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(7.9
+ ,9.1
+ ,7.6
+ ,7.5
+ ,7.9
+ ,9
+ ,7.9
+ ,7.6
+ ,8.1
+ ,9.3
+ ,7.9
+ ,7.9
+ ,8.2
+ ,9.9
+ ,8.1
+ ,7.9
+ ,8
+ ,9.8
+ ,8.2
+ ,8.1
+ ,7.5
+ ,9.3
+ ,8
+ ,8.2
+ ,6.8
+ ,8.3
+ ,7.5
+ ,8
+ ,6.5
+ ,8
+ ,6.8
+ ,7.5
+ ,6.6
+ ,8.5
+ ,6.5
+ ,6.8
+ ,7.6
+ ,10.4
+ ,6.6
+ ,6.5
+ ,8
+ ,11.1
+ ,7.6
+ ,6.6
+ ,8.1
+ ,10.9
+ ,8
+ ,7.6
+ ,7.7
+ ,10
+ ,8.1
+ ,8
+ ,7.5
+ ,9.2
+ ,7.7
+ ,8.1
+ ,7.6
+ ,9.2
+ ,7.5
+ ,7.7
+ ,7.8
+ ,9.5
+ ,7.6
+ ,7.5
+ ,7.8
+ ,9.6
+ ,7.8
+ ,7.6
+ ,7.8
+ ,9.5
+ ,7.8
+ ,7.8
+ ,7.5
+ ,9.1
+ ,7.8
+ ,7.8
+ ,7.5
+ ,8.9
+ ,7.5
+ ,7.8
+ ,7.1
+ ,9
+ ,7.5
+ ,7.5
+ ,7.5
+ ,10.1
+ ,7.1
+ ,7.5
+ ,7.5
+ ,10.3
+ ,7.5
+ ,7.1
+ ,7.6
+ ,10.2
+ ,7.5
+ ,7.5
+ ,7.7
+ ,9.6
+ ,7.6
+ ,7.5
+ ,7.7
+ ,9.2
+ ,7.7
+ ,7.6
+ ,7.9
+ ,9.3
+ ,7.7
+ ,7.7
+ ,8.1
+ ,9.4
+ ,7.9
+ ,7.7
+ ,8.2
+ ,9.4
+ ,8.1
+ ,7.9
+ ,8.2
+ ,9.2
+ ,8.2
+ ,8.1
+ ,8.2
+ ,9
+ ,8.2
+ ,8.2
+ ,7.9
+ ,9
+ ,8.2
+ ,8.2
+ ,7.3
+ ,9
+ ,7.9
+ ,8.2
+ ,6.9
+ ,9.8
+ ,7.3
+ ,7.9
+ ,6.6
+ ,10
+ ,6.9
+ ,7.3
+ ,6.7
+ ,9.8
+ ,6.6
+ ,6.9
+ ,6.9
+ ,9.3
+ ,6.7
+ ,6.6
+ ,7
+ ,9
+ ,6.9
+ ,6.7
+ ,7.1
+ ,9
+ ,7
+ ,6.9
+ ,7.2
+ ,9.1
+ ,7.1
+ ,7
+ ,7.1
+ ,9.1
+ ,7.2
+ ,7.1
+ ,6.9
+ ,9.1
+ ,7.1
+ ,7.2
+ ,7
+ ,9.2
+ ,6.9
+ ,7.1
+ ,6.8
+ ,8.8
+ ,7
+ ,6.9
+ ,6.4
+ ,8.3
+ ,6.8
+ ,7
+ ,6.7
+ ,8.4
+ ,6.4
+ ,6.8
+ ,6.6
+ ,8.1
+ ,6.7
+ ,6.4
+ ,6.4
+ ,7.7
+ ,6.6
+ ,6.7
+ ,6.3
+ ,7.9
+ ,6.4
+ ,6.6
+ ,6.2
+ ,7.9
+ ,6.3
+ ,6.4
+ ,6.5
+ ,8
+ ,6.2
+ ,6.3
+ ,6.8
+ ,7.9
+ ,6.5
+ ,6.2
+ ,6.8
+ ,7.6
+ ,6.8
+ ,6.5
+ ,6.4
+ ,7.1
+ ,6.8
+ ,6.8
+ ,6.1
+ ,6.8
+ ,6.4
+ ,6.8
+ ,5.8
+ ,6.5
+ ,6.1
+ ,6.4
+ ,6.1
+ ,6.9
+ ,5.8
+ ,6.1
+ ,7.2
+ ,8.2
+ ,6.1
+ ,5.8
+ ,7.3
+ ,8.7
+ ,7.2
+ ,6.1
+ ,6.9
+ ,8.3
+ ,7.3
+ ,7.2
+ ,6.1
+ ,7.9
+ ,6.9
+ ,7.3
+ ,5.8
+ ,7.5
+ ,6.1
+ ,6.9
+ ,6.2
+ ,7.8
+ ,5.8
+ ,6.1
+ ,7.1
+ ,8.3
+ ,6.2
+ ,5.8
+ ,7.7
+ ,8.4
+ ,7.1
+ ,6.2
+ ,7.9
+ ,8.2
+ ,7.7
+ ,7.1
+ ,7.7
+ ,7.7
+ ,7.9
+ ,7.7
+ ,7.4
+ ,7.2
+ ,7.7
+ ,7.9
+ ,7.5
+ ,7.3
+ ,7.4
+ ,7.7)
+ ,dim=c(4
+ ,69)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2')
+ ,1:69))
> y <- array(NA,dim=c(4,69),dimnames=list(c('Y','X','Y1','Y2'),1:69))
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 7.9 9.1 7.6 7.5 1 0 0 0 0 0 0 0 0 0 0 1
2 7.9 9.0 7.9 7.6 0 1 0 0 0 0 0 0 0 0 0 2
3 8.1 9.3 7.9 7.9 0 0 1 0 0 0 0 0 0 0 0 3
4 8.2 9.9 8.1 7.9 0 0 0 1 0 0 0 0 0 0 0 4
5 8.0 9.8 8.2 8.1 0 0 0 0 1 0 0 0 0 0 0 5
6 7.5 9.3 8.0 8.2 0 0 0 0 0 1 0 0 0 0 0 6
