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(8.9,0,8.8,0,8.3,0,7.5,0,7.2,0,7.4,0,8.8,0,9.3,0,9.3,0,8.7,0,8.2,0,8.3,0,8.5,0,8.6,0,8.5,0,8.2,0,8.1,0,7.9,0,8.6,0,8.7,0,8.7,0,8.5,0,8.4,0,8.5,0,8.7,0,8.7,0,8.6,0,8.5,0,8.3,0,8,0,8.2,0,8.1,0,8.1,0,8,0,7.9,0,7.9,0,8,0,8,0,7.9,0,8,0,7.7,0,7.2,0,7.5,0,7.3,0,7,0,7,0,7,0,7.2,0,7.3,1,7.1,1,6.8,1,6.4,1,6.1,1,6.5,1,7.7,1,7.9,1,7.5,1,6.9,1,6.6,1,6.9,1),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 8.9 0 1 0 0 0 0 0 0 0 0 0 0 1
2 8.8 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 7.5 0 0 0 0 1 0 0 0 0 0 0 0 4
5 7.2 0 0 0 0 0 1 0 0 0 0 0 0 5
6 7.4 0 0 0 0 0 0 1 0 0 0 0 0 6
7 8.8 0 0 0 0 0 0 0 1 0 0 0 0 7
8 9.3 0 0 0 0 0 0 0 0 1 0 0 0 8
9 9.3 0 0 0 0 0 0 0 0 0 1 0 0 9
10 8.7 0 0 0 0 0 0 0 0 0 0 1 0 10
11 8.2 0 0 0 0 0 0 0 0 0 0 0 1 11
12 8.3 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 8.6 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 8.2 0 0 0 0 1 0 0 0 0 0 0 0 16
17 8.1 0 0 0 0 0 1 0 0 0 0 0 0 17
18 7.9 0 0 0 0 0 0 1 0 0 0 0 0 18
19 8.6 0 0 0 0 0 0 0 1 0 0 0 0 19
20 8.7 0 0 0 0 0 0 0 0 1 0 0 0 20
21 8.7 0 0 0 0 0 0 0 0 0 1 0 0 21
22 8.5 0 0 0 0 0 0 0 0 0 0 1 0 22
23 8.4 0 0 0 0 0 0 0 0 0 0 0 1 23
24 8.5 0 0 0 0 0 0 0 0 0 0 0 0 24
25 8.7 0 1 0 0 0 0 0 0 0 0 0 0 25
26 8.7 0 0 1 0 0 0 0 0 0 0 0 0 26
27 8.6 0 0 0 1 0 0 0 0 0 0 0 0 27
28 8.5 0 0 0 0 1 0 0 0 0 0 0 0 28
29 8.3 0 0 0 0 0 1 0 0 0 0 0 0 29
30 8.0 0 0 0 0 0 0 1 0 0 0 0 0 30
31 8.2 0 0 0 0 0 0 0 1 0 0 0 0 31
32 8.1 0 0 0 0 0 0 0 0 1 0 0 0 32
33 8.1 0 0 0 0 0 0 0 0 0 1 0 0 33
34 8.0 0 0 0 0 0 0 0 0 0 0 1 0 34
35 7.9 0 0 0 0 0 0 0 0 0 0 0 1 35
36 7.9 0 0 0 0 0 0 0 0 0 0 0 0 36
37 8.0 0 1 0 0 0 0 0 0 0 0 0 0 37
38 8.0 0 0 1 0 0 0 0 0 0 0 0 0 38
39 7.9 0 0 0 1 0 0 0 0 0 0 0 0 39
40 8.0 0 0 0 0 1 0 0 0 0 0 0 0 40
41 7.7 0 0 0 0 0 1 0 0 0 0 0 0 41
42 7.2 0 0 0 0 0 0 1 0 0 0 0 0 42
43 7.5 0 0 0 0 0 0 0 1 0 0 0 0 43
44 7.3 0 0 0 0 0 0 0 0 1 0 0 0 44
45 7.0 0 0 0 0 0 0 0 0 0 1 0 0 45
46 7.0 0 0 0 0 0 0 0 0 0 0 1 0 46
47 7.0 0 0 0 0 0 0 0 0 0 0 0 1 47
48 7.2 0 0 0 0 0 0 0 0 0 0 0 0 48
49 7.3 1 1 0 0 0 0 0 0 0 0 0 0 49
50 7.1 1 0 1 0 0 0 0 0 0 0 0 0 50
51 6.8 1 0 0 1 0 0 0 0 0 0 0 0 51
52 6.4 1 0 0 0 1 0 0 0 0 0 0 0 52
53 6.1 1 0 0 0 0 1 0 0 0 0 0 0 53
54 6.5 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 7.9 1 0 0 0 0 0 0 0 1 0 0 0 56
57 7.5 1 0 0 0 0 0 0 0 0 1 0 0 57
58 6.9 1 0 0 0 0 0 0 0 0 0 1 0 58
59 6.6 1 0 0 0 0 0 0 0 0 0 0 1 59
60 6.9 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
8.72000 -0.43750 0.25340 0.23764 0.04188 -0.23389
M5 M6 M7 M8 M9 M10
-0.44965 -0.50542 0.27882 0.40306 0.28729 0.01153
M11 t
-0.16424 -0.02424
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.94917 -0.17083 0.02167 0.30417 0.73250
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.720000 0.246824 35.329 < 2e-16 ***
X -0.437500 0.202888 -2.156 0.0363 *
M1 0.253403 0.286009 0.886 0.3802
M2 0.237639 0.285168 0.833 0.4090
M3 0.041875 0.284405 0.147 0.8836
M4 -0.233889 0.283721 -0.824 0.4140
M5 -0.449653 0.283116 -1.588 0.1191
M6 -0.505417 0.282590 -1.789 0.0803 .
M7 0.278819 0.282145 0.988 0.3282
M8 0.403056 0.281780 1.430 0.1594
M9 0.287292 0.281496 1.021 0.3128
