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(1.43,0,0,0,0,1.43,0,0,0,0,1.43,0,0,0,0,1.43,0,0,0,0,1.43,0,0,0,0,1.43,0,0,0,0,1.44,0,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.48,1,0,0,0,1.57,1,1,0,0,1.58,1,1,0,0,1.58,1,1,0,0,1.58,1,1,0,0,1.58,1,1,0,0,1.59,1,1,1,1,1.6,1,1,1,2,1.6,1,1,1,3,1.61,1,1,1,4,1.61,1,1,1,5,1.61,1,1,1,6,1.62,1,1,1,7,1.63,1,1,1,8,1.63,1,1,1,9,1.64,1,1,1,10,1.64,1,1,1,11,1.64,1,1,1,12,1.64,1,1,1,13,1.64,1,1,1,14,1.65,1,1,1,15,1.65,1,1,1,16,1.65,1,1,1,17,1.65,1,1,1,18),dim=c(5,60),dimnames=list(c('Broodprijzen','Dummy2','Dummy3','Dummy1','Dummy4'),1:60))
> y <- array(NA,dim=c(5,60),dimnames=list(c('Broodprijzen','Dummy2','Dummy3','Dummy1','Dummy4'),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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 1.43 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
2 1.43 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
3 1.43 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
4 1.43 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
5 1.43 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
6 1.43 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
7 1.44 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
8 1.48 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0
9 1.48 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0
10 1.48 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0
11 1.48 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1
12 1.48 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
13 1.48 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0
14 1.48 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0
15 1.48 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0
16 1.48 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0
17 1.48 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0
18 1.48 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0
19 1.48 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0
20 1.48 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0
21 1.48 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0
22 1.48 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0
23 1.48 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1
24 1.48 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
25 1.48 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0
26 1.48 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0
27 1.48 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0
28 1.48 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0
29 1.48 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0
30 1.48 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0
31 1.48 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0
32 1.48 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0
33 1.48 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0
34 1.48 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0
35 1.48 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1
36 1.48 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
