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)
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> x <- array(list(135094,135411,135698,135880,135891,135971,136173,136358,136514,136506,136711,136891,137094,137182,137400,137479,137620,137687,137638,137612,137681,137772,137899,137983,137996,137913,137841,137656,137423,137245,137014,136747,136313,135804,135002,134383,133563,132837,132041,131381,130995,130493,130193,129962,129726,129505,129450,129320,129281,129246,129438,129715,130173,129981,129932,129873,129844,130015,130108,130260),dim=c(1,60),dimnames=list(c('aantal_WNs'),1:60))
> y <- array(NA,dim=c(1,60),dimnames=list(c('aantal_WNs'),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 = 'Include Monthly Dummies'
> par1 = '1'
> 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
aantal_WNs M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 135094 1 0 0 0 0 0 0 0 0 0 0
2 135411 0 1 0 0 0 0 0 0 0 0 0
3 135698 0 0 1 0 0 0 0 0 0 0 0
4 135880 0 0 0 1 0 0 0 0 0 0 0
5 135891 0 0 0 0 1 0 0 0 0 0 0
6 135971 0 0 0 0 0 1 0 0 0 0 0
7 136173 0 0 0 0 0 0 1 0 0 0 0
8 136358 0 0 0 0 0 0 0 1 0 0 0
9 136514 0 0 0 0 0 0 0 0 1 0 0
10 136506 0 0 0 0 0 0 0 0 0 1 0
11 136711 0 0 0 0 0 0 0 0 0 0 1
12 136891 0 0 0 0 0 0 0 0 0 0 0
13 137094 1 0 0 0 0 0 0 0 0 0 0
14 137182 0 1 0 0 0 0 0 0 0 0 0
15 137400 0 0 1 0 0 0 0 0 0 0 0
16 137479 0 0 0 1 0 0 0 0 0 0 0
17 137620 0 0 0 0 1 0 0 0 0 0 0
18 137687 0 0 0 0 0 1 0 0 0 0 0
19 137638 0 0 0 0 0 0 1 0 0 0 0
20 137612 0 0 0 0 0 0 0 1 0 0 0
21 137681 0 0 0 0 0 0 0 0 1 0 0
22 137772 0 0 0 0 0 0 0 0 0 1 0
23 137899 0 0 0 0 0 0 0 0 0 0 1
24 137983 0 0 0 0 0 0 0 0 0 0 0
25 137996 1 0 0 0 0 0 0 0 0 0 0
26 137913 0 1 0 0 0 0 0 0 0 0 0
27 137841 0 0 1 0 0 0 0 0 0 0 0
28 137656 0 0 0 1 0 0 0 0 0 0 0
29 137423 0 0 0 0 1 0 0 0 0 0 0
30 137245 0 0 0 0 0 1 0 0 0 0 0
31 137014 0 0 0 0 0 0 1 0 0 0 0
32 136747 0 0 0 0 0 0 0 1 0 0 0
33 136313 0 0 0 0 0 0 0 0 1 0 0
34 135804 0 0 0 0 0 0 0 0 0 1 0
35 135002 0 0 0 0 0 0 0 0 0 0 1
36 134383 0 0 0 0 0 0 0 0 0 0 0
37 133563 1 0 0 0 0 0 0 0 0 0 0
38 132837 0 1 0 0 0 0 0 0 0 0 0
39 132041 0 0 1 0 0 0 0 0 0 0 0
40 131381 0 0 0 1 0 0 0 0 0 0 0
41 130995 0 0 0 0 1 0 0 0 0 0 0
42 130493 0 0 0 0 0 1 0 0 0 0 0
43 130193 0 0 0 0 0 0 1 0 0 0 0
44 129962 0 0 0 0 0 0 0 1 0 0 0
45 129726 0 0 0 0 0 0 0 0 1 0 0
46 129505 0 0 0 0 0 0 0 0 0 1 0
47 129450 0 0 0 0 0 0 0 0 0 0 1
48 129320 0 0 0 0 0 0 0 0 0 0 0
49 129281 1 0 0 0 0 0 0 0 0 0 0
50 129246 0 1 0 0 0 0 0 0 0 0 0
51 129438 0 0 1 0 0 0 0 0 0 0 0
52 129715 0 0 0 1 0 0 0 0 0 0 0
53 130173 0 0 0 0 1 0 0 0 0 0 0
54 129981 0 0 0 0 0 1 0 0 0 0 0
55 129932 0 0 0 0 0 0 1 0 0 0 0
56 129873 0 0 0 0 0 0 0 1 0 0 0
57 129844 0 0 0 0 0 0 0 0 1 0 0
58 130015 0 0 0 0 0 0 0 0 0 1 0
59 130108 0 0 0 0 0 0 0 0 0 0 1
60 130260 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
133767.4 838.2 750.4 716.2 654.8 653.0
