R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(3.2
+ ,27.6
+ ,2.7
+ ,2.5
+ ,2.4
+ ,2.6
+ ,2.8
+ ,24.9
+ ,3.2
+ ,2.7
+ ,2.5
+ ,2.4
+ ,2.8
+ ,23.8
+ ,2.8
+ ,3.2
+ ,2.7
+ ,2.5
+ ,3
+ ,24.3
+ ,2.8
+ ,2.8
+ ,3.2
+ ,2.7
+ ,3.1
+ ,23.6
+ ,3
+ ,2.8
+ ,2.8
+ ,3.2
+ ,3.1
+ ,24.2
+ ,3.1
+ ,3
+ ,2.8
+ ,2.8
+ ,3
+ ,28.1
+ ,3.1
+ ,3.1
+ ,3
+ ,2.8
+ ,2.4
+ ,30.1
+ ,3
+ ,3.1
+ ,3.1
+ ,3
+ ,2.7
+ ,31.1
+ ,2.4
+ ,3
+ ,3.1
+ ,3.1
+ ,3
+ ,32
+ ,2.7
+ ,2.4
+ ,3
+ ,3.1
+ ,2.7
+ ,32.4
+ ,3
+ ,2.7
+ ,2.4
+ ,3
+ ,2.7
+ ,34
+ ,2.7
+ ,3
+ ,2.7
+ ,2.4
+ ,2
+ ,35.1
+ ,2.7
+ ,2.7
+ ,3
+ ,2.7
+ ,2.4
+ ,37.1
+ ,2
+ ,2.7
+ ,2.7
+ ,3
+ ,2.6
+ ,37.3
+ ,2.4
+ ,2
+ ,2.7
+ ,2.7
+ ,2.4
+ ,38.1
+ ,2.6
+ ,2.4
+ ,2
+ ,2.7
+ ,2.3
+ ,39.5
+ ,2.4
+ ,2.6
+ ,2.4
+ ,2
+ ,2.4
+ ,38.3
+ ,2.3
+ ,2.4
+ ,2.6
+ ,2.4
+ ,2.5
+ ,37.3
+ ,2.4
+ ,2.3
+ ,2.4
+ ,2.6
+ ,2.6
+ ,38.7
+ ,2.5
+ ,2.4
+ ,2.3
+ ,2.4
+ ,2.6
+ ,37.5
+ ,2.6
+ ,2.5
+ ,2.4
+ ,2.3
+ ,2.6
+ ,38.7
+ ,2.6
+ ,2.6
+ ,2.5
+ ,2.4
+ ,2.7
+ ,37.9
+ ,2.6
+ ,2.6
+ ,2.6
+ ,2.5
+ ,2.8
+ ,36.6
+ ,2.7
+ ,2.6
+ ,2.6
+ ,2.6
+ ,2.6
+ ,35.5
+ ,2.8
+ ,2.7
+ ,2.6
+ ,2.6
+ ,2.6
+ ,37.6
+ ,2.6
+ ,2.8
+ ,2.7
+ ,2.6
+ ,2
+ ,38.6
+ ,2.6
+ ,2.6
+ ,2.8
+ ,2.7
+ ,2
+ ,40.3
+ ,2
+ ,2.6
+ ,2.6
+ ,2.8
+ ,2.1
+ ,39
+ ,2
+ ,2
+ ,2.6
+ ,2.6
+ ,1.9
+ ,36.8
+ ,2.1
+ ,2
+ ,2
+ ,2.6
+ ,2
+ ,36.5
+ ,1.9
+ ,2.1
+ ,2
+ ,2
+ ,2.5
+ ,34.1
+ ,2
+ ,1.9
+ ,2.1
+ ,2
+ ,2.9
+ ,34.2
+ ,2.5
+ ,2
+ ,1.9
+ ,2.1
+ ,3.3
+ ,31.9
+ ,2.9
+ ,2.5
+ ,2
+ ,1.9
+ ,3.5
+ ,33.7
+ ,3.3
+ ,2.9
+ ,2.5
+ ,2
+ ,3.8
+ ,33.5
+ ,3.5
+ ,3.3
+ ,2.9
+ ,2.5
+ ,4.6
+ ,33.8
+ ,3.8
+ ,3.5
+ ,3.3
+ ,2.9
+ ,4.4
+ ,29.9
+ ,4.6
+ ,3.8
+ ,3.5
+ ,3.3
+ ,5.3
+ ,32.3
+ ,4.4
+ ,4.6
+ ,3.8
+ ,3.5
+ ,5.8
+ ,30.5
+ ,5.3
+ ,4.4
+ ,4.6
+ ,3.8
+ ,5.9
+ ,28.5
+ ,5.8
+ ,5.3
+ ,4.4
+ ,4.6
+ ,5.6
+ ,29
+ ,5.9
+ ,5.8
+ ,5.3
+ ,4.4
+ ,5.8
+ ,23.8
+ ,5.6
+ ,5.9
+ ,5.8
+ ,5.3
+ ,5.5
+ ,17.9
+ ,5.8
+ ,5.6
+ ,5.9
+ ,5.8
+ ,4.6
+ ,9.9
+ ,5.5
+ ,5.8
+ ,5.6
+ ,5.9
+ ,4.2
+ ,3
+ ,4.6
+ ,5.5
+ ,5.8
+ ,5.6
+ ,4
+ ,4.2
+ ,4.2
+ ,4.6
+ ,5.5
+ ,5.8
+ ,3.5
+ ,0.4
+ ,4
+ ,4.2
+ ,4.6
+ ,5.5
+ ,2.3
+ ,0
+ ,3.5
+ ,4
+ ,4.2
+ ,4.6
+ ,2.2
+ ,2.4
+ ,2.3
+ ,3.5
+ ,4
+ ,4.2
+ ,1.4
+ ,4.2
+ ,2.2
+ ,2.3
+ ,3.5
+ ,4
+ ,0.6
+ ,8.2
+ ,1.4
+ ,2.2
+ ,2.3
+ ,3.5
+ ,0
+ ,9
+ ,0.6
+ ,1.4
+ ,2.2
+ ,2.3
+ ,0.5
+ ,13.6
+ ,0
+ ,0.6
+ ,1.4
+ ,2.2
+ ,0.1
+ ,14
+ ,0.5
+ ,0
+ ,0.6
+ ,1.4
+ ,0.1
+ ,17.6
+ ,0.1
+ ,0.5
+ ,0
+ ,0.6)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:56))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 3.2 27.6 2.7 2.5 2.4 2.6 1 0 0 0 0 0 0 0 0 0 0 1
