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.
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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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(109.5
+ ,120.1
+ ,109.5
+ ,110.2
+ ,108.8
+ ,108.2
+ ,116
+ ,132.9
+ ,109.5
+ ,109.5
+ ,110.2
+ ,108.8
+ ,111.2
+ ,128.1
+ ,116
+ ,109.5
+ ,109.5
+ ,110.2
+ ,112.1
+ ,129.3
+ ,111.2
+ ,116
+ ,109.5
+ ,109.5
+ ,114
+ ,132.5
+ ,112.1
+ ,111.2
+ ,116
+ ,109.5
+ ,119.1
+ ,131
+ ,114
+ ,112.1
+ ,111.2
+ ,116
+ ,114.1
+ ,124.9
+ ,119.1
+ ,114
+ ,112.1
+ ,111.2
+ ,115.1
+ ,120.8
+ ,114.1
+ ,119.1
+ ,114
+ ,112.1
+ ,115.4
+ ,122
+ ,115.1
+ ,114.1
+ ,119.1
+ ,114
+ ,110.8
+ ,122.1
+ ,115.4
+ ,115.1
+ ,114.1
+ ,119.1
+ ,116
+ ,127.4
+ ,110.8
+ ,115.4
+ ,115.1
+ ,114.1
+ ,119.2
+ ,135.2
+ ,116
+ ,110.8
+ ,115.4
+ ,115.1
+ ,126.5
+ ,137.3
+ ,119.2
+ ,116
+ ,110.8
+ ,115.4
+ ,127.8
+ ,135
+ ,126.5
+ ,119.2
+ ,116
+ ,110.8
+ ,131.3
+ ,136
+ ,127.8
+ ,126.5
+ ,119.2
+ ,116
+ ,140.3
+ ,138.4
+ ,131.3
+ ,127.8
+ ,126.5
+ ,119.2
+ ,137.3
+ ,134.7
+ ,140.3
+ ,131.3
+ ,127.8
+ ,126.5
+ ,143
+ ,138.4
+ ,137.3
+ ,140.3
+ ,131.3
+ ,127.8
+ ,134.5
+ ,133.9
+ ,143
+ ,137.3
+ ,140.3
+ ,131.3
+ ,139.9
+ ,133.6
+ ,134.5
+ ,143
+ ,137.3
+ ,140.3
+ ,159.3
+ ,141.2
+ ,139.9
+ ,134.5
+ ,143
+ ,137.3
+ ,170.4
+ ,151.8
+ ,159.3
+ ,139.9
+ ,134.5
+ ,143
+ ,175
+ ,155.4
+ ,170.4
+ ,159.3
+ ,139.9
+ ,134.5
+ ,175.8
+ ,156.6
+ ,175
+ ,170.4
+ ,159.3
+ ,139.9
+ ,180.9
+ ,161.6
+ ,175.8
+ ,175
+ ,170.4
+ ,159.3
+ ,180.3
+ ,160.7
+ ,180.9
+ ,175.8
+ ,175
+ ,170.4
+ ,169.6
+ ,156
+ ,180.3
+ ,180.9
+ ,175.8
+ ,175
+ ,172.3
+ ,159.5
+ ,169.6
+ ,180.3
+ ,180.9
+ ,175.8
+ ,184.8
+ ,168.7
+ ,172.3
+ ,169.6
+ ,180.3
+ ,180.9
+ ,177.7
+ ,169.9
+ ,184.8
+ ,172.3
+ ,169.6
+ ,180.3
+ ,184.6
+ ,169.9
+ ,177.7
+ ,184.8
+ ,172.3
+ ,169.6
+ ,211.4
+ ,185.9
+ ,184.6
+ ,177.7
+ ,184.8
+ ,172.3
+ ,215.3
+ ,190.8
+ ,211.4
+ ,184.6
+ ,177.7
+ ,184.8
+ ,215.9
+ ,195.8
+ ,215.3
+ ,211.4
+ ,184.6
+ ,177.7
+ ,244.7
+ ,211.9
+ ,215.9
+ ,215.3
+ ,211.4
+ ,184.6
+ ,259.3
+ ,227.1
+ ,244.7
+ ,215.9
+ ,215.3
+ ,211.4
+ ,289
+ ,251.3
+ ,259.3
+ ,244.7
+ ,215.9
+ ,215.3
+ ,310.9
+ ,256.7
+ ,289
+ ,259.3
+ ,244.7
+ ,215.9
+ ,321
+ ,251.9
+ ,310.9
+ ,289
+ ,259.3
+ ,244.7
+ ,315.1
+ ,251.2
+ ,321
+ ,310.9
+ ,289
+ ,259.3
+ ,333.2
+ ,270.3
+ ,315.1
+ ,321
+ ,310.9
+ ,289
+ ,314.1
+ ,267.2
+ ,333.2
+ ,315.1
+ ,321
+ ,310.9
+ ,284.7
+ ,243
+ ,314.1
+ ,333.2
+ ,315.1
+ ,321
+ ,273.9
+ ,229.9
+ ,284.7
+ ,314.1
+ ,333.2
+ ,315.1
+ ,216
+ ,187.2
+ ,273.9
+ ,284.7
+ ,314.1
+ ,333.2
+ ,196.4
+ ,178.2
+ ,216
+ ,273.9
+ ,284.7
+ ,314.1
+ ,190.9
+ ,175.2
+ ,196.4
+ ,216
+ ,273.9