7 6.8 8.3 7.5 8.0 0 0 0 0 0 0 1 0 0 0 0 7
8 6.5 8.0 6.8 7.5 0 0 0 0 0 0 0 1 0 0 0 8
9 6.6 8.5 6.5 6.8 0 0 0 0 0 0 0 0 1 0 0 9
10 7.6 10.4 6.6 6.5 0 0 0 0 0 0 0 0 0 1 0 10
11 8.0 11.1 7.6 6.6 0 0 0 0 0 0 0 0 0 0 1 11
12 8.1 10.9 8.0 7.6 0 0 0 0 0 0 0 0 0 0 0 12
13 7.7 10.0 8.1 8.0 1 0 0 0 0 0 0 0 0 0 0 13
14 7.5 9.2 7.7 8.1 0 1 0 0 0 0 0 0 0 0 0 14
15 7.6 9.2 7.5 7.7 0 0 1 0 0 0 0 0 0 0 0 15
16 7.8 9.5 7.6 7.5 0 0 0 1 0 0 0 0 0 0 0 16
17 7.8 9.6 7.8 7.6 0 0 0 0 1 0 0 0 0 0 0 17
18 7.8 9.5 7.8 7.8 0 0 0 0 0 1 0 0 0 0 0 18
19 7.5 9.1 7.8 7.8 0 0 0 0 0 0 1 0 0 0 0 19
20 7.5 8.9 7.5 7.8 0 0 0 0 0 0 0 1 0 0 0 20
21 7.1 9.0 7.5 7.5 0 0 0 0 0 0 0 0 1 0 0 21
22 7.5 10.1 7.1 7.5 0 0 0 0 0 0 0 0 0 1 0 22
23 7.5 10.3 7.5 7.1 0 0 0 0 0 0 0 0 0 0 1 23
24 7.6 10.2 7.5 7.5 0 0 0 0 0 0 0 0 0 0 0 24
25 7.7 9.6 7.6 7.5 1 0 0 0 0 0 0 0 0 0 0 25
26 7.7 9.2 7.7 7.6 0 1 0 0 0 0 0 0 0 0 0 26
27 7.9 9.3 7.7 7.7 0 0 1 0 0 0 0 0 0 0 0 27
28 8.1 9.4 7.9 7.7 0 0 0 1 0 0 0 0 0 0 0 28
29 8.2 9.4 8.1 7.9 0 0 0 0 1 0 0 0 0 0 0 29
30 8.2 9.2 8.2 8.1 0 0 0 0 0 1 0 0 0 0 0 30
31 8.2 9.0 8.2 8.2 0 0 0 0 0 0 1 0 0 0 0 31
32 7.9 9.0 8.2 8.2 0 0 0 0 0 0 0 1 0 0 0 32
33 7.3 9.0 7.9 8.2 0 0 0 0 0 0 0 0 1 0 0 33
34 6.9 9.8 7.3 7.9 0 0 0 0 0 0 0 0 0 1 0 34
35 6.6 10.0 6.9 7.3 0 0 0 0 0 0 0 0 0 0 1 35
36 6.7 9.8 6.6 6.9 0 0 0 0 0 0 0 0 0 0 0 36
37 6.9 9.3 6.7 6.6 1 0 0 0 0 0 0 0 0 0 0 37
38 7.0 9.0 6.9 6.7 0 1 0 0 0 0 0 0 0 0 0 38
39 7.1 9.0 7.0 6.9 0 0 1 0 0 0 0 0 0 0 0 39
40 7.2 9.1 7.1 7.0 0 0 0 1 0 0 0 0 0 0 0 40
41 7.1 9.1 7.2 7.1 0 0 0 0 1 0 0 0 0 0 0 41
42 6.9 9.1 7.1 7.2 0 0 0 0 0 1 0 0 0 0 0 42
43 7.0 9.2 6.9 7.1 0 0 0 0 0 0 1 0 0 0 0 43
44 6.8 8.8 7.0 6.9 0 0 0 0 0 0 0 1 0 0 0 44
45 6.4 8.3 6.8 7.0 0 0 0 0 0 0 0 0 1 0 0 45
46 6.7 8.4 6.4 6.8 0 0 0 0 0 0 0 0 0 1 0 46
47 6.6 8.1 6.7 6.4 0 0 0 0 0 0 0 0 0 0 1 47
48 6.4 7.7 6.6 6.7 0 0 0 0 0 0 0 0 0 0 0 48
49 6.3 7.9 6.4 6.6 1 0 0 0 0 0 0 0 0 0 0 49
50 6.2 7.9 6.3 6.4 0 1 0 0 0 0 0 0 0 0 0 50
51 6.5 8.0 6.2 6.3 0 0 1 0 0 0 0 0 0 0 0 51
52 6.8 7.9 6.5 6.2 0 0 0 1 0 0 0 0 0 0 0 52
53 6.8 7.6 6.8 6.5 0 0 0 0 1 0 0 0 0 0 0 53
54 6.4 7.1 6.8 6.8 0 0 0 0 0 1 0 0 0 0 0 54
55 6.1 6.8 6.4 6.8 0 0 0 0 0 0 1 0 0 0 0 55
56 5.8 6.5 6.1 6.4 0 0 0 0 0 0 0 1 0 0 0 56
57 6.1 6.9 5.8 6.1 0 0 0 0 0 0 0 0 1 0 0 57
58 7.2 8.2 6.1 5.8 0 0 0 0 0 0 0 0 0 1 0 58
59 7.3 8.7 7.2 6.1 0 0 0 0 0 0 0 0 0 0 1 59
60 6.9 8.3 7.3 7.2 0 0 0 0 0 0 0 0 0 0 0 60
