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(15,40,35,16,42,36,15,38,35,14,34,32,13,32,30,16,40,35,18,50,40,14,25,23,11,16,15,10,12,12,9,4,4,11,7,7,13,16,14,18,50,46,21,60,50,15,35,33,14,32,31,15,33,32,16,39,34,15,33,30,16,35,31,17,40,35,14,25,23,13,19,17,12,12,12,15,19,17,16,25,22,18,29,24,19,41,34,17,50,45,18,70,60,18,65,61,18,50,45,19,45,41,20,62,51,22,82,62,21,62,53,20,42,33,18,39,35,17,35,31,16,30,28,19,40,33,21,45,39,20,42,35,20,41,35,21,45,35,20,43,35,19,30,28,16,20,18,18,25,23,19,27,24,21,38,29,22,40,29,25,60,41,24,61,41,23,55,41,22,43,38,21,34,29,20,20,17,22,38,32),dim=c(3,60),dimnames=list(c('Gem_Graden','Gem_Fietsers','Aantal_Mannen
'),1:60))
> y <- array(NA,dim=c(3,60),dimnames=list(c('Gem_Graden','Gem_Fietsers','Aantal_Mannen
'),1:60))
> 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
Gem_Graden Gem_Fietsers Aantal_Mannen\r
1 15 40 35
2 16 42 36
3 15 38 35
4 14 34 32
5 13 32 30
6 16 40 35
7 18 50 40
8 14 25 23
9 11 16 15
10 10 12 12
11 9 4 4
12 11 7 7
13 13 16 14
14 18 50 46
15 21 60 50
16 15 35 33
17 14 32 31
18 15 33 32
19 16 39 34
20 15 33 30
21 16 35 31
22 17 40 35
23 14 25 23
24 13 19 17
25 12 12 12
26 15 19 17
27 16 25 22
28 18 29 24
29 19 41 34
30 17 50 45
31 18 70 60
32 18 65 61
33 18 50 45
34 19 45 41
35 20 62 51
36 22 82 62
37 21 62 53
38 20 42 33
39 18 39 35
40 17 35 31
41 16 30 28
42 19 40 33
43 21 45 39
44 20 42 35
45 20 41 35
46 21 45 35
47 20 43 35
48 19 30 28
49 16 20 18
50 18 25 23
51 19 27 24
52 21 38 29
53 22 40 29
54 25 60 41
55 24 61 41
56 23 55 41
57 22 43 38
58 21 34 29
59 20 20 17
60 22 38 32
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Gem_Fietsers `Aantal_Mannen\r`
12.8238 0.5080 -0.4506
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4.5371 -1.3580 0.1158 1.1309 4.6778
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.82379 0.80627 15.905 < 2e-16 ***
Gem_Fietsers 0.50796 0.07939 6.399 3.17e-08 ***
`Aantal_Mannen\r` -0.45064 0.10071 -4.475 3.71e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.165 on 57 degrees of freedom
Multiple R-squared: 0.6394, Adjusted R-squared: 0.6267
F-statistic: 50.53 on 2 and 57 DF, p-value: 2.373e-13
> 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,] 1.036220e-02 0.0207243996 0.989637800
[2,] 1.775622e-03 0.0035512448 0.998224378
[3,] 3.390284e-03 0.0067805688 0.996609716
[4,] 3.460077e-03 0.0069201548 0.996539923
[5,] 1.685086e-03 0.0033701715 0.998314914
[6,] 8.033240e-04 0.0016066480 0.999196676
[7,] 1.659605e-03 0.0033192096 0.998340395
[8,] 2.669416e-03 0.0053388326 0.997330584
[9,] 3.058677e-03 0.0061173531 0.996941323
[10,] 2.695276e-03 0.0053905516 0.997304724
[11,] 1.413476e-03 0.0028269522 0.998586524
[12,] 6.922087e-04 0.0013844174 0.999307791
[13,] 4.758020e-04 0.0009516040 0.999524198
[14,] 2.352779e-04 0.0004705559 0.999764722
[15,] 1.340148e-04 0.0002680295 0.999865985
[16,] 1.058303e-04 0.0002116606 0.999894170
[17,] 7.534422e-05 0.0001506884 0.999924656
[18,] 7.602471e-05 0.0001520494 0.999923975
[19,] 1.486093e-04 0.0002972186 0.999851391
[20,] 1.080386e-03 0.0021607720 0.998919614
