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(70.5,4,370,53.5,315,6166,65,4,684,76.5,17,449,70,8,643,71,56,1551,60.5,15,616,51.5,503,36660,78,26,403,76,26,346,57.5,44,2471,61,24,7427,64.5,23,2992,78.5,38,233,79,18,609,61,96,7615,70,90,370,70,49,1066,72,66,600,64.5,21,4873,54.5,592,3485,56.5,73,2364,64.5,14,1016,64.5,88,1062,73,39,480,72,6,559,69,32,259,64,11,1340,78.5,26,275,53,23,12550,75,32,965,52.5,NA,25229,68.5,11,4883,70,5,1189,70.5,3,226,76,3,611,75.5,13,404,74.5,56,576,65,29,3096,54,NA,23193),dim=c(3,40),dimnames=list(c('Y','X1','X2'),1:40))
> y <- array(NA,dim=c(3,40),dimnames=list(c('Y','X1','X2'),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
Y X1 X2
1 70.5 4 370
2 53.5 315 6166
3 65.0 4 684
4 76.5 17 449
5 70.0 8 643
6 71.0 56 1551
7 60.5 15 616
8 51.5 503 36660
9 78.0 26 403
10 76.0 26 346
11 57.5 44 2471
12 61.0 24 7427
13 64.5 23 2992
14 78.5 38 233
15 79.0 18 609
16 61.0 96 7615
17 70.0 90 370
18 70.0 49 1066
19 72.0 66 600
20 64.5 21 4873
21 54.5 592 3485
22 56.5 73 2364
23 64.5 14 1016
24 64.5 88 1062
25 73.0 39 480
26 72.0 6 559
27 69.0 32 259
28 64.0 11 1340
29 78.5 26 275
30 53.0 23 12550
31 75.0 32 965
32 52.5 NA 25229
33 68.5 11 4883
34 70.0 5 1189
35 70.5 3 226
36 76.0 3 611
37 75.5 13 404
38 74.5 56 576
39 65.0 29 3096
40 54.0 NA 23193
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X1 X2
70.5119635 -0.0195089 -0.0004996
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-11.4067 -4.0098 0.2153 5.4247 9.1435
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 70.5119635 1.1477722 61.434 <2e-16 ***
X1 -0.0195089 0.0099579 -1.959 0.0581 .
X2 -0.0004996 0.0002032 -2.459 0.0190 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.163 on 35 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 0.4098, Adjusted R-squared: 0.3761
F-statistic: 12.15 on 2 and 35 DF, p-value: 9.814e-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,] 0.1867137 0.37342733 0.81328634
[2,] 0.5304074 0.93918523 0.46959261
[3,] 0.7476014 0.50479721 0.25239860
[4,] 0.8562778 0.28744446 0.14372223
[5,] 0.8504819 0.29903622 0.14951811
[6,] 0.9671946 0.06561082 0.03280541
[7,] 0.9672408 0.06551837 0.03275918
[8,] 0.9525684 0.09486325 0.04743163
[9,] 0.9751838 0.04963235 0.02481617
[10,] 0.9874919 0.02501624 0.01250812
[11,] 0.9813824 0.03723517 0.01861759
[12,] 0.9669782 0.06604359 0.03302179
[13,] 0.9433307 0.11333857 0.05666928
[14,] 0.9148950 0.17021007 0.08510504
[15,] 0.8753716 0.24925675 0.12462837
[16,] 0.8667655 0.26646892 0.13323446
[17,] 0.9485809 0.10283814 0.05141907
[18,] 0.9629598 0.07408038 0.03704019
[19,] 0.9672853 0.06542936 0.03271468
[20,] 0.9431988 0.11360231 0.05680115
[21,] 0.9013727 0.19725460 0.09862730
[22,] 0.8892411 0.22151785 0.11075893
[23,] 0.9593549 0.08129018 0.04064509
[24,] 0.9617836 0.07643282 0.03821641
[25,] 0.9316139 0.13677214 0.06838607
[26,] 0.8782967 0.24340656 0.12170328
[27,] 0.8860426 0.22791486 0.11395743
[28,] 0.7298585 0.54028294 0.27014147
[29,] 0.9020652 0.19586966 0.09793483
> postscript(file="/var/www/html/rcomp/tmp/1m4lg1290511219.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/2m4lg1290511219.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3m4lg1290511219.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4xvk01290511219.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xvk01290511219.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
0.25093888 -7.78587863 -5.09217417 6.54402620 -0.03462379 2.35547671
7 8 9 10 11 12
-9.41155174 9.11781645 8.19662290 6.16814342 -10.91896138 -5.33292380
13 14 15 16 17 18
-4.06833595 8.84579096 9.14347750 -3.83435038 1.42870466 0.97658900
19 20 21 22 23 24
3.07540815 -3.16753098 -2.72144687 -11.40666463 -5.23120465 -3.76456229
25 26 27 28 29 30
3.48871093 1.88438865 -0.75827183 -5.62784802 8.63266898 -10.79277717
31 33 34 35 36 37
5.59447399 0.64237637 0.17965292 0.15948183 5.85184321 5.44350678
38 39
5.36832774 -3.39931996
> postscript(file="/var/www/html/rcomp/tmp/6xvk01290511219.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 0.25093888 NA
1 -7.78587863 0.25093888
2 -5.09217417 -7.78587863
3 6.54402620 -5.09217417
4 -0.03462379 6.54402620
5 2.35547671 -0.03462379
6 -9.41155174 2.35547671
7 9.11781645 -9.41155174
8 8.19662290 9.11781645
9 6.16814342 8.19662290
10 -10.91896138 6.16814342
11 -5.33292380 -10.91896138
12 -4.06833595 -5.33292380
13 8.84579096 -4.06833595
14 9.14347750 8.84579096
15 -3.83435038 9.14347750
