R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
Natural language support but running in an English locale
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.
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> x <- array(list(6.3,0,3,2.1,3.406028945,4,9.1,1.02325246,4,15.8,-1.698970004,1,5.2,2.204119983,4,10.9,0.51851394,1,8.3,1.717337583,1,11,-0.366531544,4,3.2,2.667452953,5,6.3,-1.096910013,1,6.6,-0.102372909,2,9.5,-0.698970004,2,3.3,1.441852176,5,11,-0.920818754,2,4.7,1.929418926,1,10.4,-1,3,7.4,0.017033339,4,2.1,2.716837723,5,17.9,-2,1,6.1,1.792391689,1,11.9,-1.698970004,3,13.8,0.230448921,1,14.3,0.544068044,1,15.2,-0.318758763,2,10,1,4,11.9,0.209515015,2,6.5,2.283301229,4,7.5,0.397940009,5,10.6,-0.552841969,3,7.4,0.627365857,1,8.4,0.832508913,2,5.7,-0.124938737,2,4.9,0.556302501,3,3.2,1.744292983,5,11,-0.045757491,2,4.9,0.301029996,3,13.2,-1,2,9.7,0.622214023,4,12.8,0.544068044,1),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
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 LogWb D
1 6.3 0.00000000 3
2 2.1 3.40602895 4
3 9.1 1.02325246 4
4 15.8 -1.69897000 1
5 5.2 2.20411998 4
6 10.9 0.51851394 1
7 8.3 1.71733758 1
8 11.0 -0.36653154 4
9 3.2 2.66745295 5
10 6.3 -1.09691001 1
11 6.6 -0.10237291 2
12 9.5 -0.69897000 2
13 3.3 1.44185218 5
14 11.0 -0.92081875 2
15 4.7 1.92941893 1
16 10.4 -1.00000000 3
17 7.4 0.01703334 4
18 2.1 2.71683772 5
19 17.9 -2.00000000 1
20 6.1 1.79239169 1
21 11.9 -1.69897000 3
22 13.8 0.23044892 1
23 14.3 0.54406804 1
24 15.2 -0.31875876 2
25 10.0 1.00000000 4
26 11.9 0.20951501 2
27 6.5 2.28330123 4
28 7.5 0.39794001 5
29 10.6 -0.55284197 3
30 7.4 0.62736586 1
31 8.4 0.83250891 2
32 5.7 -0.12493874 2
33 4.9 0.55630250 3
34 3.2 1.74429298 5
35 11.0 -0.04575749 2
36 4.9 0.30103000 3
37 13.2 -1.00000000 2
38 9.7 0.62221402 4
39 12.8 0.54406804 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) LogWb D
11.6923 -1.8128 -0.8059
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-6.5750 -1.6431 0.3231 2.0186 4.5416
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11.6923 0.9393 12.448 1.32e-14 ***
LogWb -1.8128 0.3706 -4.892 2.09e-05 ***
D -0.8059 0.3361 -2.398 0.0218 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 2.655 on 36 degrees of freedom
Multiple R-squared: 0.5759, Adjusted R-squared: 0.5524
F-statistic: 24.44 on 2 and 36 DF, p-value: 1.969e-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,] 0.4832784 0.9665568 0.5167216
[2,] 0.3103763 0.6207526 0.6896237
[3,] 0.2098385 0.4196769 0.7901615
[4,] 0.1172387 0.2344773 0.8827613
[5,] 0.6755192 0.6489616 0.3244808
[6,] 0.7046082 0.5907837 0.2953918
[7,] 0.6289855 0.7420290 0.3710145
[8,] 0.5737237 0.8525525 0.4262763
[9,] 0.4808187 0.9616373 0.5191813
[10,] 0.4532449 0.9064898 0.5467551
[11,] 0.3602716 0.7205432 0.6397284
[12,] 0.2800542 0.5601085 0.7199458
[13,] 0.2069738 0.4139477 0.7930262
[14,] 0.2986207 0.5972413 0.7013793
[15,] 0.2558316 0.5116631 0.7441684
[16,] 0.1820564 0.3641127 0.8179436
[17,] 0.2221257 0.4442514 0.7778743
[18,] 0.3347294 0.6694588 0.6652706
[19,] 0.4997517 0.9995035 0.5002483
