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(110.3
+ ,0
+ ,114.1
+ ,96.8
+ ,87.4
+ ,111.4
+ ,103.9
+ ,0
+ ,110.3
+ ,114.1
+ ,96.8
+ ,87.4
+ ,101.6
+ ,0
+ ,103.9
+ ,110.3
+ ,114.1
+ ,96.8
+ ,94.6
+ ,0
+ ,101.6
+ ,103.9
+ ,110.3
+ ,114.1
+ ,95.9
+ ,0
+ ,94.6
+ ,101.6
+ ,103.9
+ ,110.3
+ ,104.7
+ ,0
+ ,95.9
+ ,94.6
+ ,101.6
+ ,103.9
+ ,102.8
+ ,0
+ ,104.7
+ ,95.9
+ ,94.6
+ ,101.6
+ ,98.1
+ ,0
+ ,102.8
+ ,104.7
+ ,95.9
+ ,94.6
+ ,113.9
+ ,0
+ ,98.1
+ ,102.8
+ ,104.7
+ ,95.9
+ ,80.9
+ ,0
+ ,113.9
+ ,98.1
+ ,102.8
+ ,104.7
+ ,95.7
+ ,0
+ ,80.9
+ ,113.9
+ ,98.1
+ ,102.8
+ ,113.2
+ ,0
+ ,95.7
+ ,80.9
+ ,113.9
+ ,98.1
+ ,105.9
+ ,0
+ ,113.2
+ ,95.7
+ ,80.9
+ ,113.9
+ ,108.8
+ ,0
+ ,105.9
+ ,113.2
+ ,95.7
+ ,80.9
+ ,102.3
+ ,0
+ ,108.8
+ ,105.9
+ ,113.2
+ ,95.7
+ ,99
+ ,0
+ ,102.3
+ ,108.8
+ ,105.9
+ ,113.2
+ ,100.7
+ ,0
+ ,99
+ ,102.3
+ ,108.8
+ ,105.9
+ ,115.5
+ ,0
+ ,100.7
+ ,99
+ ,102.3
+ ,108.8
+ ,100.7
+ ,0
+ ,115.5
+ ,100.7
+ ,99
+ ,102.3
+ ,109.9
+ ,0
+ ,100.7
+ ,115.5
+ ,100.7
+ ,99
+ ,114.6
+ ,0
+ ,109.9
+ ,100.7
+ ,115.5
+ ,100.7
+ ,85.4
+ ,0
+ ,114.6
+ ,109.9
+ ,100.7
+ ,115.5
+ ,100.5
+ ,0
+ ,85.4
+ ,114.6
+ ,109.9
+ ,100.7
+ ,114.8
+ ,0
+ ,100.5
+ ,85.4
+ ,114.6
+ ,109.9
+ ,116.5
+ ,0
+ ,114.8
+ ,100.5
+ ,85.4
+ ,114.6
+ ,112.9
+ ,0
+ ,116.5
+ ,114.8
+ ,100.5
+ ,85.4
+ ,102
+ ,0
+ ,112.9
+ ,116.5
+ ,114.8
+ ,100.5
+ ,106
+ ,0
+ ,102
+ ,112.9
+ ,116.5
+ ,114.8
+ ,105.3
+ ,0
+ ,106
+ ,102
+ ,112.9
+ ,116.5
+ ,118.8
+ ,0
+ ,105.3
+ ,106
+ ,102
+ ,112.9
+ ,106.1
+ ,0
+ ,118.8
+ ,105.3
+ ,106
+ ,102
+ ,109.3
+ ,0
+ ,106.1
+ ,118.8
+ ,105.3
+ ,106
+ ,117.2
+ ,0
+ ,109.3
+ ,106.1
+ ,118.8
+ ,105.3
+ ,92.5
+ ,0
+ ,117.2
+ ,109.3
+ ,106.1
+ ,118.8
+ ,104.2
+ ,0
+ ,92.5
+ ,117.2
+ ,109.3
+ ,106.1
+ ,112.5
+ ,0
+ ,104.2
+ ,92.5
+ ,117.2
+ ,109.3
+ ,122.4
+ ,0
+ ,112.5
+ ,104.2
+ ,92.5
+ ,117.2
+ ,113.3
+ ,0
+ ,122.4
+ ,112.5
+ ,104.2
+ ,92.5
+ ,100
+ ,0
+ ,113.3
+ ,122.4
+ ,112.5
+ ,104.2
+ ,110.7
+ ,0
+ ,100
+ ,113.3
+ ,122.4
+ ,112.5
+ ,112.8
+ ,0
+ ,110.7
+ ,100
+ ,113.3
+ ,122.4
+ ,109.8
+ ,0
+ ,112.8
+ ,110.7
+ ,100
+ ,113.3
+ ,117.3
+ ,0
+ ,109.8
+ ,112.8
+ ,110.7
+ ,100
+ ,109.1
+ ,0
+ ,117.3
+ ,109.8
+ ,112.8
+ ,110.7
+ ,115.9
+ ,0
+ ,109.1
+ ,117.3
+ ,109.8
+ ,112.8
+ ,96
+ ,0
+ ,115.9
+ ,109.1
+ ,117.3
+ ,109.8
+ ,99.8
+ ,0
+ ,96
+ ,115.9
+ ,109.1
+ ,117.3
+ ,116.8
+ ,1
+ ,99.8
+ ,96
+ ,115.9
+ ,109.1
+ ,115.7
+ ,1
+ ,116.8
+ ,99.8
+ ,96
+ ,115.9
+ ,99.4
+ ,1
+ ,115.7
+ ,116.8
+ ,99.8
+ ,96
+ ,94.3
+ ,1
+ ,99.4
+ ,115.7
+ ,116.8
+ ,99.8
+ ,91
+ ,1
+ ,94.3
+ ,99.4
+ ,115.7
+ ,116.8
+ ,93.2
+ ,1
+ ,91
+ ,94.3
+ ,99.4
+ ,115.7
+ ,103.1
+ ,1
+ ,93.2
