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(2.0
+ ,0.0
+ ,2.0
+ ,1.7
+ ,1.6
+ ,1.4
+ ,2.1
+ ,0.0
+ ,2.0
+ ,2.0
+ ,1.7
+ ,1.6
+ ,2.5
+ ,0.0
+ ,2.1
+ ,2.0
+ ,2.0
+ ,1.7
+ ,2.5
+ ,0.0
+ ,2.5
+ ,2.1
+ ,2.0
+ ,2.0
+ ,2.6
+ ,0.0
+ ,2.5
+ ,2.5
+ ,2.1
+ ,2.0
+ ,2.7
+ ,0.0
+ ,2.6
+ ,2.5
+ ,2.5
+ ,2.1
+ ,3.7
+ ,0.0
+ ,2.7
+ ,2.6
+ ,2.5
+ ,2.5
+ ,4.0
+ ,0.0
+ ,3.7
+ ,2.7
+ ,2.6
+ ,2.5
+ ,5.0
+ ,0.0
+ ,4.0
+ ,3.7
+ ,2.7
+ ,2.6
+ ,5.1
+ ,0.0
+ ,5.0
+ ,4.0
+ ,3.7
+ ,2.7
+ ,5.1
+ ,0.0
+ ,5.1
+ ,5.0
+ ,4.0
+ ,3.7
+ ,5.0
+ ,0.0
+ ,5.1
+ ,5.1
+ ,5.0
+ ,4.0
+ ,5.1
+ ,0.0
+ ,5.0
+ ,5.1
+ ,5.1
+ ,5.0
+ ,4.7
+ ,0.0
+ ,5.1
+ ,5.0
+ ,5.1
+ ,5.1
+ ,4.5
+ ,0.0
+ ,4.7
+ ,5.1
+ ,5.0
+ ,5.1
+ ,4.5
+ ,0.0
+ ,4.5
+ ,4.7
+ ,5.1
+ ,5.0
+ ,4.6
+ ,0.0
+ ,4.5
+ ,4.5
+ ,4.7
+ ,5.1
+ ,4.6
+ ,0.0
+ ,4.6
+ ,4.5
+ ,4.5
+ ,4.7
+ ,4.6
+ ,0.0
+ ,4.6
+ ,4.6
+ ,4.5
+ ,4.5
+ ,4.6
+ ,0.0
+ ,4.6
+ ,4.6
+ ,4.6
+ ,4.5
+ ,5.3
+ ,0.0
+ ,4.6
+ ,4.6
+ ,4.6
+ ,4.6
+ ,5.4
+ ,0.0
+ ,5.3
+ ,4.6
+ ,4.6
+ ,4.6
+ ,5.3
+ ,0.0
+ ,5.4
+ ,5.3
+ ,4.6
+ ,4.6
+ ,5.2
+ ,0.0
+ ,5.3
+ ,5.4
+ ,5.3
+ ,4.6
+ ,5.0
+ ,0.0
+ ,5.2
+ ,5.3
+ ,5.4
+ ,5.3
+ ,4.2
+ ,0.0
+ ,5.0
+ ,5.2
+ ,5.3
+ ,5.4
+ ,4.3
+ ,0.0
+ ,4.2
+ ,5.0
+ ,5.2
+ ,5.3
+ ,4.3
+ ,0.0
+ ,4.3
+ ,4.2
+ ,5.0
+ ,5.2
+ ,4.3
+ ,0.0
+ ,4.3
+ ,4.3
+ ,4.2
+ ,5.0
+ ,4.0
+ ,0.0
+ ,4.3
+ ,4.3
+ ,4.3
+ ,4.2
+ ,4.0
+ ,0.0
+ ,4.0
+ ,4.3
+ ,4.3
+ ,4.3
+ ,4.1
+ ,0.0
+ ,4.0
+ ,4.0
+ ,4.3
+ ,4.3
+ ,4.4
+ ,0.0
+ ,4.1
+ ,4.0
+ ,4.0
+ ,4.3
+ ,3.6
+ ,0.0
+ ,4.4
+ ,4.1
+ ,4.0
+ ,4.0
+ ,3.7
+ ,0.0
+ ,3.6
+ ,4.4
+ ,4.1
+ ,4.0
+ ,3.8
+ ,0.0
+ ,3.7
+ ,3.6
+ ,4.4
+ ,4.1
+ ,3.3
+ ,0.0
+ ,3.8
+ ,3.7
+ ,3.6
+ ,4.4
+ ,3.3
+ ,0.0
+ ,3.3
+ ,3.8
+ ,3.7
+ ,3.6
+ ,3.3
+ ,0.0
+ ,3.3
+ ,3.3
+ ,3.8
+ ,3.7
+ ,3.5
+ ,0.0
+ ,3.3
+ ,3.3
+ ,3.3
+ ,3.8
+ ,3.3
+ ,0.0
+ ,3.5
+ ,3.3
+ ,3.3
+ ,3.3
+ ,3.3
+ ,0.0
+ ,3.3
+ ,3.5
+ ,3.3
+ ,3.3
+ ,3.4
+ ,0.0
+ ,3.3
+ ,3.3
+ ,3.5
+ ,3.3
+ ,3.4
+ ,0.0
+ ,3.4
+ ,3.3
+ ,3.3
+ ,3.5
+ ,5.2
+ ,0.0
+ ,3.4
+ ,3.4
+ ,3.3
+ ,3.3
+ ,5.3
+ ,0.0
+ ,5.2
+ ,3.4
+ ,3.4
+ ,3.3
+ ,4.8
+ ,1.0
+ ,5.3
+ ,5.2
+ ,3.4
+ ,3.4
+ ,5.0
+ ,1.0
+ ,4.8
+ ,5.3
+ ,5.2
+ ,3.4
+ ,4.6
+ ,1.0
+ ,5.0
+ ,4.8
+ ,5.3
+ ,5.2
+ ,4.6
+ ,1.0
+ ,4.6
+ ,5.0
+ ,4.8
+ ,5.3
+ ,3.5
+ ,1.0
+ ,4.6
+ ,4.6
+ ,5.0
+ ,4.8
+ ,3.5
+ ,1.0
+ ,3.5
+ ,4.6
+ ,4.6
+ ,5.0)
+ ,dim=c(6
+ ,52)
+ ,dimnames=list(c('IndGez'
+ ,'InvlMex'
+ ,'Yt-1'
+ ,'Yt-2'
+ ,'Yt-3'
+ ,'Yt-4')
+ ,1:52))