[20,] 0.5363812 0.9272375 0.4636188
[21,] 0.5103888 0.9792225 0.4896112
[22,] 0.4884303 0.9768606 0.5115697
[23,] 0.3886926 0.7773851 0.6113074
[24,] 0.2870768 0.5741535 0.7129232
[25,] 0.2457997 0.4915995 0.7542003
[26,] 0.1542562 0.3085124 0.8457438
[27,] 0.2924047 0.5848094 0.7075953
[28,] 0.3323445 0.6646889 0.6676555
> postscript(file="/var/www/html/freestat/rcomp/tmp/1bixy1292318727.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2bixy1292318727.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3bixy1292318727.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4mre11292318727.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5mre11292318727.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
-2.9747062 -0.1942720 2.4861483 1.8336082 0.7268658 0.9535400 0.5268090
8 9 10 11 12 13 14
1.8666997 0.3726789 -6.5749565 -3.6661583 -1.8476902 -1.7491327 -0.7498653
15 16 17 18 19 20 21
-2.6887226 -0.6875408 -1.0379606 -0.6377947 3.3878906 -1.5371303 -0.4546578
22 23 24 25 26 27 28
3.3313257 4.3998653 4.5415700 3.3439954 2.1992430 2.1704084 0.5584272
29 30 31 32 33 34 35
0.3230828 -2.3491295 -0.1713721 -4.6070664 -3.3662217 -1.3008575 0.8364761
36 37 38 39
-3.8289886 1.3065922 2.3591319 2.8998653
> postscript(file="/var/www/html/freestat/rcomp/tmp/6mre11292318727.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 -2.9747062 NA
1 -0.1942720 -2.9747062
2 2.4861483 -0.1942720
3 1.8336082 2.4861483
4 0.7268658 1.8336082
5 0.9535400 0.7268658
6 0.5268090 0.9535400
7 1.8666997 0.5268090
8 0.3726789 1.8666997
9 -6.5749565 0.3726789
10 -3.6661583 -6.5749565
11 -1.8476902 -3.6661583
12 -1.7491327 -1.8476902
13 -0.7498653 -1.7491327
14 -2.6887226 -0.7498653
15 -0.6875408 -2.6887226
16 -1.0379606 -0.6875408
17 -0.6377947 -1.0379606
18 3.3878906 -0.6377947
19 -1.5371303 3.3878906
20 -0.4546578 -1.5371303
21 3.3313257 -0.4546578
22 4.3998653 3.3313257
23 4.5415700 4.3998653
24 3.3439954 4.5415700
25 2.1992430 3.3439954
26 2.1704084 2.1992430
27 0.5584272 2.1704084
28 0.3230828 0.5584272
29 -2.3491295 0.3230828
30 -0.1713721 -2.3491295
31 -4.6070664 -0.1713721
32 -3.3662217 -4.6070664
33 -1.3008575 -3.3662217
34 0.8364761 -1.3008575
35 -3.8289886 0.8364761
36 1.3065922 -3.8289886
37 2.3591319 1.3065922
38 2.8998653 2.3591319
39 NA 2.8998653
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.1942720 -2.9747062
[2,] 2.4861483 -0.1942720
[3,] 1.8336082 2.4861483
[4,] 0.7268658 1.8336082
[5,] 0.9535400 0.7268658
[6,] 0.5268090 0.9535400
[7,] 1.8666997 0.5268090
[8,] 0.3726789 1.8666997
[9,] -6.5749565 0.3726789
[10,] -3.6661583 -6.5749565
[11,] -1.8476902 -3.6661583
[12,] -1.7491327 -1.8476902
[13,] -0.7498653 -1.7491327
[14,] -2.6887226 -0.7498653
[15,] -0.6875408 -2.6887226
[16,] -1.0379606 -0.6875408
[17,] -0.6377947 -1.0379606
[18,] 3.3878906 -0.6377947
[19,] -1.5371303 3.3878906
[20,] -0.4546578 -1.5371303
[21,] 3.3313257 -0.4546578
[22,] 4.3998653 3.3313257
[23,] 4.5415700 4.3998653
[24,] 3.3439954 4.5415700
[25,] 2.1992430 3.3439954
[26,] 2.1704084 2.1992430
[27,] 0.5584272 2.1704084
