convert tmp/4tb2j1291989682.ps tmp/4tb2j1291989682.png",intern=TRUE))
character(0)
> try(system("convert tmp/5tb2j1291989682.ps tmp/5tb2j1291989682.png",intern=TRUE))
character(0)
> try(system("convert tmp/6tb2j1291989682.ps tmp/6tb2j1291989682.png",intern=TRUE))
character(0)
> try(system("convert tmp/7lkkm1291989682.ps tmp/7lkkm1291989682.png",intern=TRUE))
character(0)
> try(system("convert tmp/8lkkm1291989682.ps tmp/8lkkm1291989682.png",intern=TRUE))
character(0)
> try(system("convert tmp/9wb171291989682.ps tmp/9wb171291989682.png",intern=TRUE))
character(0)
> try(system("convert tmp/10wb171291989682.ps tmp/10wb171291989682.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.300 1.631 8.190