R version 2.7.0 (2008-04-22)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(82.7,0,88.9,0,105.9,0,100.8,0,94,0,105,0,58.5,0,87.6,0,113.1,0,112.5,0,89.6,0,74.5,0,82.7,0,90.1,0,109.4,0,96,0,89.2,0,109.1,0,49.1,0,92.9,0,107.7,0,103.5,0,91.1,0,79.8,0,71.9,0,82.9,0,90.1,0,100.7,0,90.7,0,108.8,0,44.1,0,93.6,0,107.4,0,96.5,0,93.6,0,76.5,0,76.7,1,84,1,103.3,1,88.5,1,99,1,105.9,1,44.7,1,94,1,107.1,1,104.8,1,102.5,1,77.7,1,85.2,1,91.3,1,106.5,1,92.4,1,97.5,1,107,1,51.1,1,98.6,1,102.2,1,114.3,1,99.4,1,72.5,1,92.3,1,99.4,1,85.9,1,109.4,1,97.6,1),dim=c(2,65),dimnames=list(c('Bouwproductie','d'),1:65))
> y <- array(NA,dim=c(2,65),dimnames=list(c('Bouwproductie','d'),1:65))
> 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'
> #'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
Bouwproductie d M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 82.7 0 1 0 0 0 0 0 0 0 0 0 0
2 88.9 0 0 1 0 0 0 0 0 0 0 0 0
3 105.9 0 0 0 1 0 0 0 0 0 0 0 0
4 100.8 0 0 0 0 1 0 0 0 0 0 0 0
5 94.0 0 0 0 0 0 1 0 0 0 0 0 0
6 105.0 0 0 0 0 0 0 1 0 0 0 0 0
7 58.5 0 0 0 0 0 0 0 1 0 0 0 0
8 87.6 0 0 0 0 0 0 0 0 1 0 0 0
9 113.1 0 0 0 0 0 0 0 0 0 1 0 0
10 112.5 0 0 0 0 0 0 0 0 0 0 1 0
11 89.6 0 0 0 0 0 0 0 0 0 0 0 1
12 74.5 0 0 0 0 0 0 0 0 0 0 0 0
13 82.7 0 1 0 0 0 0 0 0 0 0 0 0
14 90.1 0 0 1 0 0 0 0 0 0 0 0 0
15 109.4 0 0 0 1 0 0 0 0 0 0 0 0
16 96.0 0 0 0 0 1 0 0 0 0 0 0 0
17 89.2 0 0 0 0 0 1 0 0 0 0 0 0
18 109.1 0 0 0 0 0 0 1 0 0 0 0 0
19 49.1 0 0 0 0 0 0 0 1 0 0 0 0
20 92.9 0 0 0 0 0 0 0 0 1 0 0 0
21 107.7 0 0 0 0 0 0 0 0 0 1 0 0
22 103.5 0 0 0 0 0 0 0 0 0 0 1 0
23 91.1 0 0 0 0 0 0 0 0 0 0 0 1
24 79.8 0 0 0 0 0 0 0 0 0 0 0 0
25 71.9 0 1 0 0 0 0 0 0 0 0 0 0
26 82.9 0 0 1 0 0 0 0 0 0 0 0 0
27 90.1 0 0 0 1 0 0 0 0 0 0 0 0
28 100.7 0 0 0 0 1 0 0 0 0 0 0 0
29 90.7 0 0 0 0 0 1 0 0 0 0 0 0
30 108.8 0 0 0 0 0 0 1 0 0 0 0 0
31 44.1 0 0 0 0 0 0 0 1 0 0 0 0
32 93.6 0 0 0 0 0 0 0 0 1 0 0 0
33 107.4 0 0 0 0 0 0 0 0 0 1 0 0
34 96.5 0 0 0 0 0 0 0 0 0 0 1 0
35 93.6 0 0 0 0 0 0 0 0 0 0 0 1
36 76.5 0 0 0 0 0 0 0 0 0 0 0 0
37 76.7 1 1 0 0 0 0 0 0 0 0 0 0
38 84.0 1 0 1 0 0 0 0 0 0 0 0 0
39 103.3 1 0 0 1 0 0 0 0 0 0 0 0
40 88.5 1 0 0 0 1 0 0 0 0 0 0 0
41 99.0 1 0 0 0 0 1 0 0 0 0 0 0
42 105.9 1 0 0 0 0 0 1 0 0 0 0 0
43 44.7 1 0 0 0 0 0 0 1 0 0 0 0
44 94.0 1 0 0 0 0 0 0 0 1 0 0 0
45 107.1 1 0 0 0 0 0 0 0 0 1 0 0
46 104.8 1 0 0 0 0 0 0 0 0 0 1 0
47 102.5 1 0 0 0 0 0 0 0 0 0 0 1
48 77.7 1 0 0 0 0 0 0 0 0 0 0 0
49 85.2 1 1 0 0 0 0 0 0 0 0 0 0
50 91.3 1 0 1 0 0 0 0 0 0 0 0 0
51 106.5 1 0 0 1 0 0 0 0 0 0 0 0
52 92.4 1 0 0 0 1 0 0 0 0 0 0 0
53 97.5 1 0 0 0 0 1 0 0 0 0 0 0
54 107.0 1 0 0 0 0 0 1 0 0 0 0 0
