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(2.0,3.0,1.8,4.0,0.7,4.0,3.9,1.0,1.0,4.0,3.6,1.0,1.4,1.0,1.5,4.0,0.7,5.0,2.1,1.0,4.1,2.0,1.2,2.0,0.5,5.0,3.4,2.0,1.5,1.0,3.4,3.0,0.8,4.0,0.8,5.0,2.0,1.0,1.9,1.0,1.3,3.0,5.6,1.0,3.1,1.0,1.8,2.0,0.9,4.0,1.8,2.0,1.9,4.0,0.9,5.0,2.6,3.0,2.4,1.0,1.2,2.0,0.9,2.0,0.5,3.0,0.6,5.0,2.3,2.0,0.5,3.0,2.6,2.0,0.6,4.0,6.6,1.0),dim=c(2,39),dimnames=list(c('PS','D'),1:39))
> y <- array(NA,dim=c(2,39),dimnames=list(c('PS','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
PS D
1 2.0 3
2 1.8 4
3 0.7 4
4 3.9 1
5 1.0 4
6 3.6 1
7 1.4 1
8 1.5 4
9 0.7 5
10 2.1 1
11 4.1 2
12 1.2 2
13 0.5 5
14 3.4 2
15 1.5 1
16 3.4 3
17 0.8 4
18 0.8 5
19 2.0 1
20 1.9 1
21 1.3 3
22 5.6 1
23 3.1 1
24 1.8 2
25 0.9 4
26 1.8 2
27 1.9 4
28 0.9 5
29 2.6 3
30 2.4 1
31 1.2 2
32 0.9 2
33 0.5 3
34 0.6 5
35 2.3 2
36 0.5 3
37 2.6 2
38 0.6 4
39 6.6 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D
3.5532 -0.5978
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.55535 -0.70861 -0.06405 0.48813 3.64465
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.5532 0.3906 9.097 5.67e-11 ***
D -0.5978 0.1296 -4.611 4.65e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.135 on 37 degrees of freedom
Multiple R-squared: 0.365, Adjusted R-squared: 0.3478
F-statistic: 21.27 on 1 and 37 DF, p-value: 4.653e-05
> 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,] 0.07174336 0.14348671 0.9282566
[2,] 0.02489920 0.04979841 0.9751008
[3,] 0.30948366 0.61896732 0.6905163
[4,] 0.19892981 0.39785962 0.8010702
[5,] 0.11613706 0.23227412 0.8838629
[6,] 0.09255373 0.18510745 0.9074463
[7,] 0.20879693 0.41759386 0.7912031
[8,] 0.22321486 0.44642972 0.7767851
[9,] 0.15149896 0.30299791 0.8485010
[10,] 0.14236263 0.28472525 0.8576374
[11,] 0.18287473 0.36574947 0.8171253
[12,] 0.25677307 0.51354615 0.7432269
[13,] 0.19522061 0.39044122 0.8047794
[14,] 0.13810333 0.27620667 0.8618967
[15,] 0.12091104 0.24182208 0.8790890
[16,] 0.11441890 0.22883780 0.8855811
[17,] 0.07927153 0.15854305 0.9207285
[18,] 0.34531036 0.69062071 0.6546896
[19,] 0.26019700 0.52039399 0.7398030
[20,] 0.20168232 0.40336465 0.7983177
[21,] 0.14120772 0.28241545 0.8587923
[22,] 0.10181488 0.20362975 0.8981851
[23,] 0.08000885 0.16001770 0.9199912
[24,] 0.05978670 0.11957340 0.9402133
[25,] 0.05092781 0.10185563 0.9490722
[26,] 0.03705435 0.07410870 0.9629457
[27,] 0.03892755 0.07785510 0.9610724
[28,] 0.07827702 0.15655404 0.9217230
[29,] 0.08519478 0.17038957 0.9148052
[30,] 0.15804378 0.31608756 0.8419562
> postscript(file="/var/www/html/rcomp/tmp/11rbs1292239459.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/21rbs1292239459.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3c1ad1292239459.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4c1ad1292239459.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5c1ad1292239459.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
0.24030100 0.63812709 -0.46187291 0.94464883 -0.16187291 0.64464883
7 8 9 10 11 12
-1.55535117 0.33812709 0.13595318 -0.85535117 1.74247492 -1.15752508
13 14 15 16 17 18
-0.06404682 1.04247492 -1.45535117 1.64030100 -0.36187291 0.23595318
19 20 21 22 23 24
-0.95535117 -1.05535117 -0.45969900 2.64464883 0.14464883 -0.55752508
25 26 27 28 29 30
-0.26187291 -0.55752508 0.73812709 0.33595318 0.84030100 -0.55535117
31 32 33 34 35 36
-1.15752508 -1.45752508 -1.25969900 0.03595318 -0.05752508 -1.25969900
37 38 39
0.24247492 -0.56187291 3.64464883
> postscript(file="/var/www/html/rcomp/tmp/65ary1292239459.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 0.24030100 NA
1 0.63812709 0.24030100
2 -0.46187291 0.63812709
3 0.94464883 -0.46187291
4 -0.16187291 0.94464883
5 0.64464883 -0.16187291
6 -1.55535117 0.64464883
7 0.33812709 -1.55535117
8 0.13595318 0.33812709
9 -0.85535117 0.13595318
10 1.74247492 -0.85535117
11 -1.15752508 1.74247492
12 -0.06404682 -1.15752508
13 1.04247492 -0.06404682
14 -1.45535117 1.04247492
15 1.64030100 -1.45535117
16 -0.36187291 1.64030100
17 0.23595318 -0.36187291
18 -0.95535117 0.23595318
19 -1.05535117 -0.95535117
20 -0.45969900 -1.05535117
21 2.64464883 -0.45969900
22 0.14464883 2.64464883
23 -0.55752508 0.14464883
24 -0.26187291 -0.55752508
25 -0.55752508 -0.26187291
26 0.73812709 -0.55752508