2 2.8 24.9 3.2 2.7 2.5 2.4 0 1 0 0 0 0 0 0 0 0 0 2
3 2.8 23.8 2.8 3.2 2.7 2.5 0 0 1 0 0 0 0 0 0 0 0 3
4 3.0 24.3 2.8 2.8 3.2 2.7 0 0 0 1 0 0 0 0 0 0 0 4
5 3.1 23.6 3.0 2.8 2.8 3.2 0 0 0 0 1 0 0 0 0 0 0 5
6 3.1 24.2 3.1 3.0 2.8 2.8 0 0 0 0 0 1 0 0 0 0 0 6
7 3.0 28.1 3.1 3.1 3.0 2.8 0 0 0 0 0 0 1 0 0 0 0 7
8 2.4 30.1 3.0 3.1 3.1 3.0 0 0 0 0 0 0 0 1 0 0 0 8
9 2.7 31.1 2.4 3.0 3.1 3.1 0 0 0 0 0 0 0 0 1 0 0 9
10 3.0 32.0 2.7 2.4 3.0 3.1 0 0 0 0 0 0 0 0 0 1 0 10
11 2.7 32.4 3.0 2.7 2.4 3.0 0 0 0 0 0 0 0 0 0 0 1 11
12 2.7 34.0 2.7 3.0 2.7 2.4 0 0 0 0 0 0 0 0 0 0 0 12
13 2.0 35.1 2.7 2.7 3.0 2.7 1 0 0 0 0 0 0 0 0 0 0 13
14 2.4 37.1 2.0 2.7 2.7 3.0 0 1 0 0 0 0 0 0 0 0 0 14
15 2.6 37.3 2.4 2.0 2.7 2.7 0 0 1 0 0 0 0 0 0 0 0 15
16 2.4 38.1 2.6 2.4 2.0 2.7 0 0 0 1 0 0 0 0 0 0 0 16
17 2.3 39.5 2.4 2.6 2.4 2.0 0 0 0 0 1 0 0 0 0 0 0 17
18 2.4 38.3 2.3 2.4 2.6 2.4 0 0 0 0 0 1 0 0 0 0 0 18
19 2.5 37.3 2.4 2.3 2.4 2.6 0 0 0 0 0 0 1 0 0 0 0 19
20 2.6 38.7 2.5 2.4 2.3 2.4 0 0 0 0 0 0 0 1 0 0 0 20
21 2.6 37.5 2.6 2.5 2.4 2.3 0 0 0 0 0 0 0 0 1 0 0 21
22 2.6 38.7 2.6 2.6 2.5 2.4 0 0 0 0 0 0 0 0 0 1 0 22
23 2.7 37.9 2.6 2.6 2.6 2.5 0 0 0 0 0 0 0 0 0 0 1 23
24 2.8 36.6 2.7 2.6 2.6 2.6 0 0 0 0 0 0 0 0 0 0 0 24
25 2.6 35.5 2.8 2.7 2.6 2.6 1 0 0 0 0 0 0 0 0 0 0 25
26 2.6 37.6 2.6 2.8 2.7 2.6 0 1 0 0 0 0 0 0 0 0 0 26
27 2.0 38.6 2.6 2.6 2.8 2.7 0 0 1 0 0 0 0 0 0 0 0 27
28 2.0 40.3 2.0 2.6 2.6 2.8 0 0 0 1 0 0 0 0 0 0 0 28
29 2.1 39.0 2.0 2.0 2.6 2.6 0 0 0 0 1 0 0 0 0 0 0 29
30 1.9 36.8 2.1 2.0 2.0 2.6 0 0 0 0 0 1 0 0 0 0 0 30
31 2.0 36.5 1.9 2.1 2.0 2.0 0 0 0 0 0 0 1 0 0 0 0 31
32 2.5 34.1 2.0 1.9 2.1 2.0 0 0 0 0 0 0 0 1 0 0 0 32
33 2.9 34.2 2.5 2.0 1.9 2.1 0 0 0 0 0 0 0 0 1 0 0 33
34 3.3 31.9 2.9 2.5 2.0 1.9 0 0 0 0 0 0 0 0 0 1 0 34
35 3.5 33.7 3.3 2.9 2.5 2.0 0 0 0 0 0 0 0 0 0 0 1 35
36 3.8 33.5 3.5 3.3 2.9 2.5 0 0 0 0 0 0 0 0 0 0 0 36
37 4.6 33.8 3.8 3.5 3.3 2.9 1 0 0 0 0 0 0 0 0 0 0 37
38 4.4 29.9 4.6 3.8 3.5 3.3 0 1 0 0 0 0 0 0 0 0 0 38
39 5.3 32.3 4.4 4.6 3.8 3.5 0 0 1 0 0 0 0 0 0 0 0 39
40 5.8 30.5 5.3 4.4 4.6 3.8 0 0 0 1 0 0 0 0 0 0 0 40
41 5.9 28.5 5.8 5.3 4.4 4.6 0 0 0 0 1 0 0 0 0 0 0 41
42 5.6 29.0 5.9 5.8 5.3 4.4 0 0 0 0 0 1 0 0 0 0 0 42
43 5.8 23.8 5.6 5.9 5.8 5.3 0 0 0 0 0 0 1 0 0 0 0 43
44 5.5 17.9 5.8 5.6 5.9 5.8 0 0 0 0 0 0 0 1 0 0 0 44
45 4.6 9.9 5.5 5.8 5.6 5.9 0 0 0 0 0 0 0 0 1 0 0 45
46 4.2 3.0 4.6 5.5 5.8 5.6 0 0 0 0 0 0 0 0 0 1 0 46
47 4.0 4.2 4.2 4.6 5.5 5.8 0 0 0 0 0 0 0 0 0 0 1 47
