R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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(70.5,4.0,370,53.5,315.0,6166,65.0,4.0,684,76.5,1.7,449,70.0,8.0,643,71.0,5.6,1551,60.5,15.0,616,51.5,503.0,36660,78.0,2.6,403,76.0,2.6,346,57.5,44.0,2471,61.0,24.0,7427,64.5,23.0,2992,78.5,3.8,233,79.0,1.8,609,61.0,96.0,7615,70.0,90.0,370,70.0,4.9,1066,72.0,6.6,600,64.5,21.0,4873,54.5,592.0,3485,56.5,73.0,2364,64.5,14.0,1016,64.5,8.8,1062,73.0,3.9,480,72.0,6.0,559,69.0,3.2,259,64.0,11.0,1340,78.5,2.6,275,53.0,23.0,12550,75.0,3.2,965,68.5,11.0,4883,70.0,5.0,1189,70.5,3.0,226,76.0,3.0,611,75.5,1.3,404,74.5,5.6,576,65.0,29.0,3096),dim=c(3,38),dimnames=list(c('le','ppt','ppp'),1:38))
> y <- array(NA,dim=c(3,38),dimnames=list(c('le','ppt','ppp'),1:38))
> 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
> 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
le ppt ppp
1 70.5 4.0 370
2 53.5 315.0 6166
3 65.0 4.0 684
4 76.5 1.7 449
5 70.0 8.0 643
6 71.0 5.6 1551
7 60.5 15.0 616
8 51.5 503.0 36660
9 78.0 2.6 403
10 76.0 2.6 346
11 57.5 44.0 2471
12 61.0 24.0 7427
13 64.5 23.0 2992
14 78.5 3.8 233
15 79.0 1.8 609
16 61.0 96.0 7615
17 70.0 90.0 370
18 70.0 4.9 1066
19 72.0 6.6 600
20 64.5 21.0 4873
21 54.5 592.0 3485
22 56.5 73.0 2364
23 64.5 14.0 1016
24 64.5 8.8 1062
25 73.0 3.9 480
26 72.0 6.0 559
27 69.0 3.2 259
28 64.0 11.0 1340
29 78.5 2.6 275
30 53.0 23.0 12550
31 75.0 3.2 965
32 68.5 11.0 4883
33 70.0 5.0 1189
34 70.5 3.0 226
35 76.0 3.0 611
36 75.5 1.3 404
37 74.5 5.6 576
38 65.0 29.0 3096
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) ppt ppp
70.251957 -0.023495 -0.000432
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-11.2894 -4.6266 0.3977 5.0872 9.0535
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 70.2519573 1.0877047 64.587 <2e-16 ***
ppt -0.0234954 0.0096469 -2.436 0.0201 *
ppp -0.0004320 0.0002023 -2.136 0.0398 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.003 on 35 degrees of freedom
Multiple R-squared: 0.44, Adjusted R-squared: 0.408
F-statistic: 13.75 on 2 and 35 DF, p-value: 3.916e-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,] 0.3463106 0.69262116 0.65368942
[2,] 0.5329962 0.93400750 0.46700375
[3,] 0.6691158 0.66176836 0.33088418
[4,] 0.7899808 0.42003843 0.21001922
[5,] 0.7738892 0.45222168 0.22611084
[6,] 0.9430489 0.11390221 0.05695110
[7,] 0.9523906 0.09521881 0.04760941
[8,] 0.9324837 0.13503258 0.06751629
[9,] 0.9603651 0.07926990 0.03963495
[10,] 0.9802175 0.03956495 0.01978247
[11,] 0.9719639 0.05607227 0.02803613
[12,] 0.9550538 0.08989231 0.04494616
[13,] 0.9249051 0.15018976 0.07509488
[14,] 0.8842337 0.23153257 0.11576628
[15,] 0.8408458 0.31830838 0.15915419
[16,] 0.9692253 0.06154944 0.03077472
[17,] 0.9783038 0.04339239 0.02169619
[18,] 0.9734986 0.05300275 0.02650138
[19,] 0.9829577 0.03408457 0.01704229
[20,] 0.9676396 0.06472082 0.03236041
[21,] 0.9401171 0.11976582 0.05988291
[22,] 0.9396543 0.12069139 0.06034569
[23,] 0.9829482 0.03410352 0.01705176