M10 0.011528 0.281293 0.041 0.9675
M11 -0.164236 0.281171 -0.584 0.5620
t -0.024236 0.004782 -5.068 6.99e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4445 on 46 degrees of freedom
Multiple R-squared: 0.7212, Adjusted R-squared: 0.6424
F-statistic: 9.152 on 13 and 46 DF, p-value: 6.967e-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,] 0.76327299 0.4734540 0.2367270
[2,] 0.66365866 0.6726827 0.3363413
[3,] 0.61720080 0.7655984 0.3827992
[4,] 0.68827813 0.6234437 0.3117219
[5,] 0.69261425 0.6147715 0.3073857
[6,] 0.59493687 0.8101263 0.4050631
[7,] 0.49029321 0.9805864 0.5097068
[8,] 0.39414058 0.7882812 0.6058594
[9,] 0.29306553 0.5861311 0.7069345
[10,] 0.20896775 0.4179355 0.7910322
[11,] 0.14990339 0.2998068 0.8500966
[12,] 0.15825716 0.3165143 0.8417428
[13,] 0.16188701 0.3237740 0.8381130
[14,] 0.11640256 0.2328051 0.8835974
[15,] 0.13400501 0.2680100 0.8659950
[16,] 0.23243615 0.4648723 0.7675638
[17,] 0.27199051 0.5439810 0.7280095
[18,] 0.22878862 0.4575772 0.7712114
[19,] 0.17042393 0.3408479 0.8295761
[20,] 0.12284481 0.2456896 0.8771552
[21,] 0.09432853 0.1886571 0.9056715
[22,] 0.07293859 0.1458772 0.9270614
[23,] 0.06025563 0.1205113 0.9397444
[24,] 0.12438911 0.2487782 0.8756109
[25,] 0.48769978 0.9753996 0.5123002
[26,] 0.58237307 0.8352539 0.4176269
[27,] 0.45461042 0.9092208 0.5453896
> postscript(file="/var/www/html/rcomp/tmp/1fu661260103124.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2njsz1260103124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wpez1260103124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4354i1260103124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5nz1s1260103124.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
-0.049166667 -0.109166667 -0.389166667 -0.889166667 -0.949166667 -0.669166667
7 8 9 10 11 12
-0.029166667 0.370833333 0.510833333 0.210833333 -0.089166667 -0.129166667
13 14 15 16 17 18
-0.158333333 -0.018333333 0.101666667 0.101666667 0.241666667 0.121666667
19 20 21 22 23 24
0.061666667 0.061666667 0.201666667 0.301666667 0.401666667 0.361666667
25 26 27 28 29 30
0.332500000 0.372500000 0.492500000 0.692500000 0.732500000 0.512500000
31 32 33 34 35 36
-0.047500000 -0.247500000 -0.107500000 0.092500000 0.192500000 0.052500000
37 38 39 40 41 42
-0.076666667 -0.036666667 0.083333333 0.483333333 0.423333333 0.003333333
43 44 45 46 47 48
-0.456666667 -0.756666667 -0.916666667 -0.616666667 -0.416666667 -0.356666667
49 50 51 52 53 54
-0.048333333 -0.208333333 -0.288333333 -0.388333333 -0.448333333 0.031666667
55 56 57 58 59 60
0.471666667 0.571666667 0.311666667 0.011666667 -0.088333333 0.071666667
> postscript(file="/var/www/html/rcomp/tmp/60pp71260103124.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 -0.049166667 NA
1 -0.109166667 -0.049166667
2 -0.389166667 -0.109166667
3 -0.889166667 -0.389166667
4 -0.949166667 -0.889166667
5 -0.669166667 -0.949166667
6 -0.029166667 -0.669166667
7 0.370833333 -0.029166667
8 0.510833333 0.370833333
9 0.210833333 0.510833333
10 -0.089166667 0.210833333
11 -0.129166667 -0.089166667
12 -0.158333333 -0.129166667
13 -0.018333333 -0.158333333
14 0.101666667 -0.018333333
