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.
R is a collaborative project with many contributors.
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(20.3
+ ,18
+ ,13.2
+ ,15.7
+ ,12.6
+ ,12.8
+ ,23
+ ,20.3
+ ,13.2
+ ,15.7
+ ,8
+ ,20
+ ,12.8
+ ,20.3
+ ,13.2
+ ,0.9
+ ,20
+ ,8
+ ,12.8
+ ,20.3
+ ,3.6
+ ,15
+ ,0.9
+ ,8
+ ,12.8
+ ,14.1
+ ,17
+ ,3.6
+ ,0.9
+ ,8
+ ,21.7
+ ,16
+ ,14.1
+ ,3.6
+ ,0.9
+ ,24.5
+ ,15
+ ,21.7
+ ,14.1
+ ,3.6
+ ,18.9
+ ,10
+ ,24.5
+ ,21.7
+ ,14.1
+ ,13.9
+ ,13
+ ,18.9
+ ,24.5
+ ,21.7
+ ,11
+ ,10
+ ,13.9
+ ,18.9
+ ,24.5
+ ,5.8
+ ,19
+ ,11
+ ,13.9
+ ,18.9
+ ,15.5
+ ,21
+ ,5.8
+ ,11
+ ,13.9
+ ,22.4
+ ,17
+ ,15.5
+ ,5.8
+ ,11
+ ,31.7
+ ,16
+ ,22.4
+ ,15.5
+ ,5.8
+ ,30.3
+ ,17
+ ,31.7
+ ,22.4
+ ,15.5
+ ,31.4
+ ,14
+ ,30.3
+ ,31.7
+ ,22.4
+ ,20.2
+ ,18
+ ,31.4
+ ,30.3
+ ,31.7
+ ,19.7
+ ,17
+ ,20.2
+ ,31.4
+ ,30.3
+ ,10.8
+ ,14
+ ,19.7
+ ,20.2
+ ,31.4
+ ,13.2
+ ,15
+ ,10.8
+ ,19.7
+ ,20.2
+ ,15.1
+ ,16
+ ,13.2
+ ,10.8
+ ,19.7
+ ,15.6
+ ,11
+ ,15.1
+ ,13.2
+ ,10.8
+ ,15.5
+ ,15
+ ,15.6
+ ,15.1
+ ,13.2
+ ,12.7
+ ,13
+ ,15.5
+ ,15.6
+ ,15.1
+ ,10.9
+ ,17
+ ,12.7
+ ,15.5
+ ,15.6
+ ,10
+ ,16
+ ,10.9
+ ,12.7
+ ,15.5
+ ,9.1
+ ,9
+ ,10
+ ,10.9
+ ,12.7
+ ,10.3
+ ,17
+ ,9.1
+ ,10
+ ,10.9
+ ,16.9
+ ,15
+ ,10.3
+ ,9.1
+ ,10
+ ,22
+ ,12
+ ,16.9
+ ,10.3
+ ,9.1
+ ,27.6
+ ,12
+ ,22
+ ,16.9
+ ,10.3
+ ,28.9
+ ,12
+ ,27.6
+ ,22
+ ,16.9
+ ,31
+ ,12
+ ,28.9
+ ,27.6
+ ,22
+ ,32.9
+ ,4
+ ,31
+ ,28.9
+ ,27.6
+ ,38.1
+ ,7
+ ,32.9
+ ,31
+ ,28.9
+ ,28.8
+ ,4
+ ,38.1
+ ,32.9
+ ,31
+ ,29
+ ,3
+ ,28.8
+ ,38.1
+ ,32.9
+ ,21.8
+ ,3
+ ,29
+ ,28.8
+ ,38.1
+ ,28.8
+ ,0
+ ,21.8
+ ,29
+ ,28.8
+ ,25.6
+ ,5
+ ,28.8
+ ,21.8
+ ,29
+ ,28.2
+ ,3
+ ,25.6
+ ,28.8
+ ,21.8
+ ,20.2
+ ,4
+ ,28.2
+ ,25.6
+ ,28.8
+ ,17.9
+ ,3
+ ,20.2
+ ,28.2
+ ,25.6
+ ,16.3
+ ,10
+ ,17.9
+ ,20.2
+ ,28.2
+ ,13.2
+ ,4
+ ,16.3
+ ,17.9
+ ,20.2
+ ,8.1
+ ,1
+ ,13.2
+ ,16.3
+ ,17.9
+ ,4.5
+ ,1
+ ,8.1
+ ,13.2
+ ,16.3
+ ,-0.1
+ ,8
+ ,4.5
+ ,8.1
+ ,13.2
+ ,0
+ ,5
+ ,-0.1
+ ,4.5
+ ,8.1
+ ,2.3
+ ,4
+ ,0
+ ,-0.1
+ ,4.5
+ ,2.8
+ ,0
+ ,2.3
+ ,0
+ ,-0.1
+ ,2.9
+ ,2
+ ,2.8
+ ,2.3
+ ,0
+ ,0.1
+ ,7
+ ,2.9
+ ,2.8
+ ,2.3
+ ,3.5
+ ,6
+ ,0.1
+ ,2.9
+ ,2.8
+ ,8.6
+ ,9
+ ,3.5
+ ,0.1
+ ,2.9
+ ,13.8
+ ,10
+ ,8.6
+ ,3.5
+ ,0.1)
+ ,dim=c(5
+ ,57)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Yt-1'
+ ,'Yt-2'
+ ,'Yt-3')
+ ,1:57))
> y <- array(NA,dim=c(5,57),dimnames=list(c('Y','X','Yt-1','Yt-2','Yt-3'),1:57))
