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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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1.43
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0.51
+ ,1.43
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0.51
+ ,1.43
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0.51
+ ,1.43
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0.51
+ ,1.43
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.43
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.44
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.52
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.54
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.48
+ ,1
+ ,0
+ ,0
+ ,0
+ ,0.53
+ ,1.57
+ ,1
+ ,1
+ ,0
+ ,0
+ ,0.54
+ ,1.58
+ ,1
+ ,1
+ ,0
+ ,0
+ ,0.55
+ ,1.58
+ ,1
+ ,1
+ ,0
+ ,0
+ ,0.55
+ ,1.58
+ ,1
+ ,1
+ ,0
+ ,0
+ ,0.55
+ ,1.58
+ ,1
+ ,1
+ ,0
+ ,0
+ ,0.55
+ ,1.59
+ ,1
+ ,1
+ ,1
+ ,1
+ ,0.55
+ ,1.6
+ ,1
+ ,1
+ ,1
+ ,2
+ ,0.55
+ ,1.6
+ ,1
+ ,1
+ ,1
+ ,3
+ ,0.55
+ ,1.61
+ ,1
+ ,1
+ ,1
+ ,4
+ ,0.55
+ ,1.61
+ ,1
+ ,1
+ ,1
+ ,5
+ ,0.56
+ ,1.61
+ ,1
+ ,1
+ ,1
+ ,6
+ ,0.56
+ ,1.62
+ ,1
+ ,1
+ ,1
+ ,7
+ ,0.56
+ ,1.63
+ ,1
+ ,1
+ ,1
+ ,8
+ ,0.56
+ ,1.63
+ ,1
+ ,1
+ ,1
+ ,9
+ ,0.56
+ ,1.64
+ ,1
+ ,1
+ ,1
+ ,10
+ ,0.55
+ ,1.64
+ ,1
+ ,1
+ ,1
+ ,11
+ ,0.56
+ ,1.64
+ ,1
+ ,1
+ ,1
+ ,12
+ ,0.55
+ ,1.64
+ ,1
+ ,1
+ ,1
+ ,13
+ ,0.55
+ ,1.64
+ ,1
+ ,1
+ ,1
+ ,14
+ ,0.56
+ ,1.65
+ ,1
+ ,1
+ ,1
+ ,15
+ ,0.55
+ ,1.65
+ ,1
+ ,1
+ ,1
+ ,16
+ ,0.55
+ ,1.65
+ ,1
+ ,1
+ ,1
+ ,17
+ ,0.55
+ ,1.65
+ ,1
+ ,1
+ ,1
+ ,18
+ ,0.55)
+ ,dim=c(6
+ ,60)
+ ,dimnames=list(c('Broodprijzen'
+ ,'Dummy2'
+ ,'Dummy3'
+ ,'Dummy1'
+ ,'Dummy4'
+ ,'Bakmeelprijzen')
+ ,1:60))
> y <- array(NA,dim=c(6,60),dimnames=list(c('Broodprijzen','Dummy2','Dummy3','Dummy1','Dummy4','Bakmeelprijzen'),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
Broodprijzen Dummy2 Dummy3 Dummy1 Dummy4 Bakmeelprijzen M1 M2 M3 M4 M5 M6 M7
