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('Bioscoop'
+ ,'Schouwburgabonnement'
+ ,'Eendagsattracties'
+ ,'DVDhuren'
+ ,'Vrijetijdsbesteding')
+ ,1:58))
> y <- array(NA,dim=c(5,58),dimnames=list(c('Bioscoop','Schouwburgabonnement','Eendagsattracties','DVDhuren','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 = 'Do not include Seasonal Dummies'
> par1 = '2'
> #'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
Schouwburgabonnement Bioscoop Eendagsattracties DVDhuren Vrijetijdsbesteding
1 107.34 101.82 93.63 99.85 101.76
2 107.34 101.68 93.63 99.91 102.37
3 107.34 101.68 93.63 99.87 102.38
4 107.34 102.45 96.13 99.86 102.86
5 107.34 102.45 96.13 100.10 102.87
6 107.34 102.45 96.13 100.10 102.92
7 107.34 102.45 96.13 100.12 102.95
8 107.34 102.45 96.13 99.95 103.02
9 112.60 102.45 96.13 99.94 104.08
10 112.60 102.52 96.13 100.18 104.16
11 112.60 102.52 96.13 100.31 104.24
12 112.60 102.85 96.13 100.65 104.33
13 112.61 102.85 96.13 100.65 104.73
14 112.61 102.85 96.13 100.69 104.86
15 112.61 103.25 96.13 101.26 105.03
16 112.61 103.25 98.73 101.26 105.62
17 112.61 103.25 98.73 101.38 105.63
18 112.61 103.25 98.73 101.38 105.63
19 112.61 104.45 98.73 101.38 105.94
20 112.61 104.45 98.73 101.44 106.61
21 118.65 104.45 98.73 101.40 107.69
22 118.65 104.80 98.73 101.40 107.78
23 118.65 104.80 98.73 100.58 107.93
24 118.65 105.29 98.73 100.58 108.48
25 114.29 105.29 98.73 100.58 108.14
26 114.29 105.29 98.73 100.59 108.48
27 114.29 105.29 98.73 100.81 108.48
28 114.29 106.04 101.67 100.75 108.89
29 114.29 105.94 101.67 100.75 108.93
30 114.29 105.94 101.67 100.96 109.21
31 114.29 105.94 101.67 101.31 109.47
32 114.29 106.28 101.67 101.64 109.80
33 123.33 106.48 101.67 101.46 111.73
34 123.33 107.19 101.67 101.73 111.85
35 123.33 108.14 101.67 101.73 112.12
36 123.33 108.22 101.67 101.64 112.15
37 123.33 108.22 101.67 101.77 112.17
38 123.33 108.61 101.67 101.74 112.67
39 123.33 108.61 101.67 101.89 112.80
40 123.33 108.61 107.94 101.89 113.44
41 123.33 108.61 107.94 101.93 113.53
42 123.33 109.06 107.94 101.93 114.53
43 123.33 109.06 107.94 102.32 114.51
44 123.33 112.93 107.94 102.41 115.05
45 129.03 115.84 107.94 103.58 116.67
46 128.76 118.57 107.94 104.12 117.07
47 128.76 118.57 107.94 104.10 116.92
48 128.76 118.86 107.94 104.15 117.00
49 128.76 118.98 107.94 104.15 117.02
50 128.76 119.27 107.94 104.16 117.35
51 128.76 119.39 107.94 102.94 117.36
52 128.76 119.49 110.30 103.07 117.82
53 128.76 119.59 110.30 103.04 117.88
54 128.76 120.12 110.30 103.06 118.24
55 128.76 120.14 110.30 103.05 118.50
56 128.76 120.14 110.30 102.95 118.80
57 132.63 120.14 110.30 102.95 119.76
58 132.63 120.14 110.30 103.05 120.09
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Bioscoop Eendagsattracties
-111.1542 -0.1388 -0.6660
DVDhuren Vrijetijdsbesteding
0.9651 1.9488
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4.15865 -0.74346 -0.05514 0.82941 2.71758
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -111.1542 35.3791 -3.142 0.00275 **
Bioscoop -0.1388 0.1067 -1.301 0.19896
Eendagsattracties -0.6660 0.1582 -4.209 9.96e-05 ***
DVDhuren 0.9651 0.4380 2.204 0.03192 *
Vrijetijdsbesteding 1.9488 0.1818 10.722 6.94e-15 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.527 on 53 degrees of freedom
