R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
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(68.848
+ ,73.159
+ ,72.616
+ ,60.106
+ ,63.152
+ ,77.056
+ ,68.848
+ ,73.159
+ ,72.616
+ ,60.106
+ ,62.246
+ ,77.056
+ ,68.848
+ ,73.159
+ ,72.616
+ ,60.777
+ ,62.246
+ ,77.056
+ ,68.848
+ ,73.159
+ ,64.513
+ ,60.777
+ ,62.246
+ ,77.056
+ ,68.848
+ ,58.353
+ ,64.513
+ ,60.777
+ ,62.246
+ ,77.056
+ ,56.511
+ ,58.353
+ ,64.513
+ ,60.777
+ ,62.246
+ ,44.554
+ ,56.511
+ ,58.353
+ ,64.513
+ ,60.777
+ ,71.414
+ ,44.554
+ ,56.511
+ ,58.353
+ ,64.513
+ ,65.719
+ ,71.414
+ ,44.554
+ ,56.511
+ ,58.353
+ ,80.997
+ ,65.719
+ ,71.414
+ ,44.554
+ ,56.511
+ ,69.826
+ ,80.997
+ ,65.719
+ ,71.414
+ ,44.554
+ ,65.386
+ ,69.826
+ ,80.997
+ ,65.719
+ ,71.414
+ ,75.589
+ ,65.386
+ ,69.826
+ ,80.997
+ ,65.719
+ ,65.520
+ ,75.589
+ ,65.386
+ ,69.826
+ ,80.997
+ ,59.003
+ ,65.520
+ ,75.589
+ ,65.386
+ ,69.826
+ ,63.961
+ ,59.003
+ ,65.520
+ ,75.589
+ ,65.386
+ ,59.716
+ ,63.961
+ ,59.003
+ ,65.520
+ ,75.589
+ ,57.520
+ ,59.716
+ ,63.961
+ ,59.003
+ ,65.520
+ ,42.886
+ ,57.520
+ ,59.716
+ ,63.961
+ ,59.003
+ ,69.805
+ ,42.886
+ ,57.520
+ ,59.716
+ ,63.961
+ ,64.656
+ ,69.805
+ ,42.886
+ ,57.520
+ ,59.716
+ ,80.353
+ ,64.656
+ ,69.805
+ ,42.886
+ ,57.520
+ ,71.321
+ ,80.353
+ ,64.656
+ ,69.805
+ ,42.886
+ ,76.577
+ ,71.321
+ ,80.353
+ ,64.656
+ ,69.805
+ ,81.580
+ ,76.577
+ ,71.321
+ ,80.353
+ ,64.656
+ ,71.127
+ ,81.580
+ ,76.577
+ ,71.321
+ ,80.353
+ ,63.478
+ ,71.127
+ ,81.580
+ ,76.577
+ ,71.321
+ ,48.152
+ ,63.478
+ ,71.127
+ ,81.580
+ ,76.577
+ ,69.236
+ ,48.152
+ ,63.478
+ ,71.127
+ ,81.580
+ ,57.038
+ ,69.236
+ ,48.152
+ ,63.478
+ ,71.127
+ ,43.621
+ ,57.038
+ ,69.236
+ ,48.152
+ ,63.478
+ ,69.551
+ ,43.621
+ ,57.038
+ ,69.236
+ ,48.152
+ ,72.009
+ ,69.551
+ ,43.621
+ ,57.038
+ ,69.236
+ ,72.140
+ ,72.009
+ ,69.551
+ ,43.621
+ ,57.038
+ ,81.519
+ ,72.140
+ ,72.009
+ ,69.551
+ ,43.621
+ ,73.310
+ ,81.519
+ ,72.140
+ ,72.009
+ ,69.551
+ ,80.406
+ ,73.310
+ ,81.519
+ ,72.140
+ ,72.009
+ ,70.697
+ ,80.406
+ ,73.310
+ ,81.519
+ ,72.140
+ ,59.328
+ ,70.697
+ ,80.406
+ ,73.310
+ ,81.519
+ ,68.281
+ ,59.328
+ ,70.697
+ ,80.406
+ ,73.310
+ ,70.041
+ ,68.281
+ ,59.328
+ ,70.697
+ ,80.406
+ ,51.244
+ ,70.041
+ ,68.281
+ ,59.328
+ ,70.697
+ ,46.538
+ ,51.244
+ ,70.041
+ ,68.281
+ ,59.328
+ ,61.443
+ ,46.538
+ ,51.244
+ ,70.041
+ ,68.281
+ ,62.256
+ ,61.443
+ ,46.538
+ ,51.244
+ ,70.041
+ ,73.117
+ ,62.256
+ ,61.443
+ ,46.538
+ ,51.244
+ ,74.155
+ ,73.117
+ ,62.256
+ ,61.443
+ ,46.538
+ ,65.191
+ ,74.155
+ ,73.117
+ ,62.256
+ ,61.443
+ ,77.889
+ ,65.191
+ ,74.155
+ ,73.117
+ ,62.256
+ ,68.688
+ ,77.889
+ ,65.191
+ ,74.155
+ ,73.117
+ ,59.983
+ ,68.688
+ ,77.889
+ ,65.191
+ ,74.155
+ ,65.470
+ ,59.983
+ ,68.688
+ ,77.889
+ ,65.191