1 1.43 0 0 0 0 0.51 1 0 0 0 0 0 0
2 1.43 0 0 0 0 0.51 0 1 0 0 0 0 0
3 1.43 0 0 0 0 0.51 0 0 1 0 0 0 0
4 1.43 0 0 0 0 0.51 0 0 0 1 0 0 0
5 1.43 0 0 0 0 0.52 0 0 0 0 1 0 0
6 1.43 0 0 0 0 0.52 0 0 0 0 0 1 0
7 1.44 0 0 0 0 0.52 0 0 0 0 0 0 1
8 1.48 1 0 0 0 0.53 0 0 0 0 0 0 0
9 1.48 1 0 0 0 0.53 0 0 0 0 0 0 0
10 1.48 1 0 0 0 0.52 0 0 0 0 0 0 0
11 1.48 1 0 0 0 0.52 0 0 0 0 0 0 0
12 1.48 1 0 0 0 0.52 0 0 0 0 0 0 0
13 1.48 1 0 0 0 0.52 1 0 0 0 0 0 0
14 1.48 1 0 0 0 0.52 0 1 0 0 0 0 0
15 1.48 1 0 0 0 0.52 0 0 1 0 0 0 0
16 1.48 1 0 0 0 0.52 0 0 0 1 0 0 0
17 1.48 1 0 0 0 0.52 0 0 0 0 1 0 0
18 1.48 1 0 0 0 0.52 0 0 0 0 0 1 0
19 1.48 1 0 0 0 0.52 0 0 0 0 0 0 1
20 1.48 1 0 0 0 0.53 0 0 0 0 0 0 0
21 1.48 1 0 0 0 0.53 0 0 0 0 0 0 0
22 1.48 1 0 0 0 0.53 0 0 0 0 0 0 0
23 1.48 1 0 0 0 0.54 0 0 0 0 0 0 0
24 1.48 1 0 0 0 0.54 0 0 0 0 0 0 0
25 1.48 1 0 0 0 0.54 1 0 0 0 0 0 0
26 1.48 1 0 0 0 0.54 0 1 0 0 0 0 0
27 1.48 1 0 0 0 0.54 0 0 1 0 0 0 0
28 1.48 1 0 0 0 0.54 0 0 0 1 0 0 0
29 1.48 1 0 0 0 0.54 0 0 0 0 1 0 0
30 1.48 1 0 0 0 0.54 0 0 0 0 0 1 0
31 1.48 1 0 0 0 0.54 0 0 0 0 0 0 1
32 1.48 1 0 0 0 0.54 0 0 0 0 0 0 0
33 1.48 1 0 0 0 0.53 0 0 0 0 0 0 0
34 1.48 1 0 0 0 0.53 0 0 0 0 0 0 0
35 1.48 1 0 0 0 0.53 0 0 0 0 0 0 0
36 1.48 1 0 0 0 0.53 0 0 0 0 0 0 0
37 1.48 1 0 0 0 0.53 1 0 0 0 0 0 0
38 1.57 1 1 0 0 0.54 0 1 0 0 0 0 0
39 1.58 1 1 0 0 0.55 0 0 1 0 0 0 0
40 1.58 1 1 0 0 0.55 0 0 0 1 0 0 0
41 1.58 1 1 0 0 0.55 0 0 0 0 1 0 0
42 1.58 1 1 0 0 0.55 0 0 0 0 0 1 0
43 1.59 1 1 1 1 0.55 0 0 0 0 0 0 1
44 1.60 1 1 1 2 0.55 0 0 0 0 0 0 0
45 1.60 1 1 1 3 0.55 0 0 0 0 0 0 0
46 1.61 1 1 1 4 0.55 0 0 0 0 0 0 0
47 1.61 1 1 1 5 0.56 0 0 0 0 0 0 0
48 1.61 1 1 1 6 0.56 0 0 0 0 0 0 0
49 1.62 1 1 1 7 0.56 1 0 0 0 0 0 0
50 1.63 1 1 1 8 0.56 0 1 0 0 0 0 0
51 1.63 1 1 1 9 0.56 0 0 1 0 0 0 0
52 1.64 1 1 1 10 0.55 0 0 0 1 0 0 0
53 1.64 1 1 1 11 0.56 0 0 0 0 1 0 0
54 1.64 1 1 1 12 0.55 0 0 0 0 0 1 0
55 1.64 1 1 1 13 0.55 0 0 0 0 0 0 1
56 1.64 1 1 1 14 0.56 0 0 0 0 0 0 0