48 3.5 0.4 4.0 4.2 4.6 5.5 0 0 0 0 0 0 0 0 0 0 0 48
49 2.3 0.0 3.5 4.0 4.2 4.6 1 0 0 0 0 0 0 0 0 0 0 49
50 2.2 2.4 2.3 3.5 4.0 4.2 0 1 0 0 0 0 0 0 0 0 0 50
51 1.4 4.2 2.2 2.3 3.5 4.0 0 0 1 0 0 0 0 0 0 0 0 51
52 0.6 8.2 1.4 2.2 2.3 3.5 0 0 0 1 0 0 0 0 0 0 0 52
53 0.0 9.0 0.6 1.4 2.2 2.3 0 0 0 0 1 0 0 0 0 0 0 53
54 0.5 13.6 0.0 0.6 1.4 2.2 0 0 0 0 0 1 0 0 0 0 0 54
55 0.1 14.0 0.5 0.0 0.6 1.4 0 0 0 0 0 0 1 0 0 0 0 55
56 0.1 17.6 0.1 0.5 0.0 0.6 0 0 0 0 0 0 0 1 0 0 0 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
-0.242264 0.012911 1.017166 0.030952 0.145701 -0.254856
M1 M2 M3 M4 M5 M6
-0.144914 -0.037359 -0.053334 -0.038308 -0.085650 0.002250
M7 M8 M9 M10 M11 t
-0.039328 -0.082724 -0.026718 0.085124 -0.020809 0.002842
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.72448 -0.21681 -0.04931 0.24391 0.78814
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.242264 0.466128 -0.520 0.606
X 0.012911 0.008178 1.579 0.123
Y1 1.017166 0.153438 6.629 7.84e-08 ***
Y2 0.030952 0.224711 0.138 0.891
Y3 0.145701 0.235118 0.620 0.539
Y4 -0.254856 0.191886 -1.328 0.192
M1 -0.144914 0.281671 -0.514 0.610
M2 -0.037359 0.281109 -0.133 0.895
M3 -0.053334 0.282990 -0.188 0.852
M4 -0.038308 0.281863 -0.136 0.893
M5 -0.085650 0.281276 -0.305 0.762
M6 0.002250 0.281746 0.008 0.994
M7 -0.039328 0.282297 -0.139 0.890
M8 -0.082724 0.281583 -0.294 0.771
M9 -0.026718 0.296096 -0.090 0.929
M10 0.085124 0.296788 0.287 0.776
M11 -0.020809 0.296560 -0.070 0.944
t 0.002842 0.004341 0.655 0.517
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4171 on 38 degrees of freedom
Multiple R-squared: 0.9364, Adjusted R-squared: 0.908
F-statistic: 32.91 on 17 and 38 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.31208067 0.62416134 0.6879193
[2,] 0.17888385 0.35776771 0.8211161
[3,] 0.12076187 0.24152374 0.8792381
[4,] 0.05897851 0.11795702 0.9410215
[5,] 0.03370939 0.06741878 0.9662906
[6,] 0.02458151 0.04916303 0.9754185
[7,] 0.03045152 0.06090304 0.9695485
[8,] 0.03401419 0.06802837 0.9659858
[9,] 0.05397529 0.10795059 0.9460247
[10,] 0.10766075 0.21532150 0.8923392
[11,] 0.08122115 0.16244230 0.9187789
[12,] 0.04994188 0.09988376 0.9500581
[13,] 0.03993277 0.07986553 0.9600672
[14,] 0.02861822 0.05723643 0.9713818
[15,] 0.05531625 0.11063249 0.9446838
