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(2.4
+ ,0
+ ,1.7
+ ,1
+ ,1.2
+ ,1.4
+ ,2
+ ,0
+ ,2.4
+ ,1.7
+ ,1
+ ,1.2
+ ,2.1
+ ,0
+ ,2
+ ,2.4
+ ,1.7
+ ,1
+ ,2
+ ,0
+ ,2.1
+ ,2
+ ,2.4
+ ,1.7
+ ,1.8
+ ,0
+ ,2
+ ,2.1
+ ,2
+ ,2.4
+ ,2.7
+ ,0
+ ,1.8
+ ,2
+ ,2.1
+ ,2
+ ,2.3
+ ,0
+ ,2.7
+ ,1.8
+ ,2
+ ,2.1
+ ,1.9
+ ,0
+ ,2.3
+ ,2.7
+ ,1.8
+ ,2
+ ,2
+ ,0
+ ,1.9
+ ,2.3
+ ,2.7
+ ,1.8
+ ,2.3
+ ,0
+ ,2
+ ,1.9
+ ,2.3
+ ,2.7
+ ,2.8
+ ,0
+ ,2.3
+ ,2
+ ,1.9
+ ,2.3
+ ,2.4
+ ,0
+ ,2.8
+ ,2.3
+ ,2
+ ,1.9
+ ,2.3
+ ,0
+ ,2.4
+ ,2.8
+ ,2.3
+ ,2
+ ,2.7
+ ,0
+ ,2.3
+ ,2.4
+ ,2.8
+ ,2.3
+ ,2.7
+ ,0
+ ,2.7
+ ,2.3
+ ,2.4
+ ,2.8
+ ,2.9
+ ,0
+ ,2.7
+ ,2.7
+ ,2.3
+ ,2.4
+ ,3
+ ,0
+ ,2.9
+ ,2.7
+ ,2.7
+ ,2.3
+ ,2.2
+ ,0
+ ,3
+ ,2.9
+ ,2.7
+ ,2.7
+ ,2.3
+ ,0
+ ,2.2
+ ,3
+ ,2.9
+ ,2.7
+ ,2.8
+ ,0
+ ,2.3
+ ,2.2
+ ,3
+ ,2.9
+ ,2.8
+ ,0
+ ,2.8
+ ,2.3
+ ,2.2
+ ,3
+ ,2.8
+ ,0
+ ,2.8
+ ,2.8
+ ,2.3
+ ,2.2
+ ,2.2
+ ,0
+ ,2.8
+ ,2.8
+ ,2.8
+ ,2.3
+ ,2.6
+ ,0
+ ,2.2
+ ,2.8
+ ,2.8
+ ,2.8
+ ,2.8
+ ,0
+ ,2.6
+ ,2.2
+ ,2.8
+ ,2.8
+ ,2.5
+ ,0
+ ,2.8
+ ,2.6
+ ,2.2
+ ,2.8
+ ,2.4
+ ,0
+ ,2.5
+ ,2.8
+ ,2.6
+ ,2.2
+ ,2.3
+ ,0
+ ,2.4
+ ,2.5
+ ,2.8
+ ,2.6
+ ,1.9
+ ,0
+ ,2.3
+ ,2.4
+ ,2.5
+ ,2.8
+ ,1.7
+ ,0
+ ,1.9
+ ,2.3
+ ,2.4
+ ,2.5
+ ,2
+ ,0
+ ,1.7
+ ,1.9
+ ,2.3
+ ,2.4
+ ,2.1
+ ,0
+ ,2
+ ,1.7
+ ,1.9
+ ,2.3
+ ,1.7
+ ,0
+ ,2.1
+ ,2
+ ,1.7
+ ,1.9
+ ,1.8
+ ,0
+ ,1.7
+ ,2.1
+ ,2
+ ,1.7
+ ,1.8
+ ,0
+ ,1.8
+ ,1.7
+ ,2.1
+ ,2
+ ,1.8
+ ,0
+ ,1.8
+ ,1.8
+ ,1.7
+ ,2.1
+ ,1.3
+ ,1
+ ,1.8
+ ,1.8
+ ,1.8
+ ,1.7
+ ,1.3
+ ,1
+ ,1.3
+ ,1.8
+ ,1.8
+ ,1.8
+ ,1.3
+ ,1
+ ,1.3
+ ,1.3
+ ,1.8
+ ,1.8
+ ,1.2
+ ,1
+ ,1.3
+ ,1.3
+ ,1.3
+ ,1.8
+ ,1.4
+ ,1
+ ,1.2
+ ,1.3
+ ,1.3
+ ,1.3
+ ,2.2
+ ,1
+ ,1.4
+ ,1.2
+ ,1.3
+ ,1.3
+ ,2.9
+ ,1
+ ,2.2
+ ,1.4
+ ,1.2
+ ,1.3
+ ,3.1
+ ,1
+ ,2.9
+ ,2.2
+ ,1.4
+ ,1.2
+ ,3.5
+ ,1
+ ,3.1
+ ,2.9
+ ,2.2
+ ,1.4
+ ,3.6
+ ,1
+ ,3.5
+ ,3.1
+ ,2.9
+ ,2.2
+ ,4.4
+ ,1
+ ,3.6
+ ,3.5
+ ,3.1
+ ,2.9
+ ,4.1
+ ,1
+ ,4.4
+ ,3.6
+ ,3.5
+ ,3.1
+ ,5.1
+ ,1
+ ,4.1
+ ,4.4
+ ,3.6
+ ,3.5
+ ,5.8
+ ,1
+ ,5.1
+ ,4.1
+ ,4.4
+ ,3.6
+ ,5.9
+ ,1
+ ,5.8
+ ,5.1
+ ,4.1
+ ,4.4
+ ,5.4
+ ,1
+ ,5.9
+ ,5.8
+ ,5.1
+ ,4.1
+ ,5.5
+ ,1
+ ,5.4
+ ,5.9
+ ,5.8
+ ,5.1
+ ,4.8
+ ,1
+ ,5.5
+ ,5.4
+ ,5.9
+ ,5.8
+ ,3.2
+ ,1
+ ,4.8
+ ,5.5
+ ,5.4
+ ,5.9
+ ,2.7
+ ,1
+ ,3.2
+ ,4.8
+ ,5.5
+ ,5.4)
+ ,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 2.4 0 1.7 1.0 1.2 1.4 1 0 0 0 0 0 0 0 0 0 0 1
2 2.0 0 2.4 1.7 1.0 1.2 0 1 0 0 0 0 0 0 0 0 0 2