+ ,284.7
+ ,206.4
+ ,192.4
+ ,190.9
+ ,196.4
+ ,216
+ ,273.9
+ ,196.3
+ ,187
+ ,206.4
+ ,190.9
+ ,196.4
+ ,216
+ ,199.5
+ ,184
+ ,196.3
+ ,206.4
+ ,190.9
+ ,196.4
+ ,198.9
+ ,194.1
+ ,199.5
+ ,196.3
+ ,206.4
+ ,190.9
+ ,214.4
+ ,212.7
+ ,198.9
+ ,199.5
+ ,196.3
+ ,206.4
+ ,214.2
+ ,217.5
+ ,214.4
+ ,198.9
+ ,199.5
+ ,196.3
+ ,187.6
+ ,200.5
+ ,214.2
+ ,214.4
+ ,198.9
+ ,199.5
+ ,180.6
+ ,205.9
+ ,187.6
+ ,214.2
+ ,214.4
+ ,198.9
+ ,172.2
+ ,196.5
+ ,180.6
+ ,187.6
+ ,214.2
+ ,214.4)
+ ,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
1 109.5 120.1 109.5 110.2 108.8 108.2 1 0 0 0 0 0 0 0 0 0 0 1
2 116.0 132.9 109.5 109.5 110.2 108.8 0 1 0 0 0 0 0 0 0 0 0 2
3 111.2 128.1 116.0 109.5 109.5 110.2 0 0 1 0 0 0 0 0 0 0 0 3
4 112.1 129.3 111.2 116.0 109.5 109.5 0 0 0 1 0 0 0 0 0 0 0 4
5 114.0 132.5 112.1 111.2 116.0 109.5 0 0 0 0 1 0 0 0 0 0 0 5
6 119.1 131.0 114.0 112.1 111.2 116.0 0 0 0 0 0 1 0 0 0 0 0 6
7 114.1 124.9 119.1 114.0 112.1 111.2 0 0 0 0 0 0 1 0 0 0 0 7
8 115.1 120.8 114.1 119.1 114.0 112.1 0 0 0 0 0 0 0 1 0 0 0 8
9 115.4 122.0 115.1 114.1 119.1 114.0 0 0 0 0 0 0 0 0 1 0 0 9
10 110.8 122.1 115.4 115.1 114.1 119.1 0 0 0 0 0 0 0 0 0 1 0 10
11 116.0 127.4 110.8 115.4 115.1 114.1 0 0 0 0 0 0 0 0 0 0 1 11
12 119.2 135.2 116.0 110.8 115.4 115.1 0 0 0 0 0 0 0 0 0 0 0 12
13 126.5 137.3 119.2 116.0 110.8 115.4 1 0 0 0 0 0 0 0 0 0 0 13
14 127.8 135.0 126.5 119.2 116.0 110.8 0 1 0 0 0 0 0 0 0 0 0 14
15 131.3 136.0 127.8 126.5 119.2 116.0 0 0 1 0 0 0 0 0 0 0 0 15
16 140.3 138.4 131.3 127.8 126.5 119.2 0 0 0 1 0 0 0 0 0 0 0 16
17 137.3 134.7 140.3 131.3 127.8 126.5 0 0 0 0 1 0 0 0 0 0 0 17
18 143.0 138.4 137.3 140.3 131.3 127.8 0 0 0 0 0 1 0 0 0 0 0 18
19 134.5 133.9 143.0 137.3 140.3 131.3 0 0 0 0 0 0 1 0 0 0 0 19
20 139.9 133.6 134.5 143.0 137.3 140.3 0 0 0 0 0 0 0 1 0 0 0 20
21 159.3 141.2 139.9 134.5 143.0 137.3 0 0 0 0 0 0 0 0 1 0 0 21
22 170.4 151.8 159.3 139.9 134.5 143.0 0 0 0 0 0 0 0 0 0 1 0 22
23 175.0 155.4 170.4 159.3 139.9 134.5 0 0 0 0 0 0 0 0 0 0 1 23
24 175.8 156.6 175.0 170.4 159.3 139.9 0 0 0 0 0 0 0 0 0 0 0 24
25 180.9 161.6 175.8 175.0 170.4 159.3 1 0 0 0 0 0 0 0 0 0 0 25
26 180.3 160.7 180.9 175.8 175.0 170.4 0 1 0 0 0 0 0 0 0 0 0 26
27 169.6 156.0 180.3 180.9 175.8 175.0 0 0 1 0 0 0 0 0 0 0 0 27
28 172.3 159.5 169.6 180.3 180.9 175.8 0 0 0 1 0 0 0 0 0 0 0 28
29 184.8 168.7 172.3 169.6 180.3 180.9 0 0 0 0 1 0 0 0 0 0 0 29
30 177.7 169.9 184.8 172.3 169.6 180.3 0 0 0 0 0 1 0 0 0 0 0 30
31 184.6 169.9 177.7 184.8 172.3 169.6 0 0 0 0 0 0 1 0 0 0 0 31
32 211.4 185.9 184.6 177.7 184.8 172.3 0 0 0 0 0 0 0 1 0 0 0 32
33 215.3 190.8 211.4 184.6 177.7 184.8 0 0 0 0 0 0 0 0 1 0 0 33