> y <- array(NA,dim=c(6,52),dimnames=list(c('IndGez','InvlMex','Yt-1','Yt-2','Yt-3','Yt-4'),1:52))
> 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
IndGez InvlMex Yt-1 Yt-2 Yt-3 Yt-4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 2.0 0 2.0 1.7 1.6 1.4 1 0 0 0 0 0 0 0 0 0 0 1
2 2.1 0 2.0 2.0 1.7 1.6 0 1 0 0 0 0 0 0 0 0 0 2
3 2.5 0 2.1 2.0 2.0 1.7 0 0 1 0 0 0 0 0 0 0 0 3
4 2.5 0 2.5 2.1 2.0 2.0 0 0 0 1 0 0 0 0 0 0 0 4
5 2.6 0 2.5 2.5 2.1 2.0 0 0 0 0 1 0 0 0 0 0 0 5
6 2.7 0 2.6 2.5 2.5 2.1 0 0 0 0 0 1 0 0 0 0 0 6
7 3.7 0 2.7 2.6 2.5 2.5 0 0 0 0 0 0 1 0 0 0 0 7
8 4.0 0 3.7 2.7 2.6 2.5 0 0 0 0 0 0 0 1 0 0 0 8
9 5.0 0 4.0 3.7 2.7 2.6 0 0 0 0 0 0 0 0 1 0 0 9
10 5.1 0 5.0 4.0 3.7 2.7 0 0 0 0 0 0 0 0 0 1 0 10
11 5.1 0 5.1 5.0 4.0 3.7 0 0 0 0 0 0 0 0 0 0 1 11
12 5.0 0 5.1 5.1 5.0 4.0 0 0 0 0 0 0 0 0 0 0 0 12
13 5.1 0 5.0 5.1 5.1 5.0 1 0 0 0 0 0 0 0 0 0 0 13
14 4.7 0 5.1 5.0 5.1 5.1 0 1 0 0 0 0 0 0 0 0 0 14
15 4.5 0 4.7 5.1 5.0 5.1 0 0 1 0 0 0 0 0 0 0 0 15
16 4.5 0 4.5 4.7 5.1 5.0 0 0 0 1 0 0 0 0 0 0 0 16
17 4.6 0 4.5 4.5 4.7 5.1 0 0 0 0 1 0 0 0 0 0 0 17
18 4.6 0 4.6 4.5 4.5 4.7 0 0 0 0 0 1 0 0 0 0 0 18
19 4.6 0 4.6 4.6 4.5 4.5 0 0 0 0 0 0 1 0 0 0 0 19
20 4.6 0 4.6 4.6 4.6 4.5 0 0 0 0 0 0 0 1 0 0 0 20
21 5.3 0 4.6 4.6 4.6 4.6 0 0 0 0 0 0 0 0 1 0 0 21
22 5.4 0 5.3 4.6 4.6 4.6 0 0 0 0 0 0 0 0 0 1 0 22
23 5.3 0 5.4 5.3 4.6 4.6 0 0 0 0 0 0 0 0 0 0 1 23
24 5.2 0 5.3 5.4 5.3 4.6 0 0 0 0 0 0 0 0 0 0 0 24
25 5.0 0 5.2 5.3 5.4 5.3 1 0 0 0 0 0 0 0 0 0 0 25
26 4.2 0 5.0 5.2 5.3 5.4 0 1 0 0 0 0 0 0 0 0 0 26
27 4.3 0 4.2 5.0 5.2 5.3 0 0 1 0 0 0 0 0 0 0 0 27
28 4.3 0 4.3 4.2 5.0 5.2 0 0 0 1 0 0 0 0 0 0 0 28
29 4.3 0 4.3 4.3 4.2 5.0 0 0 0 0 1 0 0 0 0 0 0 29
30 4.0 0 4.3 4.3 4.3 4.2 0 0 0 0 0 1 0 0 0 0 0 30
31 4.0 0 4.0 4.3 4.3 4.3 0 0 0 0 0 0 1 0 0 0 0 31
32 4.1 0 4.0 4.0 4.3 4.3 0 0 0 0 0 0 0 1 0 0 0 32
33 4.4 0 4.1 4.0 4.0 4.3 0 0 0 0 0 0 0 0 1 0 0 33
34 3.6 0 4.4 4.1 4.0 4.0 0 0 0 0 0 0 0 0 0 1 0 34
35 3.7 0 3.6 4.4 4.1 4.0 0 0 0 0 0 0 0 0 0 0 1 35
36 3.8 0 3.7 3.6 4.4 4.1 0 0 0 0 0 0 0 0 0 0 0 36
37 3.3 0 3.8 3.7 3.6 4.4 1 0 0 0 0 0 0 0 0 0 0 37
38 3.3 0 3.3 3.8 3.7 3.6 0 1 0 0 0 0 0 0 0 0 0 38
39 3.3 0 3.3 3.3 3.8 3.7 0 0 1 0 0 0 0 0 0 0 0 39
40 3.5 0 3.3 3.3 3.3 3.8 0 0 0 1 0 0 0 0 0 0 0 40
41 3.3 0 3.5 3.3 3.3 3.3 0 0 0 0 1 0 0 0 0 0 0 41
42 3.3 0 3.3 3.5 3.3 3.3 0 0 0 0 0 1 0 0 0 0 0 42
43 3.4 0 3.3 3.3 3.5 3.3 0 0 0 0 0 0 1 0 0 0 0 43
44 3.4 0 3.4 3.3 3.3 3.5 0 0 0 0 0 0 0 1 0 0 0 44