+ ,65.089
+ ,65.470
+ ,59.983
+ ,68.688
+ ,77.889
+ ,54.795
+ ,65.089
+ ,65.470
+ ,59.983
+ ,68.688
+ ,47.123
+ ,54.795
+ ,65.089
+ ,65.470
+ ,59.983)
+ ,dim=c(5
+ ,56)
+ ,dimnames=list(c('Yt'
+ ,'Yt-1'
+ ,'Yt-2'
+ ,'Yt-3'
+ ,'Yt-4')
+ ,1:56))
> y <- array(NA,dim=c(5,56),dimnames=list(c('Yt','Yt-1','Yt-2','Yt-3','Yt-4'),1:56))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Yt Yt-1 Yt-2 Yt-3 Yt-4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 68.848 73.159 72.616 60.106 63.152 1 0 0 0 0 0 0 0 0 0 0
2 77.056 68.848 73.159 72.616 60.106 0 1 0 0 0 0 0 0 0 0 0
3 62.246 77.056 68.848 73.159 72.616 0 0 1 0 0 0 0 0 0 0 0
4 60.777 62.246 77.056 68.848 73.159 0 0 0 1 0 0 0 0 0 0 0
5 64.513 60.777 62.246 77.056 68.848 0 0 0 0 1 0 0 0 0 0 0
6 58.353 64.513 60.777 62.246 77.056 0 0 0 0 0 1 0 0 0 0 0
7 56.511 58.353 64.513 60.777 62.246 0 0 0 0 0 0 1 0 0 0 0
8 44.554 56.511 58.353 64.513 60.777 0 0 0 0 0 0 0 1 0 0 0
9 71.414 44.554 56.511 58.353 64.513 0 0 0 0 0 0 0 0 1 0 0
10 65.719 71.414 44.554 56.511 58.353 0 0 0 0 0 0 0 0 0 1 0
11 80.997 65.719 71.414 44.554 56.511 0 0 0 0 0 0 0 0 0 0 1
12 69.826 80.997 65.719 71.414 44.554 0 0 0 0 0 0 0 0 0 0 0
13 65.386 69.826 80.997 65.719 71.414 1 0 0 0 0 0 0 0 0 0 0
14 75.589 65.386 69.826 80.997 65.719 0 1 0 0 0 0 0 0 0 0 0
15 65.520 75.589 65.386 69.826 80.997 0 0 1 0 0 0 0 0 0 0 0
16 59.003 65.520 75.589 65.386 69.826 0 0 0 1 0 0 0 0 0 0 0
17 63.961 59.003 65.520 75.589 65.386 0 0 0 0 1 0 0 0 0 0 0
18 59.716 63.961 59.003 65.520 75.589 0 0 0 0 0 1 0 0 0 0 0
19 57.520 59.716 63.961 59.003 65.520 0 0 0 0 0 0 1 0 0 0 0
20 42.886 57.520 59.716 63.961 59.003 0 0 0 0 0 0 0 1 0 0 0
21 69.805 42.886 57.520 59.716 63.961 0 0 0 0 0 0 0 0 1 0 0
22 64.656 69.805 42.886 57.520 59.716 0 0 0 0 0 0 0 0 0 1 0
23 80.353 64.656 69.805 42.886 57.520 0 0 0 0 0 0 0 0 0 0 1
24 71.321 80.353 64.656 69.805 42.886 0 0 0 0 0 0 0 0 0 0 0
25 76.577 71.321 80.353 64.656 69.805 1 0 0 0 0 0 0 0 0 0 0
26 81.580 76.577 71.321 80.353 64.656 0 1 0 0 0 0 0 0 0 0 0
27 71.127 81.580 76.577 71.321 80.353 0 0 1 0 0 0 0 0 0 0 0
28 63.478 71.127 81.580 76.577 71.321 0 0 0 1 0 0 0 0 0 0 0
29 48.152 63.478 71.127 81.580 76.577 0 0 0 0 1 0 0 0 0 0 0
30 69.236 48.152 63.478 71.127 81.580 0 0 0 0 0 1 0 0 0 0 0
31 57.038 69.236 48.152 63.478 71.127 0 0 0 0 0 0 1 0 0 0 0
32 43.621 57.038 69.236 48.152 63.478 0 0 0 0 0 0 0 1 0 0 0
33 69.551 43.621 57.038 69.236 48.152 0 0 0 0 0 0 0 0 1 0 0
34 72.009 69.551 43.621 57.038 69.236 0 0 0 0 0 0 0 0 0 1 0
35 72.140 72.009 69.551 43.621 57.038 0 0 0 0 0 0 0 0 0 0 1
36 81.519 72.140 72.009 69.551 43.621 0 0 0 0 0 0 0 0 0 0 0
37 73.310 81.519 72.140 72.009 69.551 1 0 0 0 0 0 0 0 0 0 0
38 80.406 73.310 81.519 72.140 72.009 0 1 0 0 0 0 0 0 0 0 0