34 215.9 195.8 215.3 211.4 184.6 177.7 0 0 0 0 0 0 0 0 0 1 0 34
35 244.7 211.9 215.9 215.3 211.4 184.6 0 0 0 0 0 0 0 0 0 0 1 35
36 259.3 227.1 244.7 215.9 215.3 211.4 0 0 0 0 0 0 0 0 0 0 0 36
37 289.0 251.3 259.3 244.7 215.9 215.3 1 0 0 0 0 0 0 0 0 0 0 37
38 310.9 256.7 289.0 259.3 244.7 215.9 0 1 0 0 0 0 0 0 0 0 0 38
39 321.0 251.9 310.9 289.0 259.3 244.7 0 0 1 0 0 0 0 0 0 0 0 39
40 315.1 251.2 321.0 310.9 289.0 259.3 0 0 0 1 0 0 0 0 0 0 0 40
41 333.2 270.3 315.1 321.0 310.9 289.0 0 0 0 0 1 0 0 0 0 0 0 41
42 314.1 267.2 333.2 315.1 321.0 310.9 0 0 0 0 0 1 0 0 0 0 0 42
43 284.7 243.0 314.1 333.2 315.1 321.0 0 0 0 0 0 0 1 0 0 0 0 43
44 273.9 229.9 284.7 314.1 333.2 315.1 0 0 0 0 0 0 0 1 0 0 0 44
45 216.0 187.2 273.9 284.7 314.1 333.2 0 0 0 0 0 0 0 0 1 0 0 45
46 196.4 178.2 216.0 273.9 284.7 314.1 0 0 0 0 0 0 0 0 0 1 0 46
47 190.9 175.2 196.4 216.0 273.9 284.7 0 0 0 0 0 0 0 0 0 0 1 47
48 206.4 192.4 190.9 196.4 216.0 273.9 0 0 0 0 0 0 0 0 0 0 0 48
49 196.3 187.0 206.4 190.9 196.4 216.0 1 0 0 0 0 0 0 0 0 0 0 49
50 199.5 184.0 196.3 206.4 190.9 196.4 0 1 0 0 0 0 0 0 0 0 0 50
51 198.9 194.1 199.5 196.3 206.4 190.9 0 0 1 0 0 0 0 0 0 0 0 51
52 214.4 212.7 198.9 199.5 196.3 206.4 0 0 0 1 0 0 0 0 0 0 0 52
53 214.2 217.5 214.4 198.9 199.5 196.3 0 0 0 0 1 0 0 0 0 0 0 53
54 187.6 200.5 214.2 214.4 198.9 199.5 0 0 0 0 0 1 0 0 0 0 0 54
55 180.6 205.9 187.6 214.2 214.4 198.9 0 0 0 0 0 0 1 0 0 0 0 55
56 172.2 196.5 180.6 187.6 214.2 214.4 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
-28.86918 0.72263 0.68166 0.03575 -0.13674 -0.02591
M1 M2 M3 M4 M5 M6
-4.26080 -2.90302 -6.12901 -3.79239 -4.25183 -13.94083
M7 M8 M9 M10 M11 t
-11.82939 -0.02343 -2.79353 -2.46253 5.15904 -0.35171
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-17.0914 -6.7010 0.2651 5.8604 19.2504
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -28.86918 11.62268 -2.484 0.017522 *
X 0.72263 0.14173 5.099 9.75e-06 ***
Y1 0.68166 0.16193 4.210 0.000151 ***
Y2 0.03575 0.19875 0.180 0.858212
Y3 -0.13674 0.20158 -0.678 0.501679
Y4 -0.02591 0.13245 -0.196 0.845976
M1 -4.26080 6.93011 -0.615 0.542335
M2 -2.90302 7.12212 -0.408 0.685850
M3 -6.12901 7.18725 -0.853 0.399135
M4 -3.79239 7.24308 -0.524 0.603605
M5 -4.25183 7.06473 -0.602 0.550856
M6 -13.94083 6.96059 -2.003 0.052368 .
M7 -11.82939 7.51535 -1.574 0.123771
M8 -0.02343 7.46608 -0.003 0.997513
M9 -2.79353 7.62899 -0.366 0.716266
M10 -2.46253 7.71703 -0.319 0.751396
M11 5.15904 7.65129 0.674 0.504221
t -0.35171 0.17638 -1.994 0.053365 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 10.12 on 38 degrees of freedom
Multiple R-squared: 0.982, Adjusted R-squared: 0.9739