55 51.1 1 0 0 0 0 0 0 1 0 0 0 0
56 98.6 1 0 0 0 0 0 0 0 1 0 0 0
57 102.2 1 0 0 0 0 0 0 0 0 1 0 0
58 114.3 1 0 0 0 0 0 0 0 0 0 1 0
59 99.4 1 0 0 0 0 0 0 0 0 0 0 1
60 72.5 1 0 0 0 0 0 0 0 0 0 0 0
61 92.3 1 1 0 0 0 0 0 0 0 0 0 0
62 99.4 1 0 1 0 0 0 0 0 0 0 0 0
63 85.9 1 0 0 1 0 0 0 0 0 0 0 0
64 109.4 1 0 0 0 1 0 0 0 0 0 0 0
65 97.6 1 0 0 0 0 1 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) d M1 M2 M3 M4
75.501 1.747 5.542 13.059 23.809 21.592
M5 M6 M7 M8 M9 M10
18.292 30.960 -26.700 17.140 31.300 30.120
M11
19.040
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-15.1569 -3.4411 0.4517 3.1117 10.5597
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 75.501 2.720 27.758 < 2e-16 ***
d 1.747 1.488 1.174 0.245771
M1 5.542 3.597 1.541 0.129414
M2 13.059 3.597 3.631 0.000646 ***
M3 23.809 3.597 6.620 2.00e-08 ***
M4 21.592 3.597 6.003 1.90e-07 ***
M5 18.292 3.597 5.086 5.10e-06 ***
M6 30.960 3.753 8.249 5.16e-11 ***
M7 -26.700 3.753 -7.114 3.26e-09 ***
M8 17.140 3.753 4.567 3.07e-05 ***
M9 31.300 3.753 8.339 3.72e-11 ***
M10 30.120 3.753 8.025 1.16e-10 ***
M11 19.040 3.753 5.073 5.34e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.935 on 52 degrees of freedom
Multiple R-squared: 0.8916, Adjusted R-squared: 0.8666
F-statistic: 35.65 on 12 and 52 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,] 0.088670233 0.17734047 0.9113298
[2,] 0.070159127 0.14031825 0.9298409
[3,] 0.045768092 0.09153618 0.9542319
[4,] 0.112727881 0.22545576 0.8872721
[5,] 0.086103371 0.17220674 0.9138966
[6,] 0.068966678 0.13793336 0.9310333
[7,] 0.091170916 0.18234183 0.9088291
[8,] 0.055043484 0.11008697 0.9449565
[9,] 0.045769552 0.09153910 0.9542304
[10,] 0.113508020 0.22701604 0.8864920
[11,] 0.109899084 0.21979817 0.8901009
[12,] 0.369960565 0.73992113 0.6300394
[13,] 0.314166508 0.62833302 0.6858335
[14,] 0.243668603 0.48733721 0.7563314
[15,] 0.190442769 0.38088554 0.8095572
[16,] 0.196569032 0.39313806 0.8034310
[17,] 0.145418202 0.29083640 0.8545818
[18,] 0.120794339 0.24158868 0.8792057
[19,] 0.164094932 0.32818986 0.8359051
[20,] 0.131081559 0.26216312 0.8689184
[21,] 0.088061029 0.17612206 0.9119390
[22,] 0.093273823 0.18654765 0.9067262
[23,] 0.098573951 0.19714790 0.9014260
[24,] 0.083191439 0.16638288 0.9168086
[25,] 0.136870021 0.27374004 0.8631300
[26,] 0.131699594 0.26339919 0.8683004
[27,] 0.085590461 0.17118092 0.9144095
[28,] 0.065177819 0.13035564 0.9348222
[29,] 0.044719218 0.08943844 0.9552808
[30,] 0.027288477 0.05457695 0.9727115
[31,] 0.022406578 0.04481316 0.9775934
[32,] 0.019718474 0.03943695 0.9802815