61 6.1 7.9 6.9 7.3 1 0 0 0 0 0 0 0 0 0 0 61
62 5.8 7.5 6.1 6.9 0 1 0 0 0 0 0 0 0 0 0 62
63 6.2 7.8 5.8 6.1 0 0 1 0 0 0 0 0 0 0 0 63
64 7.1 8.3 6.2 5.8 0 0 0 1 0 0 0 0 0 0 0 64
65 7.7 8.4 7.1 6.2 0 0 0 0 1 0 0 0 0 0 0 65
66 7.9 8.2 7.7 7.1 0 0 0 0 0 1 0 0 0 0 0 66
67 7.7 7.7 7.9 7.7 0 0 0 0 0 0 1 0 0 0 0 67
68 7.4 7.2 7.7 7.9 0 0 0 0 0 0 0 1 0 0 0 68
69 7.5 7.3 7.4 7.7 0 0 0 0 0 0 0 0 1 0 0 69
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 M1 M2
1.103125 0.104088 1.384135 -0.677059 0.021242 0.112740
M3 M4 M5 M6 M7 M8
0.353104 0.271985 0.074798 0.062883 0.123429 0.142214
M9 M10 M11 t
0.148011 0.540049 -0.265589 -0.001221
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.47714 -0.13371 0.02330 0.12493 0.54403
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.103125 0.611330 1.804 0.076841 .
X 0.104088 0.056235 1.851 0.069754 .
Y1 1.384135 0.107835 12.836 < 2e-16 ***
Y2 -0.677059 0.103939 -6.514 2.73e-08 ***
M1 0.021242 0.137612 0.154 0.877909
M2 0.112740 0.141530 0.797 0.429248
M3 0.353104 0.138677 2.546 0.013832 *
M4 0.271985 0.138330 1.966 0.054522 .
M5 0.074798 0.141903 0.527 0.600317
M6 0.062883 0.143958 0.437 0.664018
M7 0.123429 0.149545 0.825 0.412867
M8 0.142214 0.152619 0.932 0.355653
M9 0.148011 0.146823 1.008 0.317991
M10 0.540049 0.144237 3.744 0.000447 ***
M11 -0.265589 0.148222 -1.792 0.078869 .
t -0.001221 0.002247 -0.543 0.589166
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2214 on 53 degrees of freedom
Multiple R-squared: 0.9123, Adjusted R-squared: 0.8875
F-statistic: 36.75 on 15 and 53 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,] 0.20289935 0.405798703 0.797100648
[2,] 0.57623906 0.847521887 0.423760944
[3,] 0.46097709 0.921954181 0.539022909
[4,] 0.39199944 0.783998880 0.608000560
[5,] 0.27703159 0.554063175 0.722968413
[6,] 0.19083285 0.381665708 0.809167146
[7,] 0.13229621 0.264592421 0.867703790
[8,] 0.08651373 0.173027468 0.913486266
[9,] 0.05314624 0.106292487 0.946853757
[10,] 0.03151102 0.063022046 0.968488977
[11,] 0.03284935 0.065698692 0.967150654
[12,] 0.04397094 0.087941874 0.956029063
[13,] 0.19113260 0.382265208 0.808867396
[14,] 0.22579642 0.451592845 0.774203577
[15,] 0.16057379 0.321147589 0.839426206
[16,] 0.38449939 0.768998790 0.615500605
[17,] 0.32458754 0.649175074 0.675412463
[18,] 0.32139784 0.642795675 0.678602163
[19,] 0.44375039 0.887500771 0.556249615
[20,] 0.48204762 0.964095238 0.517952381