> 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 Yt-1 Yt-2 Yt-3 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 20.3 18 13.2 15.7 12.6 1 0 0 0 0 0 0 0 0 0 0 1
2 12.8 23 20.3 13.2 15.7 0 1 0 0 0 0 0 0 0 0 0 2
3 8.0 20 12.8 20.3 13.2 0 0 1 0 0 0 0 0 0 0 0 3
4 0.9 20 8.0 12.8 20.3 0 0 0 1 0 0 0 0 0 0 0 4
5 3.6 15 0.9 8.0 12.8 0 0 0 0 1 0 0 0 0 0 0 5
6 14.1 17 3.6 0.9 8.0 0 0 0 0 0 1 0 0 0 0 0 6
7 21.7 16 14.1 3.6 0.9 0 0 0 0 0 0 1 0 0 0 0 7
8 24.5 15 21.7 14.1 3.6 0 0 0 0 0 0 0 1 0 0 0 8
9 18.9 10 24.5 21.7 14.1 0 0 0 0 0 0 0 0 1 0 0 9
10 13.9 13 18.9 24.5 21.7 0 0 0 0 0 0 0 0 0 1 0 10
11 11.0 10 13.9 18.9 24.5 0 0 0 0 0 0 0 0 0 0 1 11
12 5.8 19 11.0 13.9 18.9 0 0 0 0 0 0 0 0 0 0 0 12
13 15.5 21 5.8 11.0 13.9 1 0 0 0 0 0 0 0 0 0 0 13
14 22.4 17 15.5 5.8 11.0 0 1 0 0 0 0 0 0 0 0 0 14
15 31.7 16 22.4 15.5 5.8 0 0 1 0 0 0 0 0 0 0 0 15
16 30.3 17 31.7 22.4 15.5 0 0 0 1 0 0 0 0 0 0 0 16
17 31.4 14 30.3 31.7 22.4 0 0 0 0 1 0 0 0 0 0 0 17
18 20.2 18 31.4 30.3 31.7 0 0 0 0 0 1 0 0 0 0 0 18
19 19.7 17 20.2 31.4 30.3 0 0 0 0 0 0 1 0 0 0 0 19
20 10.8 14 19.7 20.2 31.4 0 0 0 0 0 0 0 1 0 0 0 20
21 13.2 15 10.8 19.7 20.2 0 0 0 0 0 0 0 0 1 0 0 21
22 15.1 16 13.2 10.8 19.7 0 0 0 0 0 0 0 0 0 1 0 22
23 15.6 11 15.1 13.2 10.8 0 0 0 0 0 0 0 0 0 0 1 23
24 15.5 15 15.6 15.1 13.2 0 0 0 0 0 0 0 0 0 0 0 24
25 12.7 13 15.5 15.6 15.1 1 0 0 0 0 0 0 0 0 0 0 25
26 10.9 17 12.7 15.5 15.6 0 1 0 0 0 0 0 0 0 0 0 26
27 10.0 16 10.9 12.7 15.5 0 0 1 0 0 0 0 0 0 0 0 27
28 9.1 9 10.0 10.9 12.7 0 0 0 1 0 0 0 0 0 0 0 28
29 10.3 17 9.1 10.0 10.9 0 0 0 0 1 0 0 0 0 0 0 29
30 16.9 15 10.3 9.1 10.0 0 0 0 0 0 1 0 0 0 0 0 30
31 22.0 12 16.9 10.3 9.1 0 0 0 0 0 0 1 0 0 0 0 31
32 27.6 12 22.0 16.9 10.3 0 0 0 0 0 0 0 1 0 0 0 32
33 28.9 12 27.6 22.0 16.9 0 0 0 0 0 0 0 0 1 0 0 33
34 31.0 12 28.9 27.6 22.0 0 0 0 0 0 0 0 0 0 1 0 34
35 32.9 4 31.0 28.9 27.6 0 0 0 0 0 0 0 0 0 0 1 35
36 38.1 7 32.9 31.0 28.9 0 0 0 0 0 0 0 0 0 0 0 36
37 28.8 4 38.1 32.9 31.0 1 0 0 0 0 0 0 0 0 0 0 37
38 29.0 3 28.8 38.1 32.9 0 1 0 0 0 0 0 0 0 0 0 38
39 21.8 3 29.0 28.8 38.1 0 0 1 0 0 0 0 0 0 0 0 39
40 28.8 0 21.8 29.0 28.8 0 0 0 1 0 0 0 0 0 0 0 40
41 25.6 5 28.8 21.8 29.0 0 0 0 0 1 0 0 0 0 0 0 41
42 28.2 3 25.6 28.8 21.8 0 0 0 0 0 1 0 0 0 0 0 42
43 20.2 4 28.2 25.6 28.8 0 0 0 0 0 0 1 0 0 0 0 43
44 17.9 3 20.2 28.2 25.6 0 0 0 0 0 0 0 1 0 0 0 44
45 16.3 10 17.9 20.2 28.2 0 0 0 0 0 0 0 0 1 0 0 45
46 13.2 4 16.3 17.9 20.2 0 0 0 0 0 0 0 0 0 1 0 46
47 8.1 1 13.2 16.3 17.9 0 0 0 0 0 0 0 0 0 0 1 47
48 4.5 1 8.1 13.2 16.3 0 0 0 0 0 0 0 0 0 0 0 48
