R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(2.08
+ ,1.00
+ ,2.05
+ ,2.09
+ ,2.11
+ ,2.05
+ ,2.06
+ ,1.00
+ ,2.08
+ ,2.05
+ ,2.09
+ ,2.11
+ ,2.06
+ ,1.00
+ ,2.06
+ ,2.08
+ ,2.05
+ ,2.09
+ ,2.08
+ ,1.00
+ ,2.06
+ ,2.06
+ ,2.08
+ ,2.05
+ ,2.07
+ ,1.00
+ ,2.08
+ ,2.06
+ ,2.06
+ ,2.08
+ ,2.06
+ ,1.00
+ ,2.07
+ ,2.08
+ ,2.06
+ ,2.06
+ ,2.07
+ ,1.00
+ ,2.06
+ ,2.07
+ ,2.08
+ ,2.06
+ ,2.06
+ ,1.00
+ ,2.07
+ ,2.06
+ ,2.07
+ ,2.08
+ ,2.09
+ ,1.00
+ ,2.06
+ ,2.07
+ ,2.06
+ ,2.07
+ ,2.07
+ ,1.00
+ ,2.09
+ ,2.06
+ ,2.07
+ ,2.06
+ ,2.09
+ ,1.00
+ ,2.07
+ ,2.09
+ ,2.06
+ ,2.07
+ ,2.28
+ ,1.25
+ ,2.09
+ ,2.07
+ ,2.09
+ ,2.06
+ ,2.33
+ ,1.25
+ ,2.28
+ ,2.09
+ ,2.07
+ ,2.09
+ ,2.35
+ ,1.25
+ ,2.33
+ ,2.28
+ ,2.09
+ ,2.07
+ ,2.52
+ ,1.50
+ ,2.35
+ ,2.33
+ ,2.28
+ ,2.09
+ ,2.63
+ ,1.50
+ ,2.52
+ ,2.35
+ ,2.33
+ ,2.28
+ ,2.58
+ ,1.50
+ ,2.63
+ ,2.52
+ ,2.35
+ ,2.33
+ ,2.70
+ ,1.75
+ ,2.58
+ ,2.63
+ ,2.52
+ ,2.35
+ ,2.81
+ ,1.75
+ ,2.70
+ ,2.58
+ ,2.63
+ ,2.52
+ ,2.97
+ ,2.00
+ ,2.81
+ ,2.70
+ ,2.58
+ ,2.63
+ ,3.04
+ ,2.00
+ ,2.97
+ ,2.81
+ ,2.70
+ ,2.58
+ ,3.28
+ ,2.25
+ ,3.04
+ ,2.97
+ ,2.81
+ ,2.70
+ ,3.33
+ ,2.25
+ ,3.28
+ ,3.04
+ ,2.97
+ ,2.81
+ ,3.50
+ ,2.50
+ ,3.33
+ ,3.28
+ ,3.04
+ ,2.97
+ ,3.56
+ ,2.50
+ ,3.50
+ ,3.33
+ ,3.28
+ ,3.04
+ ,3.57
+ ,2.50
+ ,3.56
+ ,3.50
+ ,3.33
+ ,3.28
+ ,3.69
+ ,2.75
+ ,3.57
+ ,3.56
+ ,3.50
+ ,3.33
+ ,3.82
+ ,2.75
+ ,3.69
+ ,3.57
+ ,3.56
+ ,3.50
+ ,3.79
+ ,2.75
+ ,3.82
+ ,3.69
+ ,3.57
+ ,3.56
+ ,3.96
+ ,3.00
+ ,3.79
+ ,3.82
+ ,3.69
+ ,3.57
+ ,4.06
+ ,3.00
+ ,3.96
+ ,3.79
+ ,3.82
+ ,3.69
+ ,4.05
+ ,3.00
+ ,4.06
+ ,3.96
+ ,3.79
+ ,3.82
+ ,4.03
+ ,3.00
+ ,4.05
+ ,4.06
+ ,3.96
+ ,3.79
+ ,3.94
+ ,3.00
+ ,4.03
+ ,4.05
+ ,4.06
+ ,3.96
+ ,4.02
+ ,3.00
+ ,3.94
+ ,4.03
+ ,4.05
+ ,4.06
+ ,3.88
+ ,3.00
+ ,4.02
+ ,3.94
+ ,4.03
+ ,4.05
+ ,4.02
+ ,3.00
+ ,3.88
+ ,4.02
+ ,3.94
+ ,4.03
+ ,4.03
+ ,3.00
+ ,4.02
+ ,3.88
+ ,4.02
+ ,3.94
+ ,4.09
+ ,3.00
+ ,4.03
+ ,4.02
+ ,3.88
+ ,4.02
+ ,3.99
+ ,3.00
+ ,4.09
+ ,4.03
+ ,4.02
+ ,3.88
+ ,4.01
+ ,3.00
+ ,3.99
+ ,4.09
+ ,4.03
+ ,4.02
+ ,4.01
+ ,3.00
+ ,4.01
+ ,3.99
+ ,4.09
+ ,4.03
+ ,4.19
+ ,3.25
+ ,4.01
+ ,4.01
+ ,3.99
+ ,4.09
+ ,4.30
+ ,3.25
+ ,4.19
+ ,4.01
+ ,4.01
+ ,3.99
+ ,4.27
+ ,3.25
+ ,4.30
+ ,4.19
+ ,4.01
+ ,4.01
+ ,3.82
+ ,3.25
+ ,4.27
+ ,4.30
+ ,4.19
+ ,4.01
+ ,3.15
+ ,2.75
+ ,3.82
+ ,4.27
+ ,4.30
+ ,4.19
+ ,2.49
+ ,2.00
+ ,3.15
+ ,3.82
+ ,4.27
+ ,4.30
+ ,1.81
+ ,1.00
+ ,2.49
+ ,3.15
+ ,3.82
+ ,4.27
+ ,1.26
+ ,1.00
+ ,1.81
+ ,2.49
+ ,3.15
+ ,3.82
+ ,1.06
+ ,0.50
+ ,1.26
+ ,1.81
+ ,2.49
+ ,3.15
+ ,0.84
+ ,0.25
+ ,1.06
+ ,1.26
+ ,1.81
+ ,2.49
+ ,0.78
+ ,0.25
+ ,0.84
+ ,1.06
+ ,1.26
+ ,1.81
+ ,0.70
+ ,0.25
+ ,0.78
+ ,0.84
+ ,1.06
