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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> x <- array(list(9.3,4,9.3,3.8,8.7,4.7,8.2,4.3,8.3,3.9,8.5,4,8.6,4.3,8.5,4.8,8.2,4.4,8.1,4.3,7.9,4.7,8.6,4.7,8.7,4.9,8.7,5,8.5,4.2,8.4,4.3,8.5,4.8,8.7,4.8,8.7,4.8,8.6,4.2,8.5,4.6,8.3,4.8,8,4.5,8.2,4.4,8.1,4.3,8.1,3.9,8,3.7,7.9,4,7.9,4.1,8,3.7,8,3.8,7.9,3.8,8,3.8,7.7,3.3,7.2,3.3,7.5,3.3,7.3,3.2,7,3.4,7,4.2,7,4.9,7.2,5.1,7.3,5.5,7.1,5.6,6.8,6.4,6.4,6.1,6.1,7.1,6.5,7.8,7.7,7.9,7.9,7.4,7.5,7.5,6.9,6.8,6.6,5.2,6.9,4.7,7.7,4.1,8,3.9,8,2.6,7.7,2.7,7.3,1.8,7.4,1,8.1,0.3),dim=c(2,60),dimnames=list(c('werklh','inflatie'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('werklh','inflatie'),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 = '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
werklh inflatie M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 9.3 4.0 1 0 0 0 0 0 0 0 0 0 0
2 9.3 3.8 0 1 0 0 0 0 0 0 0 0 0
3 8.7 4.7 0 0 1 0 0 0 0 0 0 0 0
4 8.2 4.3 0 0 0 1 0 0 0 0 0 0 0
5 8.3 3.9 0 0 0 0 1 0 0 0 0 0 0
6 8.5 4.0 0 0 0 0 0 1 0 0 0 0 0
7 8.6 4.3 0 0 0 0 0 0 1 0 0 0 0
8 8.5 4.8 0 0 0 0 0 0 0 1 0 0 0
9 8.2 4.4 0 0 0 0 0 0 0 0 1 0 0
10 8.1 4.3 0 0 0 0 0 0 0 0 0 1 0
11 7.9 4.7 0 0 0 0 0 0 0 0 0 0 1
12 8.6 4.7 0 0 0 0 0 0 0 0 0 0 0
13 8.7 4.9 1 0 0 0 0 0 0 0 0 0 0
14 8.7 5.0 0 1 0 0 0 0 0 0 0 0 0
15 8.5 4.2 0 0 1 0 0 0 0 0 0 0 0
16 8.4 4.3 0 0 0 1 0 0 0 0 0 0 0
17 8.5 4.8 0 0 0 0 1 0 0 0 0 0 0
18 8.7 4.8 0 0 0 0 0 1 0 0 0 0 0
19 8.7 4.8 0 0 0 0 0 0 1 0 0 0 0
20 8.6 4.2 0 0 0 0 0 0 0 1 0 0 0
21 8.5 4.6 0 0 0 0 0 0 0 0 1 0 0
22 8.3 4.8 0 0 0 0 0 0 0 0 0 1 0
23 8.0 4.5 0 0 0 0 0 0 0 0 0 0 1
24 8.2 4.4 0 0 0 0 0 0 0 0 0 0 0
25 8.1 4.3 1 0 0 0 0 0 0 0 0 0 0
26 8.1 3.9 0 1 0 0 0 0 0 0 0 0 0
27 8.0 3.7 0 0 1 0 0 0 0 0 0 0 0
28 7.9 4.0 0 0 0 1 0 0 0 0 0 0 0
29 7.9 4.1 0 0 0 0 1 0 0 0 0 0 0
30 8.0 3.7 0 0 0 0 0 1 0 0 0 0 0
31 8.0 3.8 0 0 0 0 0 0 1 0 0 0 0
32 7.9 3.8 0 0 0 0 0 0 0 1 0 0 0
33 8.0 3.8 0 0 0 0 0 0 0 0 1 0 0
34 7.7 3.3 0 0 0 0 0 0 0 0 0 1 0
35 7.2 3.3 0 0 0 0 0 0 0 0 0 0 1
36 7.5 3.3 0 0 0 0 0 0 0 0 0 0 0
37 7.3 3.2 1 0 0 0 0 0 0 0 0 0 0
38 7.0 3.4 0 1 0 0 0 0 0 0 0 0 0
39 7.0 4.2 0 0 1 0 0 0 0 0 0 0 0
40 7.0 4.9 0 0 0 1 0 0 0 0 0 0 0
41 7.2 5.1 0 0 0 0 1 0 0 0 0 0 0
42 7.3 5.5 0 0 0 0 0 1 0 0 0 0 0
43 7.1 5.6 0 0 0 0 0 0 1 0 0 0 0
44 6.8 6.4 0 0 0 0 0 0 0 1 0 0 0
45 6.4 6.1 0 0 0 0 0 0 0 0 1 0 0
46 6.1 7.1 0 0 0 0 0 0 0 0 0 1 0
47 6.5 7.8 0 0 0 0 0 0 0 0 0 0 1
48 7.7 7.9 0 0 0 0 0 0 0 0 0 0 0
49 7.9 7.4 1 0 0 0 0 0 0 0 0 0 0
50 7.5 7.5 0 1 0 0 0 0 0 0 0 0 0
51 6.9 6.8 0 0 1 0 0 0 0 0 0 0 0
52 6.6 5.2 0 0 0 1 0 0 0 0 0 0 0
53 6.9 4.7 0 0 0 0 1 0 0 0 0 0 0
54 7.7 4.1 0 0 0 0 0 1 0 0 0 0 0
55 8.0 3.9 0 0 0 0 0 0 1 0 0 0 0
56 8.0 2.6 0 0 0 0 0 0 0 1 0 0 0
57 7.7 2.7 0 0 0 0 0 0 0 0 1 0 0
58 7.3 1.8 0 0 0 0 0 0 0 0 0 1 0
59 7.4 1.0 0 0 0 0 0 0 0 0 0 0 1
60 8.1 0.3 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) inflatie M1 M2 M3 M4
8.64886 -0.15264 0.33769 0.19158 -0.10842 -0.33589
M5 M6 M7 M8 M9 M10
-0.19895 0.06579 0.11495 -0.02337 -0.22947 -0.49863
M11
-0.59863
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.32148 -0.49897 0.03364 0.60200 1.03957
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.64886 0.41121 21.033 <2e-16 ***
inflatie -0.15264 0.06471 -2.359 0.0225 *