15 0.101666667 0.101666667
16 0.241666667 0.101666667
17 0.121666667 0.241666667
18 0.061666667 0.121666667
19 0.061666667 0.061666667
20 0.201666667 0.061666667
21 0.301666667 0.201666667
22 0.401666667 0.301666667
23 0.361666667 0.401666667
24 0.332500000 0.361666667
25 0.372500000 0.332500000
26 0.492500000 0.372500000
27 0.692500000 0.492500000
28 0.732500000 0.692500000
29 0.512500000 0.732500000
30 -0.047500000 0.512500000
31 -0.247500000 -0.047500000
32 -0.107500000 -0.247500000
33 0.092500000 -0.107500000
34 0.192500000 0.092500000
35 0.052500000 0.192500000
36 -0.076666667 0.052500000
37 -0.036666667 -0.076666667
38 0.083333333 -0.036666667
39 0.483333333 0.083333333
40 0.423333333 0.483333333
41 0.003333333 0.423333333
42 -0.456666667 0.003333333
43 -0.756666667 -0.456666667
44 -0.916666667 -0.756666667
45 -0.616666667 -0.916666667
46 -0.416666667 -0.616666667
47 -0.356666667 -0.416666667
48 -0.048333333 -0.356666667
49 -0.208333333 -0.048333333
50 -0.288333333 -0.208333333
51 -0.388333333 -0.288333333
52 -0.448333333 -0.388333333
53 0.031666667 -0.448333333
54 0.471666667 0.031666667
55 0.571666667 0.471666667
56 0.311666667 0.571666667
57 0.011666667 0.311666667
58 -0.088333333 0.011666667
59 0.071666667 -0.088333333
60 NA 0.071666667
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.109166667 -0.049166667
[2,] -0.389166667 -0.109166667
[3,] -0.889166667 -0.389166667
[4,] -0.949166667 -0.889166667
[5,] -0.669166667 -0.949166667
[6,] -0.029166667 -0.669166667
[7,] 0.370833333 -0.029166667
[8,] 0.510833333 0.370833333
[9,] 0.210833333 0.510833333
[10,] -0.089166667 0.210833333
[11,] -0.129166667 -0.089166667
[12,] -0.158333333 -0.129166667
[13,] -0.018333333 -0.158333333
[14,] 0.101666667 -0.018333333
[15,] 0.101666667 0.101666667
[16,] 0.241666667 0.101666667
[17,] 0.121666667 0.241666667
[18,] 0.061666667 0.121666667
[19,] 0.061666667 0.061666667
[20,] 0.201666667 0.061666667
[21,] 0.301666667 0.201666667
[22,] 0.401666667 0.301666667
[23,] 0.361666667 0.401666667
[24,] 0.332500000 0.361666667
[25,] 0.372500000 0.332500000
[26,] 0.492500000 0.372500000
[27,] 0.692500000 0.492500000
[28,] 0.732500000 0.692500000
[29,] 0.512500000 0.732500000
[30,] -0.047500000 0.512500000
[31,] -0.247500000 -0.047500000
[32,] -0.107500000 -0.247500000
[33,] 0.092500000 -0.107500000
[34,] 0.192500000 0.092500000
[35,] 0.052500000 0.192500000
[36,] -0.076666667 0.052500000
[37,] -0.036666667 -0.076666667
[38,] 0.083333333 -0.036666667
[39,] 0.483333333 0.083333333
[40,] 0.423333333 0.483333333
[41,] 0.003333333 0.423333333
[42,] -0.456666667 0.003333333
[43,] -0.756666667 -0.456666667
[44,] -0.916666667 -0.756666667
[45,] -0.616666667 -0.916666667
[46,] -0.416666667 -0.616666667
[47,] -0.356666667 -0.416666667
[48,] -0.048333333 -0.356666667
[49,] -0.208333333 -0.048333333
[50,] -0.288333333 -0.208333333
[51,] -0.388333333 -0.288333333
[52,] -0.448333333 -0.388333333
[53,] 0.031666667 -0.448333333
[54,] 0.471666667 0.031666667
[55,] 0.571666667 0.471666667
[56,] 0.311666667 0.571666667
[57,] 0.011666667 0.311666667
[58,] -0.088333333 0.011666667
[59,] 0.071666667 -0.088333333
