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.
Type 'q()' to quit R.
> x <- array(list(6.3,0,3,2.1,3.406028945,4,9.1,1.02325246,4,15.8,-1.638272164,1,5.2,2.204119983,4,10.9,0.51851394,1,8.3,1.717337583,1,11,-0.37161107,4,3.2,2.667452953,5,6.3,-1.124938737,1,6.6,-0.105130343,2,9.5,-0.698970004,2,3.3,1.441852176,5,11,-0.920818754,2,4.7,1.929418926,1,10.4,-0.995678626,3,7.4,0.017033339,4,2.1,2.716837723,5,17.9,-2,1,6.1,1.792391689,1,11.9,-1.638272164,3,13.8,0.230448921,1,14.3,0.544068044,1,15.2,-0.318758763,2,10,1,4,11.9,0.209515015,2,6.5,2.283301229,4,7.5,0.397940009,5,10.6,-0.552841969,3,7.4,0.626853415,1,8.4,0.832508913,2,5.7,-0.124938737,2,4.9,0.556302501,3,3.2,1.744292983,5,11,-0.045757491,2,4.9,0.301029996,3,13.2,-0.982966661,2,9.7,0.622214023,4,12.8,0.544068044,1),dim=c(3,39),dimnames=list(c('SWS','LogBodyWheight','Total_Danger'),1:39))
> y <- array(NA,dim=c(3,39),dimnames=list(c('SWS','LogBodyWheight','Total_Danger'),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 LogBodyWheight Total_Danger
1 6.3 0.00000000 3
2 2.1 3.40602895 4
3 9.1 1.02325246 4
4 15.8 -1.63827216 1
5 5.2 2.20411998 4
6 10.9 0.51851394 1
7 8.3 1.71733758 1
8 11.0 -0.37161107 4
9 3.2 2.66745295 5
10 6.3 -1.12493874 1
11 6.6 -0.10513034 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 -0.99567863 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 -1.63827216 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 0.62685342 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 -0.98296666 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) LogBodyWheight Total_Danger
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 ***
LogBodyWheight -1.8149 0.3729 -4.866 2.26e-05 ***
Total_Danger -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,] 0.4874176 0.9748352 0.5125824
[2,] 0.3145223 0.6290446 0.6854777
[3,] 0.2118516 0.4237032 0.7881484
[4,] 0.1186435 0.2372870 0.8813565
[5,] 0.6866983 0.6266033 0.3133017
[6,] 0.7152216 0.5695569 0.2847784
[7,] 0.6410260 0.7179479 0.3589740
[8,] 0.5852073 0.8295854 0.4147927
[9,] 0.4931101 0.9862202 0.5068899
[10,] 0.4659547 0.9319093 0.5340453
[11,] 0.3727594 0.7455188 0.6272406
[12,] 0.2914924 0.5829848 0.7085076
[13,] 0.2167447 0.4334894 0.7832553
[14,] 0.3077384 0.6154768 0.6922616
[15,] 0.2636949 0.5273898 0.7363051
[16,] 0.1882603 0.3765205 0.8117397
[17,] 0.2275901 0.4551802 0.7724099
[18,] 0.3396932 0.6793864 0.6603068
[19,] 0.5035276 0.9929449 0.4964724
[20,] 0.5394326 0.9211349 0.4605674
[21,] 0.5129440 0.9741121 0.4870560
[22,] 0.4907645 0.9815291 0.5092355
[23,] 0.3908121 0.7816243 0.6091879
[24,] 0.2888068 0.5776137 0.7111932
[25,] 0.2474804 0.4949607 0.7525196
[26,] 0.1555120 0.3110241 0.8444880
[27,] 0.2939875 0.5879749 0.7060125
[28,] 0.3338171 0.6676341 0.6661829
> postscript(file="/var/www/html/freestat/rcomp/tmp/1zwqa1292413985.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2zwqa1292413985.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3s5pv1292413985.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4s5pv1292413985.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5s5pv1292413985.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
-2.9804580 -0.1927817 2.4828170 1.9338766 0.7259241 0.9481374 0.5238323
8 9 10 11 12 13 14
1.8513376 0.3730246 -6.6344960 -3.6774715 -1.8552063 -1.7512670 -0.7578303
15 16 17 18 19 20 21
-2.6912701 -0.6874734 -1.0433279 -0.6373490 3.3773919 -1.5399551 -0.3536895
22 23 24 25 26 27 28
3.3253403 4.3945145 4.5348232 3.3406171 2.1935651 2.1696268 0.5541805
29 30 31 32 33 34 35
0.3162123 -2.3552418 -0.1757893 -4.6134210 -3.3708478 -1.3023798 0.8302818
36 37 38 39
-3.8341312 1.3293801 2.3549891 2.8945145
> postscript(file="/var/www/html/freestat/rcomp/tmp/6keog1292413985.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 -2.9804580 NA
1 -0.1927817 -2.9804580
2 2.4828170 -0.1927817
3 1.9338766 2.4828170
4 0.7259241 1.9338766
5 0.9481374 0.7259241
6 0.5238323 0.9481374
7 1.8513376 0.5238323
8 0.3730246 1.8513376
9 -6.6344960 0.3730246
10 -3.6774715 -6.6344960
11 -1.8552063 -3.6774715
12 -1.7512670 -1.8552063
13 -0.7578303 -1.7512670
14 -2.6912701 -0.7578303
15 -0.6874734 -2.6912701
16 -1.0433279 -0.6874734
17 -0.6373490 -1.0433279
18 3.3773919 -0.6373490
