R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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(101.82
+ ,107.34
+ ,93.63
+ ,99.85
+ ,101.76
+ ,101.68
+ ,107.34
+ ,93.63
+ ,99.91
+ ,102.37
+ ,101.68
+ ,107.34
+ ,93.63
+ ,99.87
+ ,102.38
+ ,102.45
+ ,107.34
+ ,96.13
+ ,99.86
+ ,102.86
+ ,102.45
+ ,107.34
+ ,96.13
+ ,100.10
+ ,102.87
+ ,102.45
+ ,107.34
+ ,96.13
+ ,100.10
+ ,102.92
+ ,102.45
+ ,107.34
+ ,96.13
+ ,100.12
+ ,102.95
+ ,102.45
+ ,107.34
+ ,96.13
+ ,99.95
+ ,103.02
+ ,102.45
+ ,112.60
+ ,96.13
+ ,99.94
+ ,104.08
+ ,102.52
+ ,112.60
+ ,96.13
+ ,100.18
+ ,104.16
+ ,102.52
+ ,112.60
+ ,96.13
+ ,100.31
+ ,104.24
+ ,102.85
+ ,112.60
+ ,96.13
+ ,100.65
+ ,104.33
+ ,102.85
+ ,112.61
+ ,96.13
+ ,100.65
+ ,104.73
+ ,102.85
+ ,112.61
+ ,96.13
+ ,100.69
+ ,104.86
+ ,103.25
+ ,112.61
+ ,96.13
+ ,101.26
+ ,105.03
+ ,103.25
+ ,112.61
+ ,98.73
+ ,101.26
+ ,105.62
+ ,103.25
+ ,112.61
+ ,98.73
+ ,101.38
+ ,105.63
+ ,103.25
+ ,112.61
+ ,98.73
+ ,101.38
+ ,105.63
+ ,104.45
+ ,112.61
+ ,98.73
+ ,101.38
+ ,105.94
+ ,104.45
+ ,112.61
+ ,98.73
+ ,101.44
+ ,106.61
+ ,104.45
+ ,118.65
+ ,98.73
+ ,101.40
+ ,107.69
+ ,104.80
+ ,118.65
+ ,98.73
+ ,101.40
+ ,107.78
+ ,104.80
+ ,118.65
+ ,98.73
+ ,100.58
+ ,107.93
+ ,105.29
+ ,118.65
+ ,98.73
+ ,100.58
+ ,108.48
+ ,105.29
+ ,114.29
+ ,98.73
+ ,100.58
+ ,108.14
+ ,105.29
+ ,114.29
+ ,98.73
+ ,100.59
+ ,108.48
+ ,105.29
+ ,114.29
+ ,98.73
+ ,100.81
+ ,108.48
+ ,106.04
+ ,114.29
+ ,101.67
+ ,100.75
+ ,108.89
+ ,105.94
+ ,114.29
+ ,101.67
+ ,100.75
+ ,108.93
+ ,105.94
+ ,114.29
+ ,101.67
+ ,100.96
+ ,109.21
+ ,105.94
+ ,114.29
+ ,101.67
+ ,101.31
+ ,109.47
+ ,106.28
+ ,114.29
+ ,101.67
+ ,101.64
+ ,109.80
+ ,106.48
+ ,123.33
+ ,101.67
+ ,101.46
+ ,111.73
+ ,107.19
+ ,123.33
+ ,101.67
+ ,101.73
+ ,111.85
+ ,108.14
+ ,123.33
+ ,101.67
+ ,101.73
+ ,112.12
+ ,108.22
+ ,123.33
+ ,101.67
+ ,101.64
+ ,112.15
+ ,108.22
+ ,123.33
+ ,101.67
+ ,101.77
+ ,112.17
+ ,108.61
+ ,123.33
+ ,101.67
+ ,101.74
+ ,112.67
+ ,108.61
+ ,123.33
+ ,101.67
+ ,101.89
+ ,112.80
+ ,108.61
+ ,123.33
+ ,107.94
+ ,101.89
+ ,113.44
+ ,108.61
+ ,123.33
+ ,107.94
+ ,101.93
+ ,113.53
+ ,109.06
+ ,123.33
+ ,107.94
+ ,101.93
+ ,114.53
+ ,109.06
+ ,123.33
+ ,107.94
+ ,102.32
+ ,114.51
+ ,112.93
+ ,123.33
+ ,107.94
+ ,102.41
+ ,115.05
+ ,115.84
+ ,129.03
+ ,107.94
+ ,103.58
+ ,116.67
+ ,118.57
+ ,128.76
+ ,107.94
+ ,104.12
+ ,117.07
+ ,118.57
+ ,128.76
+ ,107.94
+ ,104.10
+ ,116.92
+ ,118.86
+ ,128.76
+ ,107.94
+ ,104.15
+ ,117.00
+ ,118.98
+ ,128.76
+ ,107.94
+ ,104.15
+ ,117.02
+ ,119.27
+ ,128.76
+ ,107.94
+ ,104.16
+ ,117.35