F-statistic: 121.8 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,] 0.24794256 0.49588513 0.7520574
[2,] 0.15403544 0.30807088 0.8459646
[3,] 0.12807609 0.25615218 0.8719239
[4,] 0.06071250 0.12142500 0.9392875
[5,] 0.05360446 0.10720892 0.9463955
[6,] 0.03692834 0.07385668 0.9630717
[7,] 0.08132111 0.16264223 0.9186789
[8,] 0.10008336 0.20016672 0.8999166
[9,] 0.12534991 0.25069981 0.8746501
[10,] 0.73710023 0.52579955 0.2628998
[11,] 0.67796273 0.64407454 0.3220373
[12,] 0.60709983 0.78580034 0.3929002
[13,] 0.63817023 0.72365955 0.3618298
[14,] 0.73899919 0.52200162 0.2610008
[15,] 0.76569504 0.46860993 0.2343050
> postscript(file="/var/www/html/rcomp/tmp/1znvo1258730546.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ad2n1258730546.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3lc261258730546.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/44q2m1258730546.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5avg21258730546.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
-4.70802139 -8.23176341 -10.47570164 -9.40628295 -8.56066201 5.84870300
7 8 9 10 11 12
-0.04867734 -4.03101700 -1.23269691 -6.67607541 -9.44373551 -9.68279358
13 14 15 16 17 18
-2.27625855 -4.81895085 0.96126288 4.89081962 -0.51753097 14.78496129
19 20 21 22 23 24
5.32013791 4.89599870 19.25037914 8.27923992 -4.73391074 -0.03017736
25 26 27 28 29 30
7.37976158 3.83552420 0.56483088 6.78406020 12.03909482 4.01667398
31 32 33 34 35 36
13.64190337 14.75505522 -0.92632768 -6.77577818 6.41491447 -2.88417200
37 38 39 40 41 42
3.14186414 3.31981121 7.21840716 -3.38903340 9.14458753 -7.85337090
43 44 45 46 47 48
-9.69778948 0.56029188 -17.09135455 5.17261367 7.76273179 12.59714294
49 50 51 52 53 54
-3.53734577 5.89537885 1.73120072 1.12043653 -12.10548937 -16.79696736
55 56
-9.21557447 -16.18032879
> postscript(file="/var/www/html/rcomp/tmp/62r9i1258730546.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 -4.70802139 NA
1 -8.23176341 -4.70802139
2 -10.47570164 -8.23176341
3 -9.40628295 -10.47570164
4 -8.56066201 -9.40628295
5 5.84870300 -8.56066201
6 -0.04867734 5.84870300
7 -4.03101700 -0.04867734
8 -1.23269691 -4.03101700
9 -6.67607541 -1.23269691
10 -9.44373551 -6.67607541
11 -9.68279358 -9.44373551
12 -2.27625855 -9.68279358
13 -4.81895085 -2.27625855
14 0.96126288 -4.81895085
15 4.89081962 0.96126288
16 -0.51753097 4.89081962
17 14.78496129 -0.51753097
18 5.32013791 14.78496129
19 4.89599870 5.32013791
20 19.25037914 4.89599870
21 8.27923992 19.25037914
22 -4.73391074 8.27923992
23 -0.03017736 -4.73391074
24 7.37976158 -0.03017736
25 3.83552420 7.37976158
26 0.56483088 3.83552420
27 6.78406020 0.56483088
28 12.03909482 6.78406020