+ ,91
+ ,94.3
+ ,99.4
+ ,94.1
+ ,1
+ ,103.1
+ ,93.2
+ ,91
+ ,94.3
+ ,91.8
+ ,1
+ ,94.1
+ ,103.1
+ ,93.2
+ ,91
+ ,102.7
+ ,1
+ ,91.8
+ ,94.1
+ ,103.1
+ ,93.2)
+ ,dim=c(6
+ ,57)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:57))
> y <- array(NA,dim=c(6,57),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),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 Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 110.3 0 114.1 96.8 87.4 111.4 1 0 0 0 0 0 0 0 0 0 0 1
2 103.9 0 110.3 114.1 96.8 87.4 0 1 0 0 0 0 0 0 0 0 0 2
3 101.6 0 103.9 110.3 114.1 96.8 0 0 1 0 0 0 0 0 0 0 0 3
4 94.6 0 101.6 103.9 110.3 114.1 0 0 0 1 0 0 0 0 0 0 0 4
5 95.9 0 94.6 101.6 103.9 110.3 0 0 0 0 1 0 0 0 0 0 0 5
6 104.7 0 95.9 94.6 101.6 103.9 0 0 0 0 0 1 0 0 0 0 0 6
7 102.8 0 104.7 95.9 94.6 101.6 0 0 0 0 0 0 1 0 0 0 0 7
8 98.1 0 102.8 104.7 95.9 94.6 0 0 0 0 0 0 0 1 0 0 0 8
9 113.9 0 98.1 102.8 104.7 95.9 0 0 0 0 0 0 0 0 1 0 0 9
10 80.9 0 113.9 98.1 102.8 104.7 0 0 0 0 0 0 0 0 0 1 0 10
11 95.7 0 80.9 113.9 98.1 102.8 0 0 0 0 0 0 0 0 0 0 1 11
12 113.2 0 95.7 80.9 113.9 98.1 0 0 0 0 0 0 0 0 0 0 0 12
13 105.9 0 113.2 95.7 80.9 113.9 1 0 0 0 0 0 0 0 0 0 0 13
14 108.8 0 105.9 113.2 95.7 80.9 0 1 0 0 0 0 0 0 0 0 0 14
15 102.3 0 108.8 105.9 113.2 95.7 0 0 1 0 0 0 0 0 0 0 0 15
16 99.0 0 102.3 108.8 105.9 113.2 0 0 0 1 0 0 0 0 0 0 0 16
17 100.7 0 99.0 102.3 108.8 105.9 0 0 0 0 1 0 0 0 0 0 0 17
18 115.5 0 100.7 99.0 102.3 108.8 0 0 0 0 0 1 0 0 0 0 0 18
19 100.7 0 115.5 100.7 99.0 102.3 0 0 0 0 0 0 1 0 0 0 0 19
20 109.9 0 100.7 115.5 100.7 99.0 0 0 0 0 0 0 0 1 0 0 0 20
21 114.6 0 109.9 100.7 115.5 100.7 0 0 0 0 0 0 0 0 1 0 0 21
22 85.4 0 114.6 109.9 100.7 115.5 0 0 0 0 0 0 0 0 0 1 0 22
23 100.5 0 85.4 114.6 109.9 100.7 0 0 0 0 0 0 0 0 0 0 1 23
24 114.8 0 100.5 85.4 114.6 109.9 0 0 0 0 0 0 0 0 0 0 0 24
25 116.5 0 114.8 100.5 85.4 114.6 1 0 0 0 0 0 0 0 0 0 0 25
26 112.9 0 116.5 114.8 100.5 85.4 0 1 0 0 0 0 0 0 0 0 0 26
27 102.0 0 112.9 116.5 114.8 100.5 0 0 1 0 0 0 0 0 0 0 0 27
28 106.0 0 102.0 112.9 116.5 114.8 0 0 0 1 0 0 0 0 0 0 0 28
29 105.3 0 106.0 102.0 112.9 116.5 0 0 0 0 1 0 0 0 0 0 0 29
30 118.8 0 105.3 106.0 102.0 112.9 0 0 0 0 0 1 0 0 0 0 0 30
31 106.1 0 118.8 105.3 106.0 102.0 0 0 0 0 0 0 1 0 0 0 0 31
32 109.3 0 106.1 118.8 105.3 106.0 0 0 0 0 0 0 0 1 0 0 0 32
33 117.2 0 109.3 106.1 118.8 105.3 0 0 0 0 0 0 0 0 1 0 0 33
34 92.5 0 117.2 109.3 106.1 118.8 0 0 0 0 0 0 0 0 0 1 0 34
35 104.2 0 92.5 117.2 109.3 106.1 0 0 0 0 0 0 0 0 0 0 1 35
36 112.5 0 104.2 92.5 117.2 109.3 0 0 0 0 0 0 0 0 0 0 0 36
37 122.4 0 112.5 104.2 92.5 117.2 1 0 0 0 0 0 0 0 0 0 0 37