+ ,119.39
+ ,128.76
+ ,107.94
+ ,102.94
+ ,117.36
+ ,119.49
+ ,128.76
+ ,110.30
+ ,103.07
+ ,117.82
+ ,119.59
+ ,128.76
+ ,110.30
+ ,103.04
+ ,117.88
+ ,120.12
+ ,128.76
+ ,110.30
+ ,103.06
+ ,118.24
+ ,120.14
+ ,128.76
+ ,110.30
+ ,103.05
+ ,118.50
+ ,120.14
+ ,128.76
+ ,110.30
+ ,102.95
+ ,118.80
+ ,120.14
+ ,132.63
+ ,110.30
+ ,102.95
+ ,119.76
+ ,120.14
+ ,132.63
+ ,110.30
+ ,103.05
+ ,120.09)
+ ,dim=c(5
+ ,58)
+ ,dimnames=list(c('bios'
+ ,'schouwburg'
+ ,'eedagsacttractie'
+ ,'huurDVD'
+ ,'vrijetijdsbesteding')
+ ,1:58))
> y <- array(NA,dim=c(5,58),dimnames=list(c('bios','schouwburg','eedagsacttractie','huurDVD','vrijetijdsbesteding'),1:58))
> 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 = '5'
> #'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
vrijetijdsbesteding bios schouwburg eedagsacttractie huurDVD M1 M2 M3 M4
1 101.76 101.82 107.34 93.63 99.85 1 0 0 0
2 102.37 101.68 107.34 93.63 99.91 0 1 0 0
3 102.38 101.68 107.34 93.63 99.87 0 0 1 0
4 102.86 102.45 107.34 96.13 99.86 0 0 0 1
5 102.87 102.45 107.34 96.13 100.10 0 0 0 0
6 102.92 102.45 107.34 96.13 100.10 0 0 0 0
7 102.95 102.45 107.34 96.13 100.12 0 0 0 0
8 103.02 102.45 107.34 96.13 99.95 0 0 0 0
9 104.08 102.45 112.60 96.13 99.94 0 0 0 0
10 104.16 102.52 112.60 96.13 100.18 0 0 0 0
11 104.24 102.52 112.60 96.13 100.31 0 0 0 0
12 104.33 102.85 112.60 96.13 100.65 0 0 0 0
13 104.73 102.85 112.61 96.13 100.65 1 0 0 0
14 104.86 102.85 112.61 96.13 100.69 0 1 0 0
15 105.03 103.25 112.61 96.13 101.26 0 0 1 0
16 105.62 103.25 112.61 98.73 101.26 0 0 0 1
17 105.63 103.25 112.61 98.73 101.38 0 0 0 0
18 105.63 103.25 112.61 98.73 101.38 0 0 0 0
19 105.94 104.45 112.61 98.73 101.38 0 0 0 0
20 106.61 104.45 112.61 98.73 101.44 0 0 0 0
21 107.69 104.45 118.65 98.73 101.40 0 0 0 0
22 107.78 104.80 118.65 98.73 101.40 0 0 0 0
23 107.93 104.80 118.65 98.73 100.58 0 0 0 0
24 108.48 105.29 118.65 98.73 100.58 0 0 0 0
25 108.14 105.29 114.29 98.73 100.58 1 0 0 0
26 108.48 105.29 114.29 98.73 100.59 0 1 0 0
27 108.48 105.29 114.29 98.73 100.81 0 0 1 0
28 108.89 106.04 114.29 101.67 100.75 0 0 0 1
29 108.93 105.94 114.29 101.67 100.75 0 0 0 0
30 109.21 105.94 114.29 101.67 100.96 0 0 0 0
31 109.47 105.94 114.29 101.67 101.31 0 0 0 0
32 109.80 106.28 114.29 101.67 101.64 0 0 0 0
33 111.73 106.48 123.33 101.67 101.46 0 0 0 0
34 111.85 107.19 123.33 101.67 101.73 0 0 0 0
35 112.12 108.14 123.33 101.67 101.73 0 0 0 0
36 112.15 108.22 123.33 101.67 101.64 0 0 0 0
37 112.17 108.22 123.33 101.67 101.77 1 0 0 0
38 112.67 108.61 123.33 101.67 101.74 0 1 0 0
39 112.80 108.61 123.33 101.67 101.89 0 0 1 0
