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
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
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> x <- array(list(6.3,0,3,4.9,0.301029996,3,10,1,4,6.1,1.792391689,1,4.7,1.929418926,1,5.2,2.204119983,4,6.5,2.283301229,4,3.2,2.667452953,5,2.1,2.716837723,5,2.1,3.406028945,4,17.9,-2,1,11.9,-1.638272164,3,15.8,-1.638272164,1,6.3,-1.124938737,1,10.4,-0.995678626,3,13.2,-0.982966661,2,11,-0.920818754,2,9.5,-0.698970004,2,10.6,-0.552841969,3,11,-0.37161107,4,15.2,-0.318758763,2,5.7,-0.124938737,2,6.6,-0.105130343,2,11,-0.045757491,2,7.4,0.017033339,4,11.9,0.209515015,2,13.8,0.230448921,1,9.1,1.02325246,4,7.5,0.397940009,5,3.3,1.441852176,5,10.9,0.51851394,1,14.3,0.544068044,1,12.8,0.544068044,1,4.9,0.556302501,3,9.7,0.622214023,4,7.4,0.626853415,1,8.3,1.717337583,1,3.2,1.744292983,5,8.4,0.832508913,2),dim=c(3,39),dimnames=list(c('SWS','BW','D'),1:39))
> y <- array(NA,dim=c(3,39),dimnames=list(c('SWS','BW','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 BW D
1 6.3 0.00000000 3
2 4.9 0.30103000 3
3 10.0 1.00000000 4
4 6.1 1.79239169 1
5 4.7 1.92941893 1
6 5.2 2.20411998 4
7 6.5 2.28330123 4
8 3.2 2.66745295 5
9 2.1 2.71683772 5
10 2.1 3.40602895 4
11 17.9 -2.00000000 1
12 11.9 -1.63827216 3
13 15.8 -1.63827216 1
14 6.3 -1.12493874 1
15 10.4 -0.99567863 3
16 13.2 -0.98296666 2
17 11.0 -0.92081875 2
18 9.5 -0.69897000 2
19 10.6 -0.55284197 3
20 11.0 -0.37161107 4
21 15.2 -0.31875876 2
22 5.7 -0.12493874 2
23 6.6 -0.10513034 2
24 11.0 -0.04575749 2
25 7.4 0.01703334 4
26 11.9 0.20951501 2
27 13.8 0.23044892 1
28 9.1 1.02325246 4
29 7.5 0.39794001 5
30 3.3 1.44185218 5
31 10.9 0.51851394 1
32 14.3 0.54406804 1
33 12.8 0.54406804 1
34 4.9 0.55630250 3
35 9.7 0.62221402 4
36 7.4 0.62685342 1
37 8.3 1.71733758 1
38 3.2 1.74429298 5
39 8.4 0.83250891 2
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) BW D
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 ***
BW -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,] 0.4685909 0.9371819 0.5314091
[2,] 0.3039330 0.6078660 0.6960670
[3,] 0.3374770 0.6749540 0.6625230
[4,] 0.3214316 0.6428632 0.6785684
[5,] 0.2279792 0.4559585 0.7720208
[6,] 0.4651931 0.9303862 0.5348069
[7,] 0.3721069 0.7442138 0.6278931
[8,] 0.3309250 0.6618501 0.6690750
[9,] 0.7506034 0.4987932 0.2493966
[10,] 0.6670804 0.6658392 0.3329196
[11,] 0.6022817 0.7954366 0.3977183
[12,] 0.5078404 0.9843192 0.4921596
[13,] 0.4553225 0.9106451 0.5446775
[14,] 0.3583950 0.7167900 0.6416050
[15,] 0.2955967 0.5911935 0.7044033
[16,] 0.4955515 0.9911030 0.5044485
[17,] 0.6747179 0.6505642 0.3252821
[18,] 0.8124244 0.3751513 0.1875756
[19,] 0.7481202 0.5037596 0.2518798
[20,] 0.7122842 0.5754316 0.2877158
[21,] 0.6515232 0.6969537 0.3484768
[22,] 0.6444058 0.7111883 0.3555942
[23,] 0.6386446 0.7227108 0.3613554
[24,] 0.5285027 0.9429945 0.4714973
[25,] 0.4188187 0.8376373 0.5811813
[26,] 0.2990382 0.5980764 0.7009618
[27,] 0.4018479 0.8036959 0.5981521
[28,] 0.4565837 0.9131674 0.5434163
> postscript(file="/var/www/html/freestat/rcomp/tmp/1q7v71291830454.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2jzua1291830454.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3jzua1291830454.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4jzua1291830454.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5jzua1291830454.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 -3.8341312 3.3406171 -1.5399551 -2.6912701 0.7259241 2.1696268
8 9 10 11 12 13 14
0.3730246 -0.6373490 -0.1927817 3.3773919 -0.3536895 1.9338766 -6.6344960
15 16 17 18 19 20 21
-0.6874734 1.3293801 -0.7578303 -1.8552063 0.3162123 1.8513376 4.5348232
22 23 24 25 26 27 28
-4.6134210 -3.6774715 0.8302818 -1.0433279 2.1935651 3.3253403 2.4828170
29 30 31 32 33 34 35
0.5541805 -1.7512670 0.9481374 4.3945145 2.8945145 -3.3708478 2.3549891
36 37 38 39
-2.3552418 0.5238323 -1.3023798 -0.1757893
> postscript(file="/var/www/html/freestat/rcomp/tmp/6c8tv1291830454.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 -3.8341312 -2.9804580
2 3.3406171 -3.8341312
3 -1.5399551 3.3406171
4 -2.6912701 -1.5399551
5 0.7259241 -2.6912701
6 2.1696268 0.7259241
7 0.3730246 2.1696268
8 -0.6373490 0.3730246
9 -0.1927817 -0.6373490
10 3.3773919 -0.1927817
11 -0.3536895 3.3773919
12 1.9338766 -0.3536895
13 -6.6344960 1.9338766