39 70.697 80.406 73.310 81.519 72.140 0 0 1 0 0 0 0 0 0 0 0
40 59.328 70.697 80.406 73.310 81.519 0 0 0 1 0 0 0 0 0 0 0
41 68.281 59.328 70.697 80.406 73.310 0 0 0 0 1 0 0 0 0 0 0
42 70.041 68.281 59.328 70.697 80.406 0 0 0 0 0 1 0 0 0 0 0
43 51.244 70.041 68.281 59.328 70.697 0 0 0 0 0 0 1 0 0 0 0
44 46.538 51.244 70.041 68.281 59.328 0 0 0 0 0 0 0 1 0 0 0
45 61.443 46.538 51.244 70.041 68.281 0 0 0 0 0 0 0 0 1 0 0
46 62.256 61.443 46.538 51.244 70.041 0 0 0 0 0 0 0 0 0 1 0
47 73.117 62.256 61.443 46.538 51.244 0 0 0 0 0 0 0 0 0 0 1
48 74.155 73.117 62.256 61.443 46.538 0 0 0 0 0 0 0 0 0 0 0
49 65.191 74.155 73.117 62.256 61.443 1 0 0 0 0 0 0 0 0 0 0
50 77.889 65.191 74.155 73.117 62.256 0 1 0 0 0 0 0 0 0 0 0
51 68.688 77.889 65.191 74.155 73.117 0 0 1 0 0 0 0 0 0 0 0
52 59.983 68.688 77.889 65.191 74.155 0 0 0 1 0 0 0 0 0 0 0
53 65.470 59.983 68.688 77.889 65.191 0 0 0 0 1 0 0 0 0 0 0
54 65.089 65.470 59.983 68.688 77.889 0 0 0 0 0 1 0 0 0 0 0
55 54.795 65.089 65.470 59.983 68.688 0 0 0 0 0 0 1 0 0 0 0
56 47.123 54.795 65.089 65.470 59.983 0 0 0 0 0 0 0 1 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `Yt-1` `Yt-2` `Yt-3` `Yt-4` M1
64.69877 -0.13265 0.16944 0.15321 -0.04421 -4.85820
M2 M3 M4 M5 M6 M7
1.78511 -6.45173 -15.94517 -14.99948 -9.12650 -17.52196
M8 M9 M10 M11
-30.16525 -7.32382 -2.70607 4.85220
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-14.2929 -1.7561 0.1705 2.4811 6.1962
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 64.69877 19.51058 3.316 0.00195 **
`Yt-1` -0.13265 0.15822 -0.838 0.40680
`Yt-2` 0.16944 0.15691 1.080 0.28667
`Yt-3` 0.15321 0.15276 1.003 0.32190
`Yt-4` -0.04421 0.15392 -0.287 0.77544
M1 -4.85820 4.65662 -1.043 0.30308
M2 1.78511 4.84632 0.368 0.71456
M3 -6.45173 5.73676 -1.125 0.26745
M4 -15.94517 5.81441 -2.742 0.00908 **
M5 -14.99948 6.20078 -2.419 0.02021 *
M6 -9.12650 6.97684 -1.308 0.19830
M7 -17.52196 5.41410 -3.236 0.00243 **
M8 -30.16525 5.39063 -5.596 1.75e-06 ***
M9 -7.32382 7.26976 -1.007 0.31978
M10 -2.70607 6.50074 -0.416 0.67944
M11 4.85220 5.12808 0.946 0.34973
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 4.477 on 40 degrees of freedom
Multiple R-squared: 0.8531, Adjusted R-squared: 0.798
F-statistic: 15.48 on 15 and 40 DF, p-value: 3.781e-12
> 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,] 2.177549e-02 0.0435509859 0.97822451
[2,] 5.002049e-03 0.0100040989 0.99499795
[3,] 1.593765e-03 0.0031875304 0.99840623
[4,] 6.233863e-04 0.0012467725 0.99937661
[5,] 3.042103e-04 0.0006084205 0.99969579
[6,] 9.552867e-05 0.0001910573 0.99990447
[7,] 5.566593e-02 0.1113318671 0.94433407
[8,] 2.780233e-02 0.0556046662 0.97219767
[9,] 1.816132e-02 0.0363226381 0.98183868
[10,] 8.159172e-03 0.0163183437 0.99184083
[11,] 8.829269e-01 0.2341462943 0.11707315