38 113.3 0 122.4 112.5 104.2 92.5 0 1 0 0 0 0 0 0 0 0 0 38
39 100.0 0 113.3 122.4 112.5 104.2 0 0 1 0 0 0 0 0 0 0 0 39
40 110.7 0 100.0 113.3 122.4 112.5 0 0 0 1 0 0 0 0 0 0 0 40
41 112.8 0 110.7 100.0 113.3 122.4 0 0 0 0 1 0 0 0 0 0 0 41
42 109.8 0 112.8 110.7 100.0 113.3 0 0 0 0 0 1 0 0 0 0 0 42
43 117.3 0 109.8 112.8 110.7 100.0 0 0 0 0 0 0 1 0 0 0 0 43
44 109.1 0 117.3 109.8 112.8 110.7 0 0 0 0 0 0 0 1 0 0 0 44
45 115.9 0 109.1 117.3 109.8 112.8 0 0 0 0 0 0 0 0 1 0 0 45
46 96.0 0 115.9 109.1 117.3 109.8 0 0 0 0 0 0 0 0 0 1 0 46
47 99.8 0 96.0 115.9 109.1 117.3 0 0 0 0 0 0 0 0 0 0 1 47
48 116.8 1 99.8 96.0 115.9 109.1 0 0 0 0 0 0 0 0 0 0 0 48
49 115.7 1 116.8 99.8 96.0 115.9 1 0 0 0 0 0 0 0 0 0 0 49
50 99.4 1 115.7 116.8 99.8 96.0 0 1 0 0 0 0 0 0 0 0 0 50
51 94.3 1 99.4 115.7 116.8 99.8 0 0 1 0 0 0 0 0 0 0 0 51
52 91.0 1 94.3 99.4 115.7 116.8 0 0 0 1 0 0 0 0 0 0 0 52
53 93.2 1 91.0 94.3 99.4 115.7 0 0 0 0 1 0 0 0 0 0 0 53
54 103.1 1 93.2 91.0 94.3 99.4 0 0 0 0 0 1 0 0 0 0 0 54
55 94.1 1 103.1 93.2 91.0 94.3 0 0 0 0 0 0 1 0 0 0 0 55
56 91.8 1 94.1 103.1 93.2 91.0 0 0 0 0 0 0 0 1 0 0 0 56
57 102.7 1 91.8 94.1 103.1 93.2 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 Y1 Y2 Y3 Y4
50.23629 -10.52653 -0.20206 0.23657 0.55483 -0.01605
M1 M2 M3 M4 M5 M6
15.34547 -1.32103 -18.42725 -18.02503 -11.37462 1.64235
M7 M8 M9 M10 M11 t
-3.43736 -8.17797 -2.59168 -24.24410 -20.51069 0.12120
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-6.19962 -2.14538 -0.02515 1.78187 6.78224
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 50.23629 17.61386 2.852 0.006912 **
X -10.52653 2.79076 -3.772 0.000538 ***
Y1 -0.20206 0.15602 -1.295 0.202908
Y2 0.23657 0.12068 1.960 0.057134 .
Y3 0.55483 0.12180 4.555 5.04e-05 ***
Y4 -0.01605 0.14937 -0.107 0.914974
M1 15.34547 5.05474 3.036 0.004259 **
M2 -1.32103 7.15049 -0.185 0.854385
M3 -18.42725 4.74728 -3.882 0.000389 ***
M4 -18.02503 3.20633 -5.622 1.74e-06 ***
M5 -11.37462 2.91686 -3.900 0.000369 ***
M6 1.64235 3.43224 0.479 0.634961
M7 -3.43736 4.61157 -0.745 0.460512
M8 -8.17797 4.62210 -1.769 0.084660 .
M9 -2.59168 3.50987 -0.738 0.464693
M10 -24.24410 4.06068 -5.970 5.69e-07 ***
M11 -20.51069 4.35130 -4.714 3.08e-05 ***
t 0.12120 0.05806 2.088 0.043413 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.496 on 39 degrees of freedom
Multiple R-squared: 0.8973, Adjusted R-squared: 0.8525
F-statistic: 20.04 on 17 and 39 DF, p-value: 3.535e-14
> 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,] 0.72911085 0.5417783 0.2708892
[2,] 0.61002310 0.7799538 0.3899769
[3,] 0.50626941 0.9874612 0.4937306
[4,] 0.36091909 0.7218382 0.6390809
