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(8
+ ,2.26
+ ,7.8
+ ,7.8
+ ,8.3
+ ,8.5
+ ,8.6
+ ,8.6
+ ,2.41
+ ,8
+ ,7.8
+ ,7.8
+ ,8.3
+ ,8.5
+ ,8.9
+ ,2.26
+ ,8.6
+ ,8
+ ,7.8
+ ,7.8
+ ,8.3
+ ,8.9
+ ,2.03
+ ,8.9
+ ,8.6
+ ,8
+ ,7.8
+ ,7.8
+ ,8.6
+ ,2.86
+ ,8.9
+ ,8.9
+ ,8.6
+ ,8
+ ,7.8
+ ,8.3
+ ,2.55
+ ,8.6
+ ,8.9
+ ,8.9
+ ,8.6
+ ,8
+ ,8.3
+ ,2.27
+ ,8.3
+ ,8.6
+ ,8.9
+ ,8.9
+ ,8.6
+ ,8.3
+ ,2.26
+ ,8.3
+ ,8.3
+ ,8.6
+ ,8.9
+ ,8.9
+ ,8.4
+ ,2.57
+ ,8.3
+ ,8.3
+ ,8.3
+ ,8.6
+ ,8.9
+ ,8.5
+ ,3.07
+ ,8.4
+ ,8.3
+ ,8.3
+ ,8.3
+ ,8.6
+ ,8.4
+ ,2.76
+ ,8.5
+ ,8.4
+ ,8.3
+ ,8.3
+ ,8.3
+ ,8.6
+ ,2.51
+ ,8.4
+ ,8.5
+ ,8.4
+ ,8.3
+ ,8.3
+ ,8.5
+ ,2.87
+ ,8.6
+ ,8.4
+ ,8.5
+ ,8.4
+ ,8.3
+ ,8.5
+ ,3.14
+ ,8.5
+ ,8.6
+ ,8.4
+ ,8.5
+ ,8.4
+ ,8.5
+ ,3.11
+ ,8.5
+ ,8.5
+ ,8.6
+ ,8.4
+ ,8.5
+ ,8.5
+ ,3.16
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.6
+ ,8.4
+ ,8.5
+ ,2.47
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.6
+ ,8.5
+ ,2.57
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,2.89
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,2.63
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,2.38
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,1.69
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,1.96
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.6
+ ,2.19
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.4
+ ,1.87
+ ,8.6
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8.1
+ ,1.6
+ ,8.4
+ ,8.6
+ ,8.5
+ ,8.5
+ ,8.5
+ ,8
+ ,1.63
+ ,8.1
+ ,8.4
+ ,8.6
+ ,8.5
+ ,8.5
+ ,8
+ ,1.22
+ ,8
+ ,8.1
+ ,8.4
+ ,8.6
+ ,8.5
+ ,8
+ ,1.21
+ ,8
+ ,8
+ ,8.1
+ ,8.4
+ ,8.6
+ ,8
+ ,1.49
+ ,8
+ ,8
+ ,8
+ ,8.1
+ ,8.4
+ ,7.9
+ ,1.64
+ ,8
+ ,8
+ ,8
+ ,8
+ ,8.1
+ ,7.8
+ ,1.66
+ ,7.9
+ ,8
+ ,8
+ ,8
+ ,8
+ ,7.8
+ ,1.77
+ ,7.8
+ ,7.9
+ ,8
+ ,8
+ ,8
+ ,7.9
+ ,1.82
+ ,7.8
+ ,7.8
+ ,7.9
+ ,8
+ ,8
+ ,8.1
+ ,1.78
+ ,7.9
+ ,7.8
+ ,7.8
+ ,7.9
+ ,8
+ ,8
+ ,1.28
+ ,8.1
+ ,7.9
+ ,7.8
+ ,7.8
+ ,7.9
+ ,7.6
+ ,1.29
+ ,8
+ ,8.1
+ ,7.9
+ ,7.8
+ ,7.8
+ ,7.3
+ ,1.37
+ ,7.6
+ ,8
+ ,8.1
+ ,7.9
+ ,7.8
+ ,7
+ ,1.12
+ ,7.3
+ ,7.6
+ ,8
+ ,8.1
+ ,7.9
+ ,6.8
+ ,1.51
+ ,7
+ ,7.3
+ ,7.6
+ ,8
+ ,8.1
+ ,7
+ ,2.24
+ ,6.8
+ ,7
+ ,7.3
+ ,7.6
+ ,8
+ ,7.1
+ ,2.94
+ ,7
+ ,6.8
+ ,7
+ ,7.3
+ ,7.6
+ ,7.2
+ ,3.09
+ ,7.1
+ ,7
+ ,6.8
+ ,7
+ ,7.3
+ ,7.1