Multiple R-squared: 0.9647, Adjusted R-squared: 0.962
F-statistic: 361.6 on 4 and 53 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,] 0.000000000 0.000000000 1.0000000000
[2,] 0.002218635 0.004437269 0.9977813653
[3,] 0.003876373 0.007752745 0.9961236274
[4,] 0.001257448 0.002514896 0.9987425519
[5,] 0.014496870 0.028993739 0.9855031304
[6,] 0.032963837 0.065927673 0.9670361633
[7,] 0.034752845 0.069505690 0.9652471552
[8,] 0.018791655 0.037583310 0.9812083449
[9,] 0.010369170 0.020738340 0.9896308300
[10,] 0.005226574 0.010453149 0.9947734256
[11,] 0.002520050 0.005040099 0.9974799505
[12,] 0.001527009 0.003054019 0.9984729907
[13,] 0.007827099 0.015654198 0.9921729008
[14,] 0.007906739 0.015813477 0.9920932613
[15,] 0.011706375 0.023412750 0.9882936252
[16,] 0.059274857 0.118549714 0.9407251428
[17,] 0.236330329 0.472660658 0.7636696709
[18,] 0.676766888 0.646466225 0.3232331124
[19,] 0.879834479 0.240331042 0.1201655212
[20,] 0.928304399 0.143391201 0.0716956006
[21,] 0.903892395 0.192215210 0.0961076051
[22,] 0.877887457 0.244225086 0.1221125428
[23,] 0.856072400 0.287855201 0.1439276005
[24,] 0.901723495 0.196553009 0.0982765047
[25,] 0.998274467 0.003451067 0.0017255335
[26,] 0.997863283 0.004273433 0.0021367166
[27,] 0.997935158 0.004129685 0.0020648425
[28,] 0.998280666 0.003438667 0.0017193337
[29,] 0.997974123 0.004051754 0.0020258768
[30,] 0.997359625 0.005280750 0.0026403749
[31,] 0.994698590 0.010602821 0.0053014103
[32,] 0.989486427 0.021027146 0.0105135729
[33,] 0.996701281 0.006597438 0.0032987188
[34,] 0.999438916 0.001122167 0.0005610836
[35,] 0.998554568 0.002890865 0.0014454324
[36,] 0.996316696 0.007366608 0.0036833042
[37,] 0.999141553 0.001716895 0.0008584475
[38,] 0.999364530 0.001270940 0.0006354699
[39,] 0.998773355 0.002453290 0.0012266448
[40,] 0.997214090 0.005571821 0.0027859104
[41,] 0.990601599 0.018796801 0.0093984007
[42,] 0.968934383 0.062131234 0.0310656169
[43,] 0.913630977 0.172738046 0.0863690232
> postscript(file="/var/www/html/rcomp/tmp/1973j1291990497.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/21h251291990497.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/31h251291990497.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4uq1p1291990497.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5uq1p1291990497.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
0.31308281 -0.95300516 -0.93388693 -0.08772117 -0.33884362 -0.43628152
7 8 9 10 11 12
-0.51404717 -0.48638554 2.71758238 2.33976529 2.05839576 1.60067357
13 14 15 16 17 18
0.83117034 0.53922599 -0.28666184 0.29518704 0.15988203 0.15988203
19 20 21 22 23 24
-0.27763143 -1.64120804 2.33273907 2.20594296 2.70504838 1.70126041
25 26 27 28 29 30
-1.99616185 -2.66839104 -2.88072300 -1.55962087 -1.65145466 -2.39978742
31 32 33 34 35 36
-3.24426536 -4.15864969 1.32174034 0.92587273 0.53160094 0.57110804
37 38 39 40 41 42
0.40666399 -0.48461517 -0.88272551 2.04592825 1.83193421 -0.05434826
43 44 45 46 47 48
-0.39177976 -0.99368222 0.82411850 -0.36754466 -0.05592805 -0.21982392
49 50 51 52 53 54
-0.24213893 -0.85461850 0.32003131 0.88379183 0.80970417 0.16243071
55 56 57 58
-0.33181824 -0.81993113 1.17926114 0.43965645
