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(70.5,4,370,74,53.5,315,6166,53,65,4,684,68,76.5,17,449,80,70,8,643,72,71,56,1551,74,60.5,15,616,61,51.5,503,36660,53,78,26,403,82,76,26,346,79,57.5,44,2471,58,61,24,7427,63,64.5,23,2992,65,78.5,38,233,82,79,18,609,82,61,96,7615,63,70,90,370,73,70,49,1066,73,72,66,600,76,64.5,21,4873,66,54.5,592,3485,56,56.5,73,2364,57,64.5,14,1016,67,64.5,88,1062,67,73,39,480,77,72,6,559,75,69,32,259,74,64,11,1340,67,78.5,26,275,82,53,23,12550,54,75,32,965,78,52.5,NA,25229,55,68.5,11,4883,71,70,5,1189,72,70.5,3,226,75,76,3,611,79,75.5,13,404,79,74.5,56,576,78,65,29,3096,67,54,NA,23193,56),dim=c(4,40),dimnames=list(c('Yt','X1t','X2t','X3t'),1:40))
> y <- array(NA,dim=c(4,40),dimnames=list(c('Yt','X1t','X2t','X3t'),1:40))
> 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
Yt X1t X2t X3t
1 70.5 4 370 74
2 53.5 315 6166 53
3 65.0 4 684 68
4 76.5 17 449 80
5 70.0 8 643 72
6 71.0 56 1551 74
7 60.5 15 616 61
8 51.5 503 36660 53
9 78.0 26 403 82
10 76.0 26 346 79
11 57.5 44 2471 58
12 61.0 24 7427 63
13 64.5 23 2992 65
14 78.5 38 233 82
15 79.0 18 609 82
16 61.0 96 7615 63
17 70.0 90 370 73
18 70.0 49 1066 73
19 72.0 66 600 76
20 64.5 21 4873 66
21 54.5 592 3485 56
22 56.5 73 2364 57
23 64.5 14 1016 67
24 64.5 88 1062 67
25 73.0 39 480 77
26 72.0 6 559 75
27 69.0 32 259 74
28 64.0 11 1340 67
29 78.5 26 275 82
30 53.0 23 12550 54
31 75.0 32 965 78
32 52.5 NA 25229 55
33 68.5 11 4883 71
34 70.0 5 1189 72
35 70.5 3 226 75
36 76.0 3 611 79
37 75.5 13 404 79
38 74.5 56 576 78
39 65.0 29 3096 67
40 54.0 NA 23193 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X1t X2t X3t
6.820e+00 -8.664e-04 -2.242e-05 8.684e-01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.05194 -0.39529 0.03299 0.49425 1.31759
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.820e+00 1.271e+00 5.366 5.74e-06 ***
X1t -8.664e-04 1.219e-03 -0.711 0.482
X2t -2.242e-05 2.552e-05 -0.879 0.386
X3t 8.684e-01 1.723e-02 50.395 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7187 on 34 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 0.9922, Adjusted R-squared: 0.9915
F-statistic: 1442 on 3 and 34 DF, p-value: < 2.2e-16
> 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,] 0.6218941 0.7562118 0.3781059
[2,] 0.5287144 0.9425711 0.4712856
[3,] 0.3748904 0.7497807 0.6251096
[4,] 0.3227079 0.6454158 0.6772921
[5,] 0.2346255 0.4692510 0.7653745
[6,] 0.1519846 0.3039693 0.8480154
[7,] 0.4112227 0.8224455 0.5887773
[8,] 0.3300929 0.6601857 0.6699071
[9,] 0.3849715 0.7699431 0.6150285
[10,] 0.3177326 0.6354651 0.6822674
[11,] 0.2803221 0.5606442 0.7196779
[12,] 0.2180361 0.4360721 0.7819639
[13,] 0.2664394 0.5328788 0.7335606
[14,] 0.2264830 0.4529659 0.7735170
[15,] 0.1975436 0.3950872 0.8024564
[16,] 0.2233100 0.4466200 0.7766900
[17,] 0.1940190 0.3880380 0.8059810
[18,] 0.1941164 0.3882328 0.8058836
[19,] 0.1624887 0.3249774 0.8375113
[20,] 0.1061885 0.2123770 0.8938115
[21,] 0.5760618 0.8478764 0.4239382
[22,] 0.5188000 0.9624000 0.4812000
[23,] 0.3969524 0.7939049 0.6030476
[24,] 0.3091813 0.6183626 0.6908187
[25,] 0.2016279 0.4032557 0.7983721
[26,] 0.2065571 0.4131143 0.7934429
[27,] 0.8785476 0.2429047 0.1214524