[5,] 0.25115540 0.5023108 0.7488446
[6,] 0.18946283 0.3789257 0.8105372
[7,] 0.21022214 0.4204443 0.7897779
[8,] 0.14518170 0.2903634 0.8548183
[9,] 0.14918484 0.2983697 0.8508152
[10,] 0.16090547 0.3218109 0.8390945
[11,] 0.15659737 0.3131947 0.8434026
[12,] 0.11023345 0.2204669 0.8897666
[13,] 0.11304187 0.2260837 0.8869581
[14,] 0.10558653 0.2111731 0.8944135
[15,] 0.05571122 0.1114224 0.9442888
[16,] 0.59968595 0.8006281 0.4003141
> postscript(file="/var/www/html/rcomp/tmp/1npqs1258736139.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2t6yn1258736139.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ufig1258736139.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4jmi91258736139.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5rknp1258736139.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
-1.95205451 -2.26792661 2.57511680 -1.51293784 -4.36492689 -5.61104725
7 8 9 10 11 12
2.76498240 -0.61499108 4.11563460 -1.85325368 1.26352186 0.08711532
13 14 15 16 17 18
-4.08157075 1.00745761 4.33337973 2.84169797 -3.08520975 3.35377108
19 20 21 22 23 24
-2.17276198 4.15871009 0.32715620 -0.11926289 -1.22799203 -0.06096645
25 26 27 28 29 30
1.76623556 2.82538706 0.08906642 1.50114404 -0.55891971 4.70508854
31 32 33 34 35 36
-2.53727443 -0.02515278 -1.68311190 3.25046538 2.25670372 -6.19962367
37 38 39 40 41 42
0.97415802 1.56830165 -3.34479995 0.93751284 6.78224101 -4.22967834
43 44 45 46 47 48
0.97563499 -1.37318887 -2.01364915 -1.27794881 -2.29223355 6.17347480
49 50 51 52 53 54
3.29323168 -3.13321970 -3.65276300 -3.76741701 1.22681534 1.78186597
55 56 57
0.96941903 -2.14537736 -0.74602975
> postscript(file="/var/www/html/rcomp/tmp/6ayzs1258736139.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 -1.95205451 NA
1 -2.26792661 -1.95205451
2 2.57511680 -2.26792661
3 -1.51293784 2.57511680
4 -4.36492689 -1.51293784
5 -5.61104725 -4.36492689
6 2.76498240 -5.61104725
7 -0.61499108 2.76498240
8 4.11563460 -0.61499108
9 -1.85325368 4.11563460
10 1.26352186 -1.85325368
11 0.08711532 1.26352186
12 -4.08157075 0.08711532
13 1.00745761 -4.08157075
14 4.33337973 1.00745761
15 2.84169797 4.33337973
16 -3.08520975 2.84169797
17 3.35377108 -3.08520975
18 -2.17276198 3.35377108
19 4.15871009 -2.17276198
20 0.32715620 4.15871009
21 -0.11926289 0.32715620
22 -1.22799203 -0.11926289
23 -0.06096645 -1.22799203
24 1.76623556 -0.06096645
25 2.82538706 1.76623556
26 0.08906642 2.82538706
27 1.50114404 0.08906642
28 -0.55891971 1.50114404
29 4.70508854 -0.55891971
30 -2.53727443 4.70508854
31 -0.02515278 -2.53727443
32 -1.68311190 -0.02515278
33 3.25046538 -1.68311190
