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(8.7,0,8.2,0,8.3,0,8.5,0,8.6,0,8.5,0,8.2,0,8.1,0,7.9,0,8.6,0,8.7,0,8.7,0,8.5,0,8.4,0,8.5,0,8.7,0,8.7,0,8.6,0,8.5,0,8.3,0,8,0,8.2,0,8.1,0,8.1,0,8,0,7.9,0,7.9,0,8,0,8,0,7.9,0,8,0,7.7,0,7.2,0,7.5,0,7.3,0,7,0,7,0,7,0,7.2,0,7.3,0,7.1,0,6.8,0,6.4,0,6.1,0,6.5,0,7.7,0,7.9,0,7.5,1,6.9,1,6.6,1,6.9,1,7.7,1,8,1,8,1,7.7,1,7.3,1,7.4,1,8.1,1,8.3,1,8.2,1),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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
Y X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 8.7 0 1 0 0 0 0 0 0 0 0 0 0 1
2 8.2 0 0 1 0 0 0 0 0 0 0 0 0 2
3 8.3 0 0 0 1 0 0 0 0 0 0 0 0 3
4 8.5 0 0 0 0 1 0 0 0 0 0 0 0 4
5 8.6 0 0 0 0 0 1 0 0 0 0 0 0 5
6 8.5 0 0 0 0 0 0 1 0 0 0 0 0 6
7 8.2 0 0 0 0 0 0 0 1 0 0 0 0 7
8 8.1 0 0 0 0 0 0 0 0 1 0 0 0 8
9 7.9 0 0 0 0 0 0 0 0 0 1 0 0 9
10 8.6 0 0 0 0 0 0 0 0 0 0 1 0 10
11 8.7 0 0 0 0 0 0 0 0 0 0 0 1 11
12 8.7 0 0 0 0 0 0 0 0 0 0 0 0 12
13 8.5 0 1 0 0 0 0 0 0 0 0 0 0 13
14 8.4 0 0 1 0 0 0 0 0 0 0 0 0 14
15 8.5 0 0 0 1 0 0 0 0 0 0 0 0 15
16 8.7 0 0 0 0 1 0 0 0 0 0 0 0 16
17 8.7 0 0 0 0 0 1 0 0 0 0 0 0 17
18 8.6 0 0 0 0 0 0 1 0 0 0 0 0 18
19 8.5 0 0 0 0 0 0 0 1 0 0 0 0 19
20 8.3 0 0 0 0 0 0 0 0 1 0 0 0 20
21 8.0 0 0 0 0 0 0 0 0 0 1 0 0 21
22 8.2 0 0 0 0 0 0 0 0 0 0 1 0 22
23 8.1 0 0 0 0 0 0 0 0 0 0 0 1 23
24 8.1 0 0 0 0 0 0 0 0 0 0 0 0 24
25 8.0 0 1 0 0 0 0 0 0 0 0 0 0 25
26 7.9 0 0 1 0 0 0 0 0 0 0 0 0 26
27 7.9 0 0 0 1 0 0 0 0 0 0 0 0 27
28 8.0 0 0 0 0 1 0 0 0 0 0 0 0 28
29 8.0 0 0 0 0 0 1 0 0 0 0 0 0 29
30 7.9 0 0 0 0 0 0 1 0 0 0 0 0 30
31 8.0 0 0 0 0 0 0 0 1 0 0 0 0 31
32 7.7 0 0 0 0 0 0 0 0 1 0 0 0 32
33 7.2 0 0 0 0 0 0 0 0 0 1 0 0 33
34 7.5 0 0 0 0 0 0 0 0 0 0 1 0 34
35 7.3 0 0 0 0 0 0 0 0 0 0 0 1 35
36 7.0 0 0 0 0 0 0 0 0 0 0 0 0 36
37 7.0 0 1 0 0 0 0 0 0 0 0 0 0 37
38 7.0 0 0 1 0 0 0 0 0 0 0 0 0 38
39 7.2 0 0 0 1 0 0 0 0 0 0 0 0 39
40 7.3 0 0 0 0 1 0 0 0 0 0 0 0 40
41 7.1 0 0 0 0 0 1 0 0 0 0 0 0 41
42 6.8 0 0 0 0 0 0 1 0 0 0 0 0 42
43 6.4 0 0 0 0 0 0 0 1 0 0 0 0 43
44 6.1 0 0 0 0 0 0 0 0 1 0 0 0 44
45 6.5 0 0 0 0 0 0 0 0 0 1 0 0 45
46 7.7 0 0 0 0 0 0 0 0 0 0 1 0 46
47 7.9 0 0 0 0 0 0 0 0 0 0 0 1 47
48 7.5 1 0 0 0 0 0 0 0 0 0 0 0 48
49 6.9 1 1 0 0 0 0 0 0 0 0 0 0 49
50 6.6 1 0 1 0 0 0 0 0 0 0 0 0 50
51 6.9 1 0 0 1 0 0 0 0 0 0 0 0 51
52 7.7 1 0 0 0 1 0 0 0 0 0 0 0 52
53 8.0 1 0 0 0 0 1 0 0 0 0 0 0 53
54 8.0 1 0 0 0 0 0 1 0 0 0 0 0 54
55 7.7 1 0 0 0 0 0 0 1 0 0 0 0 55
56 7.3 1 0 0 0 0 0 0 0 1 0 0 0 56
57 7.4 1 0 0 0 0 0 0 0 0 1 0 0 57
58 8.1 1 0 0 0 0 0 0 0 0 0 1 0 58
59 8.3 1 0 0 0 0 0 0 0 0 0 0 1 59
60 8.2 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) X M1 M2 M3 M4
8.997496 0.888870 -0.346212 -0.505849 -0.325487 -0.005125
M5 M6 M7 M8 M9 M10
0.075238 -0.004400 -0.164038 -0.383675 -0.443313 0.217049
M11 t
0.297412 -0.040362
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.7624 -0.2677 0.0644 0.3345 0.7354
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.997496 0.227349 39.576 < 2e-16 ***
X 0.888870 0.194356 4.573 3.62e-05 ***
M1 -0.346212 0.271424 -1.276 0.2085
M2 -0.505849 0.271062 -1.866 0.0684 .
M3 -0.325487 0.270779 -1.202 0.2355
M4 -0.005125 0.270577 -0.019 0.9850
M5 0.075238 0.270456 0.278 0.7821