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.109166667 -0.049166667
2 -0.389166667 -0.109166667
3 -0.889166667 -0.389166667
4 -0.949166667 -0.889166667
5 -0.669166667 -0.949166667
6 -0.029166667 -0.669166667
7 0.370833333 -0.029166667
8 0.510833333 0.370833333
9 0.210833333 0.510833333
10 -0.089166667 0.210833333
11 -0.129166667 -0.089166667
12 -0.158333333 -0.129166667
13 -0.018333333 -0.158333333
14 0.101666667 -0.018333333
15 0.101666667 0.101666667
16 0.241666667 0.101666667
17 0.121666667 0.241666667
18 0.061666667 0.121666667
19 0.061666667 0.061666667
20 0.201666667 0.061666667
21 0.301666667 0.201666667
22 0.401666667 0.301666667
23 0.361666667 0.401666667
24 0.332500000 0.361666667
25 0.372500000 0.332500000
26 0.492500000 0.372500000
27 0.692500000 0.492500000
28 0.732500000 0.692500000
29 0.512500000 0.732500000
30 -0.047500000 0.512500000
31 -0.247500000 -0.047500000
32 -0.107500000 -0.247500000
33 0.092500000 -0.107500000
34 0.192500000 0.092500000
35 0.052500000 0.192500000
36 -0.076666667 0.052500000
37 -0.036666667 -0.076666667
38 0.083333333 -0.036666667
39 0.483333333 0.083333333
40 0.423333333 0.483333333
41 0.003333333 0.423333333
42 -0.456666667 0.003333333
43 -0.756666667 -0.456666667
44 -0.916666667 -0.756666667
45 -0.616666667 -0.916666667
46 -0.416666667 -0.616666667
47 -0.356666667 -0.416666667
48 -0.048333333 -0.356666667
49 -0.208333333 -0.048333333
50 -0.288333333 -0.208333333
51 -0.388333333 -0.288333333
52 -0.448333333 -0.388333333
53 0.031666667 -0.448333333
54 0.471666667 0.031666667
55 0.571666667 0.471666667
56 0.311666667 0.571666667
57 0.011666667 0.311666667
58 -0.088333333 0.011666667
59 0.071666667 -0.088333333
> 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/7wmub1260103124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8y0ig1260103124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/948ep1260103124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10l23r1260103124.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/118euw1260103124.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/12bsju1260103124.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/13via31260103124.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/14o6lz1260103124.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/15uled1260103124.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/16le8j1260103124.tab")
+ }
>
> system("convert tmp/1fu661260103124.ps tmp/1fu661260103124.png")
> system("convert tmp/2njsz1260103124.ps tmp/2njsz1260103124.png")
> system("convert tmp/3wpez1260103124.ps tmp/3wpez1260103124.png")
> system("convert tmp/4354i1260103124.ps tmp/4354i1260103124.png")
> system("convert tmp/5nz1s1260103124.ps tmp/5nz1s1260103124.png")
> system("convert tmp/60pp71260103124.ps tmp/60pp71260103124.png")
> system("convert tmp/7wmub1260103124.ps tmp/7wmub1260103124.png")
> system("convert tmp/8y0ig1260103124.ps tmp/8y0ig1260103124.png")
> system("convert tmp/948ep1260103124.ps tmp/948ep1260103124.png")
> system("convert tmp/10l23r1260103124.ps tmp/10l23r1260103124.png")
>
>
> proc.time()
user system elapsed
2.357 1.516 2.894