29 4.01667398 12.03909482
30 13.64190337 4.01667398
31 14.75505522 13.64190337
32 -0.92632768 14.75505522
33 -6.77577818 -0.92632768
34 6.41491447 -6.77577818
35 -2.88417200 6.41491447
36 3.14186414 -2.88417200
37 3.31981121 3.14186414
38 7.21840716 3.31981121
39 -3.38903340 7.21840716
40 9.14458753 -3.38903340
41 -7.85337090 9.14458753
42 -9.69778948 -7.85337090
43 0.56029188 -9.69778948
44 -17.09135455 0.56029188
45 5.17261367 -17.09135455
46 7.76273179 5.17261367
47 12.59714294 7.76273179
48 -3.53734577 12.59714294
49 5.89537885 -3.53734577
50 1.73120072 5.89537885
51 1.12043653 1.73120072
52 -12.10548937 1.12043653
53 -16.79696736 -12.10548937
54 -9.21557447 -16.79696736
55 -16.18032879 -9.21557447
56 NA -16.18032879
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -8.23176341 -4.70802139
[2,] -10.47570164 -8.23176341
[3,] -9.40628295 -10.47570164
[4,] -8.56066201 -9.40628295
[5,] 5.84870300 -8.56066201
[6,] -0.04867734 5.84870300
[7,] -4.03101700 -0.04867734
[8,] -1.23269691 -4.03101700
[9,] -6.67607541 -1.23269691
[10,] -9.44373551 -6.67607541
[11,] -9.68279358 -9.44373551
[12,] -2.27625855 -9.68279358
[13,] -4.81895085 -2.27625855
[14,] 0.96126288 -4.81895085
[15,] 4.89081962 0.96126288
[16,] -0.51753097 4.89081962
[17,] 14.78496129 -0.51753097
[18,] 5.32013791 14.78496129
[19,] 4.89599870 5.32013791
[20,] 19.25037914 4.89599870
[21,] 8.27923992 19.25037914
[22,] -4.73391074 8.27923992
[23,] -0.03017736 -4.73391074
[24,] 7.37976158 -0.03017736
[25,] 3.83552420 7.37976158
[26,] 0.56483088 3.83552420
[27,] 6.78406020 0.56483088
[28,] 12.03909482 6.78406020
[29,] 4.01667398 12.03909482
[30,] 13.64190337 4.01667398
[31,] 14.75505522 13.64190337
[32,] -0.92632768 14.75505522
[33,] -6.77577818 -0.92632768
[34,] 6.41491447 -6.77577818
[35,] -2.88417200 6.41491447
[36,] 3.14186414 -2.88417200
[37,] 3.31981121 3.14186414
[38,] 7.21840716 3.31981121
[39,] -3.38903340 7.21840716
[40,] 9.14458753 -3.38903340
[41,] -7.85337090 9.14458753
[42,] -9.69778948 -7.85337090
[43,] 0.56029188 -9.69778948
[44,] -17.09135455 0.56029188
[45,] 5.17261367 -17.09135455
[46,] 7.76273179 5.17261367
[47,] 12.59714294 7.76273179
[48,] -3.53734577 12.59714294
[49,] 5.89537885 -3.53734577
[50,] 1.73120072 5.89537885
[51,] 1.12043653 1.73120072
[52,] -12.10548937 1.12043653
[53,] -16.79696736 -12.10548937
[54,] -9.21557447 -16.79696736
[55,] -16.18032879 -9.21557447
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -8.23176341 -4.70802139
2 -10.47570164 -8.23176341
3 -9.40628295 -10.47570164
4 -8.56066201 -9.40628295
5 5.84870300 -8.56066201
6 -0.04867734 5.84870300
7 -4.03101700 -0.04867734
8 -1.23269691 -4.03101700
9 -6.67607541 -1.23269691