+ ,1.26
+ ,0.36
+ ,0.25
+ ,0.70
+ ,0.78
+ ,0.84
+ ,1.06
+ ,0.35
+ ,0.25
+ ,0.36
+ ,0.70
+ ,0.78
+ ,0.84)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y-1'
+ ,'Y-2'
+ ,'Y-3'
+ ,'Y-4')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('Y','X','Y-1','Y-2','Y-3','Y-4'),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 Y-1 Y-2 Y-3 Y-4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 2.08 1.00 2.05 2.09 2.11 2.05 1 0 0 0 0 0 0 0 0 0 0 1
2 2.06 1.00 2.08 2.05 2.09 2.11 0 1 0 0 0 0 0 0 0 0 0 2
3 2.06 1.00 2.06 2.08 2.05 2.09 0 0 1 0 0 0 0 0 0 0 0 3
4 2.08 1.00 2.06 2.06 2.08 2.05 0 0 0 1 0 0 0 0 0 0 0 4
5 2.07 1.00 2.08 2.06 2.06 2.08 0 0 0 0 1 0 0 0 0 0 0 5
6 2.06 1.00 2.07 2.08 2.06 2.06 0 0 0 0 0 1 0 0 0 0 0 6
7 2.07 1.00 2.06 2.07 2.08 2.06 0 0 0 0 0 0 1 0 0 0 0 7
8 2.06 1.00 2.07 2.06 2.07 2.08 0 0 0 0 0 0 0 1 0 0 0 8
9 2.09 1.00 2.06 2.07 2.06 2.07 0 0 0 0 0 0 0 0 1 0 0 9
10 2.07 1.00 2.09 2.06 2.07 2.06 0 0 0 0 0 0 0 0 0 1 0 10
11 2.09 1.00 2.07 2.09 2.06 2.07 0 0 0 0 0 0 0 0 0 0 1 11
12 2.28 1.25 2.09 2.07 2.09 2.06 0 0 0 0 0 0 0 0 0 0 0 12
13 2.33 1.25 2.28 2.09 2.07 2.09 1 0 0 0 0 0 0 0 0 0 0 13
14 2.35 1.25 2.33 2.28 2.09 2.07 0 1 0 0 0 0 0 0 0 0 0 14
15 2.52 1.50 2.35 2.33 2.28 2.09 0 0 1 0 0 0 0 0 0 0 0 15
16 2.63 1.50 2.52 2.35 2.33 2.28 0 0 0 1 0 0 0 0 0 0 0 16
17 2.58 1.50 2.63 2.52 2.35 2.33 0 0 0 0 1 0 0 0 0 0 0 17
18 2.70 1.75 2.58 2.63 2.52 2.35 0 0 0 0 0 1 0 0 0 0 0 18
19 2.81 1.75 2.70 2.58 2.63 2.52 0 0 0 0 0 0 1 0 0 0 0 19
20 2.97 2.00 2.81 2.70 2.58 2.63 0 0 0 0 0 0 0 1 0 0 0 20
21 3.04 2.00 2.97 2.81 2.70 2.58 0 0 0 0 0 0 0 0 1 0 0 21
22 3.28 2.25 3.04 2.97 2.81 2.70 0 0 0 0 0 0 0 0 0 1 0 22
23 3.33 2.25 3.28 3.04 2.97 2.81 0 0 0 0 0 0 0 0 0 0 1 23
24 3.50 2.50 3.33 3.28 3.04 2.97 0 0 0 0 0 0 0 0 0 0 0 24
25 3.56 2.50 3.50 3.33 3.28 3.04 1 0 0 0 0 0 0 0 0 0 0 25
26 3.57 2.50 3.56 3.50 3.33 3.28 0 1 0 0 0 0 0 0 0 0 0 26
27 3.69 2.75 3.57 3.56 3.50 3.33 0 0 1 0 0 0 0 0 0 0 0 27
28 3.82 2.75 3.69 3.57 3.56 3.50 0 0 0 1 0 0 0 0 0 0 0 28
29 3.79 2.75 3.82 3.69 3.57 3.56 0 0 0 0 1 0 0 0 0 0 0 29
30 3.96 3.00 3.79 3.82 3.69 3.57 0 0 0 0 0 1 0 0 0 0 0 30
31 4.06 3.00 3.96 3.79 3.82 3.69 0 0 0 0 0 0 1 0 0 0 0 31
32 4.05 3.00 4.06 3.96 3.79 3.82 0 0 0 0 0 0 0 1 0 0 0 32
33 4.03 3.00 4.05 4.06 3.96 3.79 0 0 0 0 0 0 0 0 1 0 0 33
34 3.94 3.00 4.03 4.05 4.06 3.96 0 0 0 0 0 0 0 0 0 1 0 34
35 4.02 3.00 3.94 4.03 4.05 4.06 0 0 0 0 0 0 0 0 0 0 1 35
36 3.88 3.00 4.02 3.94 4.03 4.05 0 0 0 0 0 0 0 0 0 0 0 36
37 4.02 3.00 3.88 4.02 3.94 4.03 1 0 0 0 0 0 0 0 0 0 0 37
38 4.03 3.00 4.02 3.88 4.02 3.94 0 1 0 0 0 0 0 0 0 0 0 38
39 4.09 3.00 4.03 4.02 3.88 4.02 0 0 1 0 0 0 0 0 0 0 0 39