M6 -0.004400 0.270416 -0.016 0.9871
M7 -0.164038 0.270456 -0.607 0.5471
M8 -0.383675 0.270577 -1.418 0.1629
M9 -0.443313 0.270779 -1.637 0.1084
M10 0.217049 0.271062 0.801 0.4274
M11 0.297412 0.271424 1.096 0.2789
t -0.040362 0.004675 -8.633 3.51e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4254 on 46 degrees of freedom
Multiple R-squared: 0.6757, Adjusted R-squared: 0.5841
F-statistic: 7.374 on 13 and 46 DF, p-value: 1.604e-07
> 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,] 0.0360839341 0.0721678681 0.9639161
[2,] 0.0086425813 0.0172851626 0.9913574
[3,] 0.0034240284 0.0068480568 0.9965760
[4,] 0.0008811325 0.0017622651 0.9991189
[5,] 0.0001903402 0.0003806805 0.9998097
[6,] 0.0013298201 0.0026596402 0.9986702
[7,] 0.0066055270 0.0132110540 0.9933945
[8,] 0.0099992061 0.0199984123 0.9900008
[9,] 0.0143034376 0.0286068752 0.9856966
[10,] 0.0113283552 0.0226567105 0.9886716
[11,] 0.0089807994 0.0179615987 0.9910192
[12,] 0.0067128179 0.0134256358 0.9932872
[13,] 0.0050226148 0.0100452296 0.9949774
[14,] 0.0036703603 0.0073407205 0.9963296
[15,] 0.0043382609 0.0086765218 0.9956617
[16,] 0.0160384185 0.0320768369 0.9839616
[17,] 0.0327120128 0.0654240255 0.9672880
[18,] 0.0396457622 0.0792915244 0.9603542
[19,] 0.0509954932 0.1019909864 0.9490045
[20,] 0.0903225613 0.1806451225 0.9096774
[21,] 0.1339448623 0.2678897245 0.8660551
[22,] 0.2826770841 0.5653541682 0.7173229
[23,] 0.6385889053 0.7228221893 0.3614111
[24,] 0.6498569132 0.7002861737 0.3501431
[25,] 0.5407768428 0.9184463144 0.4592232
[26,] 0.5055049179 0.9889901643 0.4944951
[27,] 0.5985651074 0.8028697853 0.4014349
> postscript(file="/var/www/html/rcomp/tmp/1f3iv1261669643.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2pl171261669643.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3x3p71261669643.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/42s5c1261669643.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/55ail1261669643.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
0.08907826 -0.21092174 -0.25092174 -0.33092174 -0.27092174 -0.25092174
7 8 9 10 11 12
-0.35092174 -0.19092174 -0.29092174 -0.21092174 -0.15092174 0.18685217
13 14 15 16 17 18
0.37342609 0.47342609 0.43342609 0.35342609 0.31342609 0.33342609
19 20 21 22 23 24
0.43342609 0.49342609 0.29342609 -0.12657391 -0.26657391 0.07120000
25 26 27 28 29 30
0.35777391 0.45777391 0.31777391 0.13777391 0.09777391 0.11777391
31 32 33 34 35 36
0.41777391 0.37777391 -0.02222609 -0.34222609 -0.58222609 -0.54445217
37 38 39 40 41 42
-0.15787826 0.04212174 0.10212174 -0.07787826 -0.31787826 -0.49787826
43 44 45 46 47 48
-0.69787826 -0.73787826 -0.23787826 0.34212174 0.50212174 -0.44897391
49 50 51 52 53 54
-0.66240000 -0.76240000 -0.60240000 -0.08240000 0.17760000 0.29760000
55 56 57 58 59 60
0.19760000 0.05760000 0.25760000 0.33760000 0.49760000 0.73537391
> postscript(file="/var/www/html/rcomp/tmp/6600y1261669643.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 0.08907826 NA
1 -0.21092174 0.08907826
2 -0.25092174 -0.21092174
3 -0.33092174 -0.25092174
4 -0.27092174 -0.33092174
5 -0.25092174 -0.27092174
6 -0.35092174 -0.25092174
7 -0.19092174 -0.35092174
8 -0.29092174 -0.19092174