[33,] 0.010095136 0.02019027 0.9899049
[34,] 0.006244477 0.01248895 0.9937555
> postscript(file="/var/www/html/rcomp/tmp/197rk1229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/27w2v1229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3905z1229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4gbrx1229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5sfnh1229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 65
Frequency = 1
1 2 3 4 5 6
1.6569182 0.3402516 6.5902516 3.7069182 0.2069182 -1.4611321
7 8 9 10 11 12
9.6988679 -5.0411321 6.2988679 6.8788679 -4.9411321 -1.0011321
13 14 15 16 17 18
1.6569182 1.5402516 10.0902516 -1.0930818 -4.5930818 2.6388679
19 20 21 22 23 24
0.2988679 0.2588679 0.8988679 -2.1211321 -3.4411321 4.2988679
25 26 27 28 29 30
-9.1430818 -5.6597484 -9.2097484 3.6069182 -3.0930818 2.3388679
31 32 33 34 35 36
-4.7011321 0.9588679 0.5988679 -9.1211321 -0.9411321 0.9988679
37 38 39 40 41 42
-6.0902516 -6.3069182 2.2430818 -10.3402516 3.4597484 -2.3083019
43 44 45 46 47 48
-5.8483019 -0.3883019 -1.4483019 -2.5683019 6.2116981 0.4516981
49 50 51 52 53 54
2.4097484 0.9930818 5.4430818 -6.4402516 1.9597484 -1.2083019
55 56 57 58 59 60
0.5516981 4.2116981 -6.3483019 6.9316981 3.1116981 -4.7483019
61 62 63 64 65
9.5097484 9.0930818 -15.1569182 10.5597484 2.0597484
> postscript(file="/var/www/html/rcomp/tmp/60zpq1229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 65
Frequency = 1
lag(myerror, k = 1) myerror
0 1.6569182 NA
1 0.3402516 1.6569182
2 6.5902516 0.3402516
3 3.7069182 6.5902516
4 0.2069182 3.7069182
5 -1.4611321 0.2069182
6 9.6988679 -1.4611321
7 -5.0411321 9.6988679
8 6.2988679 -5.0411321
9 6.8788679 6.2988679
10 -4.9411321 6.8788679
11 -1.0011321 -4.9411321
12 1.6569182 -1.0011321
13 1.5402516 1.6569182
14 10.0902516 1.5402516
15 -1.0930818 10.0902516
16 -4.5930818 -1.0930818
17 2.6388679 -4.5930818
18 0.2988679 2.6388679
19 0.2588679 0.2988679
20 0.8988679 0.2588679
21 -2.1211321 0.8988679
22 -3.4411321 -2.1211321
23 4.2988679 -3.4411321
24 -9.1430818 4.2988679
25 -5.6597484 -9.1430818
26 -9.2097484 -5.6597484
27 3.6069182 -9.2097484
28 -3.0930818 3.6069182
29 2.3388679 -3.0930818
30 -4.7011321 2.3388679
31 0.9588679 -4.7011321
32 0.5988679 0.9588679
33 -9.1211321 0.5988679
34 -0.9411321 -9.1211321
35 0.9988679 -0.9411321
36 -6.0902516 0.9988679
37 -6.3069182 -6.0902516
38 2.2430818 -6.3069182
39 -10.3402516 2.2430818
40 3.4597484 -10.3402516
41 -2.3083019 3.4597484
42 -5.8483019 -2.3083019
43 -0.3883019 -5.8483019
44 -1.4483019 -0.3883019
45 -2.5683019 -1.4483019
46 6.2116981 -2.5683019
47 0.4516981 6.2116981
