R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.
> x <- array(list(8.3
+ ,101.6
+ ,8.2
+ ,8.7
+ ,9.3
+ ,9.3
+ ,8.5
+ ,94.6
+ ,8.3
+ ,8.2
+ ,8.7
+ ,9.3
+ ,8.6
+ ,95.9
+ ,8.5
+ ,8.3
+ ,8.2
+ ,8.7
+ ,8.5
+ ,104.7
+ ,8.6
+ ,8.5
+ ,8.3
+ ,8.2
+ ,8.2
+ ,102.8
+ ,8.5
+ ,8.6
+ ,8.5
+ ,8.3
+ ,8.1
+ ,98.1
+ ,8.2
+ ,8.5
+ ,8.6
+ ,8.5
+ ,7.9
+ ,113.9
+ ,8.1
+ ,8.2
+ ,8.5
+ ,8.6
+ ,8.6
+ ,80.9
+ ,7.9
+ ,8.1
+ ,8.2
+ ,8.5
+ ,8.7
+ ,95.7
+ ,8.6
+ ,7.9
+ ,8.1
+ ,8.2
+ ,8.7
+ ,113.2
+ ,8.7
+ ,8.6
+ ,7.9
+ ,8.1
+ ,8.5
+ ,105.9
+ ,8.7
+ ,8.7
+ ,8.6
+ ,7.9
+ ,8.4
+ ,108.8
+ ,8.5
+ ,8.7
+ ,8.7
+ ,8.6
+ ,8.5
+ ,102.3
+ ,8.4
+ ,8.5
+ ,8.7
+ ,8.7
+ ,8.7
+ ,99
+ ,8.5
+ ,8.4
+ ,8.5
+ ,8.7
+ ,8.7
+ ,100.7
+ ,8.7
+ ,8.5
+ ,8.4
+ ,8.5
+ ,8.6
+ ,115.5
+ ,8.7
+ ,8.7
+ ,8.5
+ ,8.4
+ ,8.5
+ ,100.7
+ ,8.6
+ ,8.7
+ ,8.7
+ ,8.5
+ ,8.3
+ ,109.9
+ ,8.5
+ ,8.6
+ ,8.7
+ ,8.7
+ ,8
+ ,114.6
+ ,8.3
+ ,8.5
+ ,8.6
+ ,8.7
+ ,8.2
+ ,85.4
+ ,8
+ ,8.3
+ ,8.5
+ ,8.6
+ ,8.1
+ ,100.5
+ ,8.2
+ ,8
+ ,8.3
+ ,8.5
+ ,8.1
+ ,114.8
+ ,8.1
+ ,8.2
+ ,8
+ ,8.3
+ ,8
+ ,116.5
+ ,8.1
+ ,8.1
+ ,8.2
+ ,8
+ ,7.9
+ ,112.9
+ ,8
+ ,8.1
+ ,8.1
+ ,8.2
+ ,7.9
+ ,102
+ ,7.9
+ ,8
+ ,8.1
+ ,8.1
+ ,8
+ ,106
+ ,7.9
+ ,7.9
+ ,8
+ ,8.1
+ ,8
+ ,105.3
+ ,8
+ ,7.9
+ ,7.9
+ ,8
+ ,7.9
+ ,118.8
+ ,8
+ ,8
+ ,7.9
+ ,7.9
+ ,8
+ ,106.1
+ ,7.9
+ ,8
+ ,8
+ ,7.9
+ ,7.7
+ ,109.3
+ ,8
+ ,7.9
+ ,8
+ ,8
+ ,7.2
+ ,117.2
+ ,7.7
+ ,8
+ ,7.9
+ ,8
+ ,7.5
+ ,92.5
+ ,7.2
+ ,7.7
+ ,8
+ ,7.9
+ ,7.3
+ ,104.2
+ ,7.5
+ ,7.2
+ ,7.7
+ ,8
+ ,7
+ ,112.5
+ ,7.3
+ ,7.5
+ ,7.2
+ ,7.7
+ ,7
+ ,122.4
+ ,7
+ ,7.3
+ ,7.5
+ ,7.2
+ ,7
+ ,113.3
+ ,7
+ ,7
+ ,7.3
+ ,7.5
+ ,7.2
+ ,100
+ ,7
+ ,7
+ ,7
+ ,7.3
+ ,7.3
+ ,110.7
+ ,7.2
+ ,7
+ ,7
+ ,7
+ ,7.1
+ ,112.8
+ ,7.3
+ ,7.2
+ ,7
+ ,7
+ ,6.8
+ ,109.8
+ ,7.1
+ ,7.3
+ ,7.2
+ ,7
+ ,6.4
+ ,117.3
+ ,6.8
+ ,7.1
+ ,7.3
+ ,7.2
+ ,6.1
+ ,109.1
+ ,6.4
+ ,6.8
+ ,7.1
+ ,7.3
+ ,6.5
+ ,115.9
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.1
+ ,7.7
+ ,96
+ ,6.5
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.9
+ ,99.8
+ ,7.7
+ ,6.5
+ ,6.1
+ ,6.4
+ ,7.5
+ ,116.8
+ ,7.9
+ ,7.7