37 1.48 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0
38 1.57 1 1 0 0 0 1 0 0 0 0 0 0 0 0 0
39 1.58 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0
40 1.58 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0
41 1.58 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0
42 1.58 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0
43 1.59 1 1 1 1 0 0 0 0 0 0 1 0 0 0 0
44 1.60 1 1 1 2 0 0 0 0 0 0 0 1 0 0 0
45 1.60 1 1 1 3 0 0 0 0 0 0 0 0 1 0 0
46 1.61 1 1 1 4 0 0 0 0 0 0 0 0 0 1 0
47 1.61 1 1 1 5 0 0 0 0 0 0 0 0 0 0 1
48 1.61 1 1 1 6 0 0 0 0 0 0 0 0 0 0 0
49 1.62 1 1 1 7 1 0 0 0 0 0 0 0 0 0 0
50 1.63 1 1 1 8 0 1 0 0 0 0 0 0 0 0 0
51 1.63 1 1 1 9 0 0 1 0 0 0 0 0 0 0 0
52 1.64 1 1 1 10 0 0 0 1 0 0 0 0 0 0 0
53 1.64 1 1 1 11 0 0 0 0 1 0 0 0 0 0 0
54 1.64 1 1 1 12 0 0 0 0 0 1 0 0 0 0 0
55 1.64 1 1 1 13 0 0 0 0 0 0 1 0 0 0 0
56 1.64 1 1 1 14 0 0 0 0 0 0 0 1 0 0 0
57 1.65 1 1 1 15 0 0 0 0 0 0 0 0 1 0 0
58 1.65 1 1 1 16 0 0 0 0 0 0 0 0 0 1 0
59 1.65 1 1 1 17 0 0 0 0 0 0 0 0 0 0 1
60 1.65 1 1 1 18 0 0 0 0 0 0 0 0 0 0 0
t
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
10 10
11 11
12 12
13 13
14 14
15 15
16 16
17 17
18 18
19 19
20 20
21 21
22 22
23 23
24 24
25 25
26 26
27 27
28 28
29 29
30 30
31 31
32 32
33 33
34 34
35 35
36 36
37 37
38 38
39 39
40 40
41 41
42 42
43 43
44 44
45 45
46 46
47 47
48 48
49 49
50 50
51 51
52 52
53 53
54 54
55 55
56 56
57 57
58 58
59 59
60 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy2 Dummy3 Dummy1 Dummy4 M1
1.427e+00 4.932e-02 9.612e-02 1.705e-02 3.591e-03 2.945e-03
M2 M3 M4 M5 M6 M7
2.982e-03 4.242e-03 5.502e-03 4.763e-03 4.023e-03 3.154e-03
M8 M9 M10 M11 t
1.832e-03 2.374e-03 2.916e-03 1.458e-03 2.154e-05
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.0075614 -0.0015442 -0.0001552 0.0013757 0.0092972
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.427e+00 2.198e-03 649.376 < 2e-16 ***
Dummy2 4.932e-02 2.075e-03 23.774 < 2e-16 ***
Dummy3 9.612e-02 2.234e-03 43.031 < 2e-16 ***
Dummy1 1.705e-02 2.458e-03 6.938 1.58e-08 ***
Dummy4 3.591e-03 1.765e-04 20.344 < 2e-16 ***
M1 2.945e-03 2.236e-03 1.317 0.1948
M2 2.982e-03 2.277e-03 1.310 0.1972
M3 4.242e-03 2.269e-03 1.869 0.0684 .
M4 5.502e-03 2.264e-03 2.430 0.0193 *
M5 4.763e-03 2.261e-03 2.107 0.0410 *
M6 4.023e-03 2.260e-03 1.780 0.0821 .
M7 3.154e-03 2.244e-03 1.405 0.1671
M8 1.832e-03 2.220e-03 0.825 0.4139
M9 2.374e-03 2.211e-03 1.074 0.2889
M10 2.916e-03 2.204e-03 1.323 0.1928
M11 1.458e-03 2.200e-03 0.663 0.5110
t 2.154e-05 7.385e-05 0.292 0.7720
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.003476 on 43 degrees of freedom
Multiple R-squared: 0.9984, Adjusted R-squared: 0.9979
F-statistic: 1720 on 16 and 43 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,] 0.601040967 0.797918067 0.3989590
[2,] 0.427733940 0.855467880 0.5722661
[3,] 0.278565378 0.557130756 0.7214346
[4,] 0.182266517 0.364533034 0.8177335
[5,] 0.170728889 0.341457779 0.8292711
[6,] 0.160741096 0.321482193 0.8392589
[7,] 0.111576047 0.223152094 0.8884240