[24,] 0.9850258 0.02994849 0.01497424
[25,] 0.9783100 0.04338007 0.02169004
[26,] 0.9510656 0.09786878 0.04893439
[27,] 0.8712952 0.25740953 0.12870476
> postscript(file="/var/wessaorg/rcomp/tmp/150zf1322142298.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/28mos1322142298.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3w8oq1322142298.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4awvj1322142298.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5zfiu1322142298.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 = 38
Frequency = 1
1 2 3 4 5 6
0.5018816 -6.6869152 -4.8624557 6.4819740 0.2138119 1.5497217
7 8 9 10 11 12
-9.1333858 8.9050556 7.9832456 5.9586189 -10.6505730 -5.4792552
13 14 15 16 17 18
-3.9188792 8.4379921 9.0534510 -3.7063641 2.0224830 0.3237321
19 20 21 22 23 24
2.1623403 -3.1531894 -0.3370171 -11.0154364 -4.9840624 -5.0863641
25 26 27 28 29 30
3.0470572 2.1305292 -1.0648719 -5.4145652 8.4279436 -11.2893736
31 32 33 34 35 36
5.2401533 0.6161774 0.3792235 0.4161714 6.0825095 5.4531337
37 38
4.6284759 -3.2329741
> postscript(file="/var/wessaorg/rcomp/tmp/6vaqp1322142298.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 = 38
Frequency = 1
lag(myerror, k = 1) myerror
0 0.5018816 NA
1 -6.6869152 0.5018816
2 -4.8624557 -6.6869152
3 6.4819740 -4.8624557
4 0.2138119 6.4819740
5 1.5497217 0.2138119
6 -9.1333858 1.5497217
7 8.9050556 -9.1333858
8 7.9832456 8.9050556
9 5.9586189 7.9832456
10 -10.6505730 5.9586189
11 -5.4792552 -10.6505730
12 -3.9188792 -5.4792552
13 8.4379921 -3.9188792
14 9.0534510 8.4379921
15 -3.7063641 9.0534510
16 2.0224830 -3.7063641
17 0.3237321 2.0224830
18 2.1623403 0.3237321
19 -3.1531894 2.1623403
20 -0.3370171 -3.1531894
21 -11.0154364 -0.3370171
22 -4.9840624 -11.0154364
23 -5.0863641 -4.9840624
24 3.0470572 -5.0863641
25 2.1305292 3.0470572
26 -1.0648719 2.1305292
27 -5.4145652 -1.0648719
28 8.4279436 -5.4145652
29 -11.2893736 8.4279436
30 5.2401533 -11.2893736
31 0.6161774 5.2401533
32 0.3792235 0.6161774
33 0.4161714 0.3792235
34 6.0825095 0.4161714
35 5.4531337 6.0825095
36 4.6284759 5.4531337
37 -3.2329741 4.6284759
38 NA -3.2329741
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -6.6869152 0.5018816
[2,] -4.8624557 -6.6869152
[3,] 6.4819740 -4.8624557
[4,] 0.2138119 6.4819740
[5,] 1.5497217 0.2138119
[6,] -9.1333858 1.5497217
[7,] 8.9050556 -9.1333858
[8,] 7.9832456 8.9050556
[9,] 5.9586189 7.9832456
[10,] -10.6505730 5.9586189
[11,] -5.4792552 -10.6505730
[12,] -3.9188792 -5.4792552
[13,] 8.4379921 -3.9188792
[14,] 9.0534510 8.4379921
[15,] -3.7063641 9.0534510
[16,] 2.0224830 -3.7063641
[17,] 0.3237321 2.0224830
[18,] 2.1623403 0.3237321
[19,] -3.1531894 2.1623403
[20,] -0.3370171 -3.1531894
[21,] -11.0154364 -0.3370171
[22,] -4.9840624 -11.0154364
[23,] -5.0863641 -4.9840624
[24,] 3.0470572 -5.0863641
[25,] 2.1305292 3.0470572
[26,] -1.0648719 2.1305292
[27,] -5.4145652 -1.0648719
[28,] 8.4279436 -5.4145652
[29,] -11.2893736 8.4279436