> postscript(file="/var/www/html/rcomp/tmp/6uq1p1291990497.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 0.31308281 NA
1 -0.95300516 0.31308281
2 -0.93388693 -0.95300516
3 -0.08772117 -0.93388693
4 -0.33884362 -0.08772117
5 -0.43628152 -0.33884362
6 -0.51404717 -0.43628152
7 -0.48638554 -0.51404717
8 2.71758238 -0.48638554
9 2.33976529 2.71758238
10 2.05839576 2.33976529
11 1.60067357 2.05839576
12 0.83117034 1.60067357
13 0.53922599 0.83117034
14 -0.28666184 0.53922599
15 0.29518704 -0.28666184
16 0.15988203 0.29518704
17 0.15988203 0.15988203
18 -0.27763143 0.15988203
19 -1.64120804 -0.27763143
20 2.33273907 -1.64120804
21 2.20594296 2.33273907
22 2.70504838 2.20594296
23 1.70126041 2.70504838
24 -1.99616185 1.70126041
25 -2.66839104 -1.99616185
26 -2.88072300 -2.66839104
27 -1.55962087 -2.88072300
28 -1.65145466 -1.55962087
29 -2.39978742 -1.65145466
30 -3.24426536 -2.39978742
31 -4.15864969 -3.24426536
32 1.32174034 -4.15864969
33 0.92587273 1.32174034
34 0.53160094 0.92587273
35 0.57110804 0.53160094
36 0.40666399 0.57110804
37 -0.48461517 0.40666399
38 -0.88272551 -0.48461517
39 2.04592825 -0.88272551
40 1.83193421 2.04592825
41 -0.05434826 1.83193421
42 -0.39177976 -0.05434826
43 -0.99368222 -0.39177976
44 0.82411850 -0.99368222
45 -0.36754466 0.82411850
46 -0.05592805 -0.36754466
47 -0.21982392 -0.05592805
48 -0.24213893 -0.21982392
49 -0.85461850 -0.24213893
50 0.32003131 -0.85461850
51 0.88379183 0.32003131
52 0.80970417 0.88379183
53 0.16243071 0.80970417
54 -0.33181824 0.16243071
55 -0.81993113 -0.33181824
56 1.17926114 -0.81993113
57 0.43965645 1.17926114
58 NA 0.43965645
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.95300516 0.31308281
[2,] -0.93388693 -0.95300516
[3,] -0.08772117 -0.93388693
[4,] -0.33884362 -0.08772117
[5,] -0.43628152 -0.33884362
[6,] -0.51404717 -0.43628152
[7,] -0.48638554 -0.51404717
[8,] 2.71758238 -0.48638554
[9,] 2.33976529 2.71758238
[10,] 2.05839576 2.33976529
[11,] 1.60067357 2.05839576
[12,] 0.83117034 1.60067357
[13,] 0.53922599 0.83117034
[14,] -0.28666184 0.53922599
[15,] 0.29518704 -0.28666184
[16,] 0.15988203 0.29518704
[17,] 0.15988203 0.15988203
[18,] -0.27763143 0.15988203
[19,] -1.64120804 -0.27763143
[20,] 2.33273907 -1.64120804
[21,] 2.20594296 2.33273907
[22,] 2.70504838 2.20594296
[23,] 1.70126041 2.70504838
[24,] -1.99616185 1.70126041
[25,] -2.66839104 -1.99616185
[26,] -2.88072300 -2.66839104
[27,] -1.55962087 -2.88072300
[28,] -1.65145466 -1.55962087
[29,] -2.39978742 -1.65145466
[30,] -3.24426536 -2.39978742
[31,] -4.15864969 -3.24426536
[32,] 1.32174034 -4.15864969
[33,] 0.92587273 1.32174034
[34,] 0.53160094 0.92587273
[35,] 0.57110804 0.53160094
[36,] 0.40666399 0.57110804
[37,] -0.48461517 0.40666399
[38,] -0.88272551 -0.48461517
[39,] 2.04592825 -0.88272551
[40,] 1.83193421 2.04592825
[41,] -0.05434826 1.83193421
[42,] -0.39177976 -0.05434826
[43,] -0.99368222 -0.39177976
[44,] 0.82411850 -0.99368222
[45,] -0.36754466 0.82411850
[46,] -0.05592805 -0.36754466
[47,] -0.21982392 -0.05592805
[48,] -0.24213893 -0.21982392
[49,] -0.85461850 -0.24213893
[50,] 0.32003131 -0.85461850
[51,] 0.88379183 0.32003131
[52,] 0.80970417 0.88379183
[53,] 0.16243071 0.80970417
[54,] -0.33181824 0.16243071
[55,] -0.81993113 -0.33181824
[56,] 1.17926114 -0.81993113
[57,] 0.43965645 1.17926114
