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 = '3'
> #'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
X2t Yt X1t X3t
1 370 70.5 4 74
2 6166 53.5 315 53
3 684 65.0 4 68
4 449 76.5 17 80
5 643 70.0 8 72
6 1551 71.0 56 74
7 616 60.5 15 61
8 36660 51.5 503 53
9 403 78.0 26 82
10 346 76.0 26 79
11 2471 57.5 44 58
12 7427 61.0 24 63
13 2992 64.5 23 65
14 233 78.5 38 82
15 609 79.0 18 82
16 7615 61.0 96 63
17 370 70.0 90 73
18 1066 70.0 49 73
19 600 72.0 66 76
20 4873 64.5 21 66
21 3485 54.5 592 56
22 2364 56.5 73 57
23 1016 64.5 14 67
24 1062 64.5 88 67
25 480 73.0 39 77
26 559 72.0 6 75
27 259 69.0 32 74
28 1340 64.0 11 67
29 275 78.5 26 82
30 12550 53.0 23 54
31 965 75.0 32 78
32 25229 52.5 NA 55
33 4883 68.5 11 71
34 1189 70.0 5 72
35 226 70.5 3 75
36 611 76.0 3 79
37 404 75.5 13 79
38 576 74.5 56 78
39 3096 65.0 29 67
40 23193 54.0 NA 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Yt X1t X3t
25578.13 -990.44 18.56 615.09
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-13545.017 -2236.329 4.996 1236.121 20155.511
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 25578.130 10607.786 2.411 0.0214 *
Yt -990.438 1127.032 -0.879 0.3857
X1t 18.557 7.513 2.470 0.0187 *
X3t 615.089 990.827 0.621 0.5389
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 4776 on 34 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 0.4575, Adjusted R-squared: 0.4097
F-statistic: 9.559 on 3 and 34 DF, p-value: 0.0001012
> 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,] 7.351565e-05 0.0001470313 0.9999264843
[2,] 9.990316e-01 0.0019368767 0.0009684384
[3,] 9.975753e-01 0.0048494560 0.0024247280
[4,] 9.947691e-01 0.0104618766 0.0052309383
[5,] 9.954721e-01 0.0090558190 0.0045279095
[6,] 9.960437e-01 0.0079125631 0.0039562816
[7,] 9.984412e-01 0.0031176506 0.0015588253
[8,] 9.965881e-01 0.0068238777 0.0034119388
[9,] 9.947427e-01 0.0105145946 0.0052572973
[10,] 9.949978e-01 0.0100043952 0.0050021976
[11,] 9.952507e-01 0.0094985887 0.0047492944
[12,] 9.911720e-01 0.0176559600 0.0088279800
[13,] 9.885740e-01 0.0228519252 0.0114259626
[14,] 9.838005e-01 0.0323989171 0.0161994585
[15,] 9.997743e-01 0.0004514931 0.0002257466
[16,] 9.998447e-01 0.0003105882 0.0001552941
[17,] 9.998455e-01 0.0003089363 0.0001544682
[18,] 9.998817e-01 0.0002366396 0.0001183198
[19,] 9.995657e-01 0.0008686565 0.0004343282
[20,] 9.985873e-01 0.0028253861 0.0014126930
[21,] 9.957255e-01 0.0085489597 0.0042744798
[22,] 9.958870e-01 0.0082260719 0.0041130360
[23,] 9.900989e-01 0.0198022323 0.0099011161
[24,] 9.909088e-01 0.0181824501 0.0090912250
[25,] 9.625704e-01 0.0748591241 0.0374295621
[26,] 9.885564e-01 0.0228872056 0.0114436028
[27,] 9.887334e-01 0.0225332269 0.0112666135
> postscript(file="/var/www/html/rcomp/tmp/1nzog1290524147.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/2nzog1290524147.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3xqni1290524147.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4xqni1290524147.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xqni1290524147.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-973.09599 -4868.89609 -2415.96862 1116.75426 -39.36490 -261.84178
7 8 9 10 11 12
-2839.44192 20155.51093 1159.21954 966.61135 -2648.64091 3069.58586
13 14 15 16 17 18
889.49625 1261.75416 2504.11313 1921.48110 -2449.12871 -992.29127
19 20 21 22 23 24
-1638.15226 2192.52133 -13545.01732 -3669.14278 -2149.66853 -3476.88731
25 26 27 28 29 30
-881.76442 49.35731 -3089.34854 -2265.21625 1526.43829 5823.44330
31 33 34 35 36 37
1098.92072 3274.39675 562.30613 -1713.62792 1658.42259 770.63374
38 39
-230.66628 147.19506
> postscript(file="/var/www/html/rcomp/tmp/6qh4m1290524147.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 -973.09599 NA
1 -4868.89609 -973.09599
2 -2415.96862 -4868.89609
3 1116.75426 -2415.96862
4 -39.36490 1116.75426
5 -261.84178 -39.36490
6 -2839.44192 -261.84178
7 20155.51093 -2839.44192
8 1159.21954 20155.51093
9 966.61135 1159.21954
10 -2648.64091 966.61135
11 3069.58586 -2648.64091
12 889.49625 3069.58586
13 1261.75416 889.49625
14 2504.11313 1261.75416
15 1921.48110 2504.11313
16 -2449.12871 1921.48110
17 -992.29127 -2449.12871
18 -1638.15226 -992.29127
19 2192.52133 -1638.15226
20 -13545.01732 2192.52133