[21,] 1.599547e-02 0.0319909389 0.984004531
[22,] 6.338027e-02 0.1267605377 0.936619731
[23,] 1.893815e-01 0.3787629312 0.810618534
[24,] 1.942091e-01 0.3884181258 0.805790937
[25,] 1.806592e-01 0.3613184996 0.819340750
[26,] 4.165036e-01 0.8330072310 0.583496384
[27,] 3.424833e-01 0.6849665607 0.657516720
[28,] 3.067856e-01 0.6135711649 0.693214418
[29,] 3.630367e-01 0.7260734394 0.636963280
[30,] 3.229975e-01 0.6459950987 0.677002451
[31,] 5.400636e-01 0.9198727319 0.459936366
[32,] 5.069332e-01 0.9861335157 0.493066758
[33,] 5.504500e-01 0.8990999106 0.449549955
[34,] 5.772143e-01 0.8455713974 0.422785699
[35,] 6.792115e-01 0.6415770794 0.320788540
[36,] 8.489045e-01 0.3021909131 0.151095457
[37,] 8.927562e-01 0.2144875611 0.107243781
[38,] 9.069298e-01 0.1861404851 0.093070243
[39,] 9.092910e-01 0.1814179139 0.090708957
[40,] 9.096791e-01 0.1806418095 0.090320905
[41,] 8.937188e-01 0.2125623641 0.106281182
[42,] 9.123978e-01 0.1752043098 0.087602155
[43,] 9.104929e-01 0.1790142193 0.089507110
[44,] 9.817258e-01 0.0365484039 0.018274202
[45,] 9.942383e-01 0.0115233394 0.005761670
[46,] 9.976187e-01 0.0047626310 0.002381315
[47,] 9.968018e-01 0.0063963968 0.003198198
[48,] 9.878929e-01 0.0242142110 0.012107106
[49,] 9.941776e-01 0.0116447666 0.005822383
> postscript(file="/var/wessaorg/rcomp/tmp/1p44f1321891884.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2hkxs1321891884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3qevi1321891884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/45jgw1321891884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5fw9q1321891884.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 = 60
Frequency = 1
1 2 3 4 5 6
-2.36989752 -1.93518345 -1.35397076 -1.67403972 -2.55939462 -1.36989752
7 8 9 10 11 12
-2.19632717 -1.15813674 -3.19159294 -3.51166190 -4.05308147 -2.22504913
13 14 15 16 17 18
-1.64223376 0.50751777 0.23044729 -0.73136228 -1.10875379 -0.16607635
19 20 21 22 23 24
-1.31257496 -1.06735799 -0.63264393 -0.36989752 -1.15813674 -1.81420142
25 26 27 28 29 30
-1.51166190 0.18579858 0.39122243 1.26065057 0.67149828 -0.94312305
31 32 33 34 35 36
-3.34277824 -0.35232053 0.05687695 1.79413054 -1.33483864 -4.53705712
37 38 39 40 41 42
0.56644301 0.71289408 1.13806586 0.36735607 0.55525049 0.72882084
43 44 45 46 47 48
2.89284889 1.61417573 2.12213911 1.09028560 1.10621235 3.55525049
49 50 51 52 53 54
1.12847603 2.84186326 3.27657733 1.94218430 1.92625754 0.17467988
55 56 57 58 59 60
-1.33328349 0.71449677 4.45813482 3.97403781 4.67783520 4.29410677
> postscript(file="/var/wessaorg/rcomp/tmp/6p3iu1321891884.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -2.36989752 NA
1 -1.93518345 -2.36989752
2 -1.35397076 -1.93518345
3 -1.67403972 -1.35397076
4 -2.55939462 -1.67403972
5 -1.36989752 -2.55939462
6 -2.19632717 -1.36989752
7 -1.15813674 -2.19632717
8 -3.19159294 -1.15813674
9 -3.51166190 -3.19159294
10 -4.05308147 -3.51166190
11 -2.22504913 -4.05308147
12 -1.64223376 -2.22504913
13 0.50751777 -1.64223376
14 0.23044729 0.50751777
15 -0.73136228 0.23044729
16 -1.10875379 -0.73136228