[8,] 0.063862096 0.127724192 0.9361379
[9,] 0.038593391 0.077186782 0.9614066
[10,] 0.022793319 0.045586638 0.9772067
[11,] 0.014270104 0.028540208 0.9857299
[12,] 0.027367526 0.054735053 0.9726325
[13,] 0.017305303 0.034610606 0.9826947
[14,] 0.009155725 0.018311450 0.9908443
[15,] 0.004029209 0.008058417 0.9959708
[16,] 0.001807654 0.003615308 0.9981923
[17,] 0.002893078 0.005786156 0.9971069
[18,] 0.001105783 0.002211565 0.9988942
[19,] 0.001360217 0.002720434 0.9986398
[20,] 0.015829533 0.031659066 0.9841705
[21,] 0.010009794 0.020019587 0.9899902
> postscript(file="/var/www/html/rcomp/tmp/1xfhm1260526148.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2wwbs1260526148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/39h7y1260526148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ciq31260526148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5qhmx1260526148.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
-3.647148e-04 -4.229667e-04 -1.704733e-03 -2.986500e-03 -2.268267e-03
6 7 8 9 10
-1.550034e-03 9.297216e-03 1.277254e-03 7.137210e-04 1.501875e-04
11 12 13 14 15
1.586654e-03 3.023120e-03 5.628708e-05 -1.964749e-06 -1.283732e-03
16 17 18 19 20
-2.565498e-03 -1.847265e-03 -1.129032e-03 -2.817825e-04 1.018791e-03
21 22 23 24 25
4.552574e-04 -1.082761e-04 1.328190e-03 2.764657e-03 -2.021765e-04
26 27 28 29 30
-2.604283e-04 -1.542195e-03 -2.823962e-03 -2.105729e-03 -1.387495e-03
31 32 33 34 35
-5.402461e-04 7.603273e-04 1.967938e-04 -3.667397e-04 1.069727e-03
36 37 38 39 40
2.506193e-03 -4.606401e-04 -6.636466e-03 2.081767e-03 8.000000e-04
41 42 43 44 45
1.518233e-03 2.236466e-03 -7.561364e-03 1.480429e-04 -4.006657e-03
46 47 48 49 50
1.838643e-03 -3.160564e-04 -2.470756e-03 9.712443e-04 7.321826e-03
51 52 53 54 55
2.448893e-03 7.575960e-03 4.703027e-03 1.830094e-03 -9.138227e-04
56 57 58 59 60
-3.204416e-03 2.640885e-03 -1.513815e-03 -3.668515e-03 -5.823215e-03
> postscript(file="/var/www/html/rcomp/tmp/6wwah1260526148.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 -3.647148e-04 NA
1 -4.229667e-04 -3.647148e-04
2 -1.704733e-03 -4.229667e-04
3 -2.986500e-03 -1.704733e-03
4 -2.268267e-03 -2.986500e-03
5 -1.550034e-03 -2.268267e-03
6 9.297216e-03 -1.550034e-03
7 1.277254e-03 9.297216e-03
8 7.137210e-04 1.277254e-03
9 1.501875e-04 7.137210e-04
10 1.586654e-03 1.501875e-04
11 3.023120e-03 1.586654e-03
12 5.628708e-05 3.023120e-03
13 -1.964749e-06 5.628708e-05
14 -1.283732e-03 -1.964749e-06
15 -2.565498e-03 -1.283732e-03
16 -1.847265e-03 -2.565498e-03
17 -1.129032e-03 -1.847265e-03
18 -2.817825e-04 -1.129032e-03
19 1.018791e-03 -2.817825e-04
20 4.552574e-04 1.018791e-03
21 -1.082761e-04 4.552574e-04
22 1.328190e-03 -1.082761e-04
23 2.764657e-03 1.328190e-03
24 -2.021765e-04 2.764657e-03
25 -2.604283e-04 -2.021765e-04
26 -1.542195e-03 -2.604283e-04
27 -2.823962e-03 -1.542195e-03
28 -2.105729e-03 -2.823962e-03
29 -1.387495e-03 -2.105729e-03
30 -5.402461e-04 -1.387495e-03
31 7.603273e-04 -5.402461e-04
32 1.967938e-04 7.603273e-04