[30,] 5.2401533 -11.2893736
[31,] 0.6161774 5.2401533
[32,] 0.3792235 0.6161774
[33,] 0.4161714 0.3792235
[34,] 6.0825095 0.4161714
[35,] 5.4531337 6.0825095
[36,] 4.6284759 5.4531337
[37,] -3.2329741 4.6284759
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -6.6869152 0.5018816
2 -4.8624557 -6.6869152
3 6.4819740 -4.8624557
4 0.2138119 6.4819740
5 1.5497217 0.2138119
6 -9.1333858 1.5497217
7 8.9050556 -9.1333858
8 7.9832456 8.9050556
9 5.9586189 7.9832456
10 -10.6505730 5.9586189
11 -5.4792552 -10.6505730
12 -3.9188792 -5.4792552
13 8.4379921 -3.9188792
14 9.0534510 8.4379921
15 -3.7063641 9.0534510
16 2.0224830 -3.7063641
17 0.3237321 2.0224830
18 2.1623403 0.3237321
19 -3.1531894 2.1623403
20 -0.3370171 -3.1531894
21 -11.0154364 -0.3370171
22 -4.9840624 -11.0154364
23 -5.0863641 -4.9840624
24 3.0470572 -5.0863641
25 2.1305292 3.0470572
26 -1.0648719 2.1305292
27 -5.4145652 -1.0648719
28 8.4279436 -5.4145652
29 -11.2893736 8.4279436
30 5.2401533 -11.2893736
31 0.6161774 5.2401533
32 0.3792235 0.6161774
33 0.4161714 0.3792235
34 6.0825095 0.4161714
35 5.4531337 6.0825095
36 4.6284759 5.4531337
37 -3.2329741 4.6284759
> 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/wessaorg/rcomp/tmp/7o15t1322142298.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8wwi11322142298.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9whh51322142298.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/1035x01322142298.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/11dmrn1322142298.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/wessaorg/rcomp/tmp/12im6i1322142298.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/wessaorg/rcomp/tmp/132pdx1322142298.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/wessaorg/rcomp/tmp/14z3no1322142298.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/wessaorg/rcomp/tmp/155si21322142298.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/wessaorg/rcomp/tmp/16o04l1322142298.tab")
+ }
>
> try(system("convert tmp/150zf1322142298.ps tmp/150zf1322142298.png",intern=TRUE))
character(0)
> try(system("convert tmp/28mos1322142298.ps tmp/28mos1322142298.png",intern=TRUE))
character(0)
> try(system("convert tmp/3w8oq1322142298.ps tmp/3w8oq1322142298.png",intern=TRUE))
character(0)
> try(system("convert tmp/4awvj1322142298.ps tmp/4awvj1322142298.png",intern=TRUE))
character(0)
> try(system("convert tmp/5zfiu1322142298.ps tmp/5zfiu1322142298.png",intern=TRUE))
character(0)
> try(system("convert tmp/6vaqp1322142298.ps tmp/6vaqp1322142298.png",intern=TRUE))
character(0)
> try(system("convert tmp/7o15t1322142298.ps tmp/7o15t1322142298.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wwi11322142298.ps tmp/8wwi11322142298.png",intern=TRUE))
character(0)
> try(system("convert tmp/9whh51322142298.ps tmp/9whh51322142298.png",intern=TRUE))
character(0)
> try(system("convert tmp/1035x01322142298.ps tmp/1035x01322142298.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.572 0.758 4.645