> postscript(file="/var/www/html/rcomp/tmp/1ak011261387666.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2qhgq1261387666.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/32b701261387666.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4cqzq1261387666.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/53yjm1261387666.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
0.71719791 -0.33865291 0.07641829 0.24259553 0.37840849 0.07007047
7 8 9 10 11 12
-0.07378369 -0.52093464 0.34618585 0.24787274 -0.20670167 -0.15177028
13 14 15 16 17 18
-0.68186934 0.41409431 0.16298766 -0.17903314 -0.29204606 -0.08658506
19 20 21 22 23 24
0.04655178 0.02781703 -0.16040529 -0.28276273 -0.05842764 -0.04152462
25 26 27 28 29 30
-0.19006250 -0.14180532 -0.72447814 -0.09937060 0.02951371 -0.24711917
31 32 33 34 35 36
-0.05708591 0.40435906 0.28716708 0.11429555 -0.07246630 0.05979906
37 38 39 40 41 42
0.73031901 -0.27993954 0.78813872 0.34414776 0.21105591 -0.48543605
43 44 45 46 47 48
0.27901322 0.01445460 -0.47294764 -0.07940556 0.33759562 0.13349584
49 50 51 52 53 54
-0.57558508 0.34630345 -0.30306653 -0.30833955 -0.32693206 0.74906982
55 56
-0.19469540 0.07430395
> postscript(file="/var/www/html/rcomp/tmp/6ncoz1261387666.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 0.71719791 NA
1 -0.33865291 0.71719791
2 0.07641829 -0.33865291
3 0.24259553 0.07641829
4 0.37840849 0.24259553
5 0.07007047 0.37840849
6 -0.07378369 0.07007047
7 -0.52093464 -0.07378369
8 0.34618585 -0.52093464
9 0.24787274 0.34618585
10 -0.20670167 0.24787274
11 -0.15177028 -0.20670167
12 -0.68186934 -0.15177028
13 0.41409431 -0.68186934
14 0.16298766 0.41409431
15 -0.17903314 0.16298766
16 -0.29204606 -0.17903314
17 -0.08658506 -0.29204606
18 0.04655178 -0.08658506
19 0.02781703 0.04655178
20 -0.16040529 0.02781703
21 -0.28276273 -0.16040529
22 -0.05842764 -0.28276273
23 -0.04152462 -0.05842764
24 -0.19006250 -0.04152462
25 -0.14180532 -0.19006250
26 -0.72447814 -0.14180532
27 -0.09937060 -0.72447814
28 0.02951371 -0.09937060
29 -0.24711917 0.02951371
30 -0.05708591 -0.24711917
31 0.40435906 -0.05708591
32 0.28716708 0.40435906
33 0.11429555 0.28716708
34 -0.07246630 0.11429555
35 0.05979906 -0.07246630
36 0.73031901 0.05979906
37 -0.27993954 0.73031901
38 0.78813872 -0.27993954
39 0.34414776 0.78813872
40 0.21105591 0.34414776
41 -0.48543605 0.21105591
42 0.27901322 -0.48543605
43 0.01445460 0.27901322
44 -0.47294764 0.01445460
45 -0.07940556 -0.47294764
46 0.33759562 -0.07940556
47 0.13349584 0.33759562
48 -0.57558508 0.13349584
49 0.34630345 -0.57558508
50 -0.30306653 0.34630345
51 -0.30833955 -0.30306653
52 -0.32693206 -0.30833955
