R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(21.1,0,21,0,20.4,0,19.5,0,18.6,0,18.8,0,23.7,0,24.8,0,25,0,23.6,0,22.3,0,21.8,0,20.8,0,19.7,0,18.3,0,17.4,0,17,0,18.1,0,23.9,0,25.6,0,25.3,0,23.6,0,21.9,0,21.4,0,20.6,0,20.5,0,20.2,0,20.6,0,19.7,0,19.3,0,22.8,0,23.5,0,23.8,0,22.6,0,22,0,21.7,0,20.7,1,20.2,1,19.1,1,19.5,1,18.7,1,18.6,1,22.2,1,23.2,1,23.5,1,21.3,1,20,1,18.7,1,18.9,1,18.3,1,18.4,1,19.9,1,19.2,1,18.5,1,20.9,1,20.5,1,19.4,1,18.1,1,17,1,17,1),dim=c(2,60),dimnames=list(c('Werkloosheid<25jr','Generatiepact'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Werkloosheid<25jr','Generatiepact'),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 = '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
Werkloosheid<25jr Generatiepact M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 21.1 0 1 0 0 0 0 0 0 0 0 0 0 1
2 21.0 0 0 1 0 0 0 0 0 0 0 0 0 2
3 20.4 0 0 0 1 0 0 0 0 0 0 0 0 3
4 19.5 0 0 0 0 1 0 0 0 0 0 0 0 4
5 18.6 0 0 0 0 0 1 0 0 0 0 0 0 5
6 18.8 0 0 0 0 0 0 1 0 0 0 0 0 6
7 23.7 0 0 0 0 0 0 0 1 0 0 0 0 7
8 24.8 0 0 0 0 0 0 0 0 1 0 0 0 8
9 25.0 0 0 0 0 0 0 0 0 0 1 0 0 9
10 23.6 0 0 0 0 0 0 0 0 0 0 1 0 10
11 22.3 0 0 0 0 0 0 0 0 0 0 0 1 11
12 21.8 0 0 0 0 0 0 0 0 0 0 0 0 12
13 20.8 0 1 0 0 0 0 0 0 0 0 0 0 13
14 19.7 0 0 1 0 0 0 0 0 0 0 0 0 14
15 18.3 0 0 0 1 0 0 0 0 0 0 0 0 15
16 17.4 0 0 0 0 1 0 0 0 0 0 0 0 16
17 17.0 0 0 0 0 0 1 0 0 0 0 0 0 17
18 18.1 0 0 0 0 0 0 1 0 0 0 0 0 18
19 23.9 0 0 0 0 0 0 0 1 0 0 0 0 19
20 25.6 0 0 0 0 0 0 0 0 1 0 0 0 20
21 25.3 0 0 0 0 0 0 0 0 0 1 0 0 21
22 23.6 0 0 0 0 0 0 0 0 0 0 1 0 22
23 21.9 0 0 0 0 0 0 0 0 0 0 0 1 23
24 21.4 0 0 0 0 0 0 0 0 0 0 0 0 24
25 20.6 0 1 0 0 0 0 0 0 0 0 0 0 25
26 20.5 0 0 1 0 0 0 0 0 0 0 0 0 26
27 20.2 0 0 0 1 0 0 0 0 0 0 0 0 27
28 20.6 0 0 0 0 1 0 0 0 0 0 0 0 28
29 19.7 0 0 0 0 0 1 0 0 0 0 0 0 29
30 19.3 0 0 0 0 0 0 1 0 0 0 0 0 30
31 22.8 0 0 0 0 0 0 0 1 0 0 0 0 31
32 23.5 0 0 0 0 0 0 0 0 1 0 0 0 32
33 23.8 0 0 0 0 0 0 0 0 0 1 0 0 33
34 22.6 0 0 0 0 0 0 0 0 0 0 1 0 34
35 22.0 0 0 0 0 0 0 0 0 0 0 0 1 35
36 21.7 0 0 0 0 0 0 0 0 0 0 0 0 36
37 20.7 1 1 0 0 0 0 0 0 0 0 0 0 37
38 20.2 1 0 1 0 0 0 0 0 0 0 0 0 38
39 19.1 1 0 0 1 0 0 0 0 0 0 0 0 39
40 19.5 1 0 0 0 1 0 0 0 0 0 0 0 40
41 18.7 1 0 0 0 0 1 0 0 0 0 0 0 41
42 18.6 1 0 0 0 0 0 1 0 0 0 0 0 42
43 22.2 1 0 0 0 0 0 0 1 0 0 0 0 43
44 23.2 1 0 0 0 0 0 0 0 1 0 0 0 44
45 23.5 1 0 0 0 0 0 0 0 0 1 0 0 45
46 21.3 1 0 0 0 0 0 0 0 0 0 1 0 46
47 20.0 1 0 0 0 0 0 0 0 0 0 0 1 47
48 18.7 1 0 0 0 0 0 0 0 0 0 0 0 48
49 18.9 1 1 0 0 0 0 0 0 0 0 0 0 49
50 18.3 1 0 1 0 0 0 0 0 0 0 0 0 50
51 18.4 1 0 0 1 0 0 0 0 0 0 0 0 51
52 19.9 1 0 0 0 1 0 0 0 0 0 0 0 52
53 19.2 1 0 0 0 0 1 0 0 0 0 0 0 53
54 18.5 1 0 0 0 0 0 1 0 0 0 0 0 54
55 20.9 1 0 0 0 0 0 0 1 0 0 0 0 55
56 20.5 1 0 0 0 0 0 0 0 1 0 0 0 56
57 19.4 1 0 0 0 0 0 0 0 0 1 0 0 57
58 18.1 1 0 0 0 0 0 0 0 0 0 1 0 58
59 17.0 1 0 0 0 0 0 0 0 0 0 0 1 59
60 17.0 1 0 0 0 0 0 0 0 0 0 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Generatiepact M1 M2 M3
21.69556 -0.66389 -0.10028 -0.54389 -1.16750
M4 M5 M6 M7 M8
-1.03111 -1.73472 -1.67833 2.39806 3.25444
M9 M10 M11 t
3.17083 1.64722 0.48361 -0.03639
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.7283 -0.4763 0.3150 0.7799 1.8317