34 2.25670372 3.25046538
35 -6.19962367 2.25670372
36 0.97415802 -6.19962367
37 1.56830165 0.97415802
38 -3.34479995 1.56830165
39 0.93751284 -3.34479995
40 6.78224101 0.93751284
41 -4.22967834 6.78224101
42 0.97563499 -4.22967834
43 -1.37318887 0.97563499
44 -2.01364915 -1.37318887
45 -1.27794881 -2.01364915
46 -2.29223355 -1.27794881
47 6.17347480 -2.29223355
48 3.29323168 6.17347480
49 -3.13321970 3.29323168
50 -3.65276300 -3.13321970
51 -3.76741701 -3.65276300
52 1.22681534 -3.76741701
53 1.78186597 1.22681534
54 0.96941903 1.78186597
55 -2.14537736 0.96941903
56 -0.74602975 -2.14537736
57 NA -0.74602975
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.26792661 -1.95205451
[2,] 2.57511680 -2.26792661
[3,] -1.51293784 2.57511680
[4,] -4.36492689 -1.51293784
[5,] -5.61104725 -4.36492689
[6,] 2.76498240 -5.61104725
[7,] -0.61499108 2.76498240
[8,] 4.11563460 -0.61499108
[9,] -1.85325368 4.11563460
[10,] 1.26352186 -1.85325368
[11,] 0.08711532 1.26352186
[12,] -4.08157075 0.08711532
[13,] 1.00745761 -4.08157075
[14,] 4.33337973 1.00745761
[15,] 2.84169797 4.33337973
[16,] -3.08520975 2.84169797
[17,] 3.35377108 -3.08520975
[18,] -2.17276198 3.35377108
[19,] 4.15871009 -2.17276198
[20,] 0.32715620 4.15871009
[21,] -0.11926289 0.32715620
[22,] -1.22799203 -0.11926289
[23,] -0.06096645 -1.22799203
[24,] 1.76623556 -0.06096645
[25,] 2.82538706 1.76623556
[26,] 0.08906642 2.82538706
[27,] 1.50114404 0.08906642
[28,] -0.55891971 1.50114404
[29,] 4.70508854 -0.55891971
[30,] -2.53727443 4.70508854
[31,] -0.02515278 -2.53727443
[32,] -1.68311190 -0.02515278
[33,] 3.25046538 -1.68311190
[34,] 2.25670372 3.25046538
[35,] -6.19962367 2.25670372
[36,] 0.97415802 -6.19962367
[37,] 1.56830165 0.97415802
[38,] -3.34479995 1.56830165
[39,] 0.93751284 -3.34479995
[40,] 6.78224101 0.93751284
[41,] -4.22967834 6.78224101
[42,] 0.97563499 -4.22967834
[43,] -1.37318887 0.97563499
[44,] -2.01364915 -1.37318887
[45,] -1.27794881 -2.01364915
[46,] -2.29223355 -1.27794881
[47,] 6.17347480 -2.29223355
[48,] 3.29323168 6.17347480
[49,] -3.13321970 3.29323168
[50,] -3.65276300 -3.13321970
[51,] -3.76741701 -3.65276300
[52,] 1.22681534 -3.76741701
[53,] 1.78186597 1.22681534
[54,] 0.96941903 1.78186597
[55,] -2.14537736 0.96941903
[56,] -0.74602975 -2.14537736
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.26792661 -1.95205451
2 2.57511680 -2.26792661
3 -1.51293784 2.57511680
4 -4.36492689 -1.51293784
5 -5.61104725 -4.36492689
6 2.76498240 -5.61104725
7 -0.61499108 2.76498240
8 4.11563460 -0.61499108
9 -1.85325368 4.11563460
10 1.26352186 -1.85325368
11 0.08711532 1.26352186