49 -0.1 8 4.5 8.1 13.2 1 0 0 0 0 0 0 0 0 0 0 49
50 0.0 5 -0.1 4.5 8.1 0 1 0 0 0 0 0 0 0 0 0 50
51 2.3 4 0.0 -0.1 4.5 0 0 1 0 0 0 0 0 0 0 0 51
52 2.8 0 2.3 0.0 -0.1 0 0 0 1 0 0 0 0 0 0 0 52
53 2.9 2 2.8 2.3 0.0 0 0 0 0 1 0 0 0 0 0 0 53
54 0.1 7 2.9 2.8 2.3 0 0 0 0 0 1 0 0 0 0 0 54
55 3.5 6 0.1 2.9 2.8 0 0 0 0 0 0 1 0 0 0 0 55
56 8.6 9 3.5 0.1 2.9 0 0 0 0 0 0 0 1 0 0 0 56
57 13.8 10 8.6 3.5 0.1 0 0 0 0 0 0 0 0 1 0 0 57
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X `Yt-1` `Yt-2` `Yt-3` M1
4.449860 -0.001978 0.994282 0.147066 -0.382512 0.261350
M2 M3 M4 M5 M6 M7
-0.168477 -0.471951 -0.510605 0.146132 0.886063 1.087922
M8 M9 M10 M11 t
0.032078 0.147371 0.201265 -0.309510 -0.018558
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-8.3172 -3.4512 -0.1450 2.6251 10.6791
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.449860 6.102328 0.729 0.4701
X -0.001978 0.228791 -0.009 0.9931
`Yt-1` 0.994282 0.146636 6.781 3.79e-08 ***
`Yt-2` 0.147066 0.216018 0.681 0.4999
`Yt-3` -0.382512 0.149498 -2.559 0.0144 *
M1 0.261350 3.492971 0.075 0.9407
M2 -0.168477 3.498967 -0.048 0.9618
M3 -0.471951 3.495366 -0.135 0.8933
M4 -0.510605 3.535994 -0.144 0.8859
M5 0.146132 3.498611 0.042 0.9669
M6 0.886063 3.505570 0.253 0.8017
M7 1.087922 3.509969 0.310 0.7582
M8 0.032078 3.519304 0.009 0.9928
M9 0.147371 3.532918 0.042 0.9669
M10 0.201265 3.673779 0.055 0.9566
M11 -0.309510 3.792425 -0.082 0.9354
t -0.018558 0.083933 -0.221 0.8261
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.188 on 40 degrees of freedom
Multiple R-squared: 0.805, Adjusted R-squared: 0.7271
F-statistic: 10.32 on 16 and 40 DF, p-value: 1.33e-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,] 0.4841799 0.9683598 0.51582009
[2,] 0.4067433 0.8134866 0.59325672
[3,] 0.3117678 0.6235355 0.68823223
[4,] 0.6262221 0.7475558 0.37377791
[5,] 0.6127515 0.7744970 0.38724848
[6,] 0.9192124 0.1615752 0.08078759
[7,] 0.9002589 0.1994822 0.09974110
[8,] 0.8806730 0.2386540 0.11932699
[9,] 0.8797371 0.2405259 0.12026293
[10,] 0.9493075 0.1013849 0.05069246
[11,] 0.9081120 0.1837760 0.09188801
[12,] 0.8744643 0.2510715 0.12553575
[13,] 0.8069661 0.3860677 0.19303386
[14,] 0.7110645 0.5778711 0.28893554
[15,] 0.8415181 0.3169637 0.15848186
[16,] 0.7639485 0.4721031 0.23605154
[17,] 0.8540689 0.2918622 0.14593111
[18,] 0.7532625 0.4934751 0.24673755