57 1.65 1 1 1 15 0.55 0 0 0 0 0 0 0
58 1.65 1 1 1 16 0.55 0 0 0 0 0 0 0
59 1.65 1 1 1 17 0.55 0 0 0 0 0 0 0
60 1.65 1 1 1 18 0.55 0 0 0 0 0 0 0
M8 M9 M10 M11 t
1 0 0 0 0 1
2 0 0 0 0 2
3 0 0 0 0 3
4 0 0 0 0 4
5 0 0 0 0 5
6 0 0 0 0 6
7 0 0 0 0 7
8 1 0 0 0 8
9 0 1 0 0 9
10 0 0 1 0 10
11 0 0 0 1 11
12 0 0 0 0 12
13 0 0 0 0 13
14 0 0 0 0 14
15 0 0 0 0 15
16 0 0 0 0 16
17 0 0 0 0 17
18 0 0 0 0 18
19 0 0 0 0 19
20 1 0 0 0 20
21 0 1 0 0 21
22 0 0 1 0 22
23 0 0 0 1 23
24 0 0 0 0 24
25 0 0 0 0 25
26 0 0 0 0 26
27 0 0 0 0 27
28 0 0 0 0 28
29 0 0 0 0 29
30 0 0 0 0 30
31 0 0 0 0 31
32 1 0 0 0 32
33 0 1 0 0 33
34 0 0 1 0 34
35 0 0 0 1 35
36 0 0 0 0 36
37 0 0 0 0 37
38 0 0 0 0 38
39 0 0 0 0 39
40 0 0 0 0 40
41 0 0 0 0 41
42 0 0 0 0 42
43 0 0 0 0 43
44 1 0 0 0 44
45 0 1 0 0 45
46 0 0 1 0 46
47 0 0 0 1 47
48 0 0 0 0 48
49 0 0 0 0 49
50 0 0 0 0 50
51 0 0 0 0 51
52 0 0 0 0 52
53 0 0 0 0 53
54 0 0 0 0 54
55 0 0 0 0 55
56 1 0 0 0 56
57 0 1 0 0 57
58 0 0 1 0 58
59 0 0 0 1 59
60 0 0 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy2 Dummy3 Dummy1 Dummy4
1.366e+00 4.878e-02 9.533e-02 1.625e-02 3.681e-03
Bakmeelprijzen M1 M2 M3 M4
1.194e-01 2.971e-03 2.982e-03 4.059e-03 5.613e-03
M5 M6 M7 M8 M9
4.451e-03 4.006e-03 3.335e-03 1.443e-03 2.500e-03
M10 M11 t
3.318e-03 1.420e-03 -5.189e-05
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7.131e-03 -1.649e-03 4.776e-05 1.608e-03 8.627e-03
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.366e+00 4.316e-02 31.656 < 2e-16 ***
Dummy2 4.878e-02 2.086e-03 23.379 < 2e-16 ***
Dummy3 9.533e-02 2.277e-03 41.874 < 2e-16 ***
Dummy1 1.625e-02 2.494e-03 6.516 7.18e-08 ***
Dummy4 3.681e-03 1.856e-04 19.836 < 2e-16 ***
Bakmeelprijzen 1.194e-01 8.426e-02 1.417 0.1638
M1 2.971e-03 2.211e-03 1.344 0.1862
M2 2.982e-03 2.250e-03 1.325 0.1923
M3 4.059e-03 2.247e-03 1.806 0.0780 .
M4 5.613e-03 2.239e-03 2.507 0.0161 *
M5 4.451e-03 2.246e-03 1.982 0.0540 .
M6 4.006e-03 2.234e-03 1.793 0.0801 .