M6 M7 M8 M9 M10 M11
508.0 422.6 343.0 248.2 153.0 66.6
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-5325 -3928 1464 2978 4216
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 133767.4 1668.1 80.189 <2e-16 ***
M1 838.2 2359.1 0.355 0.724
M2 750.4 2359.1 0.318 0.752
M3 716.2 2359.1 0.304 0.763
M4 654.8 2359.1 0.278 0.783
M5 653.0 2359.1 0.277 0.783
M6 508.0 2359.1 0.215 0.830
M7 422.6 2359.1 0.179 0.859
M8 343.0 2359.1 0.145 0.885
M9 248.2 2359.1 0.105 0.917
M10 153.0 2359.1 0.065 0.949
M11 66.6 2359.1 0.028 0.978
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3730 on 48 degrees of freedom
Multiple R-squared: 0.00661, Adjusted R-squared: -0.221
F-statistic: 0.02904 on 11 and 48 DF, p-value: 1
> 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)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 3.858056e-02 7.716112e-02 9.614194e-01
[2,] 1.523533e-02 3.047067e-02 9.847647e-01
[3,] 6.675659e-03 1.335132e-02 9.933243e-01
[4,] 3.038588e-03 6.077176e-03 9.969614e-01
[5,] 1.273947e-03 2.547893e-03 9.987261e-01
[6,] 5.061011e-04 1.012202e-03 9.994939e-01
[7,] 2.039236e-04 4.078472e-04 9.997961e-01
[8,] 9.140291e-05 1.828058e-04 9.999086e-01
[9,] 4.364024e-05 8.728047e-05 9.999564e-01
[10,] 2.243465e-05 4.486930e-05 9.999776e-01
[11,] 2.339231e-05 4.678462e-05 9.999766e-01
[12,] 2.171821e-05 4.343642e-05 9.999783e-01
[13,] 1.940759e-05 3.881517e-05 9.999806e-01
[14,] 1.759251e-05 3.518502e-05 9.999824e-01
[15,] 1.614943e-05 3.229887e-05 9.999839e-01
[16,] 1.889290e-05 3.778579e-05 9.999811e-01
[17,] 2.943953e-05 5.887907e-05 9.999706e-01
[18,] 7.000699e-05 1.400140e-04 9.999300e-01
[19,] 2.944087e-04 5.888174e-04 9.997056e-01
[20,] 2.285550e-03 4.571100e-03 9.977145e-01
[21,] 2.700965e-02 5.401929e-02 9.729904e-01
[22,] 2.452454e-01 4.904909e-01 7.547546e-01
[23,] 7.027853e-01 5.944295e-01 2.972147e-01
[24,] 9.719215e-01 5.615693e-02 2.807846e-02
[25,] 9.989885e-01 2.022902e-03 1.011451e-03
[26,] 9.999255e-01 1.490438e-04 7.452192e-05
[27,] 9.999449e-01 1.102494e-04 5.512472e-05
[28,] 9.998947e-01 2.105066e-04 1.052533e-04
[29,] 9.996318e-01 7.363896e-04 3.681948e-04
[30,] 9.983240e-01 3.352018e-03 1.676009e-03
[31,] 9.916527e-01 1.669463e-02 8.347317e-03
> postscript(file="/var/wessaorg/rcomp/tmp/1x3b61322147177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2dcpz1322147177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3a06c1322147177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4bn1b1322147177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/50vkn1322147177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 7 8 9 10
488.4 893.2 1214.4 1457.8 1470.6 1695.6 1983.0 2247.6 2498.4 2585.6
11 12 13 14 15 16 17 18 19 20
2877.0 3123.6 2488.4 2664.2 2916.4 3056.8 3199.6 3411.6 3448.0 3501.6
21 22 23 24 25 26 27 28 29 30
3665.4 3851.6 4065.0 4215.6 3390.4 3395.2 3357.4 3233.8 3002.6 2969.6