> postscript(file="/var/www/html/rcomp/tmp/13dc21290524733.ps",horizontal=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$resid)
Warning message:
In x[, 1] - mysum$resid :
longer object length is not a multiple of shorter object length
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2wmt51290524733.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3wmt51290524733.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4wmt51290524733.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/57dbq1290524733.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 38
Frequency = 1
1 2 3 4 5 6
-0.573707874 1.063131813 -0.855975808 0.228636037 0.672776519 -0.002171910
7 8 9 10 11 12
0.731168984 -0.090175101 -0.001494832 0.602572377 0.403237235 -0.345197664
13 14 15 16 17 18
1.317586719 0.505089801 0.996193409 -0.278601173 -0.130749126 -0.150664076
19 20 21 22 23 24
-0.751730477 0.489585781 -0.362341028 0.294411850 -0.471418449 -0.406273427
25 26 27 28 29 30
-0.646262636 0.063814671 -2.051937823 -0.966752134 0.495634843 -0.415147579
31 33 34 35 36 37
0.490099948 0.138903706 0.682421055 -1.446251855 0.588587678 0.092609811
38 39
0.002170418 0.088220316
> postscript(file="/var/www/html/rcomp/tmp/67dbq1290524733.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 38
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.573707874 NA
1 1.063131813 -0.573707874
2 -0.855975808 1.063131813
3 0.228636037 -0.855975808
4 0.672776519 0.228636037
5 -0.002171910 0.672776519
6 0.731168984 -0.002171910
7 -0.090175101 0.731168984
8 -0.001494832 -0.090175101
9 0.602572377 -0.001494832
10 0.403237235 0.602572377
11 -0.345197664 0.403237235
12 1.317586719 -0.345197664
13 0.505089801 1.317586719
14 0.996193409 0.505089801
15 -0.278601173 0.996193409
16 -0.130749126 -0.278601173
17 -0.150664076 -0.130749126
18 -0.751730477 -0.150664076
19 0.489585781 -0.751730477
20 -0.362341028 0.489585781
21 0.294411850 -0.362341028
22 -0.471418449 0.294411850
23 -0.406273427 -0.471418449
24 -0.646262636 -0.406273427
25 0.063814671 -0.646262636
26 -2.051937823 0.063814671
27 -0.966752134 -2.051937823
28 0.495634843 -0.966752134
29 -0.415147579 0.495634843
30 0.490099948 -0.415147579
31 0.138903706 0.490099948
32 0.682421055 0.138903706
33 -1.446251855 0.682421055
34 0.588587678 -1.446251855
35 0.092609811 0.588587678
36 0.002170418 0.092609811
37 0.088220316 0.002170418
38 NA 0.088220316
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.063131813 -0.573707874
[2,] -0.855975808 1.063131813
[3,] 0.228636037 -0.855975808
[4,] 0.672776519 0.228636037
[5,] -0.002171910 0.672776519
[6,] 0.731168984 -0.002171910
[7,] -0.090175101 0.731168984
[8,] -0.001494832 -0.090175101
[9,] 0.602572377 -0.001494832
[10,] 0.403237235 0.602572377
[11,] -0.345197664 0.403237235
[12,] 1.317586719 -0.345197664
[13,] 0.505089801 1.317586719
[14,] 0.996193409 0.505089801
[15,] -0.278601173 0.996193409
[16,] -0.130749126 -0.278601173
[17,] -0.150664076 -0.130749126
[18,] -0.751730477 -0.150664076
[19,] 0.489585781 -0.751730477
[20,] -0.362341028 0.489585781
[21,] 0.294411850 -0.362341028
[22,] -0.471418449 0.294411850
[23,] -0.406273427 -0.471418449
[24,] -0.646262636 -0.406273427
[25,] 0.063814671 -0.646262636
[26,] -2.051937823 0.063814671
[27,] -0.966752134 -2.051937823