45 5.2 0 3.4 3.4 3.3 3.3 0 0 0 0 0 0 0 0 1 0 0 45
46 5.3 0 5.2 3.4 3.4 3.3 0 0 0 0 0 0 0 0 0 1 0 46
47 4.8 1 5.3 5.2 3.4 3.4 0 0 0 0 0 0 0 0 0 0 1 47
48 5.0 1 4.8 5.3 5.2 3.4 0 0 0 0 0 0 0 0 0 0 0 48
49 4.6 1 5.0 4.8 5.3 5.2 1 0 0 0 0 0 0 0 0 0 0 49
50 4.6 1 4.6 5.0 4.8 5.3 0 1 0 0 0 0 0 0 0 0 0 50
51 3.5 1 4.6 4.6 5.0 4.8 0 0 1 0 0 0 0 0 0 0 0 51
52 3.5 1 3.5 4.6 4.6 5.0 0 0 0 1 0 0 0 0 0 0 0 52
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) InvlMex `Yt-1` `Yt-2` `Yt-3` `Yt-4`
0.680001 -0.109917 0.829084 0.040628 0.102037 -0.109824
M1 M2 M3 M4 M5 M6
-0.199445 -0.252552 -0.236224 -0.022686 -0.074551 -0.161684
M7 M8 M9 M10 M11 t
0.160658 0.042935 0.906708 -0.040783 -0.050514 -0.002753
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.72902 -0.15564 0.02206 0.13708 0.80584
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.680001 0.419206 1.622 0.11402
InvlMex -0.109917 0.225445 -0.488 0.62899
`Yt-1` 0.829084 0.169489 4.892 2.37e-05 ***
`Yt-2` 0.040628 0.247835 0.164 0.87076
`Yt-3` 0.102037 0.258943 0.394 0.69600
`Yt-4` -0.109824 0.189244 -0.580 0.56552
M1 -0.199445 0.307899 -0.648 0.52149
M2 -0.252552 0.310744 -0.813 0.42203
M3 -0.236224 0.295468 -0.799 0.42956
M4 -0.022686 0.330934 -0.069 0.94575
M5 -0.074551 0.344289 -0.217 0.82986
M6 -0.161684 0.302225 -0.535 0.59615
M7 0.160658 0.303948 0.529 0.60054
M8 0.042935 0.309732 0.139 0.89057
M9 0.906708 0.318013 2.851 0.00735 **
M10 -0.040783 0.322610 -0.126 0.90015
M11 -0.050514 0.349013 -0.145 0.88578
t -0.002753 0.004832 -0.570 0.57263
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.3424 on 34 degrees of freedom
Multiple R-squared: 0.9034, Adjusted R-squared: 0.8551
F-statistic: 18.7 on 17 and 34 DF, p-value: 1.683e-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,] 0.236818770 0.47363754 0.7631812
[2,] 0.163536222 0.32707244 0.8364638
[3,] 0.157996965 0.31599393 0.8420030
[4,] 0.121213101 0.24242620 0.8787869
[5,] 0.070886125 0.14177225 0.9291139
[6,] 0.121426373 0.24285275 0.8785736
[7,] 0.079069832 0.15813966 0.9209302
[8,] 0.044777221 0.08955444 0.9552228
[9,] 0.028842586 0.05768517 0.9711574
[10,] 0.011151380 0.02230276 0.9888486
[11,] 0.006911011 0.01382202 0.9930890