17 -0.16607635 -1.10875379
18 -1.31257496 -0.16607635
19 -1.06735799 -1.31257496
20 -0.63264393 -1.06735799
21 -0.36989752 -0.63264393
22 -1.15813674 -0.36989752
23 -1.81420142 -1.15813674
24 -1.51166190 -1.81420142
25 0.18579858 -1.51166190
26 0.39122243 0.18579858
27 1.26065057 0.39122243
28 0.67149828 1.26065057
29 -0.94312305 0.67149828
30 -3.34277824 -0.94312305
31 -0.35232053 -3.34277824
32 0.05687695 -0.35232053
33 1.79413054 0.05687695
34 -1.33483864 1.79413054
35 -4.53705712 -1.33483864
36 0.56644301 -4.53705712
37 0.71289408 0.56644301
38 1.13806586 0.71289408
39 0.36735607 1.13806586
40 0.55525049 0.36735607
41 0.72882084 0.55525049
42 2.89284889 0.72882084
43 1.61417573 2.89284889
44 2.12213911 1.61417573
45 1.09028560 2.12213911
46 1.10621235 1.09028560
47 3.55525049 1.10621235
48 1.12847603 3.55525049
49 2.84186326 1.12847603
50 3.27657733 2.84186326
51 1.94218430 3.27657733
52 1.92625754 1.94218430
53 0.17467988 1.92625754
54 -1.33328349 0.17467988
55 0.71449677 -1.33328349
56 4.45813482 0.71449677
57 3.97403781 4.45813482
58 4.67783520 3.97403781
59 4.29410677 4.67783520
60 NA 4.29410677
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.93518345 -2.36989752
[2,] -1.35397076 -1.93518345
[3,] -1.67403972 -1.35397076
[4,] -2.55939462 -1.67403972
[5,] -1.36989752 -2.55939462
[6,] -2.19632717 -1.36989752
[7,] -1.15813674 -2.19632717
[8,] -3.19159294 -1.15813674
[9,] -3.51166190 -3.19159294
[10,] -4.05308147 -3.51166190
[11,] -2.22504913 -4.05308147
[12,] -1.64223376 -2.22504913
[13,] 0.50751777 -1.64223376
[14,] 0.23044729 0.50751777
[15,] -0.73136228 0.23044729
[16,] -1.10875379 -0.73136228
[17,] -0.16607635 -1.10875379
[18,] -1.31257496 -0.16607635
[19,] -1.06735799 -1.31257496
[20,] -0.63264393 -1.06735799
[21,] -0.36989752 -0.63264393
[22,] -1.15813674 -0.36989752
[23,] -1.81420142 -1.15813674
[24,] -1.51166190 -1.81420142
[25,] 0.18579858 -1.51166190
[26,] 0.39122243 0.18579858
[27,] 1.26065057 0.39122243
[28,] 0.67149828 1.26065057
[29,] -0.94312305 0.67149828
[30,] -3.34277824 -0.94312305
[31,] -0.35232053 -3.34277824
[32,] 0.05687695 -0.35232053
[33,] 1.79413054 0.05687695
[34,] -1.33483864 1.79413054
[35,] -4.53705712 -1.33483864
[36,] 0.56644301 -4.53705712
[37,] 0.71289408 0.56644301
[38,] 1.13806586 0.71289408
[39,] 0.36735607 1.13806586
[40,] 0.55525049 0.36735607
[41,] 0.72882084 0.55525049
[42,] 2.89284889 0.72882084
[43,] 1.61417573 2.89284889
[44,] 2.12213911 1.61417573
[45,] 1.09028560 2.12213911
[46,] 1.10621235 1.09028560
[47,] 3.55525049 1.10621235
[48,] 1.12847603 3.55525049
[49,] 2.84186326 1.12847603
[50,] 3.27657733 2.84186326
[51,] 1.94218430 3.27657733
[52,] 1.92625754 1.94218430
[53,] 0.17467988 1.92625754
[54,] -1.33328349 0.17467988
[55,] 0.71449677 -1.33328349
[56,] 4.45813482 0.71449677
[57,] 3.97403781 4.45813482
[58,] 4.67783520 3.97403781
[59,] 4.29410677 4.67783520
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.93518345 -2.36989752
2 -1.35397076 -1.93518345
3 -1.67403972 -1.35397076
4 -2.55939462 -1.67403972
5 -1.36989752 -2.55939462
6 -2.19632717 -1.36989752