M7 3.335e-03 2.222e-03 1.501 0.1409
M8 1.443e-03 2.212e-03 0.652 0.5178
M9 2.500e-03 2.187e-03 1.143 0.2595
M10 3.318e-03 2.197e-03 1.511 0.1384
M11 1.420e-03 2.174e-03 0.653 0.5172
t -5.189e-05 8.951e-05 -0.580 0.5653
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.003435 on 42 degrees of freedom
Multiple R-squared: 0.9985, Adjusted R-squared: 0.9979
F-statistic: 1657 on 17 and 42 DF, p-value: < 2.2e-16
> 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,] 0.4766598982 0.953319796 0.5233401
[2,] 0.3367536894 0.673507379 0.6632463
[3,] 0.2500911234 0.500182247 0.7499089
[4,] 0.2433037450 0.486607490 0.7566963
[5,] 0.2526662876 0.505332575 0.7473337
[6,] 0.1822491734 0.364498347 0.8177508
[7,] 0.1147676368 0.229535274 0.8852324
[8,] 0.0745390100 0.149078020 0.9254610
[9,] 0.0420420044 0.084084009 0.9579580
[10,] 0.0269362600 0.053872520 0.9730637
[11,] 0.0417347162 0.083469432 0.9582653
[12,] 0.0234156151 0.046831230 0.9765844
[13,] 0.0120138224 0.024027645 0.9879862
[14,] 0.0059654674 0.011930935 0.9940345
[15,] 0.0024796159 0.004959232 0.9975204
[16,] 0.0027241209 0.005448242 0.9972759
[17,] 0.0009996293 0.001999259 0.9990004
[18,] 0.0009017241 0.001803448 0.9990983
[19,] 0.0088267628 0.017653526 0.9911732
> postscript(file="/var/www/html/rcomp/tmp/1pisd1260534981.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2lnor1260534981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3agsn1260534981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4f07w1260534981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5sxbk1260534981.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
-1.267990e-04 -8.561114e-05 -1.110648e-03 -2.613368e-03 -2.593772e-03
6 7 8 9 10
-2.096493e-03 8.626691e-03 6.000557e-04 -4.053852e-04 2.222547e-05
11 12 13 14 15
1.972152e-03 3.444395e-03 5.251334e-04 5.663213e-04 -4.587153e-04
16 17 18 19 20
-1.961436e-03 -7.476304e-04 -2.503509e-04 4.728335e-04 1.222691e-03
21 22 23 24 25
2.172505e-04 -5.493485e-04 2.063686e-04 1.678612e-03 -1.240650e-03
26 27 28 29 30
-1.199462e-03 -2.224499e-03 -3.727219e-03 -2.513414e-03 -2.016135e-03
31 32 33 34 35
-1.292950e-03 6.511174e-04 8.398861e-04 7.328718e-05 2.023214e-03
36 37 38 39 40
3.495457e-03 5.761951e-04 -5.907949e-03 1.872805e-03 3.700845e-04
41 42 43 44 45
1.583890e-03 2.081169e-03 -7.130961e-03 1.132499e-03 -3.553549e-03
46 47 48 49 50
1.999245e-03 -9.256456e-04 -3.134010e-03 2.661206e-04 6.626701e-03
51 52 53 54 55
1.921057e-03 7.931939e-03 4.270927e-03 2.281809e-03 -6.756141e-04
56 57 58 59 60
-3.606364e-03 2.901798e-03 -1.545409e-03 -3.276089e-03 -5.484454e-03
> postscript(file="/var/www/html/rcomp/tmp/63faq1260534981.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 -1.267990e-04 NA
1 -8.561114e-05 -1.267990e-04
2 -1.110648e-03 -8.561114e-05
3 -2.613368e-03 -1.110648e-03
4 -2.593772e-03 -2.613368e-03
5 -2.096493e-03 -2.593772e-03
6 8.626691e-03 -2.096493e-03
7 6.000557e-04 8.626691e-03
8 -4.053852e-04 6.000557e-04
9 2.222547e-05 -4.053852e-04
10 1.972152e-03 2.222547e-05
11 3.444395e-03 1.972152e-03
12 5.251334e-04 3.444395e-03
13 5.663213e-04 5.251334e-04
14 -4.587153e-04 5.663213e-04
15 -1.961436e-03 -4.587153e-04
16 -7.476304e-04 -1.961436e-03
17 -2.503509e-04 -7.476304e-04
18 4.728335e-04 -2.503509e-04