+ ,3.46
+ ,7.2
+ ,7.1
+ ,7
+ ,6.8
+ ,7
+ ,6.9
+ ,3.64
+ ,7.1
+ ,7.2
+ ,7.1
+ ,7
+ ,6.8
+ ,6.7
+ ,4.39
+ ,6.9
+ ,7.1
+ ,7.2
+ ,7.1
+ ,7
+ ,6.7
+ ,4.15
+ ,6.7
+ ,6.9
+ ,7.1
+ ,7.2
+ ,7.1
+ ,6.6
+ ,5.21
+ ,6.7
+ ,6.7
+ ,6.9
+ ,7.1
+ ,7.2
+ ,6.9
+ ,5.8
+ ,6.6
+ ,6.7
+ ,6.7
+ ,6.9
+ ,7.1
+ ,7.3
+ ,5.91
+ ,6.9
+ ,6.6
+ ,6.7
+ ,6.7
+ ,6.9
+ ,7.5
+ ,5.39
+ ,7.3
+ ,6.9
+ ,6.6
+ ,6.7
+ ,6.7
+ ,7.3
+ ,5.46
+ ,7.5
+ ,7.3
+ ,6.9
+ ,6.6
+ ,6.7
+ ,7.1
+ ,4.72
+ ,7.3
+ ,7.5
+ ,7.3
+ ,6.9
+ ,6.6
+ ,6.9
+ ,3.14
+ ,7.1
+ ,7.3
+ ,7.5
+ ,7.3
+ ,6.9
+ ,7.1
+ ,2.63
+ ,6.9
+ ,7.1
+ ,7.3
+ ,7.5
+ ,7.3)
+ ,dim=c(7
+ ,55)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4'
+ ,'Y5')
+ ,1:55))
> y <- array(NA,dim=c(7,55),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4','Y5'),1:55))
> 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 Y5 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 8.0 2.26 7.8 7.8 8.3 8.5 8.6 1 0 0 0 0 0 0 0 0 0 0 1
2 8.6 2.41 8.0 7.8 7.8 8.3 8.5 0 1 0 0 0 0 0 0 0 0 0 2
3 8.9 2.26 8.6 8.0 7.8 7.8 8.3 0 0 1 0 0 0 0 0 0 0 0 3
4 8.9 2.03 8.9 8.6 8.0 7.8 7.8 0 0 0 1 0 0 0 0 0 0 0 4
5 8.6 2.86 8.9 8.9 8.6 8.0 7.8 0 0 0 0 1 0 0 0 0 0 0 5
6 8.3 2.55 8.6 8.9 8.9 8.6 8.0 0 0 0 0 0 1 0 0 0 0 0 6
7 8.3 2.27 8.3 8.6 8.9 8.9 8.6 0 0 0 0 0 0 1 0 0 0 0 7
8 8.3 2.26 8.3 8.3 8.6 8.9 8.9 0 0 0 0 0 0 0 1 0 0 0 8
9 8.4 2.57 8.3 8.3 8.3 8.6 8.9 0 0 0 0 0 0 0 0 1 0 0 9
10 8.5 3.07 8.4 8.3 8.3 8.3 8.6 0 0 0 0 0 0 0 0 0 1 0 10
11 8.4 2.76 8.5 8.4 8.3 8.3 8.3 0 0 0 0 0 0 0 0 0 0 1 11
12 8.6 2.51 8.4 8.5 8.4 8.3 8.3 0 0 0 0 0 0 0 0 0 0 0 12
13 8.5 2.87 8.6 8.4 8.5 8.4 8.3 1 0 0 0 0 0 0 0 0 0 0 13
14 8.5 3.14 8.5 8.6 8.4 8.5 8.4 0 1 0 0 0 0 0 0 0 0 0 14
15 8.5 3.11 8.5 8.5 8.6 8.4 8.5 0 0 1 0 0 0 0 0 0 0 0 15
16 8.5 3.16 8.5 8.5 8.5 8.6 8.4 0 0 0 1 0 0 0 0 0 0 0 16
17 8.5 2.47 8.5 8.5 8.5 8.5 8.6 0 0 0 0 1 0 0 0 0 0 0 17
18 8.5 2.57 8.5 8.5 8.5 8.5 8.5 0 0 0 0 0 1 0 0 0 0 0 18
19 8.5 2.89 8.5 8.5 8.5 8.5 8.5 0 0 0 0 0 0 1 0 0 0 0 19
20 8.5 2.63 8.5 8.5 8.5 8.5 8.5 0 0 0 0 0 0 0 1 0 0 0 20
21 8.5 2.38 8.5 8.5 8.5 8.5 8.5 0 0 0 0 0 0 0 0 1 0 0 21
22 8.5 1.69 8.5 8.5 8.5 8.5 8.5 0 0 0 0 0 0 0 0 0 1 0 22
23 8.5 1.96 8.5 8.5 8.5 8.5 8.5 0 0 0 0 0 0 0 0 0 0 1 23
24 8.6 2.19 8.5 8.5 8.5 8.5 8.5 0 0 0 0 0 0 0 0 0 0 0 24