40 3.99 3.00 4.09 4.03 4.02 3.88 0 0 0 1 0 0 0 0 0 0 0 40
41 4.01 3.00 3.99 4.09 4.03 4.02 0 0 0 0 1 0 0 0 0 0 0 41
42 4.01 3.00 4.01 3.99 4.09 4.03 0 0 0 0 0 1 0 0 0 0 0 42
43 4.19 3.25 4.01 4.01 3.99 4.09 0 0 0 0 0 0 1 0 0 0 0 43
44 4.30 3.25 4.19 4.01 4.01 3.99 0 0 0 0 0 0 0 1 0 0 0 44
45 4.27 3.25 4.30 4.19 4.01 4.01 0 0 0 0 0 0 0 0 1 0 0 45
46 3.82 3.25 4.27 4.30 4.19 4.01 0 0 0 0 0 0 0 0 0 1 0 46
47 3.15 2.75 3.82 4.27 4.30 4.19 0 0 0 0 0 0 0 0 0 0 1 47
48 2.49 2.00 3.15 3.82 4.27 4.30 0 0 0 0 0 0 0 0 0 0 0 48
49 1.81 1.00 2.49 3.15 3.82 4.27 1 0 0 0 0 0 0 0 0 0 0 49
50 1.26 1.00 1.81 2.49 3.15 3.82 0 1 0 0 0 0 0 0 0 0 0 50
51 1.06 0.50 1.26 1.81 2.49 3.15 0 0 1 0 0 0 0 0 0 0 0 51
52 0.84 0.25 1.06 1.26 1.81 2.49 0 0 0 1 0 0 0 0 0 0 0 52
53 0.78 0.25 0.84 1.06 1.26 1.81 0 0 0 0 1 0 0 0 0 0 0 53
54 0.70 0.25 0.78 0.84 1.06 1.26 0 0 0 0 0 1 0 0 0 0 0 54
55 0.36 0.25 0.70 0.78 0.84 1.06 0 0 0 0 0 0 1 0 0 0 0 55
56 0.35 0.25 0.36 0.70 0.78 0.84 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 `Y-1` `Y-2` `Y-3` `Y-4`
0.685919 0.845279 0.788576 -0.607031 -0.244014 0.345412
M1 M2 M3 M4 M5 M6
0.082656 -0.016055 0.073721 0.040490 0.054801 0.078296
M7 M8 M9 M10 M11 t
-0.001715 0.027510 0.066628 -0.027028 0.010886 -0.010870
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.20571 -0.04492 0.01779 0.05729 0.13458
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.685919 0.112217 6.112 3.99e-07 ***
X 0.845279 0.124268 6.802 4.56e-08 ***
`Y-1` 0.788576 0.162467 4.854 2.09e-05 ***
`Y-2` -0.607031 0.220893 -2.748 0.00912 **
`Y-3` -0.244014 0.232627 -1.049 0.30083
`Y-4` 0.345412 0.128304 2.692 0.01050 *
M1 0.082656 0.066421 1.244 0.22096
M2 -0.016055 0.066433 -0.242 0.81033
M3 0.073721 0.065686 1.122 0.26877
M4 0.040490 0.068564 0.591 0.55832
M5 0.054801 0.070923 0.773 0.44448
M6 0.078296 0.065971 1.187 0.24266
M7 -0.001715 0.067359 -0.025 0.97983
M8 0.027510 0.067721 0.406 0.68686
M9 0.066628 0.071731 0.929 0.35882
M10 -0.027028 0.069232 -0.390 0.69843
M11 0.010886 0.069151 0.157 0.87575
t -0.010870 0.001735 -6.263 2.48e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.09577 on 38 degrees of freedom
Multiple R-squared: 0.9949, Adjusted R-squared: 0.9927
F-statistic: 439.7 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,] 1.974016e-02 3.948031e-02 0.9802598
[2,] 1.569491e-02 3.138982e-02 0.9843051
[3,] 3.804517e-03 7.609035e-03 0.9961955
[4,] 1.012387e-03 2.024774e-03 0.9989876
[5,] 2.800837e-04 5.601674e-04 0.9997199
[6,] 1.629921e-04 3.259843e-04 0.9998370
[7,] 1.043242e-04 2.086484e-04 0.9998957
[8,] 2.981895e-05 5.963791e-05 0.9999702
[9,] 2.546207e-05 5.092414e-05 0.9999745