> postscript(file="/var/www/html/rcomp/tmp/10s101258733609.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2orun1258733609.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/32inb1258733609.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4rqik1258733609.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5c5xs1258733609.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 = 52
Frequency = 1
1 2 3 4 5 6
-0.214545121 -0.059112476 0.224775251 -0.288758817 -0.160596187 -0.083451202
7 8 9 10 11 12
0.553918084 0.131043138 -0.018552088 0.099364859 0.067525388 -0.153388439
13 14 15 16 17 18
0.331337697 -0.080665556 0.043533749 -0.006369306 0.208171051 0.191626243
19 20 21 22 23 24
-0.153990514 -0.043718746 -0.193757105 0.276128067 0.077264051 -0.063077484
25 26 27 28 29 30
0.092764233 -0.460310139 0.296728722 0.044962804 0.155182373 -0.152994785
31 32 33 34 35 36
-0.212876352 0.019787519 -0.593530520 -0.729021798 0.024337199 0.006541298
37 38 39 40 41 42
-0.263655634 0.104620506 0.112138030 0.163354046 -0.202757237 0.044819744
43 44 45 46 47 48
-0.187051218 -0.107111911 0.805839713 0.353528872 -0.169126639 0.209924625
49 50 51 52
0.054098826 0.495467666 -0.677175751 0.086811273
> postscript(file="/var/www/html/rcomp/tmp/6blim1258733609.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 = 52
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.214545121 NA
1 -0.059112476 -0.214545121
2 0.224775251 -0.059112476
3 -0.288758817 0.224775251
4 -0.160596187 -0.288758817
5 -0.083451202 -0.160596187
6 0.553918084 -0.083451202
7 0.131043138 0.553918084
8 -0.018552088 0.131043138
9 0.099364859 -0.018552088
10 0.067525388 0.099364859
11 -0.153388439 0.067525388
12 0.331337697 -0.153388439
13 -0.080665556 0.331337697
14 0.043533749 -0.080665556
15 -0.006369306 0.043533749
16 0.208171051 -0.006369306
17 0.191626243 0.208171051
18 -0.153990514 0.191626243
19 -0.043718746 -0.153990514
20 -0.193757105 -0.043718746
21 0.276128067 -0.193757105
22 0.077264051 0.276128067
23 -0.063077484 0.077264051
24 0.092764233 -0.063077484
25 -0.460310139 0.092764233
26 0.296728722 -0.460310139
27 0.044962804 0.296728722
28 0.155182373 0.044962804
29 -0.152994785 0.155182373
30 -0.212876352 -0.152994785
31 0.019787519 -0.212876352
32 -0.593530520 0.019787519
33 -0.729021798 -0.593530520
34 0.024337199 -0.729021798
35 0.006541298 0.024337199
36 -0.263655634 0.006541298
37 0.104620506 -0.263655634
38 0.112138030 0.104620506
39 0.163354046 0.112138030
40 -0.202757237 0.163354046
41 0.044819744 -0.202757237
42 -0.187051218 0.044819744
43 -0.107111911 -0.187051218