40 113.44 108.61 123.33 107.94 101.89 0 0 0 1
41 113.53 108.61 123.33 107.94 101.93 0 0 0 0
42 114.53 109.06 123.33 107.94 101.93 0 0 0 0
43 114.51 109.06 123.33 107.94 102.32 0 0 0 0
44 115.05 112.93 123.33 107.94 102.41 0 0 0 0
45 116.67 115.84 129.03 107.94 103.58 0 0 0 0
46 117.07 118.57 128.76 107.94 104.12 0 0 0 0
47 116.92 118.57 128.76 107.94 104.10 0 0 0 0
48 117.00 118.86 128.76 107.94 104.15 0 0 0 0
49 117.02 118.98 128.76 107.94 104.15 1 0 0 0
50 117.35 119.27 128.76 107.94 104.16 0 1 0 0
51 117.36 119.39 128.76 107.94 102.94 0 0 1 0
52 117.82 119.49 128.76 110.30 103.07 0 0 0 1
53 117.88 119.59 128.76 110.30 103.04 0 0 0 0
54 118.24 120.12 128.76 110.30 103.06 0 0 0 0
55 118.50 120.14 128.76 110.30 103.05 0 0 0 0
56 118.80 120.14 128.76 110.30 102.95 0 0 0 0
57 119.76 120.14 132.63 110.30 102.95 0 0 0 0
58 120.09 120.14 132.63 110.30 103.05 0 0 0 0
M5 M6 M7 M8 M9 M10 M11
1 0 0 0 0 0 0 0
2 0 0 0 0 0 0 0
3 0 0 0 0 0 0 0
4 0 0 0 0 0 0 0
5 1 0 0 0 0 0 0
6 0 1 0 0 0 0 0
7 0 0 1 0 0 0 0
8 0 0 0 1 0 0 0
9 0 0 0 0 1 0 0
10 0 0 0 0 0 1 0
11 0 0 0 0 0 0 1
12 0 0 0 0 0 0 0
13 0 0 0 0 0 0 0
14 0 0 0 0 0 0 0
15 0 0 0 0 0 0 0
16 0 0 0 0 0 0 0
17 1 0 0 0 0 0 0
18 0 1 0 0 0 0 0
19 0 0 1 0 0 0 0
20 0 0 0 1 0 0 0
21 0 0 0 0 1 0 0
22 0 0 0 0 0 1 0
23 0 0 0 0 0 0 1
24 0 0 0 0 0 0 0
25 0 0 0 0 0 0 0
26 0 0 0 0 0 0 0
27 0 0 0 0 0 0 0
28 0 0 0 0 0 0 0
29 1 0 0 0 0 0 0
30 0 1 0 0 0 0 0
31 0 0 1 0 0 0 0
32 0 0 0 1 0 0 0
33 0 0 0 0 1 0 0
34 0 0 0 0 0 1 0
35 0 0 0 0 0 0 1
36 0 0 0 0 0 0 0
37 0 0 0 0 0 0 0
38 0 0 0 0 0 0 0
39 0 0 0 0 0 0 0
40 0 0 0 0 0 0 0
41 1 0 0 0 0 0 0
42 0 1 0 0 0 0 0
43 0 0 1 0 0 0 0
44 0 0 0 1 0 0 0
45 0 0 0 0 1 0 0
46 0 0 0 0 0 1 0
47 0 0 0 0 0 0 1
48 0 0 0 0 0 0 0
49 0 0 0 0 0 0 0
50 0 0 0 0 0 0 0
51 0 0 0 0 0 0 0
52 0 0 0 0 0 0 0
53 1 0 0 0 0 0 0
54 0 1 0 0 0 0 0
55 0 0 1 0 0 0 0
56 0 0 0 1 0 0 0
57 0 0 0 0 1 0 0
58 0 0 0 0 0 1 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) bios schouwburg eedagsacttractie
35.26894 0.06863 0.34963 0.53372
huurDVD M1 M2 M3
-0.27971 0.31601 0.69563 0.73459
M4 M5 M6 M7
-0.54769 -0.48500 -0.14758 0.04563
M8 M9 M10 M11
0.38159 -0.37001 -0.13578 -0.18806
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.9648 -0.3789 -0.1256 0.2953 1.0630
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 35.26894 14.40669 2.448 0.0186 *
bios 0.06863 0.04094 1.676 0.1011
schouwburg 0.34963 0.05655 6.182 2.17e-07 ***
eedagsacttractie 0.53372 0.09155 5.829 6.99e-07 ***
huurDVD -0.27971 0.17449 -1.603 0.1164
M1 0.31601 0.39797 0.794 0.4316
M2 0.69563 0.39816 1.747 0.0879 .