+ ,6.5
+ ,6.1
+ ,6.9
+ ,115.7
+ ,7.5
+ ,7.9
+ ,7.7
+ ,6.5
+ ,6.6
+ ,99.4
+ ,6.9
+ ,7.5
+ ,7.9
+ ,7.7
+ ,6.9
+ ,94.3
+ ,6.6
+ ,6.9
+ ,7.5
+ ,7.9
+ ,7.7
+ ,91
+ ,6.9
+ ,6.6
+ ,6.9
+ ,7.5
+ ,8
+ ,93.2
+ ,7.7
+ ,6.9
+ ,6.6
+ ,6.9
+ ,8
+ ,103.1
+ ,8
+ ,7.7
+ ,6.9
+ ,6.6
+ ,7.7
+ ,94.1
+ ,8
+ ,8
+ ,7.7
+ ,6.9
+ ,7.3
+ ,91.8
+ ,7.7
+ ,8
+ ,8
+ ,7.7
+ ,7.4
+ ,102.7
+ ,7.3
+ ,7.7
+ ,8
+ ,8
+ ,8.1
+ ,82.6
+ ,7.4
+ ,7.3
+ ,7.7
+ ,8)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),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 = '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 Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 8.3 101.6 8.2 8.7 9.3 9.3 1 0 0 0 0 0 0 0 0 0 0 1
2 8.5 94.6 8.3 8.2 8.7 9.3 0 1 0 0 0 0 0 0 0 0 0 2
3 8.6 95.9 8.5 8.3 8.2 8.7 0 0 1 0 0 0 0 0 0 0 0 3
4 8.5 104.7 8.6 8.5 8.3 8.2 0 0 0 1 0 0 0 0 0 0 0 4
5 8.2 102.8 8.5 8.6 8.5 8.3 0 0 0 0 1 0 0 0 0 0 0 5
6 8.1 98.1 8.2 8.5 8.6 8.5 0 0 0 0 0 1 0 0 0 0 0 6
7 7.9 113.9 8.1 8.2 8.5 8.6 0 0 0 0 0 0 1 0 0 0 0 7
8 8.6 80.9 7.9 8.1 8.2 8.5 0 0 0 0 0 0 0 1 0 0 0 8
9 8.7 95.7 8.6 7.9 8.1 8.2 0 0 0 0 0 0 0 0 1 0 0 9
10 8.7 113.2 8.7 8.6 7.9 8.1 0 0 0 0 0 0 0 0 0 1 0 10
11 8.5 105.9 8.7 8.7 8.6 7.9 0 0 0 0 0 0 0 0 0 0 1 11
12 8.4 108.8 8.5 8.7 8.7 8.6 0 0 0 0 0 0 0 0 0 0 0 12
13 8.5 102.3 8.4 8.5 8.7 8.7 1 0 0 0 0 0 0 0 0 0 0 13
14 8.7 99.0 8.5 8.4 8.5 8.7 0 1 0 0 0 0 0 0 0 0 0 14
15 8.7 100.7 8.7 8.5 8.4 8.5 0 0 1 0 0 0 0 0 0 0 0 15
16 8.6 115.5 8.7 8.7 8.5 8.4 0 0 0 1 0 0 0 0 0 0 0 16
17 8.5 100.7 8.6 8.7 8.7 8.5 0 0 0 0 1 0 0 0 0 0 0 17
18 8.3 109.9 8.5 8.6 8.7 8.7 0 0 0 0 0 1 0 0 0 0 0 18
19 8.0 114.6 8.3 8.5 8.6 8.7 0 0 0 0 0 0 1 0 0 0 0 19
20 8.2 85.4 8.0 8.3 8.5 8.6 0 0 0 0 0 0 0 1 0 0 0 20
21 8.1 100.5 8.2 8.0 8.3 8.5 0 0 0 0 0 0 0 0 1 0 0 21
22 8.1 114.8 8.1 8.2 8.0 8.3 0 0 0 0 0 0 0 0 0 1 0 22
23 8.0 116.5 8.1 8.1 8.2 8.0 0 0 0 0 0 0 0 0 0 0 1 23
24 7.9 112.9 8.0 8.1 8.1 8.2 0 0 0 0 0 0 0 0 0 0 0 24
25 7.9 102.0 7.9 8.0 8.1 8.1 1 0 0 0 0 0 0 0 0 0 0 25
26 8.0 106.0 7.9 7.9 8.0 8.1 0 1 0 0 0 0 0 0 0 0 0 26