[21,] 0.49166828 0.983336562 0.508331719
[22,] 0.41714167 0.834283343 0.582858329
[23,] 0.34356616 0.687132328 0.656433836
[24,] 0.27385840 0.547716803 0.726141598
[25,] 0.33495528 0.669910552 0.665044724
[26,] 0.33779493 0.675589865 0.662205068
[27,] 0.41307689 0.826153784 0.586923108
[28,] 0.61345187 0.773096256 0.386548128
[29,] 0.48570420 0.971408397 0.514295802
[30,] 0.65449843 0.691003139 0.345501570
[31,] 0.99439481 0.011210379 0.005605190
[32,] 0.99565305 0.008693906 0.004346953
> postscript(file="/var/www/html/rcomp/tmp/1a04r1258742027.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2m4k01258742027.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/33ggf1258742027.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4midc1258742027.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5w4r51258742027.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 = 69
Frequency = 1
1 2 3 4 5 6
0.388167282 -0.039235073 0.093513440 -0.063426727 -0.057611462 -0.147898520
7 8 9 10 11 12
-0.246479441 0.097548041 0.082228084 0.152113829 -0.030317515 -0.050463778
13 14 15 16 17 18
-0.244396398 0.169957266 0.036818150 0.014106073 -0.007015553 0.151941158
19 20 21 22 23 24
-0.165748255 0.252745586 -0.365356566 0.082984431 0.044548809 0.161412832
25 26 27 28 29 30
0.165430551 0.046081525 0.064235840 0.059339434 0.216332411 0.247284338
31 32 33 34 35 36
0.276483272 -0.041081001 -0.230416238 -0.477139465 0.156321501 0.157188075
37 38 39 40 41 42
0.047679488 -0.120491826 -0.262636444 -0.161413463 -0.133712801 -0.114457156
43 44 45 46 47 48
0.124930891 -0.324823611 -0.332822773 -0.015805956 0.036215719 -0.044986316
49 50 51 52 53 54
0.023296143 -0.163978373 -0.042822224 -0.133020513 -0.115508965 -0.247211394
55 56 57 58 59 60
-0.021655414 -0.163576226 0.302335974 0.257847160 -0.206768514 -0.223150813
61 62 63 64 65 66
-0.380177066 0.107666479 0.110891238 0.284415197 0.097516370 0.110341574
67 68 69
0.032468948 0.179187211 0.544031519
> postscript(file="/var/www/html/rcomp/tmp/6ih971258742027.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 = 69
Frequency = 1
lag(myerror, k = 1) myerror
0 0.388167282 NA
1 -0.039235073 0.388167282
2 0.093513440 -0.039235073
3 -0.063426727 0.093513440
4 -0.057611462 -0.063426727
5 -0.147898520 -0.057611462
6 -0.246479441 -0.147898520
7 0.097548041 -0.246479441
8 0.082228084 0.097548041
9 0.152113829 0.082228084