19 -1.5399551 3.3773919
20 -0.3536895 -1.5399551
21 3.3253403 -0.3536895
22 4.3945145 3.3253403
23 4.5348232 4.3945145
24 3.3406171 4.5348232
25 2.1935651 3.3406171
26 2.1696268 2.1935651
27 0.5541805 2.1696268
28 0.3162123 0.5541805
29 -2.3552418 0.3162123
30 -0.1757893 -2.3552418
31 -4.6134210 -0.1757893
32 -3.3708478 -4.6134210
33 -1.3023798 -3.3708478
34 0.8302818 -1.3023798
35 -3.8341312 0.8302818
36 1.3293801 -3.8341312
37 2.3549891 1.3293801
38 2.8945145 2.3549891
39 NA 2.8945145
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.1927817 -2.9804580
[2,] 2.4828170 -0.1927817
[3,] 1.9338766 2.4828170
[4,] 0.7259241 1.9338766
[5,] 0.9481374 0.7259241
[6,] 0.5238323 0.9481374
[7,] 1.8513376 0.5238323
[8,] 0.3730246 1.8513376
[9,] -6.6344960 0.3730246
[10,] -3.6774715 -6.6344960
[11,] -1.8552063 -3.6774715
[12,] -1.7512670 -1.8552063
[13,] -0.7578303 -1.7512670
[14,] -2.6912701 -0.7578303
[15,] -0.6874734 -2.6912701
[16,] -1.0433279 -0.6874734
[17,] -0.6373490 -1.0433279
[18,] 3.3773919 -0.6373490
[19,] -1.5399551 3.3773919
[20,] -0.3536895 -1.5399551
[21,] 3.3253403 -0.3536895
[22,] 4.3945145 3.3253403
[23,] 4.5348232 4.3945145
[24,] 3.3406171 4.5348232
[25,] 2.1935651 3.3406171
[26,] 2.1696268 2.1935651
[27,] 0.5541805 2.1696268
[28,] 0.3162123 0.5541805
[29,] -2.3552418 0.3162123
[30,] -0.1757893 -2.3552418
[31,] -4.6134210 -0.1757893
[32,] -3.3708478 -4.6134210
[33,] -1.3023798 -3.3708478
[34,] 0.8302818 -1.3023798
[35,] -3.8341312 0.8302818
[36,] 1.3293801 -3.8341312
[37,] 2.3549891 1.3293801
[38,] 2.8945145 2.3549891
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.1927817 -2.9804580
2 2.4828170 -0.1927817
3 1.9338766 2.4828170
4 0.7259241 1.9338766
5 0.9481374 0.7259241
6 0.5238323 0.9481374
7 1.8513376 0.5238323
8 0.3730246 1.8513376
9 -6.6344960 0.3730246
10 -3.6774715 -6.6344960
11 -1.8552063 -3.6774715
12 -1.7512670 -1.8552063
13 -0.7578303 -1.7512670
14 -2.6912701 -0.7578303
15 -0.6874734 -2.6912701
16 -1.0433279 -0.6874734
17 -0.6373490 -1.0433279
18 3.3773919 -0.6373490
19 -1.5399551 3.3773919
20 -0.3536895 -1.5399551
21 3.3253403 -0.3536895
22 4.3945145 3.3253403
23 4.5348232 4.3945145
24 3.3406171 4.5348232
25 2.1935651 3.3406171
26 2.1696268 2.1935651
27 0.5541805 2.1696268
28 0.3162123 0.5541805
29 -2.3552418 0.3162123
30 -0.1757893 -2.3552418
31 -4.6134210 -0.1757893
32 -3.3708478 -4.6134210
33 -1.3023798 -3.3708478
34 0.8302818 -1.3023798
35 -3.8341312 0.8302818
36 1.3293801 -3.8341312
37 2.3549891 1.3293801
38 2.8945145 2.3549891
> 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/7vno11292413985.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8vno11292413985.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9vno11292413985.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10ox5m1292413985.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11rflr1292413985.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/12vykf1292413985.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/139pi61292413985.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/14uqgc1292413985.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/155hxx1292413985.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/161rdo1292413985.tab")
+ }
> try(system("convert tmp/1zwqa1292413985.ps tmp/1zwqa1292413985.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zwqa1292413985.ps tmp/2zwqa1292413985.png",intern=TRUE))
character(0)
> try(system("convert tmp/3s5pv1292413985.ps tmp/3s5pv1292413985.png",intern=TRUE))
character(0)
> try(system("convert tmp/4s5pv1292413985.ps tmp/4s5pv1292413985.png",intern=TRUE))
character(0)
> try(system("convert tmp/5s5pv1292413985.ps tmp/5s5pv1292413985.png",intern=TRUE))
character(0)
> try(system("convert tmp/6keog1292413985.ps tmp/6keog1292413985.png",intern=TRUE))
character(0)
> try(system("convert tmp/7vno11292413985.ps tmp/7vno11292413985.png",intern=TRUE))
character(0)
> try(system("convert tmp/8vno11292413985.ps tmp/8vno11292413985.png",intern=TRUE))
character(0)
> try(system("convert tmp/9vno11292413985.ps tmp/9vno11292413985.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ox5m1292413985.ps tmp/10ox5m1292413985.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.656 2.436 3.996