27 8.0 105.3 8.0 7.9 7.9 8.0 0 0 1 0 0 0 0 0 0 0 0 27
28 7.9 118.8 8.0 8.0 7.9 7.9 0 0 0 1 0 0 0 0 0 0 0 28
29 8.0 106.1 7.9 8.0 8.0 7.9 0 0 0 0 1 0 0 0 0 0 0 29
30 7.7 109.3 8.0 7.9 8.0 8.0 0 0 0 0 0 1 0 0 0 0 0 30
31 7.2 117.2 7.7 8.0 7.9 8.0 0 0 0 0 0 0 1 0 0 0 0 31
32 7.5 92.5 7.2 7.7 8.0 7.9 0 0 0 0 0 0 0 1 0 0 0 32
33 7.3 104.2 7.5 7.2 7.7 8.0 0 0 0 0 0 0 0 0 1 0 0 33
34 7.0 112.5 7.3 7.5 7.2 7.7 0 0 0 0 0 0 0 0 0 1 0 34
35 7.0 122.4 7.0 7.3 7.5 7.2 0 0 0 0 0 0 0 0 0 0 1 35
36 7.0 113.3 7.0 7.0 7.3 7.5 0 0 0 0 0 0 0 0 0 0 0 36
37 7.2 100.0 7.0 7.0 7.0 7.3 1 0 0 0 0 0 0 0 0 0 0 37
38 7.3 110.7 7.2 7.0 7.0 7.0 0 1 0 0 0 0 0 0 0 0 0 38
39 7.1 112.8 7.3 7.2 7.0 7.0 0 0 1 0 0 0 0 0 0 0 0 39
40 6.8 109.8 7.1 7.3 7.2 7.0 0 0 0 1 0 0 0 0 0 0 0 40
41 6.4 117.3 6.8 7.1 7.3 7.2 0 0 0 0 1 0 0 0 0 0 0 41
42 6.1 109.1 6.4 6.8 7.1 7.3 0 0 0 0 0 1 0 0 0 0 0 42
43 6.5 115.9 6.1 6.4 6.8 7.1 0 0 0 0 0 0 1 0 0 0 0 43
44 7.7 96.0 6.5 6.1 6.4 6.8 0 0 0 0 0 0 0 1 0 0 0 44
45 7.9 99.8 7.7 6.5 6.1 6.4 0 0 0 0 0 0 0 0 1 0 0 45
46 7.5 116.8 7.9 7.7 6.5 6.1 0 0 0 0 0 0 0 0 0 1 0 46
47 6.9 115.7 7.5 7.9 7.7 6.5 0 0 0 0 0 0 0 0 0 0 1 47
48 6.6 99.4 6.9 7.5 7.9 7.7 0 0 0 0 0 0 0 0 0 0 0 48
49 6.9 94.3 6.6 6.9 7.5 7.9 1 0 0 0 0 0 0 0 0 0 0 49
50 7.7 91.0 6.9 6.6 6.9 7.5 0 1 0 0 0 0 0 0 0 0 0 50
51 8.0 93.2 7.7 6.9 6.6 6.9 0 0 1 0 0 0 0 0 0 0 0 51
52 8.0 103.1 8.0 7.7 6.9 6.6 0 0 0 1 0 0 0 0 0 0 0 52
53 7.7 94.1 8.0 8.0 7.7 6.9 0 0 0 0 1 0 0 0 0 0 0 53
54 7.3 91.8 7.7 8.0 8.0 7.7 0 0 0 0 0 1 0 0 0 0 0 54
55 7.4 102.7 7.3 7.7 8.0 8.0 0 0 0 0 0 0 1 0 0 0 0 55
56 8.1 82.6 7.4 7.3 7.7 8.0 0 0 0 0 0 0 0 1 0 0 0 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
1.985908 -0.009431 1.525983 -0.930814 0.083898 0.200461
M1 M2 M3 M4 M5 M6
0.094335 0.032358 -0.132721 0.060719 -0.026252 -0.155004
M7 M8 M9 M10 M11 t
0.047104 0.381693 -0.486310 0.092005 0.123842 -0.002516
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.24828 -0.09631 -0.01898 0.10789 0.32310
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.985908 0.981443 2.023 0.05010 .