M3 0.73459 0.39837 1.844 0.0722 .
M4 -0.54769 0.53158 -1.030 0.3088
M5 -0.48500 0.53115 -0.913 0.3664
M6 -0.14758 0.52955 -0.279 0.7819
M7 0.04563 0.52800 0.086 0.9315
M8 0.38159 0.52294 0.730 0.4696
M9 -0.37001 0.39331 -0.941 0.3522
M10 -0.13578 0.39015 -0.348 0.7296
M11 -0.18806 0.41003 -0.459 0.6488
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.5795 on 42 degrees of freedom
Multiple R-squared: 0.992, Adjusted R-squared: 0.9892
F-statistic: 348.8 on 15 and 42 DF, p-value: < 2.2e-16
> 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,] 0.03333043 0.06666087 0.9666696
[2,] 0.05653667 0.11307334 0.9434633
[3,] 0.04582661 0.09165321 0.9541734
[4,] 0.05204650 0.10409299 0.9479535
[5,] 0.10362247 0.20724494 0.8963775
[6,] 0.30245921 0.60491841 0.6975408
[7,] 0.23937423 0.47874846 0.7606258
[8,] 0.17037829 0.34075658 0.8296217
[9,] 0.10580906 0.21161812 0.8941909
[10,] 0.20743927 0.41487854 0.7925607
[11,] 0.18969979 0.37939958 0.8103002
[12,] 0.12796769 0.25593538 0.8720323
[13,] 0.14529458 0.29058917 0.8547054
[14,] 0.60950101 0.78099797 0.3904990
[15,] 0.59459941 0.81080118 0.4054006
[16,] 0.68971041 0.62057918 0.3102896
[17,] 0.57806143 0.84387713 0.4219386
[18,] 0.48710958 0.97421917 0.5128904
[19,] 0.46311648 0.92623295 0.5368835
[20,] 0.42680822 0.85361644 0.5731918
[21,] 0.40836685 0.81673371 0.5916331
> postscript(file="/var/www/html/rcomp/tmp/1aye31292586873.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2lpdo1292586873.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3lpdo1292586873.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4dhcr1292586873.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5dhcr1292586873.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 = 58
Frequency = 1
1 2 3 4 5 6
-0.38499453 -0.12822667 -0.16837618 0.20398031 0.21841230 -0.06900310
7 8 9 10 11 12
-0.22662002 -0.54013305 -0.57039362 -0.66229909 -0.49365522 -0.51926230
13 14 15 16 17 18
-0.43876742 -0.67720185 -0.41417938 0.07044704 0.05131374 -0.28610167
19 20 21 22 23 24
-0.25166766 0.09915279 -0.19221271 -0.36046491 -0.38754632 -0.05923573
25 26 27 28 29 30
0.80915460 0.77232885 0.79490415 0.84981288 0.83397719 0.83530106
31 32 33 34 35 36
0.99998871 1.06299721 0.51984790 0.43241116 0.68949502 0.50076956
37 38 39 40 41 42
0.24112316 0.32634365 0.45933919 -0.96477009 -0.92628026 -0.29457874
43 44 45 46 47 48
-0.39870265 -0.43508530 0.07116391 0.29501927 0.19170652 0.07772847
49 50 51 52 53 54
-0.22651582 -0.29324399 -0.67168777 -0.15947014 -0.17742297 -0.18561755
55 56 57 58
-0.12299838 -0.18693165 0.17159452 0.29533357
> postscript(file="/var/www/html/rcomp/tmp/6dhcr1292586873.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 = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.38499453 NA
1 -0.12822667 -0.38499453
2 -0.16837618 -0.12822667
3 0.20398031 -0.16837618
4 0.21841230 0.20398031
5 -0.06900310 0.21841230
6 -0.22662002 -0.06900310
7 -0.54013305 -0.22662002
8 -0.57039362 -0.54013305
9 -0.66229909 -0.57039362
10 -0.49365522 -0.66229909
11 -0.51926230 -0.49365522
12 -0.43876742 -0.51926230