53 0.74906982 -0.32693206
54 -0.19469540 0.74906982
55 0.07430395 -0.19469540
56 NA 0.07430395
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.33865291 0.71719791
[2,] 0.07641829 -0.33865291
[3,] 0.24259553 0.07641829
[4,] 0.37840849 0.24259553
[5,] 0.07007047 0.37840849
[6,] -0.07378369 0.07007047
[7,] -0.52093464 -0.07378369
[8,] 0.34618585 -0.52093464
[9,] 0.24787274 0.34618585
[10,] -0.20670167 0.24787274
[11,] -0.15177028 -0.20670167
[12,] -0.68186934 -0.15177028
[13,] 0.41409431 -0.68186934
[14,] 0.16298766 0.41409431
[15,] -0.17903314 0.16298766
[16,] -0.29204606 -0.17903314
[17,] -0.08658506 -0.29204606
[18,] 0.04655178 -0.08658506
[19,] 0.02781703 0.04655178
[20,] -0.16040529 0.02781703
[21,] -0.28276273 -0.16040529
[22,] -0.05842764 -0.28276273
[23,] -0.04152462 -0.05842764
[24,] -0.19006250 -0.04152462
[25,] -0.14180532 -0.19006250
[26,] -0.72447814 -0.14180532
[27,] -0.09937060 -0.72447814
[28,] 0.02951371 -0.09937060
[29,] -0.24711917 0.02951371
[30,] -0.05708591 -0.24711917
[31,] 0.40435906 -0.05708591
[32,] 0.28716708 0.40435906
[33,] 0.11429555 0.28716708
[34,] -0.07246630 0.11429555
[35,] 0.05979906 -0.07246630
[36,] 0.73031901 0.05979906
[37,] -0.27993954 0.73031901
[38,] 0.78813872 -0.27993954
[39,] 0.34414776 0.78813872
[40,] 0.21105591 0.34414776
[41,] -0.48543605 0.21105591
[42,] 0.27901322 -0.48543605
[43,] 0.01445460 0.27901322
[44,] -0.47294764 0.01445460
[45,] -0.07940556 -0.47294764
[46,] 0.33759562 -0.07940556
[47,] 0.13349584 0.33759562
[48,] -0.57558508 0.13349584
[49,] 0.34630345 -0.57558508
[50,] -0.30306653 0.34630345
[51,] -0.30833955 -0.30306653
[52,] -0.32693206 -0.30833955
[53,] 0.74906982 -0.32693206
[54,] -0.19469540 0.74906982
[55,] 0.07430395 -0.19469540
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.33865291 0.71719791
2 0.07641829 -0.33865291
3 0.24259553 0.07641829
4 0.37840849 0.24259553
5 0.07007047 0.37840849
6 -0.07378369 0.07007047
7 -0.52093464 -0.07378369
8 0.34618585 -0.52093464
9 0.24787274 0.34618585
10 -0.20670167 0.24787274
11 -0.15177028 -0.20670167
12 -0.68186934 -0.15177028
13 0.41409431 -0.68186934
14 0.16298766 0.41409431
15 -0.17903314 0.16298766
16 -0.29204606 -0.17903314
17 -0.08658506 -0.29204606
18 0.04655178 -0.08658506
19 0.02781703 0.04655178
20 -0.16040529 0.02781703
21 -0.28276273 -0.16040529
22 -0.05842764 -0.28276273
23 -0.04152462 -0.05842764
24 -0.19006250 -0.04152462
25 -0.14180532 -0.19006250
26 -0.72447814 -0.14180532
