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.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
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(475,2,60,0,0,0,530,1,67,1,0,0,550,2,91,1,1,0,550,1,150,0,2,0,625,3,110,1,2,0,650,2,86,1,2,1,650,2,86,0,0,1,720,3,145,1,2,1,795,3,150,1,0,0,515,2,85,1,2,0,535,2,100,1,2,0,550,2,84,0,0,0,600,2,94,1,0,0,600,2,149,0,1,0,660,3,105,1,2,0,695,2,106,1,0,0,720,3,132,1,0,0,750,2,130,1,2,0,750,3,165,1,2,0,850,2,127,1,2,1,850,2,119,1,0,1,875,3,126,1,2,1,900,2,133,1,2,1,595,2,89,1,1,1,765,3,147,1,2,1,495,1,59,1,0,1,525,1,58,0,0,1,525,1,56,0,0,1,595,2,90,1,2,0,650,1,80,1,0,1,695,3,135,0,0,1,615,2,125,0,2,0,460,2,80,1,0,0,650,2,100,1,1,1,650,2,76,1,0,1,475,1,65,1,1,0,530,2,75,1,1,0,575,2,95,1,2,1,650,2,85,1,1,1,650,1,106,1,0,1,875,2,135,1,0,1,500,2,95,0,1,1,625,2,60,1,2,0,730,2,112,1,2,1,750,2,150,1,1,1,700,2,100,0,2,0,830,2,125,1,0,1,995,2,100,1,2,1,850,3,150,1,2,1),dim=c(6,49),dimnames=list(c('Huurprijs','Slaapkamers','Bewoonbareopp','Terras','Garage','Nieuwbouw'),1:49))
> y <- array(NA,dim=c(6,49),dimnames=list(c('Huurprijs','Slaapkamers','Bewoonbareopp','Terras','Garage','Nieuwbouw'),1:49))
> 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
Bewoonbareopp Huurprijs Slaapkamers Terras Garage Nieuwbouw
1 60 475 2 0 0 0
2 67 530 1 1 0 0
3 91 550 2 1 1 0
4 150 550 1 0 2 0
5 110 625 3 1 2 0
6 86 650 2 1 2 1
7 86 650 2 0 0 1
8 145 720 3 1 2 1
9 150 795 3 1 0 0
10 85 515 2 1 2 0
11 100 535 2 1 2 0
12 84 550 2 0 0 0
13 94 600 2 1 0 0
14 149 600 2 0 1 0
15 105 660 3 1 2 0
16 106 695 2 1 0 0
17 132 720 3 1 0 0
18 130 750 2 1 2 0
19 165 750 3 1 2 0
20 127 850 2 1 2 1
21 119 850 2 1 0 1
22 126 875 3 1 2 1
23 133 900 2 1 2 1
24 89 595 2 1 1 1
25 147 765 3 1 2 1
26 59 495 1 1 0 1
27 58 525 1 0 0 1
28 56 525 1 0 0 1
29 90 595 2 1 2 0
30 80 650 1 1 0 1
31 135 695 3 0 0 1
32 125 615 2 0 2 0
33 80 460 2 1 0 0
34 100 650 2 1 1 1
35 76 650 2 1 0 1
36 65 475 1 1 1 0
37 75 530 2 1 1 0
38 95 575 2 1 2 1
39 85 650 2 1 1 1
40 106 650 1 1 0 1
41 135 875 2 1 0 1
42 95 500 2 0 1 1
43 60 625 2 1 2 0
44 112 730 2 1 2 1
45 150 750 2 1 1 1
46 100 700 2 0 2 0
47 125 830 2 1 0 1
48 100 995 2 1 2 1
49 150 850 3 1 2 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Huurprijs Slaapkamers Terras Garage Nieuwbouw
-5.6705 0.1373 14.8450 -12.2216 3.4755 -8.1790
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-47.1687 -13.0346 0.2197 7.8926 58.3677
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -5.67046 16.15697 -0.351 0.7273
Huurprijs 0.13729 0.03138 4.375 7.6e-05 ***
Slaapkamers 14.84505 5.94227 2.498 0.0164 *
Terras -12.22158 7.58462 -1.611 0.1144
Garage 3.47548 3.54213 0.981 0.3320
Nieuwbouw -8.17901 6.93058 -1.180 0.2444
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 20.7 on 43 degrees of freedom
Multiple R-squared: 0.5696, Adjusted R-squared: 0.5196
F-statistic: 11.38 on 5 and 43 DF, p-value: 4.948e-07
> 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,] 0.63953504 0.7209299 0.3604650
[2,] 0.47422859 0.9484572 0.5257714
[3,] 0.33181164 0.6636233 0.6681884
[4,] 0.23311341 0.4662268 0.7668866
[5,] 0.17181197 0.3436239 0.8281880
[6,] 0.22401092 0.4480218 0.7759891
[7,] 0.40272886 0.8054577 0.5972711
[8,] 0.35989287 0.7197857 0.6401071
[9,] 0.31830904 0.6366181 0.6816910
[10,] 0.53713997 0.9257201 0.4628600
[11,] 0.56122091 0.8775582 0.4387791
[12,] 0.57489344 0.8502131 0.4251066
[13,] 0.47890980 0.9578196 0.5210902
[14,] 0.51956381 0.9608724 0.4804362
[15,] 0.46937224 0.9387445 0.5306278
[16,] 0.44634051 0.8926810 0.5536595
[17,] 0.43492805 0.8698561 0.5650719
[18,] 0.38468842 0.7693768 0.6153116
[19,] 0.34013276 0.6802655 0.6598672