> postscript(file="/var/www/html/rcomp/tmp/1j7d71258747183.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/24z941258747183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3mefc1258747183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4wzxn1258747183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/528jt1258747183.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 = 57
Frequency = 1
1 2 3 4 5 6
5.02913985 -7.51853690 -6.54577305 -4.99717621 1.95123628 8.25736898
7 8 9 10 11 12
2.11921427 -2.07631981 -7.66826374 -4.63437973 -0.14496714 -4.14143426
13 14 15 16 17 18
9.00392955 6.35532351 5.69922602 -2.19279944 0.92669954 -8.31721924
19 20 21 22 23 24
1.43617304 -3.83031503 3.11343840 3.71143637 -0.91557287 -1.15715100
25 26 27 28 29 30
-3.45123137 -1.80498241 -0.22168725 -0.98978253 -0.07344453 4.39618537
31 32 33 34 35 36
2.22394807 3.31588766 0.72571301 2.62505071 4.90144629 8.11571869
37 38 39 40 41 42
-6.07942554 3.77583318 0.05578524 10.67912027 1.02623543 2.29905922
43 44 45 46 47 48
-5.31920183 -0.19893160 2.57608855 -1.70210735 -3.84090628 -2.81713343
49 50 51 52 53 54
-4.50241249 -0.80763738 1.01244904 -2.49936209 -3.83072672 -6.63539433
55 56 57
-0.46013354 2.78967878 1.25302379
> postscript(file="/var/www/html/rcomp/tmp/65nai1258747183.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 = 57
Frequency = 1
lag(myerror, k = 1) myerror
0 5.02913985 NA
1 -7.51853690 5.02913985
2 -6.54577305 -7.51853690
3 -4.99717621 -6.54577305
4 1.95123628 -4.99717621
5 8.25736898 1.95123628
6 2.11921427 8.25736898
7 -2.07631981 2.11921427
8 -7.66826374 -2.07631981
9 -4.63437973 -7.66826374
10 -0.14496714 -4.63437973
11 -4.14143426 -0.14496714
12 9.00392955 -4.14143426
13 6.35532351 9.00392955
14 5.69922602 6.35532351
15 -2.19279944 5.69922602
16 0.92669954 -2.19279944
17 -8.31721924 0.92669954
18 1.43617304 -8.31721924
19 -3.83031503 1.43617304
20 3.11343840 -3.83031503
21 3.71143637 3.11343840
22 -0.91557287 3.71143637
23 -1.15715100 -0.91557287
24 -3.45123137 -1.15715100
25 -1.80498241 -3.45123137
26 -0.22168725 -1.80498241
27 -0.98978253 -0.22168725
28 -0.07344453 -0.98978253
29 4.39618537 -0.07344453
30 2.22394807 4.39618537
31 3.31588766 2.22394807
32 0.72571301 3.31588766
33 2.62505071 0.72571301
34 4.90144629 2.62505071
35 8.11571869 4.90144629
36 -6.07942554 8.11571869
37 3.77583318 -6.07942554
38 0.05578524 3.77583318
39 10.67912027 0.05578524
40 1.02623543 10.67912027
41 2.29905922 1.02623543
42 -5.31920183 2.29905922
43 -0.19893160 -5.31920183
44 2.57608855 -0.19893160
45 -1.70210735 2.57608855