13 -0.67720185 -0.43876742
14 -0.41417938 -0.67720185
15 0.07044704 -0.41417938
16 0.05131374 0.07044704
17 -0.28610167 0.05131374
18 -0.25166766 -0.28610167
19 0.09915279 -0.25166766
20 -0.19221271 0.09915279
21 -0.36046491 -0.19221271
22 -0.38754632 -0.36046491
23 -0.05923573 -0.38754632
24 0.80915460 -0.05923573
25 0.77232885 0.80915460
26 0.79490415 0.77232885
27 0.84981288 0.79490415
28 0.83397719 0.84981288
29 0.83530106 0.83397719
30 0.99998871 0.83530106
31 1.06299721 0.99998871
32 0.51984790 1.06299721
33 0.43241116 0.51984790
34 0.68949502 0.43241116
35 0.50076956 0.68949502
36 0.24112316 0.50076956
37 0.32634365 0.24112316
38 0.45933919 0.32634365
39 -0.96477009 0.45933919
40 -0.92628026 -0.96477009
41 -0.29457874 -0.92628026
42 -0.39870265 -0.29457874
43 -0.43508530 -0.39870265
44 0.07116391 -0.43508530
45 0.29501927 0.07116391
46 0.19170652 0.29501927
47 0.07772847 0.19170652
48 -0.22651582 0.07772847
49 -0.29324399 -0.22651582
50 -0.67168777 -0.29324399
51 -0.15947014 -0.67168777
52 -0.17742297 -0.15947014
53 -0.18561755 -0.17742297
54 -0.12299838 -0.18561755
55 -0.18693165 -0.12299838
56 0.17159452 -0.18693165
57 0.29533357 0.17159452
58 NA 0.29533357
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.12822667 -0.38499453
[2,] -0.16837618 -0.12822667
[3,] 0.20398031 -0.16837618
[4,] 0.21841230 0.20398031
[5,] -0.06900310 0.21841230
[6,] -0.22662002 -0.06900310
[7,] -0.54013305 -0.22662002
[8,] -0.57039362 -0.54013305
[9,] -0.66229909 -0.57039362
[10,] -0.49365522 -0.66229909
[11,] -0.51926230 -0.49365522
[12,] -0.43876742 -0.51926230
[13,] -0.67720185 -0.43876742
[14,] -0.41417938 -0.67720185
[15,] 0.07044704 -0.41417938
[16,] 0.05131374 0.07044704
[17,] -0.28610167 0.05131374
[18,] -0.25166766 -0.28610167
[19,] 0.09915279 -0.25166766
[20,] -0.19221271 0.09915279
[21,] -0.36046491 -0.19221271
[22,] -0.38754632 -0.36046491
[23,] -0.05923573 -0.38754632
[24,] 0.80915460 -0.05923573
[25,] 0.77232885 0.80915460
[26,] 0.79490415 0.77232885
[27,] 0.84981288 0.79490415
[28,] 0.83397719 0.84981288
[29,] 0.83530106 0.83397719
[30,] 0.99998871 0.83530106
[31,] 1.06299721 0.99998871
[32,] 0.51984790 1.06299721
[33,] 0.43241116 0.51984790
[34,] 0.68949502 0.43241116
[35,] 0.50076956 0.68949502
[36,] 0.24112316 0.50076956
[37,] 0.32634365 0.24112316
[38,] 0.45933919 0.32634365
[39,] -0.96477009 0.45933919
[40,] -0.92628026 -0.96477009
[41,] -0.29457874 -0.92628026
[42,] -0.39870265 -0.29457874
[43,] -0.43508530 -0.39870265
[44,] 0.07116391 -0.43508530
[45,] 0.29501927 0.07116391
[46,] 0.19170652 0.29501927
[47,] 0.07772847 0.19170652
[48,] -0.22651582 0.07772847
[49,] -0.29324399 -0.22651582
[50,] -0.67168777 -0.29324399
[51,] -0.15947014 -0.67168777
[52,] -0.17742297 -0.15947014
[53,] -0.18561755 -0.17742297
[54,] -0.12299838 -0.18561755
[55,] -0.18693165 -0.12299838
[56,] 0.17159452 -0.18693165
[57,] 0.29533357 0.17159452
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.12822667 -0.38499453
2 -0.16837618 -0.12822667
3 0.20398031 -0.16837618
4 0.21841230 0.20398031
5 -0.06900310 0.21841230
