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.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(8.6
+ ,10
+ ,8.9
+ ,8.9
+ ,8.3
+ ,9.2
+ ,8.6
+ ,8.9
+ ,8.3
+ ,9.2
+ ,8.3
+ ,8.6
+ ,8.3
+ ,9.5
+ ,8.3
+ ,8.3
+ ,8.4
+ ,9.6
+ ,8.3
+ ,8.3
+ ,8.5
+ ,9.5
+ ,8.4
+ ,8.3
+ ,8.4
+ ,9.1
+ ,8.5
+ ,8.4
+ ,8.6
+ ,8.9
+ ,8.4
+ ,8.5
+ ,8.5
+ ,9
+ ,8.6
+ ,8.4
+ ,8.5
+ ,10.1
+ ,8.5
+ ,8.6
+ ,8.4
+ ,10.3
+ ,8.5
+ ,8.5
+ ,8.5
+ ,10.2
+ ,8.4
+ ,8.5
+ ,8.5
+ ,9.6
+ ,8.5
+ ,8.4
+ ,8.5
+ ,9.2
+ ,8.5
+ ,8.5
+ ,8.5
+ ,9.3
+ ,8.5
+ ,8.5
+ ,8.5
+ ,9.4
+ ,8.5
+ ,8.5
+ ,8.5
+ ,9.4
+ ,8.5
+ ,8.5
+ ,8.5
+ ,9.2
+ ,8.5
+ ,8.5
+ ,8.5
+ ,9
+ ,8.5
+ ,8.5
+ ,8.6
+ ,9
+ ,8.5
+ ,8.5
+ ,8.4
+ ,9
+ ,8.6
+ ,8.5
+ ,8.1
+ ,9.8
+ ,8.4
+ ,8.6
+ ,8.0
+ ,10
+ ,8.1
+ ,8.4
+ ,8.0
+ ,9.8
+ ,8.0
+ ,8.1
+ ,8.0
+ ,9.3
+ ,8.0
+ ,8.0
+ ,8.0
+ ,9
+ ,8.0
+ ,8.0
+ ,7.9
+ ,9
+ ,8.0
+ ,8.0
+ ,7.8
+ ,9.1
+ ,7.9
+ ,8.0
+ ,7.8
+ ,9.1
+ ,7.8
+ ,7.9
+ ,7.9
+ ,9.1
+ ,7.8
+ ,7.8
+ ,8.1
+ ,9.2
+ ,7.9
+ ,7.8
+ ,8.0
+ ,8.8
+ ,8.1
+ ,7.9
+ ,7.6
+ ,8.3
+ ,8.0
+ ,8.1
+ ,7.3
+ ,8.4
+ ,7.6
+ ,8.0
+ ,7.0
+ ,8.1
+ ,7.3
+ ,7.6
+ ,6.8
+ ,7.7
+ ,7.0
+ ,7.3
+ ,7.0
+ ,7.9
+ ,6.8
+ ,7.0
+ ,7.1
+ ,7.9
+ ,7.0
+ ,6.8
+ ,7.2
+ ,8
+ ,7.1
+ ,7.0
+ ,7.1
+ ,7.9
+ ,7.2
+ ,7.1
+ ,6.9
+ ,7.6
+ ,7.1
+ ,7.2
+ ,6.7
+ ,7.1
+ ,6.9
+ ,7.1
+ ,6.7
+ ,6.8
+ ,6.7
+ ,6.9
+ ,6.6
+ ,6.5
+ ,6.7
+ ,6.7
+ ,6.9
+ ,6.9
+ ,6.6
+ ,6.7
+ ,7.3
+ ,8.2
+ ,6.9
+ ,6.6
+ ,7.5
+ ,8.7
+ ,7.3
+ ,6.9
+ ,7.3
+ ,8.3
+ ,7.5
+ ,7.3
+ ,7.1
+ ,7.9
+ ,7.3
+ ,7.5
+ ,6.9
+ ,7.5
+ ,7.1
+ ,7.3
+ ,7.1
+ ,7.8
+ ,6.9
+ ,7.1
+ ,7.5
+ ,8.3
+ ,7.1
+ ,6.9
+ ,7.7
+ ,8.4
+ ,7.5
+ ,7.1
+ ,7.8
+ ,8.2
+ ,7.7
+ ,7.5
+ ,7.8
+ ,7.7
+ ,7.8
+ ,7.7
+ ,7.7
+ ,7.2
+ ,7.8
+ ,7.8
+ ,7.8
+ ,7.3
+ ,7.7
+ ,7.8
+ ,7.8
+ ,8.1
+ ,7.8
+ ,7.7
+ ,7.9
+ ,8.5
+ ,7.8
+ ,7.8)
+ ,dim=c(4
+ ,59)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2')
+ ,1:59))
> y <- array(NA,dim=c(4,59),dimnames=list(c('Y','X','Y1','Y2'),1:59))
> 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 8.6 10.0 8.9 8.9 1 0 0 0 0 0 0 0 0 0 0 1
2 8.3 9.2 8.6 8.9 0 1 0 0 0 0 0 0 0 0 0 2
3 8.3 9.2 8.3 8.6 0 0 1 0 0 0 0 0 0 0 0 3
4 8.3 9.5 8.3 8.3 0 0 0 1 0 0 0 0 0 0 0 4
5 8.4 9.6 8.3 8.3 0 0 0 0 1 0 0 0 0 0 0 5
6 8.5 9.5 8.4 8.3 0 0 0 0 0 1 0 0 0 0 0 6
7 8.4 9.1 8.5 8.4 0 0 0 0 0 0 1 0 0 0 0 7
8 8.6 8.9 8.4 8.5 0 0 0 0 0 0 0 1 0 0 0 8
9 8.5 9.0 8.6 8.4 0 0 0 0 0 0 0 0 1 0 0 9
10 8.5 10.1 8.5 8.6 0 0 0 0 0 0 0 0 0 1 0 10
11 8.4 10.3 8.5 8.5 0 0 0 0 0 0 0 0 0 0 1 11
12 8.5 10.2 8.4 8.5 0 0 0 0 0 0 0 0 0 0 0 12
13 8.5 9.6 8.5 8.4 1 0 0 0 0 0 0 0 0 0 0 13
14 8.5 9.2 8.5 8.5 0 1 0 0 0 0 0 0 0 0 0 14
15 8.5 9.3 8.5 8.5 0 0 1 0 0 0 0 0 0 0 0 15
16 8.5 9.4 8.5 8.5 0 0 0 1 0 0 0 0 0 0 0 16
17 8.5 9.4 8.5 8.5 0 0 0 0 1 0 0 0 0 0 0 17