10 -0.030317515 0.152113829
11 -0.050463778 -0.030317515
12 -0.244396398 -0.050463778
13 0.169957266 -0.244396398
14 0.036818150 0.169957266
15 0.014106073 0.036818150
16 -0.007015553 0.014106073
17 0.151941158 -0.007015553
18 -0.165748255 0.151941158
19 0.252745586 -0.165748255
20 -0.365356566 0.252745586
21 0.082984431 -0.365356566
22 0.044548809 0.082984431
23 0.161412832 0.044548809
24 0.165430551 0.161412832
25 0.046081525 0.165430551
26 0.064235840 0.046081525
27 0.059339434 0.064235840
28 0.216332411 0.059339434
29 0.247284338 0.216332411
30 0.276483272 0.247284338
31 -0.041081001 0.276483272
32 -0.230416238 -0.041081001
33 -0.477139465 -0.230416238
34 0.156321501 -0.477139465
35 0.157188075 0.156321501
36 0.047679488 0.157188075
37 -0.120491826 0.047679488
38 -0.262636444 -0.120491826
39 -0.161413463 -0.262636444
40 -0.133712801 -0.161413463
41 -0.114457156 -0.133712801
42 0.124930891 -0.114457156
43 -0.324823611 0.124930891
44 -0.332822773 -0.324823611
45 -0.015805956 -0.332822773
46 0.036215719 -0.015805956
47 -0.044986316 0.036215719
48 0.023296143 -0.044986316
49 -0.163978373 0.023296143
50 -0.042822224 -0.163978373
51 -0.133020513 -0.042822224
52 -0.115508965 -0.133020513
53 -0.247211394 -0.115508965
54 -0.021655414 -0.247211394
55 -0.163576226 -0.021655414
56 0.302335974 -0.163576226
57 0.257847160 0.302335974
58 -0.206768514 0.257847160
59 -0.223150813 -0.206768514
60 -0.380177066 -0.223150813
61 0.107666479 -0.380177066
62 0.110891238 0.107666479
63 0.284415197 0.110891238
64 0.097516370 0.284415197
65 0.110341574 0.097516370
66 0.032468948 0.110341574
67 0.179187211 0.032468948
68 0.544031519 0.179187211
69 NA 0.544031519
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.039235073 0.388167282
[2,] 0.093513440 -0.039235073
[3,] -0.063426727 0.093513440
[4,] -0.057611462 -0.063426727
[5,] -0.147898520 -0.057611462
[6,] -0.246479441 -0.147898520
[7,] 0.097548041 -0.246479441
[8,] 0.082228084 0.097548041
[9,] 0.152113829 0.082228084
[10,] -0.030317515 0.152113829
[11,] -0.050463778 -0.030317515
[12,] -0.244396398 -0.050463778
[13,] 0.169957266 -0.244396398
[14,] 0.036818150 0.169957266
[15,] 0.014106073 0.036818150
[16,] -0.007015553 0.014106073
[17,] 0.151941158 -0.007015553
[18,] -0.165748255 0.151941158
[19,] 0.252745586 -0.165748255
[20,] -0.365356566 0.252745586
[21,] 0.082984431 -0.365356566
[22,] 0.044548809 0.082984431
[23,] 0.161412832 0.044548809