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 21.69556 0.74809 29.001 < 2e-16 ***
Generatiepact -0.66389 0.67181 -0.988 0.328217
M1 -0.10028 0.83392 -0.120 0.904809
M2 -0.54389 0.82917 -0.656 0.515126
M3 -1.16750 0.82485 -1.415 0.163682
M4 -1.03111 0.82096 -1.256 0.215465
M5 -1.73472 0.81752 -2.122 0.039260 *
M6 -1.67833 0.81452 -2.061 0.045031 *
M7 2.39806 0.81198 2.953 0.004938 **
M8 3.25444 0.80989 4.018 0.000215 ***
M9 3.17083 0.80826 3.923 0.000290 ***
M10 1.64722 0.80710 2.041 0.047022 *
M11 0.48361 0.80640 0.600 0.551639
t -0.03639 0.01939 -1.876 0.066959 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.275 on 46 degrees of freedom
Multiple R-squared: 0.7452, Adjusted R-squared: 0.6732
F-statistic: 10.35 on 13 and 46 DF, p-value: 1.038e-09
> 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,] 0.21506188 0.4301238 0.7849381
[2,] 0.21728605 0.4345721 0.7827139
[3,] 0.30175202 0.6035040 0.6982480
[4,] 0.43462339 0.8692468 0.5653766
[5,] 0.39266292 0.7853258 0.6073371
[6,] 0.30836333 0.6167267 0.6916367
[7,] 0.21764506 0.4352901 0.7823549
[8,] 0.14682375 0.2936475 0.8531763
[9,] 0.11196128 0.2239226 0.8880387
[10,] 0.09648467 0.1929693 0.9035153
[11,] 0.11738396 0.2347679 0.8826160
[12,] 0.29836620 0.5967324 0.7016338
[13,] 0.40394791 0.8078958 0.5960521
[14,] 0.41311366 0.8262273 0.5868863
[15,] 0.43326119 0.8665224 0.5667388
[16,] 0.49725554 0.9945111 0.5027445
[17,] 0.47452637 0.9490527 0.5254736
[18,] 0.40586479 0.8117296 0.5941352
[19,] 0.30971377 0.6194275 0.6902862
[20,] 0.22366860 0.4473372 0.7763314
[21,] 0.15087480 0.3017496 0.8491252
[22,] 0.09560438 0.1912088 0.9043956
[23,] 0.06435239 0.1287048 0.9356476
[24,] 0.08649535 0.1729907 0.9135047
[25,] 0.19253203 0.3850641 0.8074680
[26,] 0.42278031 0.8455606 0.5772197
[27,] 0.52809814 0.9438037 0.4719019
> postscript(file="/var/www/html/rcomp/tmp/15con1227442634.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/25xd91227442634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3bvyh1227442634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4s7p31227442634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/52sy91227442634.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 = 60
Frequency = 1
1 2 3 4 5 6
-0.45888889 -0.07888889 -0.01888889 -1.01888889 -1.17888889 -0.99888889
7 8 9 10 11 12
-0.13888889 0.14111111 0.46111111 0.62111111 0.52111111 0.54111111
13 14 15 16 17 18
-0.32222222 -0.94222222 -1.68222222 -2.68222222 -2.34222222 -1.26222222
19 20 21 22 23 24
0.49777778 1.37777778 1.19777778 1.05777778 0.55777778 0.57777778
25 26 27 28 29 30
-0.08555556 0.29444444 0.65444444 0.95444444 0.79444444 0.37444444
31 32 33 34 35 36
-0.16555556 -0.28555556 0.13444444 0.49444444 1.09444444 1.31444444
37 38 39 40 41 42
1.11500000 1.09500000 0.65500000 0.95500000 0.89500000 0.77500000
43 44 45 46 47 48
0.33500000 0.51500000 0.93500000 0.29500000 0.19500000 -0.58500000
49 50 51 52 53 54
-0.24833333 -0.36833333 0.39166667 1.79166667 1.83166667 1.11166667
55 56 57 58 59 60
-0.52833333 -1.74833333 -2.72833333 -2.46833333 -2.36833333 -1.84833333
> postscript(file="/var/www/html/rcomp/tmp/6vldv1227442634.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.45888889 NA