X -0.009431 0.004171 -2.261 0.02958 *
Y1 1.525983 0.150629 10.131 2.38e-12 ***
Y2 -0.930814 0.289905 -3.211 0.00269 **
Y3 0.083898 0.289711 0.290 0.77370
Y4 0.200461 0.161051 1.245 0.22086
M1 0.094335 0.116215 0.812 0.42201
M2 0.032358 0.122634 0.264 0.79331
M3 -0.132721 0.125244 -1.060 0.29597
M4 0.060719 0.119433 0.508 0.61411
M5 -0.026252 0.115121 -0.228 0.82084
M6 -0.155004 0.110417 -1.404 0.16850
M7 0.047104 0.112013 0.421 0.67647
M8 0.381693 0.142536 2.678 0.01088 *
M9 -0.486310 0.158080 -3.076 0.00387 **
M10 0.092005 0.170344 0.540 0.59227
M11 0.123842 0.141184 0.877 0.38591
t -0.002516 0.002950 -0.853 0.39911
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1622 on 38 degrees of freedom
Multiple R-squared: 0.9589, Adjusted R-squared: 0.9406
F-statistic: 52.2 on 17 and 38 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,] 0.71718509 0.5656298 0.2828149
[2,] 0.59630211 0.8073958 0.4036979
[3,] 0.46859836 0.9371967 0.5314016
[4,] 0.36176580 0.7235316 0.6382342
[5,] 0.26536292 0.5307258 0.7346371
[6,] 0.17580226 0.3516045 0.8241977
[7,] 0.12409366 0.2481873 0.8759063
[8,] 0.08397216 0.1679443 0.9160278
[9,] 0.31701511 0.6340302 0.6829849
[10,] 0.31040220 0.6208044 0.6895978
[11,] 0.47785204 0.9557041 0.5221480
[12,] 0.34415894 0.6883179 0.6558411
[13,] 0.37543292 0.7508658 0.6245671
[14,] 0.31264437 0.6252887 0.6873556
[15,] 0.41857916 0.8371583 0.5814208
> postscript(file="/var/www/html/rcomp/tmp/1c6yn1261059874.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/28r9p1261059874.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3fez51261059875.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ljvx1261059875.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5rgf31261059875.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 6
0.12090489 -0.24828410 -0.01831887 -0.10084890 -0.12042638 0.18274848
7 8 9 10 11 12
-0.20614251 0.10790552 0.03217362 0.15720777 -0.06651266 0.14367790
13 14 15 16 17 18
0.03694915 0.04141985 0.06141367 0.10788139 0.07356757 0.11102107
19 20 21 22 23 24
-0.12374240 -0.23112083 0.13418446 0.09726603 -0.06574650 0.04755676
25 26 27 28 29 30
-0.06749309 0.05002957 0.08686076 0.03637708 0.25030346 -0.15397734
31 32 33 34 35 36
-0.21980161 0.01059328 -0.12662905 -0.23762560 0.17310878 -0.10895524
37 38 39 40 41 42
-0.06093986 -0.04059899 -0.01963511 -0.15735294 -0.17398654 -0.09216777
43 44 45 46 47 48
0.32309888 0.20741692 -0.03972902 -0.01684821 -0.04084963 -0.08227941
49 50 51 52 53 54
-0.02942108 0.19743367 -0.11032044 0.11394337 -0.02945811 -0.04762444
55 56
0.22658764 -0.09479489
> postscript(file="/var/www/html/rcomp/tmp/6ndy91261059875.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 0.12090489 NA
1 -0.24828410 0.12090489
2 -0.01831887 -0.24828410
3 -0.10084890 -0.01831887
4 -0.12042638 -0.10084890
5 0.18274848 -0.12042638
6 -0.20614251 0.18274848
7 0.10790552 -0.20614251
8 0.03217362 0.10790552
9 0.15720777 0.03217362
10 -0.06651266 0.15720777
11 0.14367790 -0.06651266
