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(4143,0,4429,0,5219,0,4929,0,5761,0,5592,0,4163,0,4962,0,5208,0,4755,0,4491,0,5732,0,5731,0,5040,0,6102,0,4904,0,5369,0,5578,0,4619,0,4731,0,5011,0,5299,0,4146,0,4625,0,4736,0,4219,0,5116,0,4205,1,4121,1,5103,1,4300,1,4578,1,3809,1,5526,1,4248,1,3830,1,4428,1,4834,1,4406,1,4565,1,4104,1,4798,1,3935,1,3792,1,4387,1,4006,1,4078,1,4724,1),dim=c(2,48),dimnames=list(c('y','x
'),1:48))
> y <- array(NA,dim=c(2,48),dimnames=list(c('y','x
'),1:48))
> 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 x\r
1 4143 0
2 4429 0
3 5219 0
4 4929 0
5 5761 0
6 5592 0
7 4163 0
8 4962 0
9 5208 0
10 4755 0
11 4491 0
12 5732 0
13 5731 0
14 5040 0
15 6102 0
16 4904 0
17 5369 0
18 5578 0
19 4619 0
20 4731 0
21 5011 0
22 5299 0
23 4146 0
24 4625 0
25 4736 0
26 4219 0
27 5116 0
28 4205 1
29 4121 1
30 5103 1
31 4300 1
32 4578 1
33 3809 1
34 5526 1
35 4248 1
36 3830 1
37 4428 1
38 4834 1
39 4406 1
40 4565 1
41 4104 1
42 4798 1
43 3935 1
44 3792 1
45 4387 1
46 4006 1
47 4078 1
48 4724 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `x\r`
4985.6 -615.2
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-842.56 -361.50 -40.06 323.50 1155.67
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4985.56 97.26 51.261 < 2e-16 ***
`x\r` -615.22 147.04 -4.184 0.000127 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 505.4 on 46 degrees of freedom
Multiple R-squared: 0.2757, Adjusted R-squared: 0.2599
F-statistic: 17.51 on 1 and 46 DF, p-value: 0.0001275
> 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,] 0.9004136 0.19917284 0.09958642
[2,] 0.9019003 0.19619941 0.09809970
[3,] 0.9370506 0.12589873 0.06294937
[4,] 0.8894791 0.22104188 0.11052094
[5,] 0.8399769 0.32004621 0.16002311
[6,] 0.7724208 0.45515843 0.22757922
[7,] 0.7437255 0.51254909 0.25627455
[8,] 0.8231759 0.35364814 0.17682407
[9,] 0.8719750 0.25605006 0.12802503
[10,] 0.8151259 0.36974828 0.18487414
[11,] 0.9505031 0.09899377 0.04949688
[12,] 0.9243679 0.15126430 0.07563215
[13,] 0.9121193 0.17576137 0.08788069
[14,] 0.9331817 0.13363660 0.06681830
[15,] 0.9160655 0.16786894 0.08393447
[16,] 0.8864271 0.22714576 0.11357288
[17,] 0.8486100 0.30278002 0.15139001
[18,] 0.8516798 0.29664038 0.14832019
[19,] 0.8921249 0.21575023 0.10787512
[20,] 0.8589970 0.28200605 0.14100302
[21,] 0.8117485 0.37650308 0.18825154
[22,] 0.8566583 0.28668335 0.14334168
[23,] 0.8021088 0.39578244 0.19789122
[24,] 0.7397137 0.52057252 0.26028626
[25,] 0.6766234 0.64675324 0.32337662
[26,] 0.7612781 0.47744383 0.23872191
[27,] 0.6867108 0.62657832 0.31328916
[28,] 0.6138301 0.77233971 0.38616986
[29,] 0.6314248 0.73715046 0.36857523
[30,] 0.9379066 0.12418675 0.06209337
[31,] 0.9005478 0.19890435 0.09945218
[32,] 0.9107465 0.17850698 0.08925349
[33,] 0.8572653 0.28546932 0.14273466
[34,] 0.8748261 0.25034770 0.12517385
[35,] 0.8038250 0.39234997 0.19617499
[36,] 0.7460697 0.50786063 0.25393032
[37,] 0.6338690 0.73226201 0.36613100
[38,] 0.7042921 0.59141577 0.29570789
[39,] 0.5843115 0.83137709 0.41568854