1 -0.07888889 -0.45888889
2 -0.01888889 -0.07888889
3 -1.01888889 -0.01888889
4 -1.17888889 -1.01888889
5 -0.99888889 -1.17888889
6 -0.13888889 -0.99888889
7 0.14111111 -0.13888889
8 0.46111111 0.14111111
9 0.62111111 0.46111111
10 0.52111111 0.62111111
11 0.54111111 0.52111111
12 -0.32222222 0.54111111
13 -0.94222222 -0.32222222
14 -1.68222222 -0.94222222
15 -2.68222222 -1.68222222
16 -2.34222222 -2.68222222
17 -1.26222222 -2.34222222
18 0.49777778 -1.26222222
19 1.37777778 0.49777778
20 1.19777778 1.37777778
21 1.05777778 1.19777778
22 0.55777778 1.05777778
23 0.57777778 0.55777778
24 -0.08555556 0.57777778
25 0.29444444 -0.08555556
26 0.65444444 0.29444444
27 0.95444444 0.65444444
28 0.79444444 0.95444444
29 0.37444444 0.79444444
30 -0.16555556 0.37444444
31 -0.28555556 -0.16555556
32 0.13444444 -0.28555556
33 0.49444444 0.13444444
34 1.09444444 0.49444444
35 1.31444444 1.09444444
36 1.11500000 1.31444444
37 1.09500000 1.11500000
38 0.65500000 1.09500000
39 0.95500000 0.65500000
40 0.89500000 0.95500000
41 0.77500000 0.89500000
42 0.33500000 0.77500000
43 0.51500000 0.33500000
44 0.93500000 0.51500000
45 0.29500000 0.93500000
46 0.19500000 0.29500000
47 -0.58500000 0.19500000
48 -0.24833333 -0.58500000
49 -0.36833333 -0.24833333
50 0.39166667 -0.36833333
51 1.79166667 0.39166667
52 1.83166667 1.79166667
53 1.11166667 1.83166667
54 -0.52833333 1.11166667
55 -1.74833333 -0.52833333
56 -2.72833333 -1.74833333
57 -2.46833333 -2.72833333
58 -2.36833333 -2.46833333
59 -1.84833333 -2.36833333
60 NA -1.84833333
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.07888889 -0.45888889
[2,] -0.01888889 -0.07888889
[3,] -1.01888889 -0.01888889
[4,] -1.17888889 -1.01888889
[5,] -0.99888889 -1.17888889
[6,] -0.13888889 -0.99888889
[7,] 0.14111111 -0.13888889
[8,] 0.46111111 0.14111111
[9,] 0.62111111 0.46111111
[10,] 0.52111111 0.62111111
[11,] 0.54111111 0.52111111
[12,] -0.32222222 0.54111111
[13,] -0.94222222 -0.32222222
[14,] -1.68222222 -0.94222222
[15,] -2.68222222 -1.68222222
[16,] -2.34222222 -2.68222222
[17,] -1.26222222 -2.34222222
[18,] 0.49777778 -1.26222222
[19,] 1.37777778 0.49777778
[20,] 1.19777778 1.37777778
[21,] 1.05777778 1.19777778
[22,] 0.55777778 1.05777778
[23,] 0.57777778 0.55777778
[24,] -0.08555556 0.57777778
[25,] 0.29444444 -0.08555556
[26,] 0.65444444 0.29444444
[27,] 0.95444444 0.65444444
[28,] 0.79444444 0.95444444
[29,] 0.37444444 0.79444444
[30,] -0.16555556 0.37444444
[31,] -0.28555556 -0.16555556
[32,] 0.13444444 -0.28555556
[33,] 0.49444444 0.13444444
[34,] 1.09444444 0.49444444
[35,] 1.31444444 1.09444444
[36,] 1.11500000 1.31444444
[37,] 1.09500000 1.11500000
[38,] 0.65500000 1.09500000
[39,] 0.95500000 0.65500000
[40,] 0.89500000 0.95500000
[41,] 0.77500000 0.89500000
[42,] 0.33500000 0.77500000
[43,] 0.51500000 0.33500000
[44,] 0.93500000 0.51500000
[45,] 0.29500000 0.93500000
[46,] 0.19500000 0.29500000
[47,] -0.58500000 0.19500000
[48,] -0.24833333 -0.58500000
[49,] -0.36833333 -0.24833333
[50,] 0.39166667 -0.36833333
[51,] 1.79166667 0.39166667
[52,] 1.83166667 1.79166667
[53,] 1.11166667 1.83166667
[54,] -0.52833333 1.11166667