27 -0.09937060 -0.72447814
28 0.02951371 -0.09937060
29 -0.24711917 0.02951371
30 -0.05708591 -0.24711917
31 0.40435906 -0.05708591
32 0.28716708 0.40435906
33 0.11429555 0.28716708
34 -0.07246630 0.11429555
35 0.05979906 -0.07246630
36 0.73031901 0.05979906
37 -0.27993954 0.73031901
38 0.78813872 -0.27993954
39 0.34414776 0.78813872
40 0.21105591 0.34414776
41 -0.48543605 0.21105591
42 0.27901322 -0.48543605
43 0.01445460 0.27901322
44 -0.47294764 0.01445460
45 -0.07940556 -0.47294764
46 0.33759562 -0.07940556
47 0.13349584 0.33759562
48 -0.57558508 0.13349584
49 0.34630345 -0.57558508
50 -0.30306653 0.34630345
51 -0.30833955 -0.30306653
52 -0.32693206 -0.30833955
53 0.74906982 -0.32693206
54 -0.19469540 0.74906982
55 0.07430395 -0.19469540
> 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/7snhi1261387666.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8p5yw1261387666.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rwty1261387666.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10grgi1261387666.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11oqll1261387666.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/1272b11261387666.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/13yw5n1261387666.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/14ow0p1261387666.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/15sks81261387666.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/16bdwp1261387666.tab")
+ }
>
> try(system("convert tmp/1ak011261387666.ps tmp/1ak011261387666.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qhgq1261387666.ps tmp/2qhgq1261387666.png",intern=TRUE))
character(0)
> try(system("convert tmp/32b701261387666.ps tmp/32b701261387666.png",intern=TRUE))
character(0)
> try(system("convert tmp/4cqzq1261387666.ps tmp/4cqzq1261387666.png",intern=TRUE))
character(0)
> try(system("convert tmp/53yjm1261387666.ps tmp/53yjm1261387666.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ncoz1261387666.ps tmp/6ncoz1261387666.png",intern=TRUE))
character(0)
> try(system("convert tmp/7snhi1261387666.ps tmp/7snhi1261387666.png",intern=TRUE))
character(0)
> try(system("convert tmp/8p5yw1261387666.ps tmp/8p5yw1261387666.png",intern=TRUE))
character(0)
> try(system("convert tmp/9rwty1261387666.ps tmp/9rwty1261387666.png",intern=TRUE))
character(0)
> try(system("convert tmp/10grgi1261387666.ps tmp/10grgi1261387666.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.354 1.561 2.981