16 1.42870466 -3.83435038
17 0.97658900 1.42870466
18 3.07540815 0.97658900
19 -3.16753098 3.07540815
20 -2.72144687 -3.16753098
21 -11.40666463 -2.72144687
22 -5.23120465 -11.40666463
23 -3.76456229 -5.23120465
24 3.48871093 -3.76456229
25 1.88438865 3.48871093
26 -0.75827183 1.88438865
27 -5.62784802 -0.75827183
28 8.63266898 -5.62784802
29 -10.79277717 8.63266898
30 5.59447399 -10.79277717
31 0.64237637 5.59447399
32 0.17965292 0.64237637
33 0.15948183 0.17965292
34 5.85184321 0.15948183
35 5.44350678 5.85184321
36 5.36832774 5.44350678
37 -3.39931996 5.36832774
38 NA -3.39931996
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7.78587863 0.25093888
[2,] -5.09217417 -7.78587863
[3,] 6.54402620 -5.09217417
[4,] -0.03462379 6.54402620
[5,] 2.35547671 -0.03462379
[6,] -9.41155174 2.35547671
[7,] 9.11781645 -9.41155174
[8,] 8.19662290 9.11781645
[9,] 6.16814342 8.19662290
[10,] -10.91896138 6.16814342
[11,] -5.33292380 -10.91896138
[12,] -4.06833595 -5.33292380
[13,] 8.84579096 -4.06833595
[14,] 9.14347750 8.84579096
[15,] -3.83435038 9.14347750
[16,] 1.42870466 -3.83435038
[17,] 0.97658900 1.42870466
[18,] 3.07540815 0.97658900
[19,] -3.16753098 3.07540815
[20,] -2.72144687 -3.16753098
[21,] -11.40666463 -2.72144687
[22,] -5.23120465 -11.40666463
[23,] -3.76456229 -5.23120465
[24,] 3.48871093 -3.76456229
[25,] 1.88438865 3.48871093
[26,] -0.75827183 1.88438865
[27,] -5.62784802 -0.75827183
[28,] 8.63266898 -5.62784802
[29,] -10.79277717 8.63266898
[30,] 5.59447399 -10.79277717
[31,] 0.64237637 5.59447399
[32,] 0.17965292 0.64237637
[33,] 0.15948183 0.17965292
[34,] 5.85184321 0.15948183
[35,] 5.44350678 5.85184321
[36,] 5.36832774 5.44350678
[37,] -3.39931996 5.36832774
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7.78587863 0.25093888
2 -5.09217417 -7.78587863
3 6.54402620 -5.09217417
4 -0.03462379 6.54402620
5 2.35547671 -0.03462379
6 -9.41155174 2.35547671
7 9.11781645 -9.41155174
8 8.19662290 9.11781645
9 6.16814342 8.19662290
10 -10.91896138 6.16814342
11 -5.33292380 -10.91896138
12 -4.06833595 -5.33292380
13 8.84579096 -4.06833595
14 9.14347750 8.84579096
15 -3.83435038 9.14347750
16 1.42870466 -3.83435038
17 0.97658900 1.42870466
18 3.07540815 0.97658900
19 -3.16753098 3.07540815
20 -2.72144687 -3.16753098
21 -11.40666463 -2.72144687
22 -5.23120465 -11.40666463
23 -3.76456229 -5.23120465
24 3.48871093 -3.76456229
25 1.88438865 3.48871093
26 -0.75827183 1.88438865
27 -5.62784802 -0.75827183
28 8.63266898 -5.62784802
29 -10.79277717 8.63266898
30 5.59447399 -10.79277717
31 0.64237637 5.59447399
32 0.17965292 0.64237637
33 0.15948183 0.17965292
34 5.85184321 0.15948183
35 5.44350678 5.85184321
36 5.36832774 5.44350678
37 -3.39931996 5.36832774
> 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/7p4141290511219.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/80vi61290511219.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/90vi61290511219.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/100vi61290511219.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11engx1290511219.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/1206fl1290511219.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13vxuu1290511219.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14zyt01290511219.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/15khso1290511219.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/16oh8b1290511219.tab")
+ }
>
> try(system("convert tmp/1m4lg1290511219.ps tmp/1m4lg1290511219.png",intern=TRUE))
character(0)
> try(system("convert tmp/2m4lg1290511219.ps tmp/2m4lg1290511219.png",intern=TRUE))
character(0)
> try(system("convert tmp/3m4lg1290511219.ps tmp/3m4lg1290511219.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xvk01290511219.ps tmp/4xvk01290511219.png",intern=TRUE))
character(0)
> try(system("convert tmp/5xvk01290511219.ps tmp/5xvk01290511219.png",intern=TRUE))
character(0)
> try(system("convert tmp/6xvk01290511219.ps tmp/6xvk01290511219.png",intern=TRUE))
character(0)
> try(system("convert tmp/7p4141290511219.ps tmp/7p4141290511219.png",intern=TRUE))
character(0)
> try(system("convert tmp/80vi61290511219.ps tmp/80vi61290511219.png",intern=TRUE))
character(0)
> try(system("convert tmp/90vi61290511219.ps tmp/90vi61290511219.png",intern=TRUE))
character(0)
> try(system("convert tmp/100vi61290511219.ps tmp/100vi61290511219.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.323 1.593 5.959