48 2.4097484 0.4516981
49 0.9930818 2.4097484
50 5.4430818 0.9930818
51 -6.4402516 5.4430818
52 1.9597484 -6.4402516
53 -1.2083019 1.9597484
54 0.5516981 -1.2083019
55 4.2116981 0.5516981
56 -6.3483019 4.2116981
57 6.9316981 -6.3483019
58 3.1116981 6.9316981
59 -4.7483019 3.1116981
60 9.5097484 -4.7483019
61 9.0930818 9.5097484
62 -15.1569182 9.0930818
63 10.5597484 -15.1569182
64 2.0597484 10.5597484
65 NA 2.0597484
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.3402516 1.6569182
[2,] 6.5902516 0.3402516
[3,] 3.7069182 6.5902516
[4,] 0.2069182 3.7069182
[5,] -1.4611321 0.2069182
[6,] 9.6988679 -1.4611321
[7,] -5.0411321 9.6988679
[8,] 6.2988679 -5.0411321
[9,] 6.8788679 6.2988679
[10,] -4.9411321 6.8788679
[11,] -1.0011321 -4.9411321
[12,] 1.6569182 -1.0011321
[13,] 1.5402516 1.6569182
[14,] 10.0902516 1.5402516
[15,] -1.0930818 10.0902516
[16,] -4.5930818 -1.0930818
[17,] 2.6388679 -4.5930818
[18,] 0.2988679 2.6388679
[19,] 0.2588679 0.2988679
[20,] 0.8988679 0.2588679
[21,] -2.1211321 0.8988679
[22,] -3.4411321 -2.1211321
[23,] 4.2988679 -3.4411321
[24,] -9.1430818 4.2988679
[25,] -5.6597484 -9.1430818
[26,] -9.2097484 -5.6597484
[27,] 3.6069182 -9.2097484
[28,] -3.0930818 3.6069182
[29,] 2.3388679 -3.0930818
[30,] -4.7011321 2.3388679
[31,] 0.9588679 -4.7011321
[32,] 0.5988679 0.9588679
[33,] -9.1211321 0.5988679
[34,] -0.9411321 -9.1211321
[35,] 0.9988679 -0.9411321
[36,] -6.0902516 0.9988679
[37,] -6.3069182 -6.0902516
[38,] 2.2430818 -6.3069182
[39,] -10.3402516 2.2430818
[40,] 3.4597484 -10.3402516
[41,] -2.3083019 3.4597484
[42,] -5.8483019 -2.3083019
[43,] -0.3883019 -5.8483019
[44,] -1.4483019 -0.3883019
[45,] -2.5683019 -1.4483019
[46,] 6.2116981 -2.5683019
[47,] 0.4516981 6.2116981
[48,] 2.4097484 0.4516981
[49,] 0.9930818 2.4097484
[50,] 5.4430818 0.9930818
[51,] -6.4402516 5.4430818
[52,] 1.9597484 -6.4402516
[53,] -1.2083019 1.9597484
[54,] 0.5516981 -1.2083019
[55,] 4.2116981 0.5516981
[56,] -6.3483019 4.2116981
[57,] 6.9316981 -6.3483019
[58,] 3.1116981 6.9316981
[59,] -4.7483019 3.1116981
[60,] 9.5097484 -4.7483019
[61,] 9.0930818 9.5097484
[62,] -15.1569182 9.0930818
[63,] 10.5597484 -15.1569182
[64,] 2.0597484 10.5597484
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.3402516 1.6569182
2 6.5902516 0.3402516
3 3.7069182 6.5902516
4 0.2069182 3.7069182
5 -1.4611321 0.2069182
6 9.6988679 -1.4611321
7 -5.0411321 9.6988679
8 6.2988679 -5.0411321
9 6.8788679 6.2988679
10 -4.9411321 6.8788679
11 -1.0011321 -4.9411321
12 1.6569182 -1.0011321
13 1.5402516 1.6569182
14 10.0902516 1.5402516
15 -1.0930818 10.0902516