33 -3.667397e-04 1.967938e-04
34 1.069727e-03 -3.667397e-04
35 2.506193e-03 1.069727e-03
36 -4.606401e-04 2.506193e-03
37 -6.636466e-03 -4.606401e-04
38 2.081767e-03 -6.636466e-03
39 8.000000e-04 2.081767e-03
40 1.518233e-03 8.000000e-04
41 2.236466e-03 1.518233e-03
42 -7.561364e-03 2.236466e-03
43 1.480429e-04 -7.561364e-03
44 -4.006657e-03 1.480429e-04
45 1.838643e-03 -4.006657e-03
46 -3.160564e-04 1.838643e-03
47 -2.470756e-03 -3.160564e-04
48 9.712443e-04 -2.470756e-03
49 7.321826e-03 9.712443e-04
50 2.448893e-03 7.321826e-03
51 7.575960e-03 2.448893e-03
52 4.703027e-03 7.575960e-03
53 1.830094e-03 4.703027e-03
54 -9.138227e-04 1.830094e-03
55 -3.204416e-03 -9.138227e-04
56 2.640885e-03 -3.204416e-03
57 -1.513815e-03 2.640885e-03
58 -3.668515e-03 -1.513815e-03
59 -5.823215e-03 -3.668515e-03
60 NA -5.823215e-03
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.229667e-04 -3.647148e-04
[2,] -1.704733e-03 -4.229667e-04
[3,] -2.986500e-03 -1.704733e-03
[4,] -2.268267e-03 -2.986500e-03
[5,] -1.550034e-03 -2.268267e-03
[6,] 9.297216e-03 -1.550034e-03
[7,] 1.277254e-03 9.297216e-03
[8,] 7.137210e-04 1.277254e-03
[9,] 1.501875e-04 7.137210e-04
[10,] 1.586654e-03 1.501875e-04
[11,] 3.023120e-03 1.586654e-03
[12,] 5.628708e-05 3.023120e-03
[13,] -1.964749e-06 5.628708e-05
[14,] -1.283732e-03 -1.964749e-06
[15,] -2.565498e-03 -1.283732e-03
[16,] -1.847265e-03 -2.565498e-03
[17,] -1.129032e-03 -1.847265e-03
[18,] -2.817825e-04 -1.129032e-03
[19,] 1.018791e-03 -2.817825e-04
[20,] 4.552574e-04 1.018791e-03
[21,] -1.082761e-04 4.552574e-04
[22,] 1.328190e-03 -1.082761e-04
[23,] 2.764657e-03 1.328190e-03
[24,] -2.021765e-04 2.764657e-03
[25,] -2.604283e-04 -2.021765e-04
[26,] -1.542195e-03 -2.604283e-04
[27,] -2.823962e-03 -1.542195e-03
[28,] -2.105729e-03 -2.823962e-03
[29,] -1.387495e-03 -2.105729e-03
[30,] -5.402461e-04 -1.387495e-03
[31,] 7.603273e-04 -5.402461e-04
[32,] 1.967938e-04 7.603273e-04
[33,] -3.667397e-04 1.967938e-04
[34,] 1.069727e-03 -3.667397e-04
[35,] 2.506193e-03 1.069727e-03
[36,] -4.606401e-04 2.506193e-03
[37,] -6.636466e-03 -4.606401e-04
[38,] 2.081767e-03 -6.636466e-03
[39,] 8.000000e-04 2.081767e-03
[40,] 1.518233e-03 8.000000e-04
[41,] 2.236466e-03 1.518233e-03
[42,] -7.561364e-03 2.236466e-03
[43,] 1.480429e-04 -7.561364e-03
[44,] -4.006657e-03 1.480429e-04
[45,] 1.838643e-03 -4.006657e-03
[46,] -3.160564e-04 1.838643e-03
[47,] -2.470756e-03 -3.160564e-04
[48,] 9.712443e-04 -2.470756e-03
[49,] 7.321826e-03 9.712443e-04
[50,] 2.448893e-03 7.321826e-03
[51,] 7.575960e-03 2.448893e-03
[52,] 4.703027e-03 7.575960e-03
[53,] 1.830094e-03 4.703027e-03
[54,] -9.138227e-04 1.830094e-03
[55,] -3.204416e-03 -9.138227e-04
[56,] 2.640885e-03 -3.204416e-03
[57,] -1.513815e-03 2.640885e-03
[58,] -3.668515e-03 -1.513815e-03
[59,] -5.823215e-03 -3.668515e-03
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.229667e-04 -3.647148e-04
2 -1.704733e-03 -4.229667e-04
3 -2.986500e-03 -1.704733e-03
4 -2.268267e-03 -2.986500e-03
5 -1.550034e-03 -2.268267e-03
6 9.297216e-03 -1.550034e-03