25 8.4 1.87 8.6 8.5 8.5 8.5 8.5 1 0 0 0 0 0 0 0 0 0 0 25
26 8.1 1.60 8.4 8.6 8.5 8.5 8.5 0 1 0 0 0 0 0 0 0 0 0 26
27 8.0 1.63 8.1 8.4 8.6 8.5 8.5 0 0 1 0 0 0 0 0 0 0 0 27
28 8.0 1.22 8.0 8.1 8.4 8.6 8.5 0 0 0 1 0 0 0 0 0 0 0 28
29 8.0 1.21 8.0 8.0 8.1 8.4 8.6 0 0 0 0 1 0 0 0 0 0 0 29
30 8.0 1.49 8.0 8.0 8.0 8.1 8.4 0 0 0 0 0 1 0 0 0 0 0 30
31 7.9 1.64 8.0 8.0 8.0 8.0 8.1 0 0 0 0 0 0 1 0 0 0 0 31
32 7.8 1.66 7.9 8.0 8.0 8.0 8.0 0 0 0 0 0 0 0 1 0 0 0 32
33 7.8 1.77 7.8 7.9 8.0 8.0 8.0 0 0 0 0 0 0 0 0 1 0 0 33
34 7.9 1.82 7.8 7.8 7.9 8.0 8.0 0 0 0 0 0 0 0 0 0 1 0 34
35 8.1 1.78 7.9 7.8 7.8 7.9 8.0 0 0 0 0 0 0 0 0 0 0 1 35
36 8.0 1.28 8.1 7.9 7.8 7.8 7.9 0 0 0 0 0 0 0 0 0 0 0 36
37 7.6 1.29 8.0 8.1 7.9 7.8 7.8 1 0 0 0 0 0 0 0 0 0 0 37
38 7.3 1.37 7.6 8.0 8.1 7.9 7.8 0 1 0 0 0 0 0 0 0 0 0 38
39 7.0 1.12 7.3 7.6 8.0 8.1 7.9 0 0 1 0 0 0 0 0 0 0 0 39
40 6.8 1.51 7.0 7.3 7.6 8.0 8.1 0 0 0 1 0 0 0 0 0 0 0 40
41 7.0 2.24 6.8 7.0 7.3 7.6 8.0 0 0 0 0 1 0 0 0 0 0 0 41
42 7.1 2.94 7.0 6.8 7.0 7.3 7.6 0 0 0 0 0 1 0 0 0 0 0 42
43 7.2 3.09 7.1 7.0 6.8 7.0 7.3 0 0 0 0 0 0 1 0 0 0 0 43
44 7.1 3.46 7.2 7.1 7.0 6.8 7.0 0 0 0 0 0 0 0 1 0 0 0 44
45 6.9 3.64 7.1 7.2 7.1 7.0 6.8 0 0 0 0 0 0 0 0 1 0 0 45
46 6.7 4.39 6.9 7.1 7.2 7.1 7.0 0 0 0 0 0 0 0 0 0 1 0 46
47 6.7 4.15 6.7 6.9 7.1 7.2 7.1 0 0 0 0 0 0 0 0 0 0 1 47
48 6.6 5.21 6.7 6.7 6.9 7.1 7.2 0 0 0 0 0 0 0 0 0 0 0 48
49 6.9 5.80 6.6 6.7 6.7 6.9 7.1 1 0 0 0 0 0 0 0 0 0 0 49
50 7.3 5.91 6.9 6.6 6.7 6.7 6.9 0 1 0 0 0 0 0 0 0 0 0 50
51 7.5 5.39 7.3 6.9 6.6 6.7 6.7 0 0 1 0 0 0 0 0 0 0 0 51
52 7.3 5.46 7.5 7.3 6.9 6.6 6.7 0 0 0 1 0 0 0 0 0 0 0 52
53 7.1 4.72 7.3 7.5 7.3 6.9 6.6 0 0 0 0 1 0 0 0 0 0 0 53
54 6.9 3.14 7.1 7.3 7.5 7.3 6.9 0 0 0 0 0 1 0 0 0 0 0 54
55 7.1 2.63 6.9 7.1 7.3 7.5 7.3 0 0 0 0 0 0 1 0 0 0 0 55
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
0.5035094 0.0414818 1.3362641 -0.4920880 -0.3059720 0.3156422
Y5 M1 M2 M3 M4 M5
0.0855267 -0.0999994 0.0366516 -0.0228981 -0.0962769 -0.0005262
M6 M7 M8 M9 M10 M11
-0.0440977 0.0416663 -0.0730110 -0.0333482 -0.0083412 0.0012634
t
-0.0046105
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.299952 -0.078021 -0.000996 0.070320 0.246289
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.5035094 0.7579021 0.664 0.5107
X 0.0414818 0.0233401 1.777 0.0840 .