> postscript(file="/var/www/html/rcomp/tmp/1k59b1258727520.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2f5y91258727520.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3cwvv1258727520.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4188c1258727520.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5y56l1258727520.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 = 48
Frequency = 1
1 2 3 4 5 6 7
-842.55556 -556.55556 233.44444 -56.55556 775.44444 606.44444 -822.55556
8 9 10 11 12 13 14
-23.55556 222.44444 -230.55556 -494.55556 746.44444 745.44444 54.44444
15 16 17 18 19 20 21
1116.44444 -81.55556 383.44444 592.44444 -366.55556 -254.55556 25.44444
22 23 24 25 26 27 28
313.44444 -839.55556 -360.55556 -249.55556 -766.55556 130.44444 -165.33333
29 30 31 32 33 34 35
-249.33333 732.66667 -70.33333 207.66667 -561.33333 1155.66667 -122.33333
36 37 38 39 40 41 42
-540.33333 57.66667 463.66667 35.66667 194.66667 -266.33333 427.66667
43 44 45 46 47 48
-435.33333 -578.33333 16.66667 -364.33333 -292.33333 353.66667
> postscript(file="/var/www/html/rcomp/tmp/63ux91258727520.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 = 48
Frequency = 1
lag(myerror, k = 1) myerror
0 -842.55556 NA
1 -556.55556 -842.55556
2 233.44444 -556.55556
3 -56.55556 233.44444
4 775.44444 -56.55556
5 606.44444 775.44444
6 -822.55556 606.44444
7 -23.55556 -822.55556
8 222.44444 -23.55556
9 -230.55556 222.44444
10 -494.55556 -230.55556
11 746.44444 -494.55556
12 745.44444 746.44444
13 54.44444 745.44444
14 1116.44444 54.44444
15 -81.55556 1116.44444
16 383.44444 -81.55556
17 592.44444 383.44444
18 -366.55556 592.44444
19 -254.55556 -366.55556
20 25.44444 -254.55556
21 313.44444 25.44444
22 -839.55556 313.44444
23 -360.55556 -839.55556
24 -249.55556 -360.55556
25 -766.55556 -249.55556
26 130.44444 -766.55556
27 -165.33333 130.44444
28 -249.33333 -165.33333
29 732.66667 -249.33333
30 -70.33333 732.66667
31 207.66667 -70.33333
32 -561.33333 207.66667
33 1155.66667 -561.33333
34 -122.33333 1155.66667
35 -540.33333 -122.33333
36 57.66667 -540.33333
37 463.66667 57.66667
38 35.66667 463.66667
39 194.66667 35.66667
40 -266.33333 194.66667
41 427.66667 -266.33333
42 -435.33333 427.66667
43 -578.33333 -435.33333
44 16.66667 -578.33333
45 -364.33333 16.66667
46 -292.33333 -364.33333
47 353.66667 -292.33333
48 NA 353.66667
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -556.55556 -842.55556
[2,] 233.44444 -556.55556
[3,] -56.55556 233.44444
[4,] 775.44444 -56.55556
[5,] 606.44444 775.44444
[6,] -822.55556 606.44444
[7,] -23.55556 -822.55556
[8,] 222.44444 -23.55556
[9,] -230.55556 222.44444
[10,] -494.55556 -230.55556
[11,] 746.44444 -494.55556
[12,] 745.44444 746.44444
[13,] 54.44444 745.44444
[14,] 1116.44444 54.44444
[15,] -81.55556 1116.44444
[16,] 383.44444 -81.55556
[17,] 592.44444 383.44444
[18,] -366.55556 592.44444
[19,] -254.55556 -366.55556
[20,] 25.44444 -254.55556
[21,] 313.44444 25.44444
[22,] -839.55556 313.44444
[23,] -360.55556 -839.55556
[24,] -249.55556 -360.55556
[25,] -766.55556 -249.55556
[26,] 130.44444 -766.55556
[27,] -165.33333 130.44444
[28,] -249.33333 -165.33333
[29,] 732.66667 -249.33333