3 2.1 0 2.0 2.4 1.7 1.0 0 0 1 0 0 0 0 0 0 0 0 3
4 2.0 0 2.1 2.0 2.4 1.7 0 0 0 1 0 0 0 0 0 0 0 4
5 1.8 0 2.0 2.1 2.0 2.4 0 0 0 0 1 0 0 0 0 0 0 5
6 2.7 0 1.8 2.0 2.1 2.0 0 0 0 0 0 1 0 0 0 0 0 6
7 2.3 0 2.7 1.8 2.0 2.1 0 0 0 0 0 0 1 0 0 0 0 7
8 1.9 0 2.3 2.7 1.8 2.0 0 0 0 0 0 0 0 1 0 0 0 8
9 2.0 0 1.9 2.3 2.7 1.8 0 0 0 0 0 0 0 0 1 0 0 9
10 2.3 0 2.0 1.9 2.3 2.7 0 0 0 0 0 0 0 0 0 1 0 10
11 2.8 0 2.3 2.0 1.9 2.3 0 0 0 0 0 0 0 0 0 0 1 11
12 2.4 0 2.8 2.3 2.0 1.9 0 0 0 0 0 0 0 0 0 0 0 12
13 2.3 0 2.4 2.8 2.3 2.0 1 0 0 0 0 0 0 0 0 0 0 13
14 2.7 0 2.3 2.4 2.8 2.3 0 1 0 0 0 0 0 0 0 0 0 14
15 2.7 0 2.7 2.3 2.4 2.8 0 0 1 0 0 0 0 0 0 0 0 15
16 2.9 0 2.7 2.7 2.3 2.4 0 0 0 1 0 0 0 0 0 0 0 16
17 3.0 0 2.9 2.7 2.7 2.3 0 0 0 0 1 0 0 0 0 0 0 17
18 2.2 0 3.0 2.9 2.7 2.7 0 0 0 0 0 1 0 0 0 0 0 18
19 2.3 0 2.2 3.0 2.9 2.7 0 0 0 0 0 0 1 0 0 0 0 19
20 2.8 0 2.3 2.2 3.0 2.9 0 0 0 0 0 0 0 1 0 0 0 20
21 2.8 0 2.8 2.3 2.2 3.0 0 0 0 0 0 0 0 0 1 0 0 21
22 2.8 0 2.8 2.8 2.3 2.2 0 0 0 0 0 0 0 0 0 1 0 22
23 2.2 0 2.8 2.8 2.8 2.3 0 0 0 0 0 0 0 0 0 0 1 23
24 2.6 0 2.2 2.8 2.8 2.8 0 0 0 0 0 0 0 0 0 0 0 24
25 2.8 0 2.6 2.2 2.8 2.8 1 0 0 0 0 0 0 0 0 0 0 25
26 2.5 0 2.8 2.6 2.2 2.8 0 1 0 0 0 0 0 0 0 0 0 26
27 2.4 0 2.5 2.8 2.6 2.2 0 0 1 0 0 0 0 0 0 0 0 27
28 2.3 0 2.4 2.5 2.8 2.6 0 0 0 1 0 0 0 0 0 0 0 28
29 1.9 0 2.3 2.4 2.5 2.8 0 0 0 0 1 0 0 0 0 0 0 29
30 1.7 0 1.9 2.3 2.4 2.5 0 0 0 0 0 1 0 0 0 0 0 30
31 2.0 0 1.7 1.9 2.3 2.4 0 0 0 0 0 0 1 0 0 0 0 31
32 2.1 0 2.0 1.7 1.9 2.3 0 0 0 0 0 0 0 1 0 0 0 32
33 1.7 0 2.1 2.0 1.7 1.9 0 0 0 0 0 0 0 0 1 0 0 33
34 1.8 0 1.7 2.1 2.0 1.7 0 0 0 0 0 0 0 0 0 1 0 34
35 1.8 0 1.8 1.7 2.1 2.0 0 0 0 0 0 0 0 0 0 0 1 35
36 1.8 0 1.8 1.8 1.7 2.1 0 0 0 0 0 0 0 0 0 0 0 36
37 1.3 1 1.8 1.8 1.8 1.7 1 0 0 0 0 0 0 0 0 0 0 37
38 1.3 1 1.3 1.8 1.8 1.8 0 1 0 0 0 0 0 0 0 0 0 38
39 1.3 1 1.3 1.3 1.8 1.8 0 0 1 0 0 0 0 0 0 0 0 39
40 1.2 1 1.3 1.3 1.3 1.8 0 0 0 1 0 0 0 0 0 0 0 40
41 1.4 1 1.2 1.3 1.3 1.3 0 0 0 0 1 0 0 0 0 0 0 41
42 2.2 1 1.4 1.2 1.3 1.3 0 0 0 0 0 1 0 0 0 0 0 42
43 2.9 1 2.2 1.4 1.2 1.3 0 0 0 0 0 0 1 0 0 0 0 43
44 3.1 1 2.9 2.2 1.4 1.2 0 0 0 0 0 0 0 1 0 0 0 44
45 3.5 1 3.1 2.9 2.2 1.4 0 0 0 0 0 0 0 0 1 0 0 45
46 3.6 1 3.5 3.1 2.9 2.2 0 0 0 0 0 0 0 0 0 1 0 46
47 4.4 1 3.6 3.5 3.1 2.9 0 0 0 0 0 0 0 0 0 0 1 47
48 4.1 1 4.4 3.6 3.5 3.1 0 0 0 0 0 0 0 0 0 0 0 48
49 5.1 1 4.1 4.4 3.6 3.5 1 0 0 0 0 0 0 0 0 0 0 49