12 0.03694915 0.14367790
13 0.04141985 0.03694915
14 0.06141367 0.04141985
15 0.10788139 0.06141367
16 0.07356757 0.10788139
17 0.11102107 0.07356757
18 -0.12374240 0.11102107
19 -0.23112083 -0.12374240
20 0.13418446 -0.23112083
21 0.09726603 0.13418446
22 -0.06574650 0.09726603
23 0.04755676 -0.06574650
24 -0.06749309 0.04755676
25 0.05002957 -0.06749309
26 0.08686076 0.05002957
27 0.03637708 0.08686076
28 0.25030346 0.03637708
29 -0.15397734 0.25030346
30 -0.21980161 -0.15397734
31 0.01059328 -0.21980161
32 -0.12662905 0.01059328
33 -0.23762560 -0.12662905
34 0.17310878 -0.23762560
35 -0.10895524 0.17310878
36 -0.06093986 -0.10895524
37 -0.04059899 -0.06093986
38 -0.01963511 -0.04059899
39 -0.15735294 -0.01963511
40 -0.17398654 -0.15735294
41 -0.09216777 -0.17398654
42 0.32309888 -0.09216777
43 0.20741692 0.32309888
44 -0.03972902 0.20741692
45 -0.01684821 -0.03972902
46 -0.04084963 -0.01684821
47 -0.08227941 -0.04084963
48 -0.02942108 -0.08227941
49 0.19743367 -0.02942108
50 -0.11032044 0.19743367
51 0.11394337 -0.11032044
52 -0.02945811 0.11394337
53 -0.04762444 -0.02945811
54 0.22658764 -0.04762444
55 -0.09479489 0.22658764
56 NA -0.09479489
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.24828410 0.12090489
[2,] -0.01831887 -0.24828410
[3,] -0.10084890 -0.01831887
[4,] -0.12042638 -0.10084890
[5,] 0.18274848 -0.12042638
[6,] -0.20614251 0.18274848
[7,] 0.10790552 -0.20614251
[8,] 0.03217362 0.10790552
[9,] 0.15720777 0.03217362
[10,] -0.06651266 0.15720777
[11,] 0.14367790 -0.06651266
[12,] 0.03694915 0.14367790
[13,] 0.04141985 0.03694915
[14,] 0.06141367 0.04141985
[15,] 0.10788139 0.06141367
[16,] 0.07356757 0.10788139
[17,] 0.11102107 0.07356757
[18,] -0.12374240 0.11102107
[19,] -0.23112083 -0.12374240
[20,] 0.13418446 -0.23112083
[21,] 0.09726603 0.13418446
[22,] -0.06574650 0.09726603
[23,] 0.04755676 -0.06574650
[24,] -0.06749309 0.04755676
[25,] 0.05002957 -0.06749309
[26,] 0.08686076 0.05002957
[27,] 0.03637708 0.08686076
[28,] 0.25030346 0.03637708
[29,] -0.15397734 0.25030346
[30,] -0.21980161 -0.15397734
[31,] 0.01059328 -0.21980161
[32,] -0.12662905 0.01059328
[33,] -0.23762560 -0.12662905
[34,] 0.17310878 -0.23762560
[35,] -0.10895524 0.17310878
[36,] -0.06093986 -0.10895524
[37,] -0.04059899 -0.06093986
[38,] -0.01963511 -0.04059899
[39,] -0.15735294 -0.01963511
[40,] -0.17398654 -0.15735294
[41,] -0.09216777 -0.17398654
[42,] 0.32309888 -0.09216777
[43,] 0.20741692 0.32309888
[44,] -0.03972902 0.20741692
[45,] -0.01684821 -0.03972902
[46,] -0.04084963 -0.01684821
[47,] -0.08227941 -0.04084963
[48,] -0.02942108 -0.08227941
[49,] 0.19743367 -0.02942108
[50,] -0.11032044 0.19743367
[51,] 0.11394337 -0.11032044
[52,] -0.02945811 0.11394337
[53,] -0.04762444 -0.02945811
[54,] 0.22658764 -0.04762444
[55,] -0.09479489 0.22658764
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.24828410 0.12090489
2 -0.01831887 -0.24828410
3 -0.10084890 -0.01831887
4 -0.12042638 -0.10084890
5 0.18274848 -0.12042638
6 -0.20614251 0.18274848