12 -4.08157075 0.08711532
13 1.00745761 -4.08157075
14 4.33337973 1.00745761
15 2.84169797 4.33337973
16 -3.08520975 2.84169797
17 3.35377108 -3.08520975
18 -2.17276198 3.35377108
19 4.15871009 -2.17276198
20 0.32715620 4.15871009
21 -0.11926289 0.32715620
22 -1.22799203 -0.11926289
23 -0.06096645 -1.22799203
24 1.76623556 -0.06096645
25 2.82538706 1.76623556
26 0.08906642 2.82538706
27 1.50114404 0.08906642
28 -0.55891971 1.50114404
29 4.70508854 -0.55891971
30 -2.53727443 4.70508854
31 -0.02515278 -2.53727443
32 -1.68311190 -0.02515278
33 3.25046538 -1.68311190
34 2.25670372 3.25046538
35 -6.19962367 2.25670372
36 0.97415802 -6.19962367
37 1.56830165 0.97415802
38 -3.34479995 1.56830165
39 0.93751284 -3.34479995
40 6.78224101 0.93751284
41 -4.22967834 6.78224101
42 0.97563499 -4.22967834
43 -1.37318887 0.97563499
44 -2.01364915 -1.37318887
45 -1.27794881 -2.01364915
46 -2.29223355 -1.27794881
47 6.17347480 -2.29223355
48 3.29323168 6.17347480
49 -3.13321970 3.29323168
50 -3.65276300 -3.13321970
51 -3.76741701 -3.65276300
52 1.22681534 -3.76741701
53 1.78186597 1.22681534
54 0.96941903 1.78186597
55 -2.14537736 0.96941903
56 -0.74602975 -2.14537736
> 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/7yec91258736139.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/87gkz1258736139.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99xjd1258736139.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10jbut1258736139.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11jyhw1258736139.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/128sn21258736139.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/13wrw51258736139.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/14c3881258736139.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/154kk71258736139.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/16159d1258736139.tab")
+ }
>
> system("convert tmp/1npqs1258736139.ps tmp/1npqs1258736139.png")
> system("convert tmp/2t6yn1258736139.ps tmp/2t6yn1258736139.png")
> system("convert tmp/3ufig1258736139.ps tmp/3ufig1258736139.png")
> system("convert tmp/4jmi91258736139.ps tmp/4jmi91258736139.png")
> system("convert tmp/5rknp1258736139.ps tmp/5rknp1258736139.png")
> system("convert tmp/6ayzs1258736139.ps tmp/6ayzs1258736139.png")
> system("convert tmp/7yec91258736139.ps tmp/7yec91258736139.png")
> system("convert tmp/87gkz1258736139.ps tmp/87gkz1258736139.png")
> system("convert tmp/99xjd1258736139.ps tmp/99xjd1258736139.png")
> system("convert tmp/10jbut1258736139.ps tmp/10jbut1258736139.png")
>
>
> proc.time()
user system elapsed
2.404 1.592 5.507