7 1.277254e-03 9.297216e-03
8 7.137210e-04 1.277254e-03
9 1.501875e-04 7.137210e-04
10 1.586654e-03 1.501875e-04
11 3.023120e-03 1.586654e-03
12 5.628708e-05 3.023120e-03
13 -1.964749e-06 5.628708e-05
14 -1.283732e-03 -1.964749e-06
15 -2.565498e-03 -1.283732e-03
16 -1.847265e-03 -2.565498e-03
17 -1.129032e-03 -1.847265e-03
18 -2.817825e-04 -1.129032e-03
19 1.018791e-03 -2.817825e-04
20 4.552574e-04 1.018791e-03
21 -1.082761e-04 4.552574e-04
22 1.328190e-03 -1.082761e-04
23 2.764657e-03 1.328190e-03
24 -2.021765e-04 2.764657e-03
25 -2.604283e-04 -2.021765e-04
26 -1.542195e-03 -2.604283e-04
27 -2.823962e-03 -1.542195e-03
28 -2.105729e-03 -2.823962e-03
29 -1.387495e-03 -2.105729e-03
30 -5.402461e-04 -1.387495e-03
31 7.603273e-04 -5.402461e-04
32 1.967938e-04 7.603273e-04
33 -3.667397e-04 1.967938e-04
34 1.069727e-03 -3.667397e-04
35 2.506193e-03 1.069727e-03
36 -4.606401e-04 2.506193e-03
37 -6.636466e-03 -4.606401e-04
38 2.081767e-03 -6.636466e-03
39 8.000000e-04 2.081767e-03
40 1.518233e-03 8.000000e-04
41 2.236466e-03 1.518233e-03
42 -7.561364e-03 2.236466e-03
43 1.480429e-04 -7.561364e-03
44 -4.006657e-03 1.480429e-04
45 1.838643e-03 -4.006657e-03
46 -3.160564e-04 1.838643e-03
47 -2.470756e-03 -3.160564e-04
48 9.712443e-04 -2.470756e-03
49 7.321826e-03 9.712443e-04
50 2.448893e-03 7.321826e-03
51 7.575960e-03 2.448893e-03
52 4.703027e-03 7.575960e-03
53 1.830094e-03 4.703027e-03
54 -9.138227e-04 1.830094e-03
55 -3.204416e-03 -9.138227e-04
56 2.640885e-03 -3.204416e-03
57 -1.513815e-03 2.640885e-03
58 -3.668515e-03 -1.513815e-03
59 -5.823215e-03 -3.668515e-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/7uv0f1260526148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8kdox1260526148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/903lb1260526148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ljf01260526148.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/118znr1260526148.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/12knzi1260526148.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/13qcdm1260526148.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/14l0nm1260526148.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/15idci1260526148.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/16p67n1260526148.tab")
+ }
>
> system("convert tmp/1xfhm1260526148.ps tmp/1xfhm1260526148.png")
> system("convert tmp/2wwbs1260526148.ps tmp/2wwbs1260526148.png")
> system("convert tmp/39h7y1260526148.ps tmp/39h7y1260526148.png")
> system("convert tmp/4ciq31260526148.ps tmp/4ciq31260526148.png")
> system("convert tmp/5qhmx1260526148.ps tmp/5qhmx1260526148.png")
> system("convert tmp/6wwah1260526148.ps tmp/6wwah1260526148.png")
> system("convert tmp/7uv0f1260526148.ps tmp/7uv0f1260526148.png")
> system("convert tmp/8kdox1260526148.ps tmp/8kdox1260526148.png")
> system("convert tmp/903lb1260526148.ps tmp/903lb1260526148.png")
> system("convert tmp/10ljf01260526148.ps tmp/10ljf01260526148.png")
>
>
> proc.time()
user system elapsed
2.253 1.493 3.154