[30,] -70.33333 732.66667
[31,] 207.66667 -70.33333
[32,] -561.33333 207.66667
[33,] 1155.66667 -561.33333
[34,] -122.33333 1155.66667
[35,] -540.33333 -122.33333
[36,] 57.66667 -540.33333
[37,] 463.66667 57.66667
[38,] 35.66667 463.66667
[39,] 194.66667 35.66667
[40,] -266.33333 194.66667
[41,] 427.66667 -266.33333
[42,] -435.33333 427.66667
[43,] -578.33333 -435.33333
[44,] 16.66667 -578.33333
[45,] -364.33333 16.66667
[46,] -292.33333 -364.33333
[47,] 353.66667 -292.33333
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -556.55556 -842.55556
2 233.44444 -556.55556
3 -56.55556 233.44444
4 775.44444 -56.55556
5 606.44444 775.44444
6 -822.55556 606.44444
7 -23.55556 -822.55556
8 222.44444 -23.55556
9 -230.55556 222.44444
10 -494.55556 -230.55556
11 746.44444 -494.55556
12 745.44444 746.44444
13 54.44444 745.44444
14 1116.44444 54.44444
15 -81.55556 1116.44444
16 383.44444 -81.55556
17 592.44444 383.44444
18 -366.55556 592.44444
19 -254.55556 -366.55556
20 25.44444 -254.55556
21 313.44444 25.44444
22 -839.55556 313.44444
23 -360.55556 -839.55556
24 -249.55556 -360.55556
25 -766.55556 -249.55556
26 130.44444 -766.55556
27 -165.33333 130.44444
28 -249.33333 -165.33333
29 732.66667 -249.33333
30 -70.33333 732.66667
31 207.66667 -70.33333
32 -561.33333 207.66667
33 1155.66667 -561.33333
34 -122.33333 1155.66667
35 -540.33333 -122.33333
36 57.66667 -540.33333
37 463.66667 57.66667
38 35.66667 463.66667
39 194.66667 35.66667
40 -266.33333 194.66667
41 427.66667 -266.33333
42 -435.33333 427.66667
43 -578.33333 -435.33333
44 16.66667 -578.33333
45 -364.33333 16.66667
46 -292.33333 -364.33333
47 353.66667 -292.33333
> 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/76gk31258727520.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/81l1a1258727520.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9p30g1258727520.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10g4441258727520.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11geyv1258727520.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/12g2ac1258727520.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/13k0e91258727520.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/142fgu1258727520.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/15ae2b1258727520.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/1626521258727520.tab")
+ }
>
> system("convert tmp/1k59b1258727520.ps tmp/1k59b1258727520.png")
> system("convert tmp/2f5y91258727520.ps tmp/2f5y91258727520.png")
> system("convert tmp/3cwvv1258727520.ps tmp/3cwvv1258727520.png")
> system("convert tmp/4188c1258727520.ps tmp/4188c1258727520.png")
> system("convert tmp/5y56l1258727520.ps tmp/5y56l1258727520.png")
> system("convert tmp/63ux91258727520.ps tmp/63ux91258727520.png")
> system("convert tmp/76gk31258727520.ps tmp/76gk31258727520.png")
> system("convert tmp/81l1a1258727520.ps tmp/81l1a1258727520.png")
> system("convert tmp/9p30g1258727520.ps tmp/9p30g1258727520.png")
> system("convert tmp/10g4441258727520.ps tmp/10g4441258727520.png")
>
>
> proc.time()
user system elapsed
2.381 1.546 3.869