44 0.805839713 -0.107111911
45 0.353528872 0.805839713
46 -0.169126639 0.353528872
47 0.209924625 -0.169126639
48 0.054098826 0.209924625
49 0.495467666 0.054098826
50 -0.677175751 0.495467666
51 0.086811273 -0.677175751
52 NA 0.086811273
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.059112476 -0.214545121
[2,] 0.224775251 -0.059112476
[3,] -0.288758817 0.224775251
[4,] -0.160596187 -0.288758817
[5,] -0.083451202 -0.160596187
[6,] 0.553918084 -0.083451202
[7,] 0.131043138 0.553918084
[8,] -0.018552088 0.131043138
[9,] 0.099364859 -0.018552088
[10,] 0.067525388 0.099364859
[11,] -0.153388439 0.067525388
[12,] 0.331337697 -0.153388439
[13,] -0.080665556 0.331337697
[14,] 0.043533749 -0.080665556
[15,] -0.006369306 0.043533749
[16,] 0.208171051 -0.006369306
[17,] 0.191626243 0.208171051
[18,] -0.153990514 0.191626243
[19,] -0.043718746 -0.153990514
[20,] -0.193757105 -0.043718746
[21,] 0.276128067 -0.193757105
[22,] 0.077264051 0.276128067
[23,] -0.063077484 0.077264051
[24,] 0.092764233 -0.063077484
[25,] -0.460310139 0.092764233
[26,] 0.296728722 -0.460310139
[27,] 0.044962804 0.296728722
[28,] 0.155182373 0.044962804
[29,] -0.152994785 0.155182373
[30,] -0.212876352 -0.152994785
[31,] 0.019787519 -0.212876352
[32,] -0.593530520 0.019787519
[33,] -0.729021798 -0.593530520
[34,] 0.024337199 -0.729021798
[35,] 0.006541298 0.024337199
[36,] -0.263655634 0.006541298
[37,] 0.104620506 -0.263655634
[38,] 0.112138030 0.104620506
[39,] 0.163354046 0.112138030
[40,] -0.202757237 0.163354046
[41,] 0.044819744 -0.202757237
[42,] -0.187051218 0.044819744
[43,] -0.107111911 -0.187051218
[44,] 0.805839713 -0.107111911
[45,] 0.353528872 0.805839713
[46,] -0.169126639 0.353528872
[47,] 0.209924625 -0.169126639
[48,] 0.054098826 0.209924625
[49,] 0.495467666 0.054098826
[50,] -0.677175751 0.495467666
[51,] 0.086811273 -0.677175751
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.059112476 -0.214545121
2 0.224775251 -0.059112476
3 -0.288758817 0.224775251
4 -0.160596187 -0.288758817
5 -0.083451202 -0.160596187
6 0.553918084 -0.083451202
7 0.131043138 0.553918084
8 -0.018552088 0.131043138
9 0.099364859 -0.018552088
10 0.067525388 0.099364859
11 -0.153388439 0.067525388
12 0.331337697 -0.153388439
13 -0.080665556 0.331337697
14 0.043533749 -0.080665556
15 -0.006369306 0.043533749
16 0.208171051 -0.006369306
17 0.191626243 0.208171051