19 1.222691e-03 4.728335e-04
20 2.172505e-04 1.222691e-03
21 -5.493485e-04 2.172505e-04
22 2.063686e-04 -5.493485e-04
23 1.678612e-03 2.063686e-04
24 -1.240650e-03 1.678612e-03
25 -1.199462e-03 -1.240650e-03
26 -2.224499e-03 -1.199462e-03
27 -3.727219e-03 -2.224499e-03
28 -2.513414e-03 -3.727219e-03
29 -2.016135e-03 -2.513414e-03
30 -1.292950e-03 -2.016135e-03
31 6.511174e-04 -1.292950e-03
32 8.398861e-04 6.511174e-04
33 7.328718e-05 8.398861e-04
34 2.023214e-03 7.328718e-05
35 3.495457e-03 2.023214e-03
36 5.761951e-04 3.495457e-03
37 -5.907949e-03 5.761951e-04
38 1.872805e-03 -5.907949e-03
39 3.700845e-04 1.872805e-03
40 1.583890e-03 3.700845e-04
41 2.081169e-03 1.583890e-03
42 -7.130961e-03 2.081169e-03
43 1.132499e-03 -7.130961e-03
44 -3.553549e-03 1.132499e-03
45 1.999245e-03 -3.553549e-03
46 -9.256456e-04 1.999245e-03
47 -3.134010e-03 -9.256456e-04
48 2.661206e-04 -3.134010e-03
49 6.626701e-03 2.661206e-04
50 1.921057e-03 6.626701e-03
51 7.931939e-03 1.921057e-03
52 4.270927e-03 7.931939e-03
53 2.281809e-03 4.270927e-03
54 -6.756141e-04 2.281809e-03
55 -3.606364e-03 -6.756141e-04
56 2.901798e-03 -3.606364e-03
57 -1.545409e-03 2.901798e-03
58 -3.276089e-03 -1.545409e-03
59 -5.484454e-03 -3.276089e-03
60 NA -5.484454e-03
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -8.561114e-05 -1.267990e-04
[2,] -1.110648e-03 -8.561114e-05
[3,] -2.613368e-03 -1.110648e-03
[4,] -2.593772e-03 -2.613368e-03
[5,] -2.096493e-03 -2.593772e-03
[6,] 8.626691e-03 -2.096493e-03
[7,] 6.000557e-04 8.626691e-03
[8,] -4.053852e-04 6.000557e-04
[9,] 2.222547e-05 -4.053852e-04
[10,] 1.972152e-03 2.222547e-05
[11,] 3.444395e-03 1.972152e-03
[12,] 5.251334e-04 3.444395e-03
[13,] 5.663213e-04 5.251334e-04
[14,] -4.587153e-04 5.663213e-04
[15,] -1.961436e-03 -4.587153e-04
[16,] -7.476304e-04 -1.961436e-03
[17,] -2.503509e-04 -7.476304e-04
[18,] 4.728335e-04 -2.503509e-04
[19,] 1.222691e-03 4.728335e-04
[20,] 2.172505e-04 1.222691e-03
[21,] -5.493485e-04 2.172505e-04
[22,] 2.063686e-04 -5.493485e-04
[23,] 1.678612e-03 2.063686e-04
[24,] -1.240650e-03 1.678612e-03
[25,] -1.199462e-03 -1.240650e-03
[26,] -2.224499e-03 -1.199462e-03
[27,] -3.727219e-03 -2.224499e-03
[28,] -2.513414e-03 -3.727219e-03
[29,] -2.016135e-03 -2.513414e-03
[30,] -1.292950e-03 -2.016135e-03
[31,] 6.511174e-04 -1.292950e-03
[32,] 8.398861e-04 6.511174e-04
[33,] 7.328718e-05 8.398861e-04
[34,] 2.023214e-03 7.328718e-05
[35,] 3.495457e-03 2.023214e-03
[36,] 5.761951e-04 3.495457e-03
[37,] -5.907949e-03 5.761951e-04
[38,] 1.872805e-03 -5.907949e-03
[39,] 3.700845e-04 1.872805e-03
[40,] 1.583890e-03 3.700845e-04
[41,] 2.081169e-03 1.583890e-03
[42,] -7.130961e-03 2.081169e-03
[43,] 1.132499e-03 -7.130961e-03
[44,] -3.553549e-03 1.132499e-03
[45,] 1.999245e-03 -3.553549e-03
[46,] -9.256456e-04 1.999245e-03
[47,] -3.134010e-03 -9.256456e-04
[48,] 2.661206e-04 -3.134010e-03
[49,] 6.626701e-03 2.661206e-04
[50,] 1.921057e-03 6.626701e-03
[51,] 7.931939e-03 1.921057e-03
[52,] 4.270927e-03 7.931939e-03
[53,] 2.281809e-03 4.270927e-03
[54,] -6.756141e-04 2.281809e-03
[55,] -3.606364e-03 -6.756141e-04
[56,] 2.901798e-03 -3.606364e-03
[57,] -1.545409e-03 2.901798e-03
[58,] -3.276089e-03 -1.545409e-03
[59,] -5.484454e-03 -3.276089e-03
