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(21.1,0,21,0,20.4,0,19.5,0,18.6,0,18.8,0,23.7,0,24.8,0,25,0,23.6,0,22.3,0,21.8,0,20.8,0,19.7,0,18.3,0,17.4,0,17,0,18.1,0,23.9,0,25.6,0,25.3,0,23.6,0,21.9,0,21.4,0,20.6,0,20.5,0,20.2,0,20.6,0,19.7,0,19.3,0,22.8,0,23.5,0,23.8,0,22.6,0,22,0,21.7,0,20.7,0,20.2,0,19.1,0,19.5,0,18.7,0,18.6,0,22.2,0,23.2,0,23.5,0,21.3,0,20,0,18.7,0,18.9,1,18.3,1,18.4,1,19.9,1,19.2,1,18.5,1,20.9,1,20.5,1,19.4,1,18.1,1,17,1,17,1),dim=c(2,60),dimnames=list(c('Werkloosheid','2007'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Werkloosheid','2007'),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 2007 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 0 1 0 0 0 0 0 0 0 0 0 0 37
38 20.2 0 0 1 0 0 0 0 0 0 0 0 0 38
39 19.1 0 0 0 1 0 0 0 0 0 0 0 0 39
40 19.5 0 0 0 0 1 0 0 0 0 0 0 0 40
41 18.7 0 0 0 0 0 1 0 0 0 0 0 0 41
42 18.6 0 0 0 0 0 0 1 0 0 0 0 0 42
43 22.2 0 0 0 0 0 0 0 1 0 0 0 0 43
44 23.2 0 0 0 0 0 0 0 0 1 0 0 0 44
45 23.5 0 0 0 0 0 0 0 0 0 1 0 0 45
46 21.3 0 0 0 0 0 0 0 0 0 0 1 0 46
47 20.0 0 0 0 0 0 0 0 0 0 0 0 1 47
48 18.7 0 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) `2007` M1 M2 M3 M4
21.429167 -1.495833 -0.008611 -0.460556 -1.092500 -0.964444
M5 M6 M7 M8 M9 M10
-1.676389 -1.628333 2.439722 3.287778 3.195833 1.663889
M11 t
0.491944 -0.028056
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.6158 -0.5275 0.1192 0.6317 2.4300
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 21.429167 0.663035 32.320 < 2e-16 ***
`2007` -1.495833 0.545011 -2.745 0.008612 **
M1 -0.008611 0.768296 -0.011 0.991106
M2 -0.460556 0.766038 -0.601 0.550646
M3 -1.092500 0.763988 -1.430 0.159476
M4 -0.964444 0.762150 -1.265 0.212091
M5 -1.676389 0.760525 -2.204 0.032549 *
M6 -1.628333 0.759113 -2.145 0.037263 *
M7 2.439722 0.757916 3.219 0.002361 **
M8 3.287778 0.756936 4.344 7.65e-05 ***
M9 3.195833 0.756172 4.226 0.000111 ***
M10 1.663889 0.755627 2.202 0.032718 *
M11 0.491944 0.755299 0.651 0.518078
t -0.028056 0.012846 -2.184 0.034099 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.194 on 46 degrees of freedom
Multiple R-squared: 0.7764, Adjusted R-squared: 0.7132
F-statistic: 12.29 on 13 and 46 DF, p-value: 6.361e-11
> 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,] 0.22515497 0.4503099 0.7748450
[2,] 0.21413749 0.4282750 0.7858625
[3,] 0.29153854 0.5830771 0.7084615
[4,] 0.42828252 0.8565650 0.5717175
[5,] 0.39416746 0.7883349 0.6058325
[6,] 0.31809897 0.6361979 0.6819010
[7,] 0.22206510 0.4441302 0.7779349
[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,] 0.15120296 0.3024059 0.8487970
[22,] 0.09585265 0.1917053 0.9041474
[23,] 0.06435644 0.1287129 0.9356436
[24,] 0.08710373 0.1742075 0.9128963
[25,] 0.19519691 0.3903938 0.8048031
[26,] 0.42585028 0.8517006 0.5741497
[27,] 0.52818104 0.9436379 0.4718190
> postscript(file="/var/www/html/rcomp/tmp/1vn8c1229787302.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2k73l1229787302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3rzyg1229787302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4peie1229787302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vzt11229787302.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 7
-0.2925000 0.0875000 0.1475000 -0.8525000 -1.0125000 -0.8325000 0.0275000
8 9 10 11 12 13 14
0.3075000 0.6275000 0.7875000 0.6875000 0.7075000 -0.2558333 -0.8758333