[12,] 9.713585e-01 0.0572830100 0.02864150
[13,] 9.491717e-01 0.1016566453 0.05082832
[14,] 9.524056e-01 0.0951888678 0.04759443
[15,] 9.398911e-01 0.1202177024 0.06010885
[16,] 9.234744e-01 0.1530512570 0.07652563
[17,] 8.693217e-01 0.2613565112 0.13067826
[18,] 8.890059e-01 0.2219881999 0.11099410
[19,] 8.128676e-01 0.3742648648 0.18713243
> postscript(file="/var/www/html/rcomp/tmp/1ec7p1290960676.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ec7p1290960676.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3pl6a1290960676.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4pl6a1290960676.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5pl6a1290960676.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 = 56
Frequency = 1
1 2 3 4 5
-0.009661804 -1.160173293 -5.444278027 -0.090596858 3.566129341
6 7 8 9 10
-5.090447825 -0.416750194 0.431619299 4.285188635 -0.428764035
11 12 13 14 15
3.734904900 -4.236235044 -5.828606211 -3.557595029 -0.897111160
16 17 18 19 20
-0.798659447 2.295784319 -4.066550993 1.283111123 -1.327337310
21 22 23 24 25
2.050736717 -1.516903223 3.522695674 -2.473760941 5.761557339
26 27 28 29 30
3.716217307 3.350839239 1.756452863 -14.292858674 2.003966644
31 32 33 34 35
4.304838293 0.350617742 -0.181548321 6.172561810 -3.805834360
36 37 38 39 40
5.460320640 4.101103358 1.964291711 1.393140339 -1.300294992
41 42 43 44 45
5.393965888 6.196174636 -4.176232770 -0.904818296 -6.154377031
46 47 48 49 50
-4.226894551 -3.451766215 1.249675345 -4.024392682 -0.962740696
51 52 53 54 55
1.597409610 0.433098434 3.036979126 0.956857537 -0.994966453
56
1.449918565
> postscript(file="/var/www/html/rcomp/tmp/60c5v1290960676.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 = 56
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.009661804 NA
1 -1.160173293 -0.009661804
2 -5.444278027 -1.160173293
3 -0.090596858 -5.444278027
4 3.566129341 -0.090596858
5 -5.090447825 3.566129341
6 -0.416750194 -5.090447825
7 0.431619299 -0.416750194
8 4.285188635 0.431619299
9 -0.428764035 4.285188635
10 3.734904900 -0.428764035
11 -4.236235044 3.734904900
12 -5.828606211 -4.236235044
13 -3.557595029 -5.828606211
14 -0.897111160 -3.557595029
15 -0.798659447 -0.897111160
16 2.295784319 -0.798659447
17 -4.066550993 2.295784319
18 1.283111123 -4.066550993
19 -1.327337310 1.283111123
20 2.050736717 -1.327337310
21 -1.516903223 2.050736717
22 3.522695674 -1.516903223
23 -2.473760941 3.522695674
24 5.761557339 -2.473760941
25 3.716217307 5.761557339
26 3.350839239 3.716217307
27 1.756452863 3.350839239
28 -14.292858674 1.756452863
29 2.003966644 -14.292858674
30 4.304838293 2.003966644
31 0.350617742 4.304838293
32 -0.181548321 0.350617742
33 6.172561810 -0.181548321
34 -3.805834360 6.172561810
35 5.460320640 -3.805834360