[24,] 0.165430551 0.161412832
[25,] 0.046081525 0.165430551
[26,] 0.064235840 0.046081525
[27,] 0.059339434 0.064235840
[28,] 0.216332411 0.059339434
[29,] 0.247284338 0.216332411
[30,] 0.276483272 0.247284338
[31,] -0.041081001 0.276483272
[32,] -0.230416238 -0.041081001
[33,] -0.477139465 -0.230416238
[34,] 0.156321501 -0.477139465
[35,] 0.157188075 0.156321501
[36,] 0.047679488 0.157188075
[37,] -0.120491826 0.047679488
[38,] -0.262636444 -0.120491826
[39,] -0.161413463 -0.262636444
[40,] -0.133712801 -0.161413463
[41,] -0.114457156 -0.133712801
[42,] 0.124930891 -0.114457156
[43,] -0.324823611 0.124930891
[44,] -0.332822773 -0.324823611
[45,] -0.015805956 -0.332822773
[46,] 0.036215719 -0.015805956
[47,] -0.044986316 0.036215719
[48,] 0.023296143 -0.044986316
[49,] -0.163978373 0.023296143
[50,] -0.042822224 -0.163978373
[51,] -0.133020513 -0.042822224
[52,] -0.115508965 -0.133020513
[53,] -0.247211394 -0.115508965
[54,] -0.021655414 -0.247211394
[55,] -0.163576226 -0.021655414
[56,] 0.302335974 -0.163576226
[57,] 0.257847160 0.302335974
[58,] -0.206768514 0.257847160
[59,] -0.223150813 -0.206768514
[60,] -0.380177066 -0.223150813
[61,] 0.107666479 -0.380177066
[62,] 0.110891238 0.107666479
[63,] 0.284415197 0.110891238
[64,] 0.097516370 0.284415197
[65,] 0.110341574 0.097516370
[66,] 0.032468948 0.110341574
[67,] 0.179187211 0.032468948
[68,] 0.544031519 0.179187211
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.039235073 0.388167282
2 0.093513440 -0.039235073
3 -0.063426727 0.093513440
4 -0.057611462 -0.063426727
5 -0.147898520 -0.057611462
6 -0.246479441 -0.147898520
7 0.097548041 -0.246479441
8 0.082228084 0.097548041
9 0.152113829 0.082228084
10 -0.030317515 0.152113829
11 -0.050463778 -0.030317515
12 -0.244396398 -0.050463778
13 0.169957266 -0.244396398
14 0.036818150 0.169957266
15 0.014106073 0.036818150
16 -0.007015553 0.014106073
17 0.151941158 -0.007015553
18 -0.165748255 0.151941158
19 0.252745586 -0.165748255
20 -0.365356566 0.252745586
21 0.082984431 -0.365356566
22 0.044548809 0.082984431
23 0.161412832 0.044548809
24 0.165430551 0.161412832
25 0.046081525 0.165430551
26 0.064235840 0.046081525
27 0.059339434 0.064235840
28 0.216332411 0.059339434
29 0.247284338 0.216332411
30 0.276483272 0.247284338
31 -0.041081001 0.276483272
32 -0.230416238 -0.041081001
33 -0.477139465 -0.230416238
34 0.156321501 -0.477139465