M1 0.33769 0.44468 0.759 0.4514
M2 0.19158 0.44445 0.431 0.6684
M3 -0.10842 0.44445 -0.244 0.8083
M4 -0.33589 0.44358 -0.757 0.4527
M5 -0.19895 0.44351 -0.449 0.6558
M6 0.06579 0.44318 0.148 0.8826
M7 0.11495 0.44336 0.259 0.7966
M8 -0.02337 0.44302 -0.053 0.9582
M9 -0.22947 0.44294 -0.518 0.6068
M10 -0.49863 0.44284 -1.126 0.2659
M11 -0.59863 0.44284 -1.352 0.1829
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.7001 on 47 degrees of freedom
Multiple R-squared: 0.2214, Adjusted R-squared: 0.02257
F-statistic: 1.114 on 12 and 47 DF, p-value: 0.3722
> 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,] 0.044160144 0.088320288 0.9558399
[2,] 0.051289399 0.102578798 0.9487106
[3,] 0.036246759 0.072493517 0.9637532
[4,] 0.018630932 0.037261863 0.9813691
[5,] 0.008526846 0.017053692 0.9914732
[6,] 0.007158212 0.014316425 0.9928418
[7,] 0.007233305 0.014466610 0.9927667
[8,] 0.004793437 0.009586874 0.9952066
[9,] 0.004835083 0.009670166 0.9951649
[10,] 0.037619478 0.075238957 0.9623805
[11,] 0.102622641 0.205245281 0.8973774
[12,] 0.120070094 0.240140189 0.8799299
[13,] 0.137705397 0.275410794 0.8622946
[14,] 0.151290466 0.302580932 0.8487095
[15,] 0.133111578 0.266223155 0.8668884
[16,] 0.113621768 0.227243535 0.8863782
[17,] 0.097416911 0.194833821 0.9025831
[18,] 0.108678048 0.217356096 0.8913220
[19,] 0.129651880 0.259303761 0.8703481
[20,] 0.090058540 0.180117079 0.9099415
[21,] 0.080310302 0.160620605 0.9196897
[22,] 0.221560129 0.443120258 0.7784399
[23,] 0.592415910 0.815168180 0.4075841
[24,] 0.693213943 0.613572114 0.3067861
[25,] 0.758141573 0.483716853 0.2418584
[26,] 0.760092408 0.479815184 0.2399076
[27,] 0.725688796 0.548622408 0.2743112
[28,] 0.733290379 0.533419242 0.2667096
[29,] 0.714811495 0.570377010 0.2851885
> postscript(file="/var/www/html/rcomp/tmp/16itx1261058633.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2etbi1261058633.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3oanh1261058633.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4c5ht1261058633.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5bqgj1261058633.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
0.92399604 1.03957415 0.87694726 0.54336717 0.44536519 0.39589255
7 8 9 10 11 12
0.49252538 0.60716019 0.45221094 0.60610547 0.56716019 0.66852934
13 14 15 16 17 18
0.46136915 0.62273830 0.60062887 0.74336717 0.78273830 0.71800198
19 20 21 22 23 24
0.66884377 0.61557811 0.78273830 0.88242387 0.63663283 0.22273830
25 26 27 28 29 30
-0.23021293 -0.14516217 0.02431047 0.19757613 0.07589255 -0.14989849
31 32 33 34 35 36
-0.18379302 -0.14547661 0.16062887 0.05346868 -0.34653132 -0.64516217
37 38 39 40 41 42
-1.19811340 -1.32148057 -0.89937113 -0.56505075 -0.47147066 -0.57515226
43 44 45 46 47 48
-0.80904679 -0.84862094 -1.08830650 -0.96651150 -0.35966574 0.25696709
49 50 51 52 53 54
0.04296114 -0.19566971 -0.60251547 -0.91925971 -0.83252538 -0.38884377
55 56 57 58 59 60
-0.16852934 -0.22864076 -0.30727161 -0.57548652 -0.49759595 -0.50307256
> postscript(file="/var/www/html/rcomp/tmp/6zvh21261058633.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 0.92399604 NA
1 1.03957415 0.92399604
2 0.87694726 1.03957415
3 0.54336717 0.87694726
4 0.44536519 0.54336717