36 4.101103358 5.460320640
37 1.964291711 4.101103358
38 1.393140339 1.964291711
39 -1.300294992 1.393140339
40 5.393965888 -1.300294992
41 6.196174636 5.393965888
42 -4.176232770 6.196174636
43 -0.904818296 -4.176232770
44 -6.154377031 -0.904818296
45 -4.226894551 -6.154377031
46 -3.451766215 -4.226894551
47 1.249675345 -3.451766215
48 -4.024392682 1.249675345
49 -0.962740696 -4.024392682
50 1.597409610 -0.962740696
51 0.433098434 1.597409610
52 3.036979126 0.433098434
53 0.956857537 3.036979126
54 -0.994966453 0.956857537
55 1.449918565 -0.994966453
56 NA 1.449918565
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.16017329 -0.009661804
[2,] -5.44427803 -1.160173293
[3,] -0.09059686 -5.444278027
[4,] 3.56612934 -0.090596858
[5,] -5.09044783 3.566129341
[6,] -0.41675019 -5.090447825
[7,] 0.43161930 -0.416750194
[8,] 4.28518864 0.431619299
[9,] -0.42876403 4.285188635
[10,] 3.73490490 -0.428764035
[11,] -4.23623504 3.734904900
[12,] -5.82860621 -4.236235044
[13,] -3.55759503 -5.828606211
[14,] -0.89711116 -3.557595029
[15,] -0.79865945 -0.897111160
[16,] 2.29578432 -0.798659447
[17,] -4.06655099 2.295784319
[18,] 1.28311112 -4.066550993
[19,] -1.32733731 1.283111123
[20,] 2.05073672 -1.327337310
[21,] -1.51690322 2.050736717
[22,] 3.52269567 -1.516903223
[23,] -2.47376094 3.522695674
[24,] 5.76155734 -2.473760941
[25,] 3.71621731 5.761557339
[26,] 3.35083924 3.716217307
[27,] 1.75645286 3.350839239
[28,] -14.29285867 1.756452863
[29,] 2.00396664 -14.292858674
[30,] 4.30483829 2.003966644
[31,] 0.35061774 4.304838293
[32,] -0.18154832 0.350617742
[33,] 6.17256181 -0.181548321
[34,] -3.80583436 6.172561810
[35,] 5.46032064 -3.805834360
[36,] 4.10110336 5.460320640
[37,] 1.96429171 4.101103358
[38,] 1.39314034 1.964291711
[39,] -1.30029499 1.393140339
[40,] 5.39396589 -1.300294992
[41,] 6.19617464 5.393965888
[42,] -4.17623277 6.196174636
[43,] -0.90481830 -4.176232770
[44,] -6.15437703 -0.904818296
[45,] -4.22689455 -6.154377031
[46,] -3.45176621 -4.226894551
[47,] 1.24967535 -3.451766215
[48,] -4.02439268 1.249675345
[49,] -0.96274070 -4.024392682
[50,] 1.59740961 -0.962740696
[51,] 0.43309843 1.597409610
[52,] 3.03697913 0.433098434
[53,] 0.95685754 3.036979126
[54,] -0.99496645 0.956857537
[55,] 1.44991856 -0.994966453
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.16017329 -0.009661804
2 -5.44427803 -1.160173293
3 -0.09059686 -5.444278027
4 3.56612934 -0.090596858
5 -5.09044783 3.566129341
6 -0.41675019 -5.090447825
7 0.43161930 -0.416750194
8 4.28518864 0.431619299
9 -0.42876403 4.285188635
10 3.73490490 -0.428764035
11 -4.23623504 3.734904900
12 -5.82860621 -4.236235044
13 -3.55759503 -5.828606211
14 -0.89711116 -3.557595029
15 -0.79865945 -0.897111160
16 2.29578432 -0.798659447