35 0.157188075 0.156321501
36 0.047679488 0.157188075
37 -0.120491826 0.047679488
38 -0.262636444 -0.120491826
39 -0.161413463 -0.262636444
40 -0.133712801 -0.161413463
41 -0.114457156 -0.133712801
42 0.124930891 -0.114457156
43 -0.324823611 0.124930891
44 -0.332822773 -0.324823611
45 -0.015805956 -0.332822773
46 0.036215719 -0.015805956
47 -0.044986316 0.036215719
48 0.023296143 -0.044986316
49 -0.163978373 0.023296143
50 -0.042822224 -0.163978373
51 -0.133020513 -0.042822224
52 -0.115508965 -0.133020513
53 -0.247211394 -0.115508965
54 -0.021655414 -0.247211394
55 -0.163576226 -0.021655414
56 0.302335974 -0.163576226
57 0.257847160 0.302335974
58 -0.206768514 0.257847160
59 -0.223150813 -0.206768514
60 -0.380177066 -0.223150813
61 0.107666479 -0.380177066
62 0.110891238 0.107666479
63 0.284415197 0.110891238
64 0.097516370 0.284415197
65 0.110341574 0.097516370
66 0.032468948 0.110341574
67 0.179187211 0.032468948
68 0.544031519 0.179187211
> 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/7us7d1258742027.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ry5s1258742027.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9jonj1258742027.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/107nth1258742027.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11pic71258742027.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/12qkh31258742027.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/13xejr1258742027.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/149llb1258742027.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/150pe91258742027.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/16im2r1258742027.tab")
+ }
>
> system("convert tmp/1a04r1258742027.ps tmp/1a04r1258742027.png")
> system("convert tmp/2m4k01258742027.ps tmp/2m4k01258742027.png")
> system("convert tmp/33ggf1258742027.ps tmp/33ggf1258742027.png")
> system("convert tmp/4midc1258742027.ps tmp/4midc1258742027.png")
> system("convert tmp/5w4r51258742027.ps tmp/5w4r51258742027.png")
> system("convert tmp/6ih971258742027.ps tmp/6ih971258742027.png")
> system("convert tmp/7us7d1258742027.ps tmp/7us7d1258742027.png")
> system("convert tmp/8ry5s1258742027.ps tmp/8ry5s1258742027.png")
> system("convert tmp/9jonj1258742027.ps tmp/9jonj1258742027.png")
> system("convert tmp/107nth1258742027.ps tmp/107nth1258742027.png")
>
>
> proc.time()
user system elapsed
2.558 1.582 2.917