R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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> x <- array(list(124.1,0,124.4,0,115.7,0,108.3,0,102.3,0,104.6,0,104,0,103.5,0,96,0,96.6,0,95.4,0,92.1,0,93,0,90.4,0,93.3,0,97.1,0,111,1,114.1,1,113.3,1,111,1,107.2,1,118.3,1,134.1,1,139,1,116.7,1,112.5,1,122.8,1,130,1,125.6,1,123.8,1,135.8,1,136.4,1,135.3,1,149.5,1,159.6,1,161.4,1,175.2,1,199.5,1,245,1,257.8,1),dim=c(2,40),dimnames=list(c('Index','Dummy'),1:40))
> y <- array(NA,dim=c(2,40),dimnames=list(c('Index','Dummy'),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 = 'Include Quarterly 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
Index Dummy Q1 Q2 Q3
1 124.1 0 1 0 0
2 124.4 0 0 1 0
3 115.7 0 0 0 1
4 108.3 0 0 0 0
5 102.3 0 1 0 0
6 104.6 0 0 1 0
7 104.0 0 0 0 1
8 103.5 0 0 0 0
9 96.0 0 1 0 0
10 96.6 0 0 1 0
11 95.4 0 0 0 1
12 92.1 0 0 0 0
13 93.0 0 1 0 0
14 90.4 0 0 1 0
15 93.3 0 0 0 1
16 97.1 0 0 0 0
17 111.0 1 1 0 0
18 114.1 1 0 1 0
19 113.3 1 0 0 1
20 111.0 1 0 0 0
21 107.2 1 1 0 0
22 118.3 1 0 1 0
23 134.1 1 0 0 1
24 139.0 1 0 0 0
25 116.7 1 1 0 0
26 112.5 1 0 1 0
27 122.8 1 0 0 1
28 130.0 1 0 0 0
29 125.6 1 1 0 0
30 123.8 1 0 1 0
31 135.8 1 0 0 1
32 136.4 1 0 0 0
33 135.3 1 1 0 0
34 149.5 1 0 1 0
35 159.6 1 0 0 1
36 161.4 1 0 0 0
37 175.2 1 1 0 0
38 199.5 1 0 1 0
39 245.0 1 0 0 1
40 257.8 1 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy Q1 Q2 Q3
109.32 40.57 -15.02 -10.29 -1.76
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-38.888 -17.455 -8.948 8.038 107.912
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 109.32 12.13 9.009 1.21e-10 ***
Dummy 40.57 10.56 3.841 0.000493 ***
Q1 -15.02 14.63 -1.026 0.311771
Q2 -10.29 14.63 -0.703 0.486623
Q3 -1.76 14.63 -0.120 0.904962
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 32.72 on 35 degrees of freedom
Multiple R-squared: 0.316, Adjusted R-squared: 0.2378
F-statistic: 4.042 on 4 and 35 DF, p-value: 0.00848
> 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,] 5.981969e-02 1.196394e-01 0.9401803
[2,] 3.106214e-02 6.212428e-02 0.9689379
[3,] 1.679868e-02 3.359735e-02 0.9832013
[4,] 7.489616e-03 1.497923e-02 0.9925104
[5,] 3.225589e-03 6.451179e-03 0.9967744
[6,] 1.499892e-03 2.999785e-03 0.9985001
[7,] 8.545506e-04 1.709101e-03 0.9991454
[8,] 3.280940e-04 6.561880e-04 0.9996719
[9,] 9.526463e-05 1.905293e-04 0.9999047
[10,] 2.646862e-05 5.293724e-05 0.9999735
[11,] 7.322642e-06 1.464528e-05 0.9999927
[12,] 2.447909e-06 4.895818e-06 0.9999976
[13,] 9.494907e-07 1.898981e-06 0.9999991
[14,] 2.798039e-07 5.596078e-07 0.9999997
[15,] 7.588817e-08 1.517763e-07 0.9999999
[16,] 8.663496e-08 1.732699e-07 0.9999999
[17,] 1.481680e-07 2.963359e-07 0.9999999
[18,] 3.944177e-08 7.888354e-08 1.0000000
[19,] 1.562788e-08 3.125575e-08 1.0000000
[20,] 8.752578e-09 1.750516e-08 1.0000000
[21,] 7.026047e-09 1.405209e-08 1.0000000
[22,] 2.209552e-09 4.419104e-09 1.0000000
[23,] 1.098409e-09 2.196819e-09 1.0000000
[24,] 2.465612e-09 4.931224e-09 1.0000000