18 8.5 9.2 8.5 8.5 0 0 0 0 0 1 0 0 0 0 0 18
19 8.5 9.0 8.5 8.5 0 0 0 0 0 0 1 0 0 0 0 19
20 8.6 9.0 8.5 8.5 0 0 0 0 0 0 0 1 0 0 0 20
21 8.4 9.0 8.6 8.5 0 0 0 0 0 0 0 0 1 0 0 21
22 8.1 9.8 8.4 8.6 0 0 0 0 0 0 0 0 0 1 0 22
23 8.0 10.0 8.1 8.4 0 0 0 0 0 0 0 0 0 0 1 23
24 8.0 9.8 8.0 8.1 0 0 0 0 0 0 0 0 0 0 0 24
25 8.0 9.3 8.0 8.0 1 0 0 0 0 0 0 0 0 0 0 25
26 8.0 9.0 8.0 8.0 0 1 0 0 0 0 0 0 0 0 0 26
27 7.9 9.0 8.0 8.0 0 0 1 0 0 0 0 0 0 0 0 27
28 7.8 9.1 7.9 8.0 0 0 0 1 0 0 0 0 0 0 0 28
29 7.8 9.1 7.8 7.9 0 0 0 0 1 0 0 0 0 0 0 29
30 7.9 9.1 7.8 7.8 0 0 0 0 0 1 0 0 0 0 0 30
31 8.1 9.2 7.9 7.8 0 0 0 0 0 0 1 0 0 0 0 31
32 8.0 8.8 8.1 7.9 0 0 0 0 0 0 0 1 0 0 0 32
33 7.6 8.3 8.0 8.1 0 0 0 0 0 0 0 0 1 0 0 33
34 7.3 8.4 7.6 8.0 0 0 0 0 0 0 0 0 0 1 0 34
35 7.0 8.1 7.3 7.6 0 0 0 0 0 0 0 0 0 0 1 35
36 6.8 7.7 7.0 7.3 0 0 0 0 0 0 0 0 0 0 0 36
37 7.0 7.9 6.8 7.0 1 0 0 0 0 0 0 0 0 0 0 37
38 7.1 7.9 7.0 6.8 0 1 0 0 0 0 0 0 0 0 0 38
39 7.2 8.0 7.1 7.0 0 0 1 0 0 0 0 0 0 0 0 39
40 7.1 7.9 7.2 7.1 0 0 0 1 0 0 0 0 0 0 0 40
41 6.9 7.6 7.1 7.2 0 0 0 0 1 0 0 0 0 0 0 41
42 6.7 7.1 6.9 7.1 0 0 0 0 0 1 0 0 0 0 0 42
43 6.7 6.8 6.7 6.9 0 0 0 0 0 0 1 0 0 0 0 43
44 6.6 6.5 6.7 6.7 0 0 0 0 0 0 0 1 0 0 0 44
45 6.9 6.9 6.6 6.7 0 0 0 0 0 0 0 0 1 0 0 45
46 7.3 8.2 6.9 6.6 0 0 0 0 0 0 0 0 0 1 0 46
47 7.5 8.7 7.3 6.9 0 0 0 0 0 0 0 0 0 0 1 47
48 7.3 8.3 7.5 7.3 0 0 0 0 0 0 0 0 0 0 0 48
49 7.1 7.9 7.3 7.5 1 0 0 0 0 0 0 0 0 0 0 49
50 6.9 7.5 7.1 7.3 0 1 0 0 0 0 0 0 0 0 0 50
51 7.1 7.8 6.9 7.1 0 0 1 0 0 0 0 0 0 0 0 51
52 7.5 8.3 7.1 6.9 0 0 0 1 0 0 0 0 0 0 0 52
53 7.7 8.4 7.5 7.1 0 0 0 0 1 0 0 0 0 0 0 53
54 7.8 8.2 7.7 7.5 0 0 0 0 0 1 0 0 0 0 0 54
55 7.8 7.7 7.8 7.7 0 0 0 0 0 0 1 0 0 0 0 55
56 7.7 7.2 7.8 7.8 0 0 0 0 0 0 0 1 0 0 0 56
57 7.8 7.3 7.7 7.8 0 0 0 0 0 0 0 0 1 0 0 57
58 7.8 8.1 7.8 7.7 0 0 0 0 0 0 0 0 0 1 0 58
59 7.9 8.5 7.8 7.8 0 0 0 0 0 0 0 0 0 0 1 59
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 M1 M2
0.201644 0.211283 1.074428 -0.360758 0.082501 0.123583
M3 M4 M5 M6 M7 M8
0.204738 0.132844 0.126497 0.179670 0.238305 0.281165
M9 M10 M11 t
0.222129 0.071317 0.008367 0.002026
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.317548 -0.092015 0.005887 0.083010 0.261817
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.201644 0.515655 0.391 0.69770
X 0.211283 0.068560 3.082 0.00358 **
Y1 1.074428 0.159756 6.725 3.22e-08 ***
Y2 -0.360758 0.133760 -2.697 0.00995 **
M1 0.082501 0.101940 0.809 0.42279
M2 0.123583 0.108378 1.140 0.26047
M3 0.204738 0.103707 1.974 0.05480 .
M4 0.132844 0.103238 1.287 0.20506
M5 0.126497 0.103685 1.220 0.22911
M6 0.179670 0.107244 1.675 0.10112
M7 0.238305 0.114831 2.075 0.04398 *