Y1 1.3362641 0.1674898 7.978 1.79e-09 ***
Y2 -0.4920880 0.2690449 -1.829 0.0757 .
Y3 -0.3059720 0.2638443 -1.160 0.2538
Y4 0.3156422 0.2499602 1.263 0.2148
Y5 0.0855267 0.1486741 0.575 0.5687
M1 -0.0999994 0.0923418 -1.083 0.2860
M2 0.0366516 0.0936200 0.391 0.6977
M3 -0.0228981 0.0930560 -0.246 0.8070
M4 -0.0962769 0.0933964 -1.031 0.3095
M5 -0.0005262 0.0938266 -0.006 0.9956
M6 -0.0440977 0.0930473 -0.474 0.6384
M7 0.0416663 0.0927342 0.449 0.6559
M8 -0.0730110 0.0967134 -0.755 0.4552
M9 -0.0333482 0.0973233 -0.343 0.7339
M10 -0.0083412 0.0968620 -0.086 0.9319
M11 0.0012634 0.0966482 0.013 0.9896
t -0.0046105 0.0026755 -1.723 0.0934 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1361 on 36 degrees of freedom
Multiple R-squared: 0.9727, Adjusted R-squared: 0.9591
F-statistic: 71.35 on 18 and 36 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,] 0.13668352 0.2733670 0.8633165
[2,] 0.07306661 0.1461332 0.9269334
[3,] 0.09387265 0.1877453 0.9061273
[4,] 0.06406046 0.1281209 0.9359395
[5,] 0.27016415 0.5403283 0.7298358
[6,] 0.22025126 0.4405025 0.7797487
[7,] 0.36283174 0.7256635 0.6371683
[8,] 0.53004053 0.9399189 0.4699595
[9,] 0.38915418 0.7783084 0.6108458
[10,] 0.31125324 0.6225065 0.6887468
[11,] 0.19655647 0.3931129 0.8034435
[12,] 0.10688309 0.2137662 0.8931169
> postscript(file="/var/www/html/rcomp/tmp/1501a1258556322.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2lvn21258556322.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3pdmc1258556322.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4qfja1258556322.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/519fw1258556322.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 = 55
Frequency = 1
1 2 3 4 5
0.0438567205 0.1570361736 -0.0009959024 0.0848655255 -0.0726234635
6 7 8 9 10
-0.0254019073 0.0123036651 -0.1330697918 -0.0780804448 -0.0324935999
11 12 13 14 15
-0.1833879146 0.2462887878 -0.0814633813 -0.0633741119 0.0370275987
16 17 18 19 20
0.0277698543 -0.0202890653 0.0322974259 -0.0621302469 0.0679427598
21 22 23 24 25
0.0432608734 0.0514868197 0.0352926463 0.1316256695 -0.0841166405
26 27 28 29 30
-0.1884954858 0.1074790200 0.0957172756 -0.0814327808 0.0363351056
31 32 33 34 35
-0.0938184197 0.0668187672 0.1116210451 0.1093444540 0.1733502457
36 37 38 39 40
-0.0779621479 -0.1025731630 -0.0230052261 -0.1467089089 -0.1395745938
41 42 43 44 45
0.1016478219 -0.1077661217 -0.0711944351 -0.0016917352 -0.0768014738
46 47 48 49 50
-0.1283376738 -0.0252549774 -0.2999523094 0.2242964644 0.1178386502
51 52 53 54 55
0.0031981926 -0.0687780616 0.0726974877 0.0645354976 0.2148394366
> postscript(file="/var/www/html/rcomp/tmp/6uav61258556322.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 = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 0.0438567205 NA
1 0.1570361736 0.0438567205
2 -0.0009959024 0.1570361736
3 0.0848655255 -0.0009959024
4 -0.0726234635 0.0848655255
5 -0.0254019073 -0.0726234635
6 0.0123036651 -0.0254019073
7 -0.1330697918 0.0123036651
8 -0.0780804448 -0.1330697918
9 -0.0324935999 -0.0780804448
10 -0.1833879146 -0.0324935999
11 0.2462887878 -0.1833879146