[20,] 0.36562976 0.7312595 0.6343702
[21,] 0.32673131 0.6534626 0.6732687
[22,] 0.26447866 0.5289573 0.7355213
[23,] 0.22372093 0.4474419 0.7762791
[24,] 0.25556268 0.5111254 0.7444373
[25,] 0.19653441 0.3930688 0.8034656
[26,] 0.13684042 0.2736808 0.8631596
[27,] 0.24829684 0.4965937 0.7517032
[28,] 0.19302981 0.3860596 0.8069702
[29,] 0.12790995 0.2558199 0.8720900
[30,] 0.07626289 0.1525258 0.9237371
[31,] 0.09377419 0.1875484 0.9062258
[32,] 0.07543009 0.1508602 0.9245699
> postscript(file="/var/www/html/freestat/rcomp/tmp/1mkpn1290526697.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2wto81290526697.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wto81290526697.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4wto81290526697.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5wto81290526697.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 = 49
Frequency = 1
1 2 3 4 5 6
-29.2300523 -2.7141029 0.2196702 58.3676520 -9.3972374 -13.8053119
7 8 9 10 11 12
-19.0759378 20.7396854 14.2152537 -4.4508305 7.8034674 -15.5264350
13 14 15 16 17 18
-0.1691057 39.1338306 -19.2022160 -1.2111904 6.5116364 8.2871704
19 20 21 22 23 24
28.4421248 -0.2623324 -1.3113739 -19.5395055 -1.1265876 0.2208480
25 26 27 28 29 30
16.5618557 2.2698831 -15.0702544 -17.0702544 -10.4336387 1.9906922
31 32 33 34 35 36
8.9011871 9.5990748 5.0508087 3.6701674 -16.8543533 -0.6389016
37 38 39 40 41 42
-13.0346278 5.4910708 -11.3298326 27.9906922 11.2564986 7.0413484
43 44 45 46 47 48
-44.5521918 1.2118799 39.9416571 -27.0701590 7.4343282 -47.1686723
49
7.8926220
> postscript(file="/var/www/html/freestat/rcomp/tmp/6pk6t1290526697.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 = 49
Frequency = 1
lag(myerror, k = 1) myerror
0 -29.2300523 NA
1 -2.7141029 -29.2300523
2 0.2196702 -2.7141029
3 58.3676520 0.2196702
4 -9.3972374 58.3676520
5 -13.8053119 -9.3972374
6 -19.0759378 -13.8053119
7 20.7396854 -19.0759378
8 14.2152537 20.7396854
9 -4.4508305 14.2152537
10 7.8034674 -4.4508305
11 -15.5264350 7.8034674
12 -0.1691057 -15.5264350
13 39.1338306 -0.1691057
14 -19.2022160 39.1338306
15 -1.2111904 -19.2022160
16 6.5116364 -1.2111904
17 8.2871704 6.5116364
18 28.4421248 8.2871704
19 -0.2623324 28.4421248
20 -1.3113739 -0.2623324
21 -19.5395055 -1.3113739
22 -1.1265876 -19.5395055
23 0.2208480 -1.1265876
24 16.5618557 0.2208480
25 2.2698831 16.5618557
26 -15.0702544 2.2698831
27 -17.0702544 -15.0702544
28 -10.4336387 -17.0702544
29 1.9906922 -10.4336387
30 8.9011871 1.9906922
31 9.5990748 8.9011871
32 5.0508087 9.5990748
33 3.6701674 5.0508087
34 -16.8543533 3.6701674
35 -0.6389016 -16.8543533
36 -13.0346278 -0.6389016
37 5.4910708 -13.0346278
38 -11.3298326 5.4910708
39 27.9906922 -11.3298326
40 11.2564986 27.9906922
41 7.0413484 11.2564986
42 -44.5521918 7.0413484
43 1.2118799 -44.5521918
44 39.9416571 1.2118799
45 -27.0701590 39.9416571
46 7.4343282 -27.0701590
47 -47.1686723 7.4343282
48 7.8926220 -47.1686723
49 NA 7.8926220
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.7141029 -29.2300523
[2,] 0.2196702 -2.7141029
[3,] 58.3676520 0.2196702
[4,] -9.3972374 58.3676520
[5,] -13.8053119 -9.3972374
[6,] -19.0759378 -13.8053119
[7,] 20.7396854 -19.0759378
[8,] 14.2152537 20.7396854
[9,] -4.4508305 14.2152537
[10,] 7.8034674 -4.4508305
[11,] -15.5264350 7.8034674
[12,] -0.1691057 -15.5264350
[13,] 39.1338306 -0.1691057
[14,] -19.2022160 39.1338306
[15,] -1.2111904 -19.2022160
[16,] 6.5116364 -1.2111904
[17,] 8.2871704 6.5116364
[18,] 28.4421248 8.2871704
[19,] -0.2623324 28.4421248
[20,] -1.3113739 -0.2623324
[21,] -19.5395055 -1.3113739
[22,] -1.1265876 -19.5395055
[23,] 0.2208480 -1.1265876