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -8.561114e-05 -1.267990e-04
2 -1.110648e-03 -8.561114e-05
3 -2.613368e-03 -1.110648e-03
4 -2.593772e-03 -2.613368e-03
5 -2.096493e-03 -2.593772e-03
6 8.626691e-03 -2.096493e-03
7 6.000557e-04 8.626691e-03
8 -4.053852e-04 6.000557e-04
9 2.222547e-05 -4.053852e-04
10 1.972152e-03 2.222547e-05
11 3.444395e-03 1.972152e-03
12 5.251334e-04 3.444395e-03
13 5.663213e-04 5.251334e-04
14 -4.587153e-04 5.663213e-04
15 -1.961436e-03 -4.587153e-04
16 -7.476304e-04 -1.961436e-03
17 -2.503509e-04 -7.476304e-04
18 4.728335e-04 -2.503509e-04
19 1.222691e-03 4.728335e-04
20 2.172505e-04 1.222691e-03
21 -5.493485e-04 2.172505e-04
22 2.063686e-04 -5.493485e-04
23 1.678612e-03 2.063686e-04
24 -1.240650e-03 1.678612e-03
25 -1.199462e-03 -1.240650e-03
26 -2.224499e-03 -1.199462e-03
27 -3.727219e-03 -2.224499e-03
28 -2.513414e-03 -3.727219e-03
29 -2.016135e-03 -2.513414e-03
30 -1.292950e-03 -2.016135e-03
31 6.511174e-04 -1.292950e-03
32 8.398861e-04 6.511174e-04
33 7.328718e-05 8.398861e-04
34 2.023214e-03 7.328718e-05
35 3.495457e-03 2.023214e-03
36 5.761951e-04 3.495457e-03
37 -5.907949e-03 5.761951e-04
38 1.872805e-03 -5.907949e-03
39 3.700845e-04 1.872805e-03
40 1.583890e-03 3.700845e-04
41 2.081169e-03 1.583890e-03
42 -7.130961e-03 2.081169e-03
43 1.132499e-03 -7.130961e-03
44 -3.553549e-03 1.132499e-03
45 1.999245e-03 -3.553549e-03
46 -9.256456e-04 1.999245e-03
47 -3.134010e-03 -9.256456e-04
48 2.661206e-04 -3.134010e-03
49 6.626701e-03 2.661206e-04
50 1.921057e-03 6.626701e-03
51 7.931939e-03 1.921057e-03
52 4.270927e-03 7.931939e-03
53 2.281809e-03 4.270927e-03
54 -6.756141e-04 2.281809e-03
55 -3.606364e-03 -6.756141e-04
56 2.901798e-03 -3.606364e-03
57 -1.545409e-03 2.901798e-03
58 -3.276089e-03 -1.545409e-03
59 -5.484454e-03 -3.276089e-03
> 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/74rg71260534981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8jg2e1260534981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/92jua1260534981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10cyea1260534981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11qejp1260534981.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/12k4qh1260534981.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/131ts61260534981.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/1432it1260534981.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/15bcox1260534981.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/16re561260534981.tab")
+ }
>
> system("convert tmp/1pisd1260534981.ps tmp/1pisd1260534981.png")
> system("convert tmp/2lnor1260534981.ps tmp/2lnor1260534981.png")
> system("convert tmp/3agsn1260534981.ps tmp/3agsn1260534981.png")
> system("convert tmp/4f07w1260534981.ps tmp/4f07w1260534981.png")
> system("convert tmp/5sxbk1260534981.ps tmp/5sxbk1260534981.png")
> system("convert tmp/63faq1260534981.ps tmp/63faq1260534981.png")
> system("convert tmp/74rg71260534981.ps tmp/74rg71260534981.png")
> system("convert tmp/8jg2e1260534981.ps tmp/8jg2e1260534981.png")
> system("convert tmp/92jua1260534981.ps tmp/92jua1260534981.png")
> system("convert tmp/10cyea1260534981.ps tmp/10cyea1260534981.png")
>
>
> proc.time()
user system elapsed
2.354 1.538 7.593