12 -0.0814633813 0.2462887878
13 -0.0633741119 -0.0814633813
14 0.0370275987 -0.0633741119
15 0.0277698543 0.0370275987
16 -0.0202890653 0.0277698543
17 0.0322974259 -0.0202890653
18 -0.0621302469 0.0322974259
19 0.0679427598 -0.0621302469
20 0.0432608734 0.0679427598
21 0.0514868197 0.0432608734
22 0.0352926463 0.0514868197
23 0.1316256695 0.0352926463
24 -0.0841166405 0.1316256695
25 -0.1884954858 -0.0841166405
26 0.1074790200 -0.1884954858
27 0.0957172756 0.1074790200
28 -0.0814327808 0.0957172756
29 0.0363351056 -0.0814327808
30 -0.0938184197 0.0363351056
31 0.0668187672 -0.0938184197
32 0.1116210451 0.0668187672
33 0.1093444540 0.1116210451
34 0.1733502457 0.1093444540
35 -0.0779621479 0.1733502457
36 -0.1025731630 -0.0779621479
37 -0.0230052261 -0.1025731630
38 -0.1467089089 -0.0230052261
39 -0.1395745938 -0.1467089089
40 0.1016478219 -0.1395745938
41 -0.1077661217 0.1016478219
42 -0.0711944351 -0.1077661217
43 -0.0016917352 -0.0711944351
44 -0.0768014738 -0.0016917352
45 -0.1283376738 -0.0768014738
46 -0.0252549774 -0.1283376738
47 -0.2999523094 -0.0252549774
48 0.2242964644 -0.2999523094
49 0.1178386502 0.2242964644
50 0.0031981926 0.1178386502
51 -0.0687780616 0.0031981926
52 0.0726974877 -0.0687780616
53 0.0645354976 0.0726974877
54 0.2148394366 0.0645354976
55 NA 0.2148394366
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.1570361736 0.0438567205
[2,] -0.0009959024 0.1570361736
[3,] 0.0848655255 -0.0009959024
[4,] -0.0726234635 0.0848655255
[5,] -0.0254019073 -0.0726234635
[6,] 0.0123036651 -0.0254019073
[7,] -0.1330697918 0.0123036651
[8,] -0.0780804448 -0.1330697918
[9,] -0.0324935999 -0.0780804448
[10,] -0.1833879146 -0.0324935999
[11,] 0.2462887878 -0.1833879146
[12,] -0.0814633813 0.2462887878
[13,] -0.0633741119 -0.0814633813
[14,] 0.0370275987 -0.0633741119
[15,] 0.0277698543 0.0370275987
[16,] -0.0202890653 0.0277698543
[17,] 0.0322974259 -0.0202890653
[18,] -0.0621302469 0.0322974259
[19,] 0.0679427598 -0.0621302469
[20,] 0.0432608734 0.0679427598
[21,] 0.0514868197 0.0432608734
[22,] 0.0352926463 0.0514868197
[23,] 0.1316256695 0.0352926463
[24,] -0.0841166405 0.1316256695
[25,] -0.1884954858 -0.0841166405
[26,] 0.1074790200 -0.1884954858
[27,] 0.0957172756 0.1074790200
[28,] -0.0814327808 0.0957172756
[29,] 0.0363351056 -0.0814327808
[30,] -0.0938184197 0.0363351056
[31,] 0.0668187672 -0.0938184197
[32,] 0.1116210451 0.0668187672
[33,] 0.1093444540 0.1116210451
[34,] 0.1733502457 0.1093444540
[35,] -0.0779621479 0.1733502457
[36,] -0.1025731630 -0.0779621479
[37,] -0.0230052261 -0.1025731630
[38,] -0.1467089089 -0.0230052261
[39,] -0.1395745938 -0.1467089089
[40,] 0.1016478219 -0.1395745938
[41,] -0.1077661217 0.1016478219
[42,] -0.0711944351 -0.1077661217
[43,] -0.0016917352 -0.0711944351
[44,] -0.0768014738 -0.0016917352
[45,] -0.1283376738 -0.0768014738
[46,] -0.0252549774 -0.1283376738
[47,] -0.2999523094 -0.0252549774
[48,] 0.2242964644 -0.2999523094
[49,] 0.1178386502 0.2242964644
[50,] 0.0031981926 0.1178386502
[51,] -0.0687780616 0.0031981926
[52,] 0.0726974877 -0.0687780616
[53,] 0.0645354976 0.0726974877
[54,] 0.2148394366 0.0645354976