[10,] 8.135629e-06 1.627126e-05 0.9999919
[11,] 3.451683e-06 6.903367e-06 0.9999965
[12,] 8.554821e-07 1.710964e-06 0.9999991
[13,] 1.100148e-06 2.200297e-06 0.9999989
[14,] 4.810552e-06 9.621105e-06 0.9999952
[15,] 1.247376e-04 2.494752e-04 0.9998753
> postscript(file="/var/www/html/rcomp/tmp/1j6dh1258737503.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2eg461258737503.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/30dct1258737503.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/43n801258737503.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ytz41258737503.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
-0.064096862 -0.048059448 -0.095835107 -0.022738695 -0.067194162 -0.062884314
7 8 9 10 11 12
0.044691716 -0.006967668 0.009754434 0.070446273 0.091490926 0.074789229
13 14 15 16 17 18
-0.099928479 0.117347906 0.051156727 0.029912001 -0.019467827 0.017363931
19 20 21 22 23 24
0.061385072 -0.072385281 -0.043479870 0.117042232 -0.005720585 0.042788950
25 26 27 28 29 30
-0.038319258 0.066444150 -0.051033579 -0.009571430 -0.090968563 -0.016514280
31 32 33 34 35 36
0.012369507 -0.043871786 0.028313735 0.018221524 0.093027947 -0.144361413
37 38 39 40 41 42
0.067762520 0.042566576 0.038964478 0.024339876 0.110260531 0.032347887
43 44 45 46 47 48
0.058923022 0.048045770 0.005411700 -0.205710030 -0.178798288 0.026783234
49 50 51 52 53 54
0.134582080 -0.178299184 0.056747482 -0.021941752 0.067370021 0.029686776
55 56
-0.177369316 0.075178964
> postscript(file="/var/www/html/rcomp/tmp/63elj1258737503.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 -0.064096862 NA
1 -0.048059448 -0.064096862
2 -0.095835107 -0.048059448
3 -0.022738695 -0.095835107
4 -0.067194162 -0.022738695
5 -0.062884314 -0.067194162
6 0.044691716 -0.062884314
7 -0.006967668 0.044691716
8 0.009754434 -0.006967668
9 0.070446273 0.009754434
10 0.091490926 0.070446273
11 0.074789229 0.091490926
12 -0.099928479 0.074789229
13 0.117347906 -0.099928479
14 0.051156727 0.117347906
15 0.029912001 0.051156727
16 -0.019467827 0.029912001
17 0.017363931 -0.019467827
18 0.061385072 0.017363931
19 -0.072385281 0.061385072
20 -0.043479870 -0.072385281
21 0.117042232 -0.043479870
22 -0.005720585 0.117042232
23 0.042788950 -0.005720585
24 -0.038319258 0.042788950
25 0.066444150 -0.038319258
26 -0.051033579 0.066444150
27 -0.009571430 -0.051033579
28 -0.090968563 -0.009571430
29 -0.016514280 -0.090968563
30 0.012369507 -0.016514280
31 -0.043871786 0.012369507
32 0.028313735 -0.043871786
33 0.018221524 0.028313735
34 0.093027947 0.018221524
35 -0.144361413 0.093027947
36 0.067762520 -0.144361413
37 0.042566576 0.067762520