16 -4.5930818 -1.0930818
17 2.6388679 -4.5930818
18 0.2988679 2.6388679
19 0.2588679 0.2988679
20 0.8988679 0.2588679
21 -2.1211321 0.8988679
22 -3.4411321 -2.1211321
23 4.2988679 -3.4411321
24 -9.1430818 4.2988679
25 -5.6597484 -9.1430818
26 -9.2097484 -5.6597484
27 3.6069182 -9.2097484
28 -3.0930818 3.6069182
29 2.3388679 -3.0930818
30 -4.7011321 2.3388679
31 0.9588679 -4.7011321
32 0.5988679 0.9588679
33 -9.1211321 0.5988679
34 -0.9411321 -9.1211321
35 0.9988679 -0.9411321
36 -6.0902516 0.9988679
37 -6.3069182 -6.0902516
38 2.2430818 -6.3069182
39 -10.3402516 2.2430818
40 3.4597484 -10.3402516
41 -2.3083019 3.4597484
42 -5.8483019 -2.3083019
43 -0.3883019 -5.8483019
44 -1.4483019 -0.3883019
45 -2.5683019 -1.4483019
46 6.2116981 -2.5683019
47 0.4516981 6.2116981
48 2.4097484 0.4516981
49 0.9930818 2.4097484
50 5.4430818 0.9930818
51 -6.4402516 5.4430818
52 1.9597484 -6.4402516
53 -1.2083019 1.9597484
54 0.5516981 -1.2083019
55 4.2116981 0.5516981
56 -6.3483019 4.2116981
57 6.9316981 -6.3483019
58 3.1116981 6.9316981
59 -4.7483019 3.1116981
60 9.5097484 -4.7483019
61 9.0930818 9.5097484
62 -15.1569182 9.0930818
63 10.5597484 -15.1569182
64 2.0597484 10.5597484
> 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/757t11229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ogrz1229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/91wcc1229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1017ks1229032645.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1120pg1229032645.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/12v1il1229032645.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/13n79o1229032645.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/1483cc1229032646.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/152hk91229032646.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/163tmo1229032646.tab")
+ }
>
> system("convert tmp/197rk1229032645.ps tmp/197rk1229032645.png")
> system("convert tmp/27w2v1229032645.ps tmp/27w2v1229032645.png")
> system("convert tmp/3905z1229032645.ps tmp/3905z1229032645.png")
> system("convert tmp/4gbrx1229032645.ps tmp/4gbrx1229032645.png")
> system("convert tmp/5sfnh1229032645.ps tmp/5sfnh1229032645.png")
> system("convert tmp/60zpq1229032645.ps tmp/60zpq1229032645.png")
> system("convert tmp/757t11229032645.ps tmp/757t11229032645.png")
> system("convert tmp/8ogrz1229032645.ps tmp/8ogrz1229032645.png")
> system("convert tmp/91wcc1229032645.ps tmp/91wcc1229032645.png")
> system("convert tmp/1017ks1229032645.ps tmp/1017ks1229032645.png")
>
>
> proc.time()
user system elapsed
5.352 2.775 5.742