[55,] -1.74833333 -0.52833333
[56,] -2.72833333 -1.74833333
[57,] -2.46833333 -2.72833333
[58,] -2.36833333 -2.46833333
[59,] -1.84833333 -2.36833333
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.07888889 -0.45888889
2 -0.01888889 -0.07888889
3 -1.01888889 -0.01888889
4 -1.17888889 -1.01888889
5 -0.99888889 -1.17888889
6 -0.13888889 -0.99888889
7 0.14111111 -0.13888889
8 0.46111111 0.14111111
9 0.62111111 0.46111111
10 0.52111111 0.62111111
11 0.54111111 0.52111111
12 -0.32222222 0.54111111
13 -0.94222222 -0.32222222
14 -1.68222222 -0.94222222
15 -2.68222222 -1.68222222
16 -2.34222222 -2.68222222
17 -1.26222222 -2.34222222
18 0.49777778 -1.26222222
19 1.37777778 0.49777778
20 1.19777778 1.37777778
21 1.05777778 1.19777778
22 0.55777778 1.05777778
23 0.57777778 0.55777778
24 -0.08555556 0.57777778
25 0.29444444 -0.08555556
26 0.65444444 0.29444444
27 0.95444444 0.65444444
28 0.79444444 0.95444444
29 0.37444444 0.79444444
30 -0.16555556 0.37444444
31 -0.28555556 -0.16555556
32 0.13444444 -0.28555556
33 0.49444444 0.13444444
34 1.09444444 0.49444444
35 1.31444444 1.09444444
36 1.11500000 1.31444444
37 1.09500000 1.11500000
38 0.65500000 1.09500000
39 0.95500000 0.65500000
40 0.89500000 0.95500000
41 0.77500000 0.89500000
42 0.33500000 0.77500000
43 0.51500000 0.33500000
44 0.93500000 0.51500000
45 0.29500000 0.93500000
46 0.19500000 0.29500000
47 -0.58500000 0.19500000
48 -0.24833333 -0.58500000
49 -0.36833333 -0.24833333
50 0.39166667 -0.36833333
51 1.79166667 0.39166667
52 1.83166667 1.79166667
53 1.11166667 1.83166667
54 -0.52833333 1.11166667
55 -1.74833333 -0.52833333
56 -2.72833333 -1.74833333
57 -2.46833333 -2.72833333
58 -2.36833333 -2.46833333
59 -1.84833333 -2.36833333
> 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/7lmq11227442634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8bwip1227442634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/91aoz1227442634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10kxa01227442634.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/110gw91227442634.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/1221hp1227442634.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/13fk4d1227442634.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/14urr21227442634.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/152rgs1227442635.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/1611d61227442635.tab")
+ }
>
> system("convert tmp/15con1227442634.ps tmp/15con1227442634.png")
> system("convert tmp/25xd91227442634.ps tmp/25xd91227442634.png")
> system("convert tmp/3bvyh1227442634.ps tmp/3bvyh1227442634.png")
> system("convert tmp/4s7p31227442634.ps tmp/4s7p31227442634.png")
> system("convert tmp/52sy91227442634.ps tmp/52sy91227442634.png")
> system("convert tmp/6vldv1227442634.ps tmp/6vldv1227442634.png")
> system("convert tmp/7lmq11227442634.ps tmp/7lmq11227442634.png")
> system("convert tmp/8bwip1227442634.ps tmp/8bwip1227442634.png")
> system("convert tmp/91aoz1227442634.ps tmp/91aoz1227442634.png")
> system("convert tmp/10kxa01227442634.ps tmp/10kxa01227442634.png")
>
>
> proc.time()
user system elapsed
2.348 1.535 2.961