38 0.038964478 0.042566576
39 0.024339876 0.038964478
40 0.110260531 0.024339876
41 0.032347887 0.110260531
42 0.058923022 0.032347887
43 0.048045770 0.058923022
44 0.005411700 0.048045770
45 -0.205710030 0.005411700
46 -0.178798288 -0.205710030
47 0.026783234 -0.178798288
48 0.134582080 0.026783234
49 -0.178299184 0.134582080
50 0.056747482 -0.178299184
51 -0.021941752 0.056747482
52 0.067370021 -0.021941752
53 0.029686776 0.067370021
54 -0.177369316 0.029686776
55 0.075178964 -0.177369316
56 NA 0.075178964
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.048059448 -0.064096862
[2,] -0.095835107 -0.048059448
[3,] -0.022738695 -0.095835107
[4,] -0.067194162 -0.022738695
[5,] -0.062884314 -0.067194162
[6,] 0.044691716 -0.062884314
[7,] -0.006967668 0.044691716
[8,] 0.009754434 -0.006967668
[9,] 0.070446273 0.009754434
[10,] 0.091490926 0.070446273
[11,] 0.074789229 0.091490926
[12,] -0.099928479 0.074789229
[13,] 0.117347906 -0.099928479
[14,] 0.051156727 0.117347906
[15,] 0.029912001 0.051156727
[16,] -0.019467827 0.029912001
[17,] 0.017363931 -0.019467827
[18,] 0.061385072 0.017363931
[19,] -0.072385281 0.061385072
[20,] -0.043479870 -0.072385281
[21,] 0.117042232 -0.043479870
[22,] -0.005720585 0.117042232
[23,] 0.042788950 -0.005720585
[24,] -0.038319258 0.042788950
[25,] 0.066444150 -0.038319258
[26,] -0.051033579 0.066444150
[27,] -0.009571430 -0.051033579
[28,] -0.090968563 -0.009571430
[29,] -0.016514280 -0.090968563
[30,] 0.012369507 -0.016514280
[31,] -0.043871786 0.012369507
[32,] 0.028313735 -0.043871786
[33,] 0.018221524 0.028313735
[34,] 0.093027947 0.018221524
[35,] -0.144361413 0.093027947
[36,] 0.067762520 -0.144361413
[37,] 0.042566576 0.067762520
[38,] 0.038964478 0.042566576
[39,] 0.024339876 0.038964478
[40,] 0.110260531 0.024339876
[41,] 0.032347887 0.110260531
[42,] 0.058923022 0.032347887
[43,] 0.048045770 0.058923022
[44,] 0.005411700 0.048045770
[45,] -0.205710030 0.005411700
[46,] -0.178798288 -0.205710030
[47,] 0.026783234 -0.178798288
[48,] 0.134582080 0.026783234
[49,] -0.178299184 0.134582080
[50,] 0.056747482 -0.178299184
[51,] -0.021941752 0.056747482
[52,] 0.067370021 -0.021941752
[53,] 0.029686776 0.067370021
[54,] -0.177369316 0.029686776
[55,] 0.075178964 -0.177369316
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.048059448 -0.064096862
2 -0.095835107 -0.048059448
3 -0.022738695 -0.095835107
4 -0.067194162 -0.022738695
5 -0.062884314 -0.067194162
6 0.044691716 -0.062884314
7 -0.006967668 0.044691716
8 0.009754434 -0.006967668
9 0.070446273 0.009754434
10 0.091490926 0.070446273
11 0.074789229 0.091490926
12 -0.099928479 0.074789229