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.95300516 0.31308281
2 -0.93388693 -0.95300516
3 -0.08772117 -0.93388693
4 -0.33884362 -0.08772117
5 -0.43628152 -0.33884362
6 -0.51404717 -0.43628152
7 -0.48638554 -0.51404717
8 2.71758238 -0.48638554
9 2.33976529 2.71758238
10 2.05839576 2.33976529
11 1.60067357 2.05839576
12 0.83117034 1.60067357
13 0.53922599 0.83117034
14 -0.28666184 0.53922599
15 0.29518704 -0.28666184
16 0.15988203 0.29518704
17 0.15988203 0.15988203
18 -0.27763143 0.15988203
19 -1.64120804 -0.27763143
20 2.33273907 -1.64120804
21 2.20594296 2.33273907
22 2.70504838 2.20594296
23 1.70126041 2.70504838
24 -1.99616185 1.70126041
25 -2.66839104 -1.99616185
26 -2.88072300 -2.66839104
27 -1.55962087 -2.88072300
28 -1.65145466 -1.55962087
29 -2.39978742 -1.65145466
30 -3.24426536 -2.39978742
31 -4.15864969 -3.24426536
32 1.32174034 -4.15864969
33 0.92587273 1.32174034
34 0.53160094 0.92587273
35 0.57110804 0.53160094
36 0.40666399 0.57110804
37 -0.48461517 0.40666399
38 -0.88272551 -0.48461517
39 2.04592825 -0.88272551
40 1.83193421 2.04592825
41 -0.05434826 1.83193421
42 -0.39177976 -0.05434826
43 -0.99368222 -0.39177976
44 0.82411850 -0.99368222
45 -0.36754466 0.82411850
46 -0.05592805 -0.36754466
47 -0.21982392 -0.05592805
48 -0.24213893 -0.21982392
49 -0.85461850 -0.24213893
50 0.32003131 -0.85461850
51 0.88379183 0.32003131
52 0.80970417 0.88379183
53 0.16243071 0.80970417
54 -0.33181824 0.16243071
55 -0.81993113 -0.33181824
56 1.17926114 -0.81993113
57 0.43965645 1.17926114
> 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/7nh1s1291990497.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8fqid1291990497.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9fqid1291990497.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10fqid1291990497.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11b0ym1291990497.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/12mrxp1291990497.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/13tac11291990497.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/14ebb71291990497.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/1572ar1291990497.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/163uqi1291990497.tab")
+ }
>
> try(system("convert tmp/1973j1291990497.ps tmp/1973j1291990497.png",intern=TRUE))
character(0)
> try(system("convert tmp/21h251291990497.ps tmp/21h251291990497.png",intern=TRUE))
character(0)
> try(system("convert tmp/31h251291990497.ps tmp/31h251291990497.png",intern=TRUE))
character(0)
> try(system("convert tmp/4uq1p1291990497.ps tmp/4uq1p1291990497.png",intern=TRUE))
character(0)
> try(system("convert tmp/5uq1p1291990497.ps tmp/5uq1p1291990497.png",intern=TRUE))
character(0)
> try(system("convert tmp/6uq1p1291990497.ps tmp/6uq1p1291990497.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nh1s1291990497.ps tmp/7nh1s1291990497.png",intern=TRUE))
character(0)
> try(system("convert tmp/8fqid1291990497.ps tmp/8fqid1291990497.png",intern=TRUE))
character(0)
> try(system("convert tmp/9fqid1291990497.ps tmp/9fqid1291990497.png",intern=TRUE))
character(0)
> try(system("convert tmp/10fqid1291990497.ps tmp/10fqid1291990497.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.567 1.680 8.883