46 -3.84090628 -1.70210735
47 -2.81713343 -3.84090628
48 -4.50241249 -2.81713343
49 -0.80763738 -4.50241249
50 1.01244904 -0.80763738
51 -2.49936209 1.01244904
52 -3.83072672 -2.49936209
53 -6.63539433 -3.83072672
54 -0.46013354 -6.63539433
55 2.78967878 -0.46013354
56 1.25302379 2.78967878
57 NA 1.25302379
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7.51853690 5.02913985
[2,] -6.54577305 -7.51853690
[3,] -4.99717621 -6.54577305
[4,] 1.95123628 -4.99717621
[5,] 8.25736898 1.95123628
[6,] 2.11921427 8.25736898
[7,] -2.07631981 2.11921427
[8,] -7.66826374 -2.07631981
[9,] -4.63437973 -7.66826374
[10,] -0.14496714 -4.63437973
[11,] -4.14143426 -0.14496714
[12,] 9.00392955 -4.14143426
[13,] 6.35532351 9.00392955
[14,] 5.69922602 6.35532351
[15,] -2.19279944 5.69922602
[16,] 0.92669954 -2.19279944
[17,] -8.31721924 0.92669954
[18,] 1.43617304 -8.31721924
[19,] -3.83031503 1.43617304
[20,] 3.11343840 -3.83031503
[21,] 3.71143637 3.11343840
[22,] -0.91557287 3.71143637
[23,] -1.15715100 -0.91557287
[24,] -3.45123137 -1.15715100
[25,] -1.80498241 -3.45123137
[26,] -0.22168725 -1.80498241
[27,] -0.98978253 -0.22168725
[28,] -0.07344453 -0.98978253
[29,] 4.39618537 -0.07344453
[30,] 2.22394807 4.39618537
[31,] 3.31588766 2.22394807
[32,] 0.72571301 3.31588766
[33,] 2.62505071 0.72571301
[34,] 4.90144629 2.62505071
[35,] 8.11571869 4.90144629
[36,] -6.07942554 8.11571869
[37,] 3.77583318 -6.07942554
[38,] 0.05578524 3.77583318
[39,] 10.67912027 0.05578524
[40,] 1.02623543 10.67912027
[41,] 2.29905922 1.02623543
[42,] -5.31920183 2.29905922
[43,] -0.19893160 -5.31920183
[44,] 2.57608855 -0.19893160
[45,] -1.70210735 2.57608855
[46,] -3.84090628 -1.70210735
[47,] -2.81713343 -3.84090628
[48,] -4.50241249 -2.81713343
[49,] -0.80763738 -4.50241249
[50,] 1.01244904 -0.80763738
[51,] -2.49936209 1.01244904
[52,] -3.83072672 -2.49936209
[53,] -6.63539433 -3.83072672
[54,] -0.46013354 -6.63539433
[55,] 2.78967878 -0.46013354
[56,] 1.25302379 2.78967878
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7.51853690 5.02913985
2 -6.54577305 -7.51853690
3 -4.99717621 -6.54577305
4 1.95123628 -4.99717621
5 8.25736898 1.95123628
6 2.11921427 8.25736898
7 -2.07631981 2.11921427
8 -7.66826374 -2.07631981
9 -4.63437973 -7.66826374
10 -0.14496714 -4.63437973
11 -4.14143426 -0.14496714
12 9.00392955 -4.14143426
13 6.35532351 9.00392955
14 5.69922602 6.35532351
15 -2.19279944 5.69922602
16 0.92669954 -2.19279944
17 -8.31721924 0.92669954