50 5.8 1 5.1 4.1 4.4 3.6 0 1 0 0 0 0 0 0 0 0 0 50
51 5.9 1 5.8 5.1 4.1 4.4 0 0 1 0 0 0 0 0 0 0 0 51
52 5.4 1 5.9 5.8 5.1 4.1 0 0 0 1 0 0 0 0 0 0 0 52
53 5.5 1 5.4 5.9 5.8 5.1 0 0 0 0 1 0 0 0 0 0 0 53
54 4.8 1 5.5 5.4 5.9 5.8 0 0 0 0 0 1 0 0 0 0 0 54
55 3.2 1 4.8 5.5 5.4 5.9 0 0 0 0 0 0 1 0 0 0 0 55
56 2.7 1 3.2 4.8 5.5 5.4 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
0.2645856 0.1360197 1.1180927 -0.2687107 0.2744169 -0.2844884
M1 M2 M3 M4 M5 M6
0.2895800 0.0893610 0.0956344 -0.0744593 0.0764603 0.1055700
M7 M8 M9 M10 M11 t
-0.0471980 0.1102574 0.0274259 0.1524678 0.2161284 0.0006394
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.95305 -0.25219 -0.04914 0.31808 0.98444
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.2645856 0.3277436 0.807 0.425
x 0.1360197 0.2803443 0.485 0.630
y1 1.1180927 0.1553891 7.195 1.34e-08 ***
y2 -0.2687107 0.2346615 -1.145 0.259
y3 0.2744169 0.2388746 1.149 0.258
y4 -0.2844884 0.1872064 -1.520 0.137
M1 0.2895800 0.3403492 0.851 0.400
M2 0.0893610 0.3377544 0.265 0.793
M3 0.0956344 0.3373401 0.283 0.778
M4 -0.0744593 0.3378739 -0.220 0.827
M5 0.0764603 0.3392823 0.225 0.823
M6 0.1055700 0.3393434 0.311 0.757
M7 -0.0471980 0.3380179 -0.140 0.890
M8 0.1102574 0.3383325 0.326 0.746
M9 0.0274259 0.3506864 0.078 0.938
M10 0.1524678 0.3503877 0.435 0.666
M11 0.2161284 0.3488724 0.620 0.539
t 0.0006394 0.0087949 0.073 0.942
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4922 on 38 degrees of freedom
Multiple R-squared: 0.8738, Adjusted R-squared: 0.8174
F-statistic: 15.48 on 17 and 38 DF, p-value: 3.882e-12
> 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,] 0.42611292 0.8522258 0.5738871
[2,] 0.28314823 0.5662965 0.7168518
[3,] 0.43382590 0.8676518 0.5661741
[4,] 0.43647144 0.8729429 0.5635286
[5,] 0.36163519 0.7232704 0.6383648
[6,] 0.29837188 0.5967438 0.7016281
[7,] 0.23943717 0.4788743 0.7605628
[8,] 0.22744365 0.4548873 0.7725564
[9,] 0.18545308 0.3709062 0.8145469
[10,] 0.12853387 0.2570677 0.8714661
[11,] 0.14987851 0.2997570 0.8501215
[12,] 0.23266569 0.4653314 0.7673343
[13,] 0.16802942 0.3360588 0.8319706
[14,] 0.12262447 0.2452489 0.8773755
[15,] 0.08432488 0.1686498 0.9156751
> postscript(file="/var/www/html/rcomp/tmp/1xl6n1259096602.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2lyjw1259096602.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/33sr51259096602.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4rt7t1259096602.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vvys1259096602.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