14 -0.6874734 -6.6344960
15 1.3293801 -0.6874734
16 -0.7578303 1.3293801
17 -1.8552063 -0.7578303
18 0.3162123 -1.8552063
19 1.8513376 0.3162123
20 4.5348232 1.8513376
21 -4.6134210 4.5348232
22 -3.6774715 -4.6134210
23 0.8302818 -3.6774715
24 -1.0433279 0.8302818
25 2.1935651 -1.0433279
26 3.3253403 2.1935651
27 2.4828170 3.3253403
28 0.5541805 2.4828170
29 -1.7512670 0.5541805
30 0.9481374 -1.7512670
31 4.3945145 0.9481374
32 2.8945145 4.3945145
33 -3.3708478 2.8945145
34 2.3549891 -3.3708478
35 -2.3552418 2.3549891
36 0.5238323 -2.3552418
37 -1.3023798 0.5238323
38 -0.1757893 -1.3023798
39 NA -0.1757893
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.8341312 -2.9804580
[2,] 3.3406171 -3.8341312
[3,] -1.5399551 3.3406171
[4,] -2.6912701 -1.5399551
[5,] 0.7259241 -2.6912701
[6,] 2.1696268 0.7259241
[7,] 0.3730246 2.1696268
[8,] -0.6373490 0.3730246
[9,] -0.1927817 -0.6373490
[10,] 3.3773919 -0.1927817
[11,] -0.3536895 3.3773919
[12,] 1.9338766 -0.3536895
[13,] -6.6344960 1.9338766
[14,] -0.6874734 -6.6344960
[15,] 1.3293801 -0.6874734
[16,] -0.7578303 1.3293801
[17,] -1.8552063 -0.7578303
[18,] 0.3162123 -1.8552063
[19,] 1.8513376 0.3162123
[20,] 4.5348232 1.8513376
[21,] -4.6134210 4.5348232
[22,] -3.6774715 -4.6134210
[23,] 0.8302818 -3.6774715
[24,] -1.0433279 0.8302818
[25,] 2.1935651 -1.0433279
[26,] 3.3253403 2.1935651
[27,] 2.4828170 3.3253403
[28,] 0.5541805 2.4828170
[29,] -1.7512670 0.5541805
[30,] 0.9481374 -1.7512670
[31,] 4.3945145 0.9481374
[32,] 2.8945145 4.3945145
[33,] -3.3708478 2.8945145
[34,] 2.3549891 -3.3708478
[35,] -2.3552418 2.3549891
[36,] 0.5238323 -2.3552418
[37,] -1.3023798 0.5238323
[38,] -0.1757893 -1.3023798
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.8341312 -2.9804580
2 3.3406171 -3.8341312
3 -1.5399551 3.3406171
4 -2.6912701 -1.5399551
5 0.7259241 -2.6912701
6 2.1696268 0.7259241
7 0.3730246 2.1696268
8 -0.6373490 0.3730246
9 -0.1927817 -0.6373490
10 3.3773919 -0.1927817
11 -0.3536895 3.3773919
12 1.9338766 -0.3536895
13 -6.6344960 1.9338766
14 -0.6874734 -6.6344960
15 1.3293801 -0.6874734
16 -0.7578303 1.3293801
17 -1.8552063 -0.7578303
18 0.3162123 -1.8552063
19 1.8513376 0.3162123
20 4.5348232 1.8513376
21 -4.6134210 4.5348232
22 -3.6774715 -4.6134210
23 0.8302818 -3.6774715
24 -1.0433279 0.8302818
25 2.1935651 -1.0433279
26 3.3253403 2.1935651
27 2.4828170 3.3253403
28 0.5541805 2.4828170
29 -1.7512670 0.5541805
30 0.9481374 -1.7512670
31 4.3945145 0.9481374
32 2.8945145 4.3945145
33 -3.3708478 2.8945145
34 2.3549891 -3.3708478
35 -2.3552418 2.3549891
36 0.5238323 -2.3552418
37 -1.3023798 0.5238323
38 -0.1757893 -1.3023798
> 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/7mzty1291830454.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8mzty1291830454.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9mzty1291830454.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10fqsj1291830454.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11jrq71291830454.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/12mapv1291830454.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/13i1n31291830454.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/1442391291830454.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/15pkkf1291830454.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/16slil1291830454.tab")
+ }
>
> try(system("convert tmp/1q7v71291830454.ps tmp/1q7v71291830454.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jzua1291830454.ps tmp/2jzua1291830454.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jzua1291830454.ps tmp/3jzua1291830454.png",intern=TRUE))
character(0)
> try(system("convert tmp/4jzua1291830454.ps tmp/4jzua1291830454.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jzua1291830454.ps tmp/5jzua1291830454.png",intern=TRUE))
character(0)
> try(system("convert tmp/6c8tv1291830454.ps tmp/6c8tv1291830454.png",intern=TRUE))
character(0)
> try(system("convert tmp/7mzty1291830454.ps tmp/7mzty1291830454.png",intern=TRUE))
character(0)
> try(system("convert tmp/8mzty1291830454.ps tmp/8mzty1291830454.png",intern=TRUE))
character(0)
> try(system("convert tmp/9mzty1291830454.ps tmp/9mzty1291830454.png",intern=TRUE))
character(0)
> try(system("convert tmp/10fqsj1291830454.ps tmp/10fqsj1291830454.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.792 2.637 4.508