21 -3669.14278 -13545.01732
22 -2149.66853 -3669.14278
23 -3476.88731 -2149.66853
24 -881.76442 -3476.88731
25 49.35731 -881.76442
26 -3089.34854 49.35731
27 -2265.21625 -3089.34854
28 1526.43829 -2265.21625
29 5823.44330 1526.43829
30 1098.92072 5823.44330
31 3274.39675 1098.92072
32 562.30613 3274.39675
33 -1713.62792 562.30613
34 1658.42259 -1713.62792
35 770.63374 1658.42259
36 -230.66628 770.63374
37 147.19506 -230.66628
38 NA 147.19506
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4868.89609 -973.09599
[2,] -2415.96862 -4868.89609
[3,] 1116.75426 -2415.96862
[4,] -39.36490 1116.75426
[5,] -261.84178 -39.36490
[6,] -2839.44192 -261.84178
[7,] 20155.51093 -2839.44192
[8,] 1159.21954 20155.51093
[9,] 966.61135 1159.21954
[10,] -2648.64091 966.61135
[11,] 3069.58586 -2648.64091
[12,] 889.49625 3069.58586
[13,] 1261.75416 889.49625
[14,] 2504.11313 1261.75416
[15,] 1921.48110 2504.11313
[16,] -2449.12871 1921.48110
[17,] -992.29127 -2449.12871
[18,] -1638.15226 -992.29127
[19,] 2192.52133 -1638.15226
[20,] -13545.01732 2192.52133
[21,] -3669.14278 -13545.01732
[22,] -2149.66853 -3669.14278
[23,] -3476.88731 -2149.66853
[24,] -881.76442 -3476.88731
[25,] 49.35731 -881.76442
[26,] -3089.34854 49.35731
[27,] -2265.21625 -3089.34854
[28,] 1526.43829 -2265.21625
[29,] 5823.44330 1526.43829
[30,] 1098.92072 5823.44330
[31,] 3274.39675 1098.92072
[32,] 562.30613 3274.39675
[33,] -1713.62792 562.30613
[34,] 1658.42259 -1713.62792
[35,] 770.63374 1658.42259
[36,] -230.66628 770.63374
[37,] 147.19506 -230.66628
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4868.89609 -973.09599
2 -2415.96862 -4868.89609
3 1116.75426 -2415.96862
4 -39.36490 1116.75426
5 -261.84178 -39.36490
6 -2839.44192 -261.84178
7 20155.51093 -2839.44192
8 1159.21954 20155.51093
9 966.61135 1159.21954
10 -2648.64091 966.61135
11 3069.58586 -2648.64091
12 889.49625 3069.58586
13 1261.75416 889.49625
14 2504.11313 1261.75416
15 1921.48110 2504.11313
16 -2449.12871 1921.48110
17 -992.29127 -2449.12871
18 -1638.15226 -992.29127
19 2192.52133 -1638.15226
20 -13545.01732 2192.52133
21 -3669.14278 -13545.01732
22 -2149.66853 -3669.14278
23 -3476.88731 -2149.66853
24 -881.76442 -3476.88731
25 49.35731 -881.76442
26 -3089.34854 49.35731
27 -2265.21625 -3089.34854
28 1526.43829 -2265.21625
29 5823.44330 1526.43829
30 1098.92072 5823.44330
31 3274.39675 1098.92072
32 562.30613 3274.39675
33 -1713.62792 562.30613
34 1658.42259 -1713.62792
35 770.63374 1658.42259
36 -230.66628 770.63374
37 147.19506 -230.66628
> 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/70qlo1290524147.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/80qlo1290524147.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/90qlo1290524147.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/10b03r1290524147.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11fijf1290524147.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/1201il1290524147.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13eayc1290524147.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14ibw01290524147.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/153bdo1290524147.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/166ctc1290524147.tab")
+ }
>
> try(system("convert tmp/1nzog1290524147.ps tmp/1nzog1290524147.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nzog1290524147.ps tmp/2nzog1290524147.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xqni1290524147.ps tmp/3xqni1290524147.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xqni1290524147.ps tmp/4xqni1290524147.png",intern=TRUE))
character(0)
> try(system("convert tmp/5xqni1290524147.ps tmp/5xqni1290524147.png",intern=TRUE))
character(0)
> try(system("convert tmp/6qh4m1290524147.ps tmp/6qh4m1290524147.png",intern=TRUE))
character(0)
> try(system("convert tmp/70qlo1290524147.ps tmp/70qlo1290524147.png",intern=TRUE))
character(0)
> try(system("convert tmp/80qlo1290524147.ps tmp/80qlo1290524147.png",intern=TRUE))
character(0)
> try(system("convert tmp/90qlo1290524147.ps tmp/90qlo1290524147.png",intern=TRUE))
character(0)
> try(system("convert tmp/10b03r1290524147.ps tmp/10b03r1290524147.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.312 1.588 5.369