0.28213156 -0.51487053 -0.03543830 -0.17822746 -0.08219745 0.84356381
7 8 9 10 11 12
-0.40844263 -0.25102613 -0.03295418 0.28787733 0.41099200 -0.39318924
13 14 15 16 17 18
-0.25569241 0.29635030 0.06734025 0.45792516 0.04453204 -0.72948889
19 20 21 22 23 24
0.38910163 0.43368503 0.23168410 -0.01467425 -0.78773381 0.64085502
25 26 27 28 29 30
-0.05782789 -0.10973239 -0.10793509 0.05162728 -0.27577075 -0.14305873
31 32 33 34 35 36
0.42419702 0.05825021 -0.34966583 -0.04046168 -0.26615036 0.11442528
37 38 39 40 41 42
-0.95305088 -0.16597603 -0.30724423 -0.10058148 -0.08257540 0.43718583
43 44 45 46 47 48
0.47602410 -0.13309923 0.15093591 -0.23274140 0.64289217 -0.36209105
49 50 51 52 53 54
0.98443962 0.49422865 0.38327738 -0.23074350 0.39601156 -0.40820202
55 56
-0.88088011 -0.10780988
> postscript(file="/var/www/html/rcomp/tmp/6qio61259096602.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 0.28213156 NA
1 -0.51487053 0.28213156
2 -0.03543830 -0.51487053
3 -0.17822746 -0.03543830
4 -0.08219745 -0.17822746
5 0.84356381 -0.08219745
6 -0.40844263 0.84356381
7 -0.25102613 -0.40844263
8 -0.03295418 -0.25102613
9 0.28787733 -0.03295418
10 0.41099200 0.28787733
11 -0.39318924 0.41099200
12 -0.25569241 -0.39318924
13 0.29635030 -0.25569241
14 0.06734025 0.29635030
15 0.45792516 0.06734025
16 0.04453204 0.45792516
17 -0.72948889 0.04453204
18 0.38910163 -0.72948889
19 0.43368503 0.38910163
20 0.23168410 0.43368503
21 -0.01467425 0.23168410
22 -0.78773381 -0.01467425
23 0.64085502 -0.78773381
24 -0.05782789 0.64085502
25 -0.10973239 -0.05782789
26 -0.10793509 -0.10973239
27 0.05162728 -0.10793509
28 -0.27577075 0.05162728
29 -0.14305873 -0.27577075
30 0.42419702 -0.14305873
31 0.05825021 0.42419702
32 -0.34966583 0.05825021
33 -0.04046168 -0.34966583
34 -0.26615036 -0.04046168
35 0.11442528 -0.26615036
36 -0.95305088 0.11442528
37 -0.16597603 -0.95305088
38 -0.30724423 -0.16597603
39 -0.10058148 -0.30724423
40 -0.08257540 -0.10058148
41 0.43718583 -0.08257540
42 0.47602410 0.43718583
43 -0.13309923 0.47602410
44 0.15093591 -0.13309923
45 -0.23274140 0.15093591
46 0.64289217 -0.23274140
47 -0.36209105 0.64289217
48 0.98443962 -0.36209105
49 0.49422865 0.98443962