13 0.117347906 -0.099928479
14 0.051156727 0.117347906
15 0.029912001 0.051156727
16 -0.019467827 0.029912001
17 0.017363931 -0.019467827
18 0.061385072 0.017363931
19 -0.072385281 0.061385072
20 -0.043479870 -0.072385281
21 0.117042232 -0.043479870
22 -0.005720585 0.117042232
23 0.042788950 -0.005720585
24 -0.038319258 0.042788950
25 0.066444150 -0.038319258
26 -0.051033579 0.066444150
27 -0.009571430 -0.051033579
28 -0.090968563 -0.009571430
29 -0.016514280 -0.090968563
30 0.012369507 -0.016514280
31 -0.043871786 0.012369507
32 0.028313735 -0.043871786
33 0.018221524 0.028313735
34 0.093027947 0.018221524
35 -0.144361413 0.093027947
36 0.067762520 -0.144361413
37 0.042566576 0.067762520
38 0.038964478 0.042566576
39 0.024339876 0.038964478
40 0.110260531 0.024339876
41 0.032347887 0.110260531
42 0.058923022 0.032347887
43 0.048045770 0.058923022
44 0.005411700 0.048045770
45 -0.205710030 0.005411700
46 -0.178798288 -0.205710030
47 0.026783234 -0.178798288
48 0.134582080 0.026783234
49 -0.178299184 0.134582080
50 0.056747482 -0.178299184
51 -0.021941752 0.056747482
52 0.067370021 -0.021941752
53 0.029686776 0.067370021
54 -0.177369316 0.029686776
55 0.075178964 -0.177369316
> 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/7e0vt1258737503.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/84i7d1258737503.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9lfjr1258737503.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ovsi1258737503.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11i66g1258737503.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/12dyaf1258737503.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/136fez1258737503.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/14u2hz1258737503.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/15fyrq1258737503.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/16iosp1258737503.tab")
+ }
>
> system("convert tmp/1j6dh1258737503.ps tmp/1j6dh1258737503.png")
> system("convert tmp/2eg461258737503.ps tmp/2eg461258737503.png")
> system("convert tmp/30dct1258737503.ps tmp/30dct1258737503.png")
> system("convert tmp/43n801258737503.ps tmp/43n801258737503.png")
> system("convert tmp/5ytz41258737503.ps tmp/5ytz41258737503.png")
> system("convert tmp/63elj1258737503.ps tmp/63elj1258737503.png")
> system("convert tmp/7e0vt1258737503.ps tmp/7e0vt1258737503.png")
> system("convert tmp/84i7d1258737503.ps tmp/84i7d1258737503.png")
> system("convert tmp/9lfjr1258737503.ps tmp/9lfjr1258737503.png")
> system("convert tmp/10ovsi1258737503.ps tmp/10ovsi1258737503.png")
>
>
> proc.time()
user system elapsed
2.372 1.569 3.892