10 -9.44373551 -6.67607541
11 -9.68279358 -9.44373551
12 -2.27625855 -9.68279358
13 -4.81895085 -2.27625855
14 0.96126288 -4.81895085
15 4.89081962 0.96126288
16 -0.51753097 4.89081962
17 14.78496129 -0.51753097
18 5.32013791 14.78496129
19 4.89599870 5.32013791
20 19.25037914 4.89599870
21 8.27923992 19.25037914
22 -4.73391074 8.27923992
23 -0.03017736 -4.73391074
24 7.37976158 -0.03017736
25 3.83552420 7.37976158
26 0.56483088 3.83552420
27 6.78406020 0.56483088
28 12.03909482 6.78406020
29 4.01667398 12.03909482
30 13.64190337 4.01667398
31 14.75505522 13.64190337
32 -0.92632768 14.75505522
33 -6.77577818 -0.92632768
34 6.41491447 -6.77577818
35 -2.88417200 6.41491447
36 3.14186414 -2.88417200
37 3.31981121 3.14186414
38 7.21840716 3.31981121
39 -3.38903340 7.21840716
40 9.14458753 -3.38903340
41 -7.85337090 9.14458753
42 -9.69778948 -7.85337090
43 0.56029188 -9.69778948
44 -17.09135455 0.56029188
45 5.17261367 -17.09135455
46 7.76273179 5.17261367
47 12.59714294 7.76273179
48 -3.53734577 12.59714294
49 5.89537885 -3.53734577
50 1.73120072 5.89537885
51 1.12043653 1.73120072
52 -12.10548937 1.12043653
53 -16.79696736 -12.10548937
54 -9.21557447 -16.79696736
55 -16.18032879 -9.21557447
> 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/7ly4d1258730546.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8s94o1258730546.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9og1o1258730546.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10fipx1258730546.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ukip1258730546.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/12nxg51258730546.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/138t1m1258730546.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/14qc2o1258730546.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/15dw8d1258730546.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/165y6b1258730546.tab")
+ }
>
> system("convert tmp/1znvo1258730546.ps tmp/1znvo1258730546.png")
> system("convert tmp/2ad2n1258730546.ps tmp/2ad2n1258730546.png")
> system("convert tmp/3lc261258730546.ps tmp/3lc261258730546.png")
> system("convert tmp/44q2m1258730546.ps tmp/44q2m1258730546.png")
> system("convert tmp/5avg21258730546.ps tmp/5avg21258730546.png")
> system("convert tmp/62r9i1258730546.ps tmp/62r9i1258730546.png")
> system("convert tmp/7ly4d1258730546.ps tmp/7ly4d1258730546.png")
> system("convert tmp/8s94o1258730546.ps tmp/8s94o1258730546.png")
> system("convert tmp/9og1o1258730546.ps tmp/9og1o1258730546.png")
> system("convert tmp/10fipx1258730546.ps tmp/10fipx1258730546.png")
>
>
> proc.time()
user system elapsed
2.382 1.586 2.784