7 -1.15813674 -2.19632717
8 -3.19159294 -1.15813674
9 -3.51166190 -3.19159294
10 -4.05308147 -3.51166190
11 -2.22504913 -4.05308147
12 -1.64223376 -2.22504913
13 0.50751777 -1.64223376
14 0.23044729 0.50751777
15 -0.73136228 0.23044729
16 -1.10875379 -0.73136228
17 -0.16607635 -1.10875379
18 -1.31257496 -0.16607635
19 -1.06735799 -1.31257496
20 -0.63264393 -1.06735799
21 -0.36989752 -0.63264393
22 -1.15813674 -0.36989752
23 -1.81420142 -1.15813674
24 -1.51166190 -1.81420142
25 0.18579858 -1.51166190
26 0.39122243 0.18579858
27 1.26065057 0.39122243
28 0.67149828 1.26065057
29 -0.94312305 0.67149828
30 -3.34277824 -0.94312305
31 -0.35232053 -3.34277824
32 0.05687695 -0.35232053
33 1.79413054 0.05687695
34 -1.33483864 1.79413054
35 -4.53705712 -1.33483864
36 0.56644301 -4.53705712
37 0.71289408 0.56644301
38 1.13806586 0.71289408
39 0.36735607 1.13806586
40 0.55525049 0.36735607
41 0.72882084 0.55525049
42 2.89284889 0.72882084
43 1.61417573 2.89284889
44 2.12213911 1.61417573
45 1.09028560 2.12213911
46 1.10621235 1.09028560
47 3.55525049 1.10621235
48 1.12847603 3.55525049
49 2.84186326 1.12847603
50 3.27657733 2.84186326
51 1.94218430 3.27657733
52 1.92625754 1.94218430
53 0.17467988 1.92625754
54 -1.33328349 0.17467988
55 0.71449677 -1.33328349
56 4.45813482 0.71449677
57 3.97403781 4.45813482
58 4.67783520 3.97403781
59 4.29410677 4.67783520
> 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/7a5qa1321891884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/85tmv1321891884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9xrbf1321891884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10b8711321891884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11m2kr1321891884.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/12m0o11321891884.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/13xxsm1321891884.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/141agb1321891884.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/15g6lm1321891884.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/1608hy1321891884.tab")
+ }
>
> try(system("convert tmp/1p44f1321891884.ps tmp/1p44f1321891884.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hkxs1321891884.ps tmp/2hkxs1321891884.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qevi1321891884.ps tmp/3qevi1321891884.png",intern=TRUE))
character(0)
> try(system("convert tmp/45jgw1321891884.ps tmp/45jgw1321891884.png",intern=TRUE))
character(0)
> try(system("convert tmp/5fw9q1321891884.ps tmp/5fw9q1321891884.png",intern=TRUE))
character(0)
> try(system("convert tmp/6p3iu1321891884.ps tmp/6p3iu1321891884.png",intern=TRUE))
character(0)
> try(system("convert tmp/7a5qa1321891884.ps tmp/7a5qa1321891884.png",intern=TRUE))
character(0)
> try(system("convert tmp/85tmv1321891884.ps tmp/85tmv1321891884.png",intern=TRUE))
character(0)
> try(system("convert tmp/9xrbf1321891884.ps tmp/9xrbf1321891884.png",intern=TRUE))
character(0)
> try(system("convert tmp/10b8711321891884.ps tmp/10b8711321891884.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.166 0.554 3.746