50 0.38327738 0.49422865
51 -0.23074350 0.38327738
52 0.39601156 -0.23074350
53 -0.40820202 0.39601156
54 -0.88088011 -0.40820202
55 -0.10780988 -0.88088011
56 NA -0.10780988
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.51487053 0.28213156
[2,] -0.03543830 -0.51487053
[3,] -0.17822746 -0.03543830
[4,] -0.08219745 -0.17822746
[5,] 0.84356381 -0.08219745
[6,] -0.40844263 0.84356381
[7,] -0.25102613 -0.40844263
[8,] -0.03295418 -0.25102613
[9,] 0.28787733 -0.03295418
[10,] 0.41099200 0.28787733
[11,] -0.39318924 0.41099200
[12,] -0.25569241 -0.39318924
[13,] 0.29635030 -0.25569241
[14,] 0.06734025 0.29635030
[15,] 0.45792516 0.06734025
[16,] 0.04453204 0.45792516
[17,] -0.72948889 0.04453204
[18,] 0.38910163 -0.72948889
[19,] 0.43368503 0.38910163
[20,] 0.23168410 0.43368503
[21,] -0.01467425 0.23168410
[22,] -0.78773381 -0.01467425
[23,] 0.64085502 -0.78773381
[24,] -0.05782789 0.64085502
[25,] -0.10973239 -0.05782789
[26,] -0.10793509 -0.10973239
[27,] 0.05162728 -0.10793509
[28,] -0.27577075 0.05162728
[29,] -0.14305873 -0.27577075
[30,] 0.42419702 -0.14305873
[31,] 0.05825021 0.42419702
[32,] -0.34966583 0.05825021
[33,] -0.04046168 -0.34966583
[34,] -0.26615036 -0.04046168
[35,] 0.11442528 -0.26615036
[36,] -0.95305088 0.11442528
[37,] -0.16597603 -0.95305088
[38,] -0.30724423 -0.16597603
[39,] -0.10058148 -0.30724423
[40,] -0.08257540 -0.10058148
[41,] 0.43718583 -0.08257540
[42,] 0.47602410 0.43718583
[43,] -0.13309923 0.47602410
[44,] 0.15093591 -0.13309923
[45,] -0.23274140 0.15093591
[46,] 0.64289217 -0.23274140
[47,] -0.36209105 0.64289217
[48,] 0.98443962 -0.36209105
[49,] 0.49422865 0.98443962
[50,] 0.38327738 0.49422865
[51,] -0.23074350 0.38327738
[52,] 0.39601156 -0.23074350
[53,] -0.40820202 0.39601156
[54,] -0.88088011 -0.40820202
[55,] -0.10780988 -0.88088011
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.51487053 0.28213156
2 -0.03543830 -0.51487053
3 -0.17822746 -0.03543830
4 -0.08219745 -0.17822746
5 0.84356381 -0.08219745
6 -0.40844263 0.84356381
7 -0.25102613 -0.40844263
8 -0.03295418 -0.25102613
9 0.28787733 -0.03295418
10 0.41099200 0.28787733
11 -0.39318924 0.41099200
12 -0.25569241 -0.39318924
13 0.29635030 -0.25569241
14 0.06734025 0.29635030
15 0.45792516 0.06734025
16 0.04453204 0.45792516
17 -0.72948889 0.04453204
18 0.38910163 -0.72948889
19 0.43368503 0.38910163
20 0.23168410 0.43368503