[24,] 16.5618557 0.2208480
[25,] 2.2698831 16.5618557
[26,] -15.0702544 2.2698831
[27,] -17.0702544 -15.0702544
[28,] -10.4336387 -17.0702544
[29,] 1.9906922 -10.4336387
[30,] 8.9011871 1.9906922
[31,] 9.5990748 8.9011871
[32,] 5.0508087 9.5990748
[33,] 3.6701674 5.0508087
[34,] -16.8543533 3.6701674
[35,] -0.6389016 -16.8543533
[36,] -13.0346278 -0.6389016
[37,] 5.4910708 -13.0346278
[38,] -11.3298326 5.4910708
[39,] 27.9906922 -11.3298326
[40,] 11.2564986 27.9906922
[41,] 7.0413484 11.2564986
[42,] -44.5521918 7.0413484
[43,] 1.2118799 -44.5521918
[44,] 39.9416571 1.2118799
[45,] -27.0701590 39.9416571
[46,] 7.4343282 -27.0701590
[47,] -47.1686723 7.4343282
[48,] 7.8926220 -47.1686723
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.7141029 -29.2300523
2 0.2196702 -2.7141029
3 58.3676520 0.2196702
4 -9.3972374 58.3676520
5 -13.8053119 -9.3972374
6 -19.0759378 -13.8053119
7 20.7396854 -19.0759378
8 14.2152537 20.7396854
9 -4.4508305 14.2152537
10 7.8034674 -4.4508305
11 -15.5264350 7.8034674
12 -0.1691057 -15.5264350
13 39.1338306 -0.1691057
14 -19.2022160 39.1338306
15 -1.2111904 -19.2022160
16 6.5116364 -1.2111904
17 8.2871704 6.5116364
18 28.4421248 8.2871704
19 -0.2623324 28.4421248
20 -1.3113739 -0.2623324
21 -19.5395055 -1.3113739
22 -1.1265876 -19.5395055
23 0.2208480 -1.1265876
24 16.5618557 0.2208480
25 2.2698831 16.5618557
26 -15.0702544 2.2698831
27 -17.0702544 -15.0702544
28 -10.4336387 -17.0702544
29 1.9906922 -10.4336387
30 8.9011871 1.9906922
31 9.5990748 8.9011871
32 5.0508087 9.5990748
33 3.6701674 5.0508087
34 -16.8543533 3.6701674
35 -0.6389016 -16.8543533
36 -13.0346278 -0.6389016
37 5.4910708 -13.0346278
38 -11.3298326 5.4910708
39 27.9906922 -11.3298326
40 11.2564986 27.9906922
41 7.0413484 11.2564986
42 -44.5521918 7.0413484
43 1.2118799 -44.5521918
44 39.9416571 1.2118799
45 -27.0701590 39.9416571
46 7.4343282 -27.0701590
47 -47.1686723 7.4343282
48 7.8926220 -47.1686723
> 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/70cnw1290526697.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/80cnw1290526697.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9tl4h1290526697.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10tl4h1290526697.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11w43n1290526697.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/12hm1s1290526697.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/13vwzj1290526697.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/14zegp1290526697.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/152fev1290526697.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/16ypum1290526697.tab")
+ }
>
> try(system("convert tmp/1mkpn1290526697.ps tmp/1mkpn1290526697.png",intern=TRUE))
character(0)
> try(system("convert tmp/2wto81290526697.ps tmp/2wto81290526697.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wto81290526697.ps tmp/3wto81290526697.png",intern=TRUE))
character(0)
> try(system("convert tmp/4wto81290526697.ps tmp/4wto81290526697.png",intern=TRUE))
character(0)
> try(system("convert tmp/5wto81290526697.ps tmp/5wto81290526697.png",intern=TRUE))
character(0)
> try(system("convert tmp/6pk6t1290526697.ps tmp/6pk6t1290526697.png",intern=TRUE))
character(0)
> try(system("convert tmp/70cnw1290526697.ps tmp/70cnw1290526697.png",intern=TRUE))
character(0)
> try(system("convert tmp/80cnw1290526697.ps tmp/80cnw1290526697.png",intern=TRUE))
character(0)
> try(system("convert tmp/9tl4h1290526697.ps tmp/9tl4h1290526697.png",intern=TRUE))
character(0)
> try(system("convert tmp/10tl4h1290526697.ps tmp/10tl4h1290526697.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.833 2.525 8.931