[28,] 0.495634843 -0.966752134
[29,] -0.415147579 0.495634843
[30,] 0.490099948 -0.415147579
[31,] 0.138903706 0.490099948
[32,] 0.682421055 0.138903706
[33,] -1.446251855 0.682421055
[34,] 0.588587678 -1.446251855
[35,] 0.092609811 0.588587678
[36,] 0.002170418 0.092609811
[37,] 0.088220316 0.002170418
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.063131813 -0.573707874
2 -0.855975808 1.063131813
3 0.228636037 -0.855975808
4 0.672776519 0.228636037
5 -0.002171910 0.672776519
6 0.731168984 -0.002171910
7 -0.090175101 0.731168984
8 -0.001494832 -0.090175101
9 0.602572377 -0.001494832
10 0.403237235 0.602572377
11 -0.345197664 0.403237235
12 1.317586719 -0.345197664
13 0.505089801 1.317586719
14 0.996193409 0.505089801
15 -0.278601173 0.996193409
16 -0.130749126 -0.278601173
17 -0.150664076 -0.130749126
18 -0.751730477 -0.150664076
19 0.489585781 -0.751730477
20 -0.362341028 0.489585781
21 0.294411850 -0.362341028
22 -0.471418449 0.294411850
23 -0.406273427 -0.471418449
24 -0.646262636 -0.406273427
25 0.063814671 -0.646262636
26 -2.051937823 0.063814671
27 -0.966752134 -2.051937823
28 0.495634843 -0.966752134
29 -0.415147579 0.495634843
30 0.490099948 -0.415147579
31 0.138903706 0.490099948
32 0.682421055 0.138903706
33 -1.446251855 0.682421055
34 0.588587678 -1.446251855
35 0.092609811 0.588587678
36 0.002170418 0.092609811
37 0.088220316 0.002170418
> 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/7z5at1290524733.ps",horizontal=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/8z5at1290524733.ps",horizontal=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/9aw9e1290524733.ps",horizontal=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/10aw9e1290524733.ps",horizontal=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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11depk1290524733.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12hxo71290524733.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13ny3j1290524733.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14yp2m1290524733.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/1528js1290524733.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/16yih11290524733.tab")
+ }
>
> try(system("convert tmp/13dc21290524733.ps tmp/13dc21290524733.png",intern=TRUE))
character(0)
> try(system("convert tmp/2wmt51290524733.ps tmp/2wmt51290524733.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wmt51290524733.ps tmp/3wmt51290524733.png",intern=TRUE))
character(0)
> try(system("convert tmp/4wmt51290524733.ps tmp/4wmt51290524733.png",intern=TRUE))
character(0)
> try(system("convert tmp/57dbq1290524733.ps tmp/57dbq1290524733.png",intern=TRUE))
character(0)
> try(system("convert tmp/67dbq1290524733.ps tmp/67dbq1290524733.png",intern=TRUE))
character(0)
> try(system("convert tmp/7z5at1290524733.ps tmp/7z5at1290524733.png",intern=TRUE))
character(0)
> try(system("convert tmp/8z5at1290524733.ps tmp/8z5at1290524733.png",intern=TRUE))
character(0)
> try(system("convert tmp/9aw9e1290524733.ps tmp/9aw9e1290524733.png",intern=TRUE))
character(0)
> try(system("convert tmp/10aw9e1290524733.ps tmp/10aw9e1290524733.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.298 1.595 5.284