17 -4.06655099 2.295784319
18 1.28311112 -4.066550993
19 -1.32733731 1.283111123
20 2.05073672 -1.327337310
21 -1.51690322 2.050736717
22 3.52269567 -1.516903223
23 -2.47376094 3.522695674
24 5.76155734 -2.473760941
25 3.71621731 5.761557339
26 3.35083924 3.716217307
27 1.75645286 3.350839239
28 -14.29285867 1.756452863
29 2.00396664 -14.292858674
30 4.30483829 2.003966644
31 0.35061774 4.304838293
32 -0.18154832 0.350617742
33 6.17256181 -0.181548321
34 -3.80583436 6.172561810
35 5.46032064 -3.805834360
36 4.10110336 5.460320640
37 1.96429171 4.101103358
38 1.39314034 1.964291711
39 -1.30029499 1.393140339
40 5.39396589 -1.300294992
41 6.19617464 5.393965888
42 -4.17623277 6.196174636
43 -0.90481830 -4.176232770
44 -6.15437703 -0.904818296
45 -4.22689455 -6.154377031
46 -3.45176621 -4.226894551
47 1.24967535 -3.451766215
48 -4.02439268 1.249675345
49 -0.96274070 -4.024392682
50 1.59740961 -0.962740696
51 0.43309843 1.597409610
52 3.03697913 0.433098434
53 0.95685754 3.036979126
54 -0.99496645 0.956857537
55 1.44991856 -0.994966453
> 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/7a4ng1290960676.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8a4ng1290960676.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9a4ng1290960676.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ld4j1290960676.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/117v371290960676.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/12sw1v1290960676.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/13oohl1290960676.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/14roxr1290960676.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/15dpex1290960676.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/16ryuo1290960676.tab")
+ }
> try(system("convert tmp/1ec7p1290960676.ps tmp/1ec7p1290960676.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ec7p1290960676.ps tmp/2ec7p1290960676.png",intern=TRUE))
character(0)
> try(system("convert tmp/3pl6a1290960676.ps tmp/3pl6a1290960676.png",intern=TRUE))
character(0)
> try(system("convert tmp/4pl6a1290960676.ps tmp/4pl6a1290960676.png",intern=TRUE))
character(0)
> try(system("convert tmp/5pl6a1290960676.ps tmp/5pl6a1290960676.png",intern=TRUE))
character(0)
> try(system("convert tmp/60c5v1290960676.ps tmp/60c5v1290960676.png",intern=TRUE))
character(0)
> try(system("convert tmp/7a4ng1290960676.ps tmp/7a4ng1290960676.png",intern=TRUE))
character(0)
> try(system("convert tmp/8a4ng1290960676.ps tmp/8a4ng1290960676.png",intern=TRUE))
character(0)
> try(system("convert tmp/9a4ng1290960676.ps tmp/9a4ng1290960676.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ld4j1290960676.ps tmp/10ld4j1290960676.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.339 1.565 5.213