M8 0.281165 0.125354 2.243 0.03011 *
M9 0.222129 0.123218 1.803 0.07844 .
M10 0.071317 0.100561 0.709 0.48203
M11 0.008367 0.100645 0.083 0.93413
t 0.002026 0.002383 0.850 0.40004
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1483 on 43 degrees of freedom
Multiple R-squared: 0.9566, Adjusted R-squared: 0.9414
F-statistic: 63.12 on 15 and 43 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,] 0.02639316 0.05278633 0.973606836
[2,] 0.14827175 0.29654351 0.851728247
[3,] 0.10141766 0.20283532 0.898582339
[4,] 0.39967367 0.79934735 0.600326327
[5,] 0.27702597 0.55405194 0.722974030
[6,] 0.34087032 0.68174064 0.659129679
[7,] 0.25668632 0.51337264 0.743313680
[8,] 0.29550875 0.59101750 0.704491248
[9,] 0.41708783 0.83417566 0.582912170
[10,] 0.36500685 0.73001369 0.634993153
[11,] 0.32628998 0.65257997 0.673710017
[12,] 0.27955774 0.55911549 0.720442255
[13,] 0.24055995 0.48111991 0.759440045
[14,] 0.41629681 0.83259362 0.583703188
[15,] 0.57850118 0.84299763 0.421498816
[16,] 0.72243062 0.55513876 0.277569380
[17,] 0.87511740 0.24976519 0.124882595
[18,] 0.79782048 0.40435904 0.202179519
[19,] 0.90456407 0.19087185 0.095435925
[20,] 0.96352613 0.07294774 0.036473870
[21,] 0.99281061 0.01437878 0.007189389
[22,] 0.98073645 0.03852710 0.019263550
> postscript(file="/var/www/html/rcomp/tmp/1evt61258723826.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ir2j1258723826.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3k0c71258723826.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4lexw1258723826.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/509191258723826.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 = 59
Frequency = 1
1 2 3 4 5 6
-0.150662663 -0.002415729 0.128504817 0.026761285 0.109954146 0.068441328
7 8 9 10 11 12
-0.079072679 0.261816648 -0.053262469 0.042706992 -0.074700429 0.160211745
13 14 15 16 17 18
0.058936386 0.136417612 0.032108852 0.080849211 0.085170356 0.072228603
19 20 21 22 23 24
0.053825034 0.108939237 -0.141493041 -0.210771718 -0.041926572 0.005886567
25 26 27 28 29 30
-0.009074297 0.011202871 -0.171977604 -0.115794465 -0.040106313 -0.031380409
31 32 33 34 35 36
-0.020611614 -0.259794058 -0.317547804 -0.096194472 -0.093859447 0.011095823
37 38 39 40 41 42
0.190970977 -0.039173817 -0.078773811 -0.159143889 -0.147919335 -0.118666446
43 44 45 46 47 48
0.026792284 -0.126860205 0.253079938 0.168794387 0.002534083 -0.177194135
49 50 51 52 53 54
-0.090170403 -0.106030937 0.090137747 0.167327858 -0.007098855 0.009376924
55 56 57 58 59
0.019066976 0.015898378 0.259223376 0.095464811 0.207952366
> postscript(file="/var/www/html/rcomp/tmp/6q15c1258723826.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 = 59