5 0.39589255 0.44536519
6 0.49252538 0.39589255
7 0.60716019 0.49252538
8 0.45221094 0.60716019
9 0.60610547 0.45221094
10 0.56716019 0.60610547
11 0.66852934 0.56716019
12 0.46136915 0.66852934
13 0.62273830 0.46136915
14 0.60062887 0.62273830
15 0.74336717 0.60062887
16 0.78273830 0.74336717
17 0.71800198 0.78273830
18 0.66884377 0.71800198
19 0.61557811 0.66884377
20 0.78273830 0.61557811
21 0.88242387 0.78273830
22 0.63663283 0.88242387
23 0.22273830 0.63663283
24 -0.23021293 0.22273830
25 -0.14516217 -0.23021293
26 0.02431047 -0.14516217
27 0.19757613 0.02431047
28 0.07589255 0.19757613
29 -0.14989849 0.07589255
30 -0.18379302 -0.14989849
31 -0.14547661 -0.18379302
32 0.16062887 -0.14547661
33 0.05346868 0.16062887
34 -0.34653132 0.05346868
35 -0.64516217 -0.34653132
36 -1.19811340 -0.64516217
37 -1.32148057 -1.19811340
38 -0.89937113 -1.32148057
39 -0.56505075 -0.89937113
40 -0.47147066 -0.56505075
41 -0.57515226 -0.47147066
42 -0.80904679 -0.57515226
43 -0.84862094 -0.80904679
44 -1.08830650 -0.84862094
45 -0.96651150 -1.08830650
46 -0.35966574 -0.96651150
47 0.25696709 -0.35966574
48 0.04296114 0.25696709
49 -0.19566971 0.04296114
50 -0.60251547 -0.19566971
51 -0.91925971 -0.60251547
52 -0.83252538 -0.91925971
53 -0.38884377 -0.83252538
54 -0.16852934 -0.38884377
55 -0.22864076 -0.16852934
56 -0.30727161 -0.22864076
57 -0.57548652 -0.30727161
58 -0.49759595 -0.57548652
59 -0.50307256 -0.49759595
60 NA -0.50307256
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.03957415 0.92399604
[2,] 0.87694726 1.03957415
[3,] 0.54336717 0.87694726
[4,] 0.44536519 0.54336717
[5,] 0.39589255 0.44536519
[6,] 0.49252538 0.39589255
[7,] 0.60716019 0.49252538
[8,] 0.45221094 0.60716019
[9,] 0.60610547 0.45221094
[10,] 0.56716019 0.60610547
[11,] 0.66852934 0.56716019
[12,] 0.46136915 0.66852934
[13,] 0.62273830 0.46136915
[14,] 0.60062887 0.62273830
[15,] 0.74336717 0.60062887
[16,] 0.78273830 0.74336717
[17,] 0.71800198 0.78273830
[18,] 0.66884377 0.71800198
[19,] 0.61557811 0.66884377
[20,] 0.78273830 0.61557811
[21,] 0.88242387 0.78273830
[22,] 0.63663283 0.88242387
[23,] 0.22273830 0.63663283
[24,] -0.23021293 0.22273830
[25,] -0.14516217 -0.23021293
[26,] 0.02431047 -0.14516217
[27,] 0.19757613 0.02431047
[28,] 0.07589255 0.19757613
[29,] -0.14989849 0.07589255
[30,] -0.18379302 -0.14989849
[31,] -0.14547661 -0.18379302
[32,] 0.16062887 -0.14547661
[33,] 0.05346868 0.16062887
[34,] -0.34653132 0.05346868
[35,] -0.64516217 -0.34653132
[36,] -1.19811340 -0.64516217
[37,] -1.32148057 -1.19811340
[38,] -0.89937113 -1.32148057
[39,] -0.56505075 -0.89937113
[40,] -0.47147066 -0.56505075
[41,] -0.57515226 -0.47147066
[42,] -0.80904679 -0.57515226
[43,] -0.84862094 -0.80904679
[44,] -1.08830650 -0.84862094
[45,] -0.96651150 -1.08830650
[46,] -0.35966574 -0.96651150
[47,] 0.25696709 -0.35966574
[48,] 0.04296114 0.25696709
[49,] -0.19566971 0.04296114
[50,] -0.60251547 -0.19566971
[51,] -0.91925971 -0.60251547
[52,] -0.83252538 -0.91925971
[53,] -0.38884377 -0.83252538
[54,] -0.16852934 -0.38884377
[55,] -0.22864076 -0.16852934
[56,] -0.30727161 -0.22864076
[57,] -0.57548652 -0.30727161
[58,] -0.49759595 -0.57548652
[59,] -0.50307256 -0.49759595
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.03957415 0.92399604