[25,] 1.441012e-08 2.882025e-08 1.0000000
> postscript(file="/var/www/html/freestat/rcomp/tmp/19ke91229529409.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2v09s1229529409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3cp1m1229529409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4rs2e1229529409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5kms91229529409.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 = 40
Frequency = 1
1 2 3 4 5 6
29.8025000 25.3725000 8.1425000 -1.0175000 8.0025000 5.5725000
7 8 9 10 11 12
-3.5575000 -5.8175000 1.7025000 -2.4275000 -12.1575000 -17.2175000
13 14 15 16 17 18
-1.2975000 -8.6275000 -14.2575000 -12.2175000 -23.8683333 -25.4983333
19 20 21 22 23 24
-34.8283333 -38.8883333 -27.6683333 -21.2983333 -14.0283333 -10.8883333
25 26 27 28 29 30
-18.1683333 -27.0983333 -25.3283333 -19.8883333 -9.2683333 -15.7983333
31 32 33 34 35 36
-12.3283333 -13.4883333 0.4316667 9.9016667 11.4716667 11.5116667
37 38 39 40
40.3316667 59.9016667 96.8716667 107.9116667
> postscript(file="/var/www/html/freestat/rcomp/tmp/6q3a91229529409.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 = 40
Frequency = 1
lag(myerror, k = 1) myerror
0 29.8025000 NA
1 25.3725000 29.8025000
2 8.1425000 25.3725000
3 -1.0175000 8.1425000
4 8.0025000 -1.0175000
5 5.5725000 8.0025000
6 -3.5575000 5.5725000
7 -5.8175000 -3.5575000
8 1.7025000 -5.8175000
9 -2.4275000 1.7025000
10 -12.1575000 -2.4275000
11 -17.2175000 -12.1575000
12 -1.2975000 -17.2175000
13 -8.6275000 -1.2975000
14 -14.2575000 -8.6275000
15 -12.2175000 -14.2575000
16 -23.8683333 -12.2175000
17 -25.4983333 -23.8683333
18 -34.8283333 -25.4983333
19 -38.8883333 -34.8283333
20 -27.6683333 -38.8883333
21 -21.2983333 -27.6683333
22 -14.0283333 -21.2983333
23 -10.8883333 -14.0283333
24 -18.1683333 -10.8883333
25 -27.0983333 -18.1683333
26 -25.3283333 -27.0983333
27 -19.8883333 -25.3283333
28 -9.2683333 -19.8883333
29 -15.7983333 -9.2683333
30 -12.3283333 -15.7983333
31 -13.4883333 -12.3283333
32 0.4316667 -13.4883333
33 9.9016667 0.4316667
34 11.4716667 9.9016667
35 11.5116667 11.4716667
36 40.3316667 11.5116667
37 59.9016667 40.3316667
38 96.8716667 59.9016667
39 107.9116667 96.8716667
40 NA 107.9116667
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 25.3725000 29.8025000
[2,] 8.1425000 25.3725000
[3,] -1.0175000 8.1425000
[4,] 8.0025000 -1.0175000
[5,] 5.5725000 8.0025000
[6,] -3.5575000 5.5725000
[7,] -5.8175000 -3.5575000
[8,] 1.7025000 -5.8175000
[9,] -2.4275000 1.7025000
[10,] -12.1575000 -2.4275000
[11,] -17.2175000 -12.1575000
[12,] -1.2975000 -17.2175000
[13,] -8.6275000 -1.2975000
[14,] -14.2575000 -8.6275000
[15,] -12.2175000 -14.2575000
[16,] -23.8683333 -12.2175000
[17,] -25.4983333 -23.8683333
[18,] -34.8283333 -25.4983333
[19,] -38.8883333 -34.8283333
[20,] -27.6683333 -38.8883333
[21,] -21.2983333 -27.6683333
[22,] -14.0283333 -21.2983333
[23,] -10.8883333 -14.0283333
[24,] -18.1683333 -10.8883333
[25,] -27.0983333 -18.1683333