15 16 17 18 19 20 21
-1.6158333 -2.6158333 -2.2758333 -1.1958333 0.5641667 1.4441667 1.2641667
22 23 24 25 26 27 28
1.1241667 0.6241667 0.6441667 -0.1191667 0.2608333 0.6208333 0.9208333
29 30 31 32 33 34 35
0.7608333 0.3408333 -0.1991667 -0.3191667 0.1008333 0.4608333 1.0608333
36 37 38 39 40 41 42
1.2808333 0.3175000 0.2975000 -0.1425000 0.1575000 0.0975000 -0.0225000
43 44 45 46 47 48 49
-0.4625000 -0.2825000 0.1375000 -0.5025000 -0.6025000 -1.3825000 0.3500000
50 51 52 53 54 55 56
0.2300000 0.9900000 2.3900000 2.4300000 1.7100000 0.0700000 -1.1500000
57 58 59 60
-2.1300000 -1.8700000 -1.7700000 -1.2500000
> postscript(file="/var/www/html/rcomp/tmp/6adnd1229787302.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 -0.2925000 NA
1 0.0875000 -0.2925000
2 0.1475000 0.0875000
3 -0.8525000 0.1475000
4 -1.0125000 -0.8525000
5 -0.8325000 -1.0125000
6 0.0275000 -0.8325000
7 0.3075000 0.0275000
8 0.6275000 0.3075000
9 0.7875000 0.6275000
10 0.6875000 0.7875000
11 0.7075000 0.6875000
12 -0.2558333 0.7075000
13 -0.8758333 -0.2558333
14 -1.6158333 -0.8758333
15 -2.6158333 -1.6158333
16 -2.2758333 -2.6158333
17 -1.1958333 -2.2758333
18 0.5641667 -1.1958333
19 1.4441667 0.5641667
20 1.2641667 1.4441667
21 1.1241667 1.2641667
22 0.6241667 1.1241667
23 0.6441667 0.6241667
24 -0.1191667 0.6441667
25 0.2608333 -0.1191667
26 0.6208333 0.2608333
27 0.9208333 0.6208333
28 0.7608333 0.9208333
29 0.3408333 0.7608333
30 -0.1991667 0.3408333
31 -0.3191667 -0.1991667
32 0.1008333 -0.3191667
33 0.4608333 0.1008333
34 1.0608333 0.4608333
35 1.2808333 1.0608333
36 0.3175000 1.2808333
37 0.2975000 0.3175000
38 -0.1425000 0.2975000
39 0.1575000 -0.1425000
40 0.0975000 0.1575000
41 -0.0225000 0.0975000
42 -0.4625000 -0.0225000
43 -0.2825000 -0.4625000
44 0.1375000 -0.2825000
45 -0.5025000 0.1375000
46 -0.6025000 -0.5025000
47 -1.3825000 -0.6025000
48 0.3500000 -1.3825000
49 0.2300000 0.3500000
50 0.9900000 0.2300000
51 2.3900000 0.9900000
52 2.4300000 2.3900000
53 1.7100000 2.4300000
54 0.0700000 1.7100000
55 -1.1500000 0.0700000
56 -2.1300000 -1.1500000
57 -1.8700000 -2.1300000
58 -1.7700000 -1.8700000
59 -1.2500000 -1.7700000
60 NA -1.2500000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.0875000 -0.2925000
[2,] 0.1475000 0.0875000
[3,] -0.8525000 0.1475000
[4,] -1.0125000 -0.8525000
[5,] -0.8325000 -1.0125000
[6,] 0.0275000 -0.8325000
[7,] 0.3075000 0.0275000
[8,] 0.6275000 0.3075000
[9,] 0.7875000 0.6275000
[10,] 0.6875000 0.7875000
[11,] 0.7075000 0.6875000
[12,] -0.2558333 0.7075000
[13,] -0.8758333 -0.2558333
[14,] -1.6158333 -0.8758333
[15,] -2.6158333 -1.6158333
[16,] -2.2758333 -2.6158333
[17,] -1.1958333 -2.2758333
[18,] 0.5641667 -1.1958333
[19,] 1.4441667 0.5641667
[20,] 1.2641667 1.4441667
[21,] 1.1241667 1.2641667
[22,] 0.6241667 1.1241667
[23,] 0.6441667 0.6241667
[24,] -0.1191667 0.6441667
[25,] 0.2608333 -0.1191667
[26,] 0.6208333 0.2608333
[27,] 0.9208333 0.6208333
[28,] 0.7608333 0.9208333
[29,] 0.3408333 0.7608333
[30,] -0.1991667 0.3408333
[31,] -0.3191667 -0.1991667
[32,] 0.1008333 -0.3191667
[33,] 0.4608333 0.1008333
[34,] 1.0608333 0.4608333
[35,] 1.2808333 1.0608333
[36,] 0.3175000 1.2808333
[37,] 0.2975000 0.3175000
[38,] -0.1425000 0.2975000
[39,] 0.1575000 -0.1425000
[40,] 0.0975000 0.1575000
[41,] -0.0225000 0.0975000
[42,] -0.4625000 -0.0225000