7 0.10790552 -0.20614251
8 0.03217362 0.10790552
9 0.15720777 0.03217362
10 -0.06651266 0.15720777
11 0.14367790 -0.06651266
12 0.03694915 0.14367790
13 0.04141985 0.03694915
14 0.06141367 0.04141985
15 0.10788139 0.06141367
16 0.07356757 0.10788139
17 0.11102107 0.07356757
18 -0.12374240 0.11102107
19 -0.23112083 -0.12374240
20 0.13418446 -0.23112083
21 0.09726603 0.13418446
22 -0.06574650 0.09726603
23 0.04755676 -0.06574650
24 -0.06749309 0.04755676
25 0.05002957 -0.06749309
26 0.08686076 0.05002957
27 0.03637708 0.08686076
28 0.25030346 0.03637708
29 -0.15397734 0.25030346
30 -0.21980161 -0.15397734
31 0.01059328 -0.21980161
32 -0.12662905 0.01059328
33 -0.23762560 -0.12662905
34 0.17310878 -0.23762560
35 -0.10895524 0.17310878
36 -0.06093986 -0.10895524
37 -0.04059899 -0.06093986
38 -0.01963511 -0.04059899
39 -0.15735294 -0.01963511
40 -0.17398654 -0.15735294
41 -0.09216777 -0.17398654
42 0.32309888 -0.09216777
43 0.20741692 0.32309888
44 -0.03972902 0.20741692
45 -0.01684821 -0.03972902
46 -0.04084963 -0.01684821
47 -0.08227941 -0.04084963
48 -0.02942108 -0.08227941
49 0.19743367 -0.02942108
50 -0.11032044 0.19743367
51 0.11394337 -0.11032044
52 -0.02945811 0.11394337
53 -0.04762444 -0.02945811
54 0.22658764 -0.04762444
55 -0.09479489 0.22658764
> 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/7qhf81261059875.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8c68a1261059875.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9zncm1261059875.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10m91t1261059875.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11erun1261059875.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/129sbi1261059875.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/13rst51261059875.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/14d4771261059875.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/159mxz1261059875.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/1681vv1261059875.tab")
+ }
>
> try(system("convert tmp/1c6yn1261059874.ps tmp/1c6yn1261059874.png",intern=TRUE))
character(0)
> try(system("convert tmp/28r9p1261059874.ps tmp/28r9p1261059874.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fez51261059875.ps tmp/3fez51261059875.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ljvx1261059875.ps tmp/4ljvx1261059875.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rgf31261059875.ps tmp/5rgf31261059875.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ndy91261059875.ps tmp/6ndy91261059875.png",intern=TRUE))
character(0)
> try(system("convert tmp/7qhf81261059875.ps tmp/7qhf81261059875.png",intern=TRUE))
character(0)
> try(system("convert tmp/8c68a1261059875.ps tmp/8c68a1261059875.png",intern=TRUE))
character(0)
> try(system("convert tmp/9zncm1261059875.ps tmp/9zncm1261059875.png",intern=TRUE))
character(0)
> try(system("convert tmp/10m91t1261059875.ps tmp/10m91t1261059875.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.358 1.562 3.201