31 32 33 34 35 36 37 38 39 40
2824.0 2636.6 2297.4 1883.6 1168.0 615.6 -1042.6 -1680.8 -2442.6 -3041.2
41 42 43 44 45 46 47 48 49 50
-3425.4 -3782.4 -3997.0 -4148.4 -4289.6 -4415.4 -4384.0 -4447.4 -5324.6 -5271.8
51 52 53 54 55 56 57 58 59 60
-5045.6 -4707.2 -4247.4 -4294.4 -4258.0 -4237.4 -4171.6 -3905.4 -3726.0 -3507.4
> postscript(file="/var/wessaorg/rcomp/tmp/619t01322147177.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
0 488.4 NA
1 893.2 488.4
2 1214.4 893.2
3 1457.8 1214.4
4 1470.6 1457.8
5 1695.6 1470.6
6 1983.0 1695.6
7 2247.6 1983.0
8 2498.4 2247.6
9 2585.6 2498.4
10 2877.0 2585.6
11 3123.6 2877.0
12 2488.4 3123.6
13 2664.2 2488.4
14 2916.4 2664.2
15 3056.8 2916.4
16 3199.6 3056.8
17 3411.6 3199.6
18 3448.0 3411.6
19 3501.6 3448.0
20 3665.4 3501.6
21 3851.6 3665.4
22 4065.0 3851.6
23 4215.6 4065.0
24 3390.4 4215.6
25 3395.2 3390.4
26 3357.4 3395.2
27 3233.8 3357.4
28 3002.6 3233.8
29 2969.6 3002.6
30 2824.0 2969.6
31 2636.6 2824.0
32 2297.4 2636.6
33 1883.6 2297.4
34 1168.0 1883.6
35 615.6 1168.0
36 -1042.6 615.6
37 -1680.8 -1042.6
38 -2442.6 -1680.8
39 -3041.2 -2442.6
40 -3425.4 -3041.2
41 -3782.4 -3425.4
42 -3997.0 -3782.4
43 -4148.4 -3997.0
44 -4289.6 -4148.4
45 -4415.4 -4289.6
46 -4384.0 -4415.4
47 -4447.4 -4384.0
48 -5324.6 -4447.4
49 -5271.8 -5324.6
50 -5045.6 -5271.8
51 -4707.2 -5045.6
52 -4247.4 -4707.2
53 -4294.4 -4247.4
54 -4258.0 -4294.4
55 -4237.4 -4258.0
56 -4171.6 -4237.4
57 -3905.4 -4171.6
58 -3726.0 -3905.4
59 -3507.4 -3726.0
60 NA -3507.4
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 893.2 488.4
[2,] 1214.4 893.2
[3,] 1457.8 1214.4
[4,] 1470.6 1457.8
[5,] 1695.6 1470.6
[6,] 1983.0 1695.6
[7,] 2247.6 1983.0
[8,] 2498.4 2247.6
[9,] 2585.6 2498.4
[10,] 2877.0 2585.6
[11,] 3123.6 2877.0
[12,] 2488.4 3123.6
[13,] 2664.2 2488.4
[14,] 2916.4 2664.2
[15,] 3056.8 2916.4
[16,] 3199.6 3056.8
[17,] 3411.6 3199.6
[18,] 3448.0 3411.6
[19,] 3501.6 3448.0
[20,] 3665.4 3501.6
[21,] 3851.6 3665.4
[22,] 4065.0 3851.6
[23,] 4215.6 4065.0
[24,] 3390.4 4215.6
[25,] 3395.2 3390.4
[26,] 3357.4 3395.2
[27,] 3233.8 3357.4
[28,] 3002.6 3233.8
[29,] 2969.6 3002.6
[30,] 2824.0 2969.6
[31,] 2636.6 2824.0
[32,] 2297.4 2636.6
[33,] 1883.6 2297.4
[34,] 1168.0 1883.6
[35,] 615.6 1168.0
[36,] -1042.6 615.6
[37,] -1680.8 -1042.6
[38,] -2442.6 -1680.8
[39,] -3041.2 -2442.6
[40,] -3425.4 -3041.2
[41,] -3782.4 -3425.4
[42,] -3997.0 -3782.4
[43,] -4148.4 -3997.0
[44,] -4289.6 -4148.4
[45,] -4415.4 -4289.6
[46,] -4384.0 -4415.4
[47,] -4447.4 -4384.0
[48,] -5324.6 -4447.4
[49,] -5271.8 -5324.6
[50,] -5045.6 -5271.8
[51,] -4707.2 -5045.6
[52,] -4247.4 -4707.2
[53,] -4294.4 -4247.4
[54,] -4258.0 -4294.4
[55,] -4237.4 -4258.0
[56,] -4171.6 -4237.4
[57,] -3905.4 -4171.6
[58,] -3726.0 -3905.4
[59,] -3507.4 -3726.0
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 893.2 488.4
2 1214.4 893.2
3 1457.8 1214.4