18 1.43617304 -8.31721924
19 -3.83031503 1.43617304
20 3.11343840 -3.83031503
21 3.71143637 3.11343840
22 -0.91557287 3.71143637
23 -1.15715100 -0.91557287
24 -3.45123137 -1.15715100
25 -1.80498241 -3.45123137
26 -0.22168725 -1.80498241
27 -0.98978253 -0.22168725
28 -0.07344453 -0.98978253
29 4.39618537 -0.07344453
30 2.22394807 4.39618537
31 3.31588766 2.22394807
32 0.72571301 3.31588766
33 2.62505071 0.72571301
34 4.90144629 2.62505071
35 8.11571869 4.90144629
36 -6.07942554 8.11571869
37 3.77583318 -6.07942554
38 0.05578524 3.77583318
39 10.67912027 0.05578524
40 1.02623543 10.67912027
41 2.29905922 1.02623543
42 -5.31920183 2.29905922
43 -0.19893160 -5.31920183
44 2.57608855 -0.19893160
45 -1.70210735 2.57608855
46 -3.84090628 -1.70210735
47 -2.81713343 -3.84090628
48 -4.50241249 -2.81713343
49 -0.80763738 -4.50241249
50 1.01244904 -0.80763738
51 -2.49936209 1.01244904
52 -3.83072672 -2.49936209
53 -6.63539433 -3.83072672
54 -0.46013354 -6.63539433
55 2.78967878 -0.46013354
56 1.25302379 2.78967878
> 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/7o7u21258747183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8dpfa1258747183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9x8ql1258747183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10j5381258747183.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11s5bu1258747183.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/12okmf1258747183.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/136hw51258747183.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/14q05m1258747183.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/15vy331258747183.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/16x1s01258747183.tab")
+ }
> system("convert tmp/1j7d71258747183.ps tmp/1j7d71258747183.png")
> system("convert tmp/24z941258747183.ps tmp/24z941258747183.png")
> system("convert tmp/3mefc1258747183.ps tmp/3mefc1258747183.png")
> system("convert tmp/4wzxn1258747183.ps tmp/4wzxn1258747183.png")
> system("convert tmp/528jt1258747183.ps tmp/528jt1258747183.png")
> system("convert tmp/65nai1258747183.ps tmp/65nai1258747183.png")
> system("convert tmp/7o7u21258747183.ps tmp/7o7u21258747183.png")
> system("convert tmp/8dpfa1258747183.ps tmp/8dpfa1258747183.png")
> system("convert tmp/9x8ql1258747183.ps tmp/9x8ql1258747183.png")
> system("convert tmp/10j5381258747183.ps tmp/10j5381258747183.png")
>
>
> proc.time()
user system elapsed
2.352 1.540 4.132