9 -0.21092174 -0.29092174
10 -0.15092174 -0.21092174
11 0.18685217 -0.15092174
12 0.37342609 0.18685217
13 0.47342609 0.37342609
14 0.43342609 0.47342609
15 0.35342609 0.43342609
16 0.31342609 0.35342609
17 0.33342609 0.31342609
18 0.43342609 0.33342609
19 0.49342609 0.43342609
20 0.29342609 0.49342609
21 -0.12657391 0.29342609
22 -0.26657391 -0.12657391
23 0.07120000 -0.26657391
24 0.35777391 0.07120000
25 0.45777391 0.35777391
26 0.31777391 0.45777391
27 0.13777391 0.31777391
28 0.09777391 0.13777391
29 0.11777391 0.09777391
30 0.41777391 0.11777391
31 0.37777391 0.41777391
32 -0.02222609 0.37777391
33 -0.34222609 -0.02222609
34 -0.58222609 -0.34222609
35 -0.54445217 -0.58222609
36 -0.15787826 -0.54445217
37 0.04212174 -0.15787826
38 0.10212174 0.04212174
39 -0.07787826 0.10212174
40 -0.31787826 -0.07787826
41 -0.49787826 -0.31787826
42 -0.69787826 -0.49787826
43 -0.73787826 -0.69787826
44 -0.23787826 -0.73787826
45 0.34212174 -0.23787826
46 0.50212174 0.34212174
47 -0.44897391 0.50212174
48 -0.66240000 -0.44897391
49 -0.76240000 -0.66240000
50 -0.60240000 -0.76240000
51 -0.08240000 -0.60240000
52 0.17760000 -0.08240000
53 0.29760000 0.17760000
54 0.19760000 0.29760000
55 0.05760000 0.19760000
56 0.25760000 0.05760000
57 0.33760000 0.25760000
58 0.49760000 0.33760000
59 0.73537391 0.49760000
60 NA 0.73537391
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.21092174 0.08907826
[2,] -0.25092174 -0.21092174
[3,] -0.33092174 -0.25092174
[4,] -0.27092174 -0.33092174
[5,] -0.25092174 -0.27092174
[6,] -0.35092174 -0.25092174
[7,] -0.19092174 -0.35092174
[8,] -0.29092174 -0.19092174
[9,] -0.21092174 -0.29092174
[10,] -0.15092174 -0.21092174
[11,] 0.18685217 -0.15092174
[12,] 0.37342609 0.18685217
[13,] 0.47342609 0.37342609
[14,] 0.43342609 0.47342609
[15,] 0.35342609 0.43342609
[16,] 0.31342609 0.35342609
[17,] 0.33342609 0.31342609
[18,] 0.43342609 0.33342609
[19,] 0.49342609 0.43342609
[20,] 0.29342609 0.49342609
[21,] -0.12657391 0.29342609
[22,] -0.26657391 -0.12657391
[23,] 0.07120000 -0.26657391
[24,] 0.35777391 0.07120000
[25,] 0.45777391 0.35777391
[26,] 0.31777391 0.45777391
[27,] 0.13777391 0.31777391
[28,] 0.09777391 0.13777391
[29,] 0.11777391 0.09777391
[30,] 0.41777391 0.11777391
[31,] 0.37777391 0.41777391
[32,] -0.02222609 0.37777391
[33,] -0.34222609 -0.02222609
[34,] -0.58222609 -0.34222609
[35,] -0.54445217 -0.58222609
[36,] -0.15787826 -0.54445217
[37,] 0.04212174 -0.15787826
[38,] 0.10212174 0.04212174
[39,] -0.07787826 0.10212174
[40,] -0.31787826 -0.07787826
[41,] -0.49787826 -0.31787826
[42,] -0.69787826 -0.49787826
[43,] -0.73787826 -0.69787826
[44,] -0.23787826 -0.73787826
[45,] 0.34212174 -0.23787826
[46,] 0.50212174 0.34212174
[47,] -0.44897391 0.50212174
[48,] -0.66240000 -0.44897391
[49,] -0.76240000 -0.66240000
[50,] -0.60240000 -0.76240000
[51,] -0.08240000 -0.60240000
[52,] 0.17760000 -0.08240000
[53,] 0.29760000 0.17760000
[54,] 0.19760000 0.29760000
[55,] 0.05760000 0.19760000
[56,] 0.25760000 0.05760000
[57,] 0.33760000 0.25760000
[58,] 0.49760000 0.33760000
[59,] 0.73537391 0.49760000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.21092174 0.08907826
2 -0.25092174 -0.21092174