[28,] 0.3230828 0.5584272
[29,] -2.3491295 0.3230828
[30,] -0.1713721 -2.3491295
[31,] -4.6070664 -0.1713721
[32,] -3.3662217 -4.6070664
[33,] -1.3008575 -3.3662217
[34,] 0.8364761 -1.3008575
[35,] -3.8289886 0.8364761
[36,] 1.3065922 -3.8289886
[37,] 2.3591319 1.3065922
[38,] 2.8998653 2.3591319
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.1942720 -2.9747062
2 2.4861483 -0.1942720
3 1.8336082 2.4861483
4 0.7268658 1.8336082
5 0.9535400 0.7268658
6 0.5268090 0.9535400
7 1.8666997 0.5268090
8 0.3726789 1.8666997
9 -6.5749565 0.3726789
10 -3.6661583 -6.5749565
11 -1.8476902 -3.6661583
12 -1.7491327 -1.8476902
13 -0.7498653 -1.7491327
14 -2.6887226 -0.7498653
15 -0.6875408 -2.6887226
16 -1.0379606 -0.6875408
17 -0.6377947 -1.0379606
18 3.3878906 -0.6377947
19 -1.5371303 3.3878906
20 -0.4546578 -1.5371303
21 3.3313257 -0.4546578
22 4.3998653 3.3313257
23 4.5415700 4.3998653
24 3.3439954 4.5415700
25 2.1992430 3.3439954
26 2.1704084 2.1992430
27 0.5584272 2.1704084
28 0.3230828 0.5584272
29 -2.3491295 0.3230828
30 -0.1713721 -2.3491295
31 -4.6070664 -0.1713721
32 -3.3662217 -4.6070664
33 -1.3008575 -3.3662217
34 0.8364761 -1.3008575
35 -3.8289886 0.8364761
36 1.3065922 -3.8289886
37 2.3591319 1.3065922
38 2.8998653 2.3591319
> 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/freestat/rcomp/tmp/7f1w41292318727.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8psdp1292318727.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9psdp1292318727.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/100jcs1292318727.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11wcdb1292318728.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/freestat/rcomp/tmp/12huuz1292318728.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/freestat/rcomp/tmp/13d4s71292318728.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/freestat/rcomp/tmp/146v9a1292318728.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/freestat/rcomp/tmp/1525pj1292318728.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/freestat/rcomp/tmp/165nnp1292318728.tab")
+ }
>
> try(system("convert tmp/1bixy1292318727.ps tmp/1bixy1292318727.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bixy1292318727.ps tmp/2bixy1292318727.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bixy1292318727.ps tmp/3bixy1292318727.png",intern=TRUE))
character(0)
> try(system("convert tmp/4mre11292318727.ps tmp/4mre11292318727.png",intern=TRUE))
character(0)
> try(system("convert tmp/5mre11292318727.ps tmp/5mre11292318727.png",intern=TRUE))
character(0)
> try(system("convert tmp/6mre11292318727.ps tmp/6mre11292318727.png",intern=TRUE))
character(0)
> try(system("convert tmp/7f1w41292318727.ps tmp/7f1w41292318727.png",intern=TRUE))
character(0)
> try(system("convert tmp/8psdp1292318727.ps tmp/8psdp1292318727.png",intern=TRUE))
character(0)
> try(system("convert tmp/9psdp1292318727.ps tmp/9psdp1292318727.png",intern=TRUE))
character(0)
> try(system("convert tmp/100jcs1292318727.ps tmp/100jcs1292318727.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.575 2.410 3.875