21 -0.01467425 0.23168410
22 -0.78773381 -0.01467425
23 0.64085502 -0.78773381
24 -0.05782789 0.64085502
25 -0.10973239 -0.05782789
26 -0.10793509 -0.10973239
27 0.05162728 -0.10793509
28 -0.27577075 0.05162728
29 -0.14305873 -0.27577075
30 0.42419702 -0.14305873
31 0.05825021 0.42419702
32 -0.34966583 0.05825021
33 -0.04046168 -0.34966583
34 -0.26615036 -0.04046168
35 0.11442528 -0.26615036
36 -0.95305088 0.11442528
37 -0.16597603 -0.95305088
38 -0.30724423 -0.16597603
39 -0.10058148 -0.30724423
40 -0.08257540 -0.10058148
41 0.43718583 -0.08257540
42 0.47602410 0.43718583
43 -0.13309923 0.47602410
44 0.15093591 -0.13309923
45 -0.23274140 0.15093591
46 0.64289217 -0.23274140
47 -0.36209105 0.64289217
48 0.98443962 -0.36209105
49 0.49422865 0.98443962
50 0.38327738 0.49422865
51 -0.23074350 0.38327738
52 0.39601156 -0.23074350
53 -0.40820202 0.39601156
54 -0.88088011 -0.40820202
55 -0.10780988 -0.88088011
> 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/77yba1259096602.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8rdbl1259096602.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9vohf1259096602.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10cgkv1259096602.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11txts1259096602.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/12xvnc1259096602.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/135cyj1259096602.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/145zhv1259096602.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/15dvbg1259096602.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/16mtfd1259096602.tab")
+ }
>
> system("convert tmp/1xl6n1259096602.ps tmp/1xl6n1259096602.png")
> system("convert tmp/2lyjw1259096602.ps tmp/2lyjw1259096602.png")
> system("convert tmp/33sr51259096602.ps tmp/33sr51259096602.png")
> system("convert tmp/4rt7t1259096602.ps tmp/4rt7t1259096602.png")
> system("convert tmp/5vvys1259096602.ps tmp/5vvys1259096602.png")
> system("convert tmp/6qio61259096602.ps tmp/6qio61259096602.png")
> system("convert tmp/77yba1259096602.ps tmp/77yba1259096602.png")
> system("convert tmp/8rdbl1259096602.ps tmp/8rdbl1259096602.png")
> system("convert tmp/9vohf1259096602.ps tmp/9vohf1259096602.png")
> system("convert tmp/10cgkv1259096602.ps tmp/10cgkv1259096602.png")
>
>
> proc.time()
user system elapsed
2.331 1.531 2.725