3 -0.33092174 -0.25092174
4 -0.27092174 -0.33092174
5 -0.25092174 -0.27092174
6 -0.35092174 -0.25092174
7 -0.19092174 -0.35092174
8 -0.29092174 -0.19092174
9 -0.21092174 -0.29092174
10 -0.15092174 -0.21092174
11 0.18685217 -0.15092174
12 0.37342609 0.18685217
13 0.47342609 0.37342609
14 0.43342609 0.47342609
15 0.35342609 0.43342609
16 0.31342609 0.35342609
17 0.33342609 0.31342609
18 0.43342609 0.33342609
19 0.49342609 0.43342609
20 0.29342609 0.49342609
21 -0.12657391 0.29342609
22 -0.26657391 -0.12657391
23 0.07120000 -0.26657391
24 0.35777391 0.07120000
25 0.45777391 0.35777391
26 0.31777391 0.45777391
27 0.13777391 0.31777391
28 0.09777391 0.13777391
29 0.11777391 0.09777391
30 0.41777391 0.11777391
31 0.37777391 0.41777391
32 -0.02222609 0.37777391
33 -0.34222609 -0.02222609
34 -0.58222609 -0.34222609
35 -0.54445217 -0.58222609
36 -0.15787826 -0.54445217
37 0.04212174 -0.15787826
38 0.10212174 0.04212174
39 -0.07787826 0.10212174
40 -0.31787826 -0.07787826
41 -0.49787826 -0.31787826
42 -0.69787826 -0.49787826
43 -0.73787826 -0.69787826
44 -0.23787826 -0.73787826
45 0.34212174 -0.23787826
46 0.50212174 0.34212174
47 -0.44897391 0.50212174
48 -0.66240000 -0.44897391
49 -0.76240000 -0.66240000
50 -0.60240000 -0.76240000
51 -0.08240000 -0.60240000
52 0.17760000 -0.08240000
53 0.29760000 0.17760000
54 0.19760000 0.29760000
55 0.05760000 0.19760000
56 0.25760000 0.05760000
57 0.33760000 0.25760000
58 0.49760000 0.33760000
59 0.73537391 0.49760000
> 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/7ur5r1261669643.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8yrpb1261669643.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9w0oj1261669643.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/109fo61261669643.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11j6qv1261669643.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/12vbdl1261669643.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/13tmc31261669643.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/144sxx1261669643.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/15p0ov1261669643.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/16kk281261669643.tab")
+ }
>
> try(system("convert tmp/1f3iv1261669643.ps tmp/1f3iv1261669643.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pl171261669643.ps tmp/2pl171261669643.png",intern=TRUE))
character(0)
> try(system("convert tmp/3x3p71261669643.ps tmp/3x3p71261669643.png",intern=TRUE))
character(0)
> try(system("convert tmp/42s5c1261669643.ps tmp/42s5c1261669643.png",intern=TRUE))
character(0)
> try(system("convert tmp/55ail1261669643.ps tmp/55ail1261669643.png",intern=TRUE))
character(0)
> try(system("convert tmp/6600y1261669643.ps tmp/6600y1261669643.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ur5r1261669643.ps tmp/7ur5r1261669643.png",intern=TRUE))
character(0)
> try(system("convert tmp/8yrpb1261669643.ps tmp/8yrpb1261669643.png",intern=TRUE))
character(0)
> try(system("convert tmp/9w0oj1261669643.ps tmp/9w0oj1261669643.png",intern=TRUE))
character(0)
> try(system("convert tmp/109fo61261669643.ps tmp/109fo61261669643.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.408 1.566 3.430