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.1570361736 0.0438567205
2 -0.0009959024 0.1570361736
3 0.0848655255 -0.0009959024
4 -0.0726234635 0.0848655255
5 -0.0254019073 -0.0726234635
6 0.0123036651 -0.0254019073
7 -0.1330697918 0.0123036651
8 -0.0780804448 -0.1330697918
9 -0.0324935999 -0.0780804448
10 -0.1833879146 -0.0324935999
11 0.2462887878 -0.1833879146
12 -0.0814633813 0.2462887878
13 -0.0633741119 -0.0814633813
14 0.0370275987 -0.0633741119
15 0.0277698543 0.0370275987
16 -0.0202890653 0.0277698543
17 0.0322974259 -0.0202890653
18 -0.0621302469 0.0322974259
19 0.0679427598 -0.0621302469
20 0.0432608734 0.0679427598
21 0.0514868197 0.0432608734
22 0.0352926463 0.0514868197
23 0.1316256695 0.0352926463
24 -0.0841166405 0.1316256695
25 -0.1884954858 -0.0841166405
26 0.1074790200 -0.1884954858
27 0.0957172756 0.1074790200
28 -0.0814327808 0.0957172756
29 0.0363351056 -0.0814327808
30 -0.0938184197 0.0363351056
31 0.0668187672 -0.0938184197
32 0.1116210451 0.0668187672
33 0.1093444540 0.1116210451
34 0.1733502457 0.1093444540
35 -0.0779621479 0.1733502457
36 -0.1025731630 -0.0779621479
37 -0.0230052261 -0.1025731630
38 -0.1467089089 -0.0230052261
39 -0.1395745938 -0.1467089089
40 0.1016478219 -0.1395745938
41 -0.1077661217 0.1016478219
42 -0.0711944351 -0.1077661217
43 -0.0016917352 -0.0711944351
44 -0.0768014738 -0.0016917352
45 -0.1283376738 -0.0768014738
46 -0.0252549774 -0.1283376738
47 -0.2999523094 -0.0252549774
48 0.2242964644 -0.2999523094
49 0.1178386502 0.2242964644
50 0.0031981926 0.1178386502
51 -0.0687780616 0.0031981926
52 0.0726974877 -0.0687780616
53 0.0645354976 0.0726974877
54 0.2148394366 0.0645354976
> 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/741nq1258556322.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/83b3u1258556322.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9meag1258556322.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10dhqs1258556322.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11hg6y1258556322.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/12e3iz1258556322.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/13hoxt1258556322.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/14581c1258556322.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/15a2f01258556322.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/166k9s1258556322.tab")
+ }
>
> system("convert tmp/1501a1258556322.ps tmp/1501a1258556322.png")
> system("convert tmp/2lvn21258556322.ps tmp/2lvn21258556322.png")
> system("convert tmp/3pdmc1258556322.ps tmp/3pdmc1258556322.png")
> system("convert tmp/4qfja1258556322.ps tmp/4qfja1258556322.png")
> system("convert tmp/519fw1258556322.ps tmp/519fw1258556322.png")
> system("convert tmp/6uav61258556322.ps tmp/6uav61258556322.png")
> system("convert tmp/741nq1258556322.ps tmp/741nq1258556322.png")
> system("convert tmp/83b3u1258556322.ps tmp/83b3u1258556322.png")
> system("convert tmp/9meag1258556322.ps tmp/9meag1258556322.png")
> system("convert tmp/10dhqs1258556322.ps tmp/10dhqs1258556322.png")
>
>
> proc.time()
user system elapsed
2.335 1.565 3.474