[26,] -25.3283333 -27.0983333
[27,] -19.8883333 -25.3283333
[28,] -9.2683333 -19.8883333
[29,] -15.7983333 -9.2683333
[30,] -12.3283333 -15.7983333
[31,] -13.4883333 -12.3283333
[32,] 0.4316667 -13.4883333
[33,] 9.9016667 0.4316667
[34,] 11.4716667 9.9016667
[35,] 11.5116667 11.4716667
[36,] 40.3316667 11.5116667
[37,] 59.9016667 40.3316667
[38,] 96.8716667 59.9016667
[39,] 107.9116667 96.8716667
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 25.3725000 29.8025000
2 8.1425000 25.3725000
3 -1.0175000 8.1425000
4 8.0025000 -1.0175000
5 5.5725000 8.0025000
6 -3.5575000 5.5725000
7 -5.8175000 -3.5575000
8 1.7025000 -5.8175000
9 -2.4275000 1.7025000
10 -12.1575000 -2.4275000
11 -17.2175000 -12.1575000
12 -1.2975000 -17.2175000
13 -8.6275000 -1.2975000
14 -14.2575000 -8.6275000
15 -12.2175000 -14.2575000
16 -23.8683333 -12.2175000
17 -25.4983333 -23.8683333
18 -34.8283333 -25.4983333
19 -38.8883333 -34.8283333
20 -27.6683333 -38.8883333
21 -21.2983333 -27.6683333
22 -14.0283333 -21.2983333
23 -10.8883333 -14.0283333
24 -18.1683333 -10.8883333
25 -27.0983333 -18.1683333
26 -25.3283333 -27.0983333
27 -19.8883333 -25.3283333
28 -9.2683333 -19.8883333
29 -15.7983333 -9.2683333
30 -12.3283333 -15.7983333
31 -13.4883333 -12.3283333
32 0.4316667 -13.4883333
33 9.9016667 0.4316667
34 11.4716667 9.9016667
35 11.5116667 11.4716667
36 40.3316667 11.5116667
37 59.9016667 40.3316667
38 96.8716667 59.9016667
39 107.9116667 96.8716667
> 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/freestat/rcomp/tmp/7d5a11229529409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/821w71229529409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9k9yr1229529409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10er2x1229529409.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11kk9j1229529409.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/freestat/rcomp/tmp/12x42g1229529409.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/freestat/rcomp/tmp/13i3hj1229529409.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/freestat/rcomp/tmp/14jqfq1229529409.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/freestat/rcomp/tmp/15d05k1229529409.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/freestat/rcomp/tmp/16v8921229529409.tab")
+ }
>
> system("convert tmp/19ke91229529409.ps tmp/19ke91229529409.png")
> system("convert tmp/2v09s1229529409.ps tmp/2v09s1229529409.png")
> system("convert tmp/3cp1m1229529409.ps tmp/3cp1m1229529409.png")
> system("convert tmp/4rs2e1229529409.ps tmp/4rs2e1229529409.png")
> system("convert tmp/5kms91229529409.ps tmp/5kms91229529409.png")
> system("convert tmp/6q3a91229529409.ps tmp/6q3a91229529409.png")
> system("convert tmp/7d5a11229529409.ps tmp/7d5a11229529409.png")
> system("convert tmp/821w71229529409.ps tmp/821w71229529409.png")
> system("convert tmp/9k9yr1229529409.ps tmp/9k9yr1229529409.png")
> system("convert tmp/10er2x1229529409.ps tmp/10er2x1229529409.png")
>
>
> proc.time()
user system elapsed
3.430 2.428 4.082