4 1470.6 1457.8
5 1695.6 1470.6
6 1983.0 1695.6
7 2247.6 1983.0
8 2498.4 2247.6
9 2585.6 2498.4
10 2877.0 2585.6
11 3123.6 2877.0
12 2488.4 3123.6
13 2664.2 2488.4
14 2916.4 2664.2
15 3056.8 2916.4
16 3199.6 3056.8
17 3411.6 3199.6
18 3448.0 3411.6
19 3501.6 3448.0
20 3665.4 3501.6
21 3851.6 3665.4
22 4065.0 3851.6
23 4215.6 4065.0
24 3390.4 4215.6
25 3395.2 3390.4
26 3357.4 3395.2
27 3233.8 3357.4
28 3002.6 3233.8
29 2969.6 3002.6
30 2824.0 2969.6
31 2636.6 2824.0
32 2297.4 2636.6
33 1883.6 2297.4
34 1168.0 1883.6
35 615.6 1168.0
36 -1042.6 615.6
37 -1680.8 -1042.6
38 -2442.6 -1680.8
39 -3041.2 -2442.6
40 -3425.4 -3041.2
41 -3782.4 -3425.4
42 -3997.0 -3782.4
43 -4148.4 -3997.0
44 -4289.6 -4148.4
45 -4415.4 -4289.6
46 -4384.0 -4415.4
47 -4447.4 -4384.0
48 -5324.6 -4447.4
49 -5271.8 -5324.6
50 -5045.6 -5271.8
51 -4707.2 -5045.6
52 -4247.4 -4707.2
53 -4294.4 -4247.4
54 -4258.0 -4294.4
55 -4237.4 -4258.0
56 -4171.6 -4237.4
57 -3905.4 -4171.6
58 -3726.0 -3905.4
59 -3507.4 -3726.0
> 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/7umyc1322147177.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/8w0xu1322147177.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/9391h1322147177.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')
hat values (leverages) are all = 0.2
and there are no factor predictors; no plot no. 5
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10lqgv1322147177.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11qn821322147177.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12baeb1322147177.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/136yy71322147177.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/147s721322147177.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/15f6fb1322147177.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/166c6a1322147177.tab")
+ }
>
> try(system("convert tmp/1x3b61322147177.ps tmp/1x3b61322147177.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dcpz1322147177.ps tmp/2dcpz1322147177.png",intern=TRUE))
character(0)
> try(system("convert tmp/3a06c1322147177.ps tmp/3a06c1322147177.png",intern=TRUE))
character(0)
> try(system("convert tmp/4bn1b1322147177.ps tmp/4bn1b1322147177.png",intern=TRUE))
character(0)
> try(system("convert tmp/50vkn1322147177.ps tmp/50vkn1322147177.png",intern=TRUE))
character(0)
> try(system("convert tmp/619t01322147177.ps tmp/619t01322147177.png",intern=TRUE))
character(0)
> try(system("convert tmp/7umyc1322147177.ps tmp/7umyc1322147177.png",intern=TRUE))
character(0)
> try(system("convert tmp/8w0xu1322147177.ps tmp/8w0xu1322147177.png",intern=TRUE))
character(0)
> try(system("convert tmp/9391h1322147177.ps tmp/9391h1322147177.png",intern=TRUE))
character(0)
> try(system("convert tmp/10lqgv1322147177.ps tmp/10lqgv1322147177.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.219 0.489 3.726