[43,] -0.2825000 -0.4625000
[44,] 0.1375000 -0.2825000
[45,] -0.5025000 0.1375000
[46,] -0.6025000 -0.5025000
[47,] -1.3825000 -0.6025000
[48,] 0.3500000 -1.3825000
[49,] 0.2300000 0.3500000
[50,] 0.9900000 0.2300000
[51,] 2.3900000 0.9900000
[52,] 2.4300000 2.3900000
[53,] 1.7100000 2.4300000
[54,] 0.0700000 1.7100000
[55,] -1.1500000 0.0700000
[56,] -2.1300000 -1.1500000
[57,] -1.8700000 -2.1300000
[58,] -1.7700000 -1.8700000
[59,] -1.2500000 -1.7700000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.0875000 -0.2925000
2 0.1475000 0.0875000
3 -0.8525000 0.1475000
4 -1.0125000 -0.8525000
5 -0.8325000 -1.0125000
6 0.0275000 -0.8325000
7 0.3075000 0.0275000
8 0.6275000 0.3075000
9 0.7875000 0.6275000
10 0.6875000 0.7875000
11 0.7075000 0.6875000
12 -0.2558333 0.7075000
13 -0.8758333 -0.2558333
14 -1.6158333 -0.8758333
15 -2.6158333 -1.6158333
16 -2.2758333 -2.6158333
17 -1.1958333 -2.2758333
18 0.5641667 -1.1958333
19 1.4441667 0.5641667
20 1.2641667 1.4441667
21 1.1241667 1.2641667
22 0.6241667 1.1241667
23 0.6441667 0.6241667
24 -0.1191667 0.6441667
25 0.2608333 -0.1191667
26 0.6208333 0.2608333
27 0.9208333 0.6208333
28 0.7608333 0.9208333
29 0.3408333 0.7608333
30 -0.1991667 0.3408333
31 -0.3191667 -0.1991667
32 0.1008333 -0.3191667
33 0.4608333 0.1008333
34 1.0608333 0.4608333
35 1.2808333 1.0608333
36 0.3175000 1.2808333
37 0.2975000 0.3175000
38 -0.1425000 0.2975000
39 0.1575000 -0.1425000
40 0.0975000 0.1575000
41 -0.0225000 0.0975000
42 -0.4625000 -0.0225000
43 -0.2825000 -0.4625000
44 0.1375000 -0.2825000
45 -0.5025000 0.1375000
46 -0.6025000 -0.5025000
47 -1.3825000 -0.6025000
48 0.3500000 -1.3825000
49 0.2300000 0.3500000
50 0.9900000 0.2300000
51 2.3900000 0.9900000
52 2.4300000 2.3900000
53 1.7100000 2.4300000
54 0.0700000 1.7100000
55 -1.1500000 0.0700000
56 -2.1300000 -1.1500000
57 -1.8700000 -2.1300000
58 -1.7700000 -1.8700000
59 -1.2500000 -1.7700000
> 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/7x4031229787302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8tyg11229787302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9kypg1229787302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10yy3m1229787302.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11sqwr1229787302.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/129yg91229787302.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/13ddxu1229787302.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/141lpi1229787302.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/15xr121229787302.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/16xj6a1229787302.tab")
+ }
>
> system("convert tmp/1vn8c1229787302.ps tmp/1vn8c1229787302.png")
> system("convert tmp/2k73l1229787302.ps tmp/2k73l1229787302.png")
> system("convert tmp/3rzyg1229787302.ps tmp/3rzyg1229787302.png")
> system("convert tmp/4peie1229787302.ps tmp/4peie1229787302.png")
> system("convert tmp/5vzt11229787302.ps tmp/5vzt11229787302.png")
> system("convert tmp/6adnd1229787302.ps tmp/6adnd1229787302.png")
> system("convert tmp/7x4031229787302.ps tmp/7x4031229787302.png")
> system("convert tmp/8tyg11229787302.ps tmp/8tyg11229787302.png")
> system("convert tmp/9kypg1229787302.ps tmp/9kypg1229787302.png")
> system("convert tmp/10yy3m1229787302.ps tmp/10yy3m1229787302.png")
>
>
> proc.time()
user system elapsed
2.424 1.566 2.928