6 -0.22662002 -0.06900310
7 -0.54013305 -0.22662002
8 -0.57039362 -0.54013305
9 -0.66229909 -0.57039362
10 -0.49365522 -0.66229909
11 -0.51926230 -0.49365522
12 -0.43876742 -0.51926230
13 -0.67720185 -0.43876742
14 -0.41417938 -0.67720185
15 0.07044704 -0.41417938
16 0.05131374 0.07044704
17 -0.28610167 0.05131374
18 -0.25166766 -0.28610167
19 0.09915279 -0.25166766
20 -0.19221271 0.09915279
21 -0.36046491 -0.19221271
22 -0.38754632 -0.36046491
23 -0.05923573 -0.38754632
24 0.80915460 -0.05923573
25 0.77232885 0.80915460
26 0.79490415 0.77232885
27 0.84981288 0.79490415
28 0.83397719 0.84981288
29 0.83530106 0.83397719
30 0.99998871 0.83530106
31 1.06299721 0.99998871
32 0.51984790 1.06299721
33 0.43241116 0.51984790
34 0.68949502 0.43241116
35 0.50076956 0.68949502
36 0.24112316 0.50076956
37 0.32634365 0.24112316
38 0.45933919 0.32634365
39 -0.96477009 0.45933919
40 -0.92628026 -0.96477009
41 -0.29457874 -0.92628026
42 -0.39870265 -0.29457874
43 -0.43508530 -0.39870265
44 0.07116391 -0.43508530
45 0.29501927 0.07116391
46 0.19170652 0.29501927
47 0.07772847 0.19170652
48 -0.22651582 0.07772847
49 -0.29324399 -0.22651582
50 -0.67168777 -0.29324399
51 -0.15947014 -0.67168777
52 -0.17742297 -0.15947014
53 -0.18561755 -0.17742297
54 -0.12299838 -0.18561755
55 -0.18693165 -0.12299838
56 0.17159452 -0.18693165
57 0.29533357 0.17159452
> 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/768uu1292586873.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/868uu1292586873.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9hzbx1292586873.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10hzbx1292586873.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11vrr61292586873.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/126i891292586873.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/13c1521292586873.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/145b451292586873.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/15jkkw1292586873.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/16n3jk1292586873.tab")
+ }
>
> try(system("convert tmp/1aye31292586873.ps tmp/1aye31292586873.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lpdo1292586873.ps tmp/2lpdo1292586873.png",intern=TRUE))
character(0)
> try(system("convert tmp/3lpdo1292586873.ps tmp/3lpdo1292586873.png",intern=TRUE))
character(0)
> try(system("convert tmp/4dhcr1292586873.ps tmp/4dhcr1292586873.png",intern=TRUE))
character(0)
> try(system("convert tmp/5dhcr1292586873.ps tmp/5dhcr1292586873.png",intern=TRUE))
character(0)
> try(system("convert tmp/6dhcr1292586873.ps tmp/6dhcr1292586873.png",intern=TRUE))
character(0)
> try(system("convert tmp/768uu1292586873.ps tmp/768uu1292586873.png",intern=TRUE))
character(0)
> try(system("convert tmp/868uu1292586873.ps tmp/868uu1292586873.png",intern=TRUE))
character(0)
> try(system("convert tmp/9hzbx1292586873.ps tmp/9hzbx1292586873.png",intern=TRUE))
character(0)
> try(system("convert tmp/10hzbx1292586873.ps tmp/10hzbx1292586873.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.415 1.686 8.160