18 -0.153990514 0.191626243
19 -0.043718746 -0.153990514
20 -0.193757105 -0.043718746
21 0.276128067 -0.193757105
22 0.077264051 0.276128067
23 -0.063077484 0.077264051
24 0.092764233 -0.063077484
25 -0.460310139 0.092764233
26 0.296728722 -0.460310139
27 0.044962804 0.296728722
28 0.155182373 0.044962804
29 -0.152994785 0.155182373
30 -0.212876352 -0.152994785
31 0.019787519 -0.212876352
32 -0.593530520 0.019787519
33 -0.729021798 -0.593530520
34 0.024337199 -0.729021798
35 0.006541298 0.024337199
36 -0.263655634 0.006541298
37 0.104620506 -0.263655634
38 0.112138030 0.104620506
39 0.163354046 0.112138030
40 -0.202757237 0.163354046
41 0.044819744 -0.202757237
42 -0.187051218 0.044819744
43 -0.107111911 -0.187051218
44 0.805839713 -0.107111911
45 0.353528872 0.805839713
46 -0.169126639 0.353528872
47 0.209924625 -0.169126639
48 0.054098826 0.209924625
49 0.495467666 0.054098826
50 -0.677175751 0.495467666
51 0.086811273 -0.677175751
> 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/74be11258733609.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8t5bm1258733609.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9qo611258733609.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10j90z1258733609.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11btuk1258733609.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/12c27j1258733609.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/13ijp71258733609.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/14dryp1258733609.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/15s8kg1258733609.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/16y9ap1258733609.tab")
+ }
>
> system("convert tmp/10s101258733609.ps tmp/10s101258733609.png")
> system("convert tmp/2orun1258733609.ps tmp/2orun1258733609.png")
> system("convert tmp/32inb1258733609.ps tmp/32inb1258733609.png")
> system("convert tmp/4rqik1258733609.ps tmp/4rqik1258733609.png")
> system("convert tmp/5c5xs1258733609.ps tmp/5c5xs1258733609.png")
> system("convert tmp/6blim1258733609.ps tmp/6blim1258733609.png")
> system("convert tmp/74be11258733609.ps tmp/74be11258733609.png")
> system("convert tmp/8t5bm1258733609.ps tmp/8t5bm1258733609.png")
> system("convert tmp/9qo611258733609.ps tmp/9qo611258733609.png")
> system("convert tmp/10j90z1258733609.ps tmp/10j90z1258733609.png")
>
>
> proc.time()
user system elapsed
2.337 1.569 5.318