2 0.87694726 1.03957415
3 0.54336717 0.87694726
4 0.44536519 0.54336717
5 0.39589255 0.44536519
6 0.49252538 0.39589255
7 0.60716019 0.49252538
8 0.45221094 0.60716019
9 0.60610547 0.45221094
10 0.56716019 0.60610547
11 0.66852934 0.56716019
12 0.46136915 0.66852934
13 0.62273830 0.46136915
14 0.60062887 0.62273830
15 0.74336717 0.60062887
16 0.78273830 0.74336717
17 0.71800198 0.78273830
18 0.66884377 0.71800198
19 0.61557811 0.66884377
20 0.78273830 0.61557811
21 0.88242387 0.78273830
22 0.63663283 0.88242387
23 0.22273830 0.63663283
24 -0.23021293 0.22273830
25 -0.14516217 -0.23021293
26 0.02431047 -0.14516217
27 0.19757613 0.02431047
28 0.07589255 0.19757613
29 -0.14989849 0.07589255
30 -0.18379302 -0.14989849
31 -0.14547661 -0.18379302
32 0.16062887 -0.14547661
33 0.05346868 0.16062887
34 -0.34653132 0.05346868
35 -0.64516217 -0.34653132
36 -1.19811340 -0.64516217
37 -1.32148057 -1.19811340
38 -0.89937113 -1.32148057
39 -0.56505075 -0.89937113
40 -0.47147066 -0.56505075
41 -0.57515226 -0.47147066
42 -0.80904679 -0.57515226
43 -0.84862094 -0.80904679
44 -1.08830650 -0.84862094
45 -0.96651150 -1.08830650
46 -0.35966574 -0.96651150
47 0.25696709 -0.35966574
48 0.04296114 0.25696709
49 -0.19566971 0.04296114
50 -0.60251547 -0.19566971
51 -0.91925971 -0.60251547
52 -0.83252538 -0.91925971
53 -0.38884377 -0.83252538
54 -0.16852934 -0.38884377
55 -0.22864076 -0.16852934
56 -0.30727161 -0.22864076
57 -0.57548652 -0.30727161
58 -0.49759595 -0.57548652
59 -0.50307256 -0.49759595
> 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/7wi7g1261058633.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8d7ny1261058633.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gk561261058633.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10rft01261058633.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11hmb51261058634.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/1288ep1261058634.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/13a5ep1261058634.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/148cr01261058634.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/15q4na1261058634.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/16oagn1261058634.tab")
+ }
>
> try(system("convert tmp/16itx1261058633.ps tmp/16itx1261058633.png",intern=TRUE))
character(0)
> try(system("convert tmp/2etbi1261058633.ps tmp/2etbi1261058633.png",intern=TRUE))
character(0)
> try(system("convert tmp/3oanh1261058633.ps tmp/3oanh1261058633.png",intern=TRUE))
character(0)
> try(system("convert tmp/4c5ht1261058633.ps tmp/4c5ht1261058633.png",intern=TRUE))
character(0)
> try(system("convert tmp/5bqgj1261058633.ps tmp/5bqgj1261058633.png",intern=TRUE))
character(0)
> try(system("convert tmp/6zvh21261058633.ps tmp/6zvh21261058633.png",intern=TRUE))
character(0)
> try(system("convert tmp/7wi7g1261058633.ps tmp/7wi7g1261058633.png",intern=TRUE))
character(0)
> try(system("convert tmp/8d7ny1261058633.ps tmp/8d7ny1261058633.png",intern=TRUE))
character(0)
> try(system("convert tmp/9gk561261058633.ps tmp/9gk561261058633.png",intern=TRUE))
character(0)
> try(system("convert tmp/10rft01261058633.ps tmp/10rft01261058633.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.487 1.587 3.401