27 0.33595318 0.73812709
28 0.84030100 0.33595318
29 -0.55535117 0.84030100
30 -1.15752508 -0.55535117
31 -1.45752508 -1.15752508
32 -1.25969900 -1.45752508
33 0.03595318 -1.25969900
34 -0.05752508 0.03595318
35 -1.25969900 -0.05752508
36 0.24247492 -1.25969900
37 -0.56187291 0.24247492
38 3.64464883 -0.56187291
39 NA 3.64464883
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.63812709 0.24030100
[2,] -0.46187291 0.63812709
[3,] 0.94464883 -0.46187291
[4,] -0.16187291 0.94464883
[5,] 0.64464883 -0.16187291
[6,] -1.55535117 0.64464883
[7,] 0.33812709 -1.55535117
[8,] 0.13595318 0.33812709
[9,] -0.85535117 0.13595318
[10,] 1.74247492 -0.85535117
[11,] -1.15752508 1.74247492
[12,] -0.06404682 -1.15752508
[13,] 1.04247492 -0.06404682
[14,] -1.45535117 1.04247492
[15,] 1.64030100 -1.45535117
[16,] -0.36187291 1.64030100
[17,] 0.23595318 -0.36187291
[18,] -0.95535117 0.23595318
[19,] -1.05535117 -0.95535117
[20,] -0.45969900 -1.05535117
[21,] 2.64464883 -0.45969900
[22,] 0.14464883 2.64464883
[23,] -0.55752508 0.14464883
[24,] -0.26187291 -0.55752508
[25,] -0.55752508 -0.26187291
[26,] 0.73812709 -0.55752508
[27,] 0.33595318 0.73812709
[28,] 0.84030100 0.33595318
[29,] -0.55535117 0.84030100
[30,] -1.15752508 -0.55535117
[31,] -1.45752508 -1.15752508
[32,] -1.25969900 -1.45752508
[33,] 0.03595318 -1.25969900
[34,] -0.05752508 0.03595318
[35,] -1.25969900 -0.05752508
[36,] 0.24247492 -1.25969900
[37,] -0.56187291 0.24247492
[38,] 3.64464883 -0.56187291
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.63812709 0.24030100
2 -0.46187291 0.63812709
3 0.94464883 -0.46187291
4 -0.16187291 0.94464883
5 0.64464883 -0.16187291
6 -1.55535117 0.64464883
7 0.33812709 -1.55535117
8 0.13595318 0.33812709
9 -0.85535117 0.13595318
10 1.74247492 -0.85535117
11 -1.15752508 1.74247492
12 -0.06404682 -1.15752508
13 1.04247492 -0.06404682
14 -1.45535117 1.04247492
15 1.64030100 -1.45535117
16 -0.36187291 1.64030100
17 0.23595318 -0.36187291
18 -0.95535117 0.23595318
19 -1.05535117 -0.95535117
20 -0.45969900 -1.05535117
21 2.64464883 -0.45969900
22 0.14464883 2.64464883
23 -0.55752508 0.14464883
24 -0.26187291 -0.55752508
25 -0.55752508 -0.26187291
26 0.73812709 -0.55752508
27 0.33595318 0.73812709
28 0.84030100 0.33595318
29 -0.55535117 0.84030100
30 -1.15752508 -0.55535117
31 -1.45752508 -1.15752508
32 -1.25969900 -1.45752508
33 0.03595318 -1.25969900
34 -0.05752508 0.03595318
35 -1.25969900 -0.05752508
36 0.24247492 -1.25969900
37 -0.56187291 0.24247492
38 3.64464883 -0.56187291
> 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/7x1911292239459.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8x1911292239459.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9x1911292239459.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10qs841292239459.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11btor1292239459.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/12ftny1292239459.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/13t3l71292239459.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/14fm1u1292239459.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/1504001292239459.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/163ngo1292239459.tab")
+ }
>
> try(system("convert tmp/11rbs1292239459.ps tmp/11rbs1292239459.png",intern=TRUE))
character(0)
> try(system("convert tmp/21rbs1292239459.ps tmp/21rbs1292239459.png",intern=TRUE))
character(0)
> try(system("convert tmp/3c1ad1292239459.ps tmp/3c1ad1292239459.png",intern=TRUE))
character(0)
> try(system("convert tmp/4c1ad1292239459.ps tmp/4c1ad1292239459.png",intern=TRUE))
character(0)
> try(system("convert tmp/5c1ad1292239459.ps tmp/5c1ad1292239459.png",intern=TRUE))
character(0)
> try(system("convert tmp/65ary1292239459.ps tmp/65ary1292239459.png",intern=TRUE))
character(0)
> try(system("convert tmp/7x1911292239459.ps tmp/7x1911292239459.png",intern=TRUE))
character(0)
> try(system("convert tmp/8x1911292239459.ps tmp/8x1911292239459.png",intern=TRUE))
character(0)
> try(system("convert tmp/9x1911292239459.ps tmp/9x1911292239459.png",intern=TRUE))
character(0)
> try(system("convert tmp/10qs841292239459.ps tmp/10qs841292239459.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.286 1.610 6.607