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.150662663 NA
1 -0.002415729 -0.150662663
2 0.128504817 -0.002415729
3 0.026761285 0.128504817
4 0.109954146 0.026761285
5 0.068441328 0.109954146
6 -0.079072679 0.068441328
7 0.261816648 -0.079072679
8 -0.053262469 0.261816648
9 0.042706992 -0.053262469
10 -0.074700429 0.042706992
11 0.160211745 -0.074700429
12 0.058936386 0.160211745
13 0.136417612 0.058936386
14 0.032108852 0.136417612
15 0.080849211 0.032108852
16 0.085170356 0.080849211
17 0.072228603 0.085170356
18 0.053825034 0.072228603
19 0.108939237 0.053825034
20 -0.141493041 0.108939237
21 -0.210771718 -0.141493041
22 -0.041926572 -0.210771718
23 0.005886567 -0.041926572
24 -0.009074297 0.005886567
25 0.011202871 -0.009074297
26 -0.171977604 0.011202871
27 -0.115794465 -0.171977604
28 -0.040106313 -0.115794465
29 -0.031380409 -0.040106313
30 -0.020611614 -0.031380409
31 -0.259794058 -0.020611614
32 -0.317547804 -0.259794058
33 -0.096194472 -0.317547804
34 -0.093859447 -0.096194472
35 0.011095823 -0.093859447
36 0.190970977 0.011095823
37 -0.039173817 0.190970977
38 -0.078773811 -0.039173817
39 -0.159143889 -0.078773811
40 -0.147919335 -0.159143889
41 -0.118666446 -0.147919335
42 0.026792284 -0.118666446
43 -0.126860205 0.026792284
44 0.253079938 -0.126860205
45 0.168794387 0.253079938
46 0.002534083 0.168794387
47 -0.177194135 0.002534083
48 -0.090170403 -0.177194135
49 -0.106030937 -0.090170403
50 0.090137747 -0.106030937
51 0.167327858 0.090137747
52 -0.007098855 0.167327858
53 0.009376924 -0.007098855
54 0.019066976 0.009376924
55 0.015898378 0.019066976
56 0.259223376 0.015898378
57 0.095464811 0.259223376
58 0.207952366 0.095464811
59 NA 0.207952366
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.002415729 -0.150662663
[2,] 0.128504817 -0.002415729
[3,] 0.026761285 0.128504817
[4,] 0.109954146 0.026761285
[5,] 0.068441328 0.109954146
[6,] -0.079072679 0.068441328
[7,] 0.261816648 -0.079072679
[8,] -0.053262469 0.261816648
[9,] 0.042706992 -0.053262469
[10,] -0.074700429 0.042706992
[11,] 0.160211745 -0.074700429
[12,] 0.058936386 0.160211745
[13,] 0.136417612 0.058936386
[14,] 0.032108852 0.136417612
[15,] 0.080849211 0.032108852
[16,] 0.085170356 0.080849211
[17,] 0.072228603 0.085170356
[18,] 0.053825034 0.072228603
[19,] 0.108939237 0.053825034
[20,] -0.141493041 0.108939237
[21,] -0.210771718 -0.141493041
[22,] -0.041926572 -0.210771718
[23,] 0.005886567 -0.041926572
[24,] -0.009074297 0.005886567
[25,] 0.011202871 -0.009074297
[26,] -0.171977604 0.011202871
[27,] -0.115794465 -0.171977604
[28,] -0.040106313 -0.115794465
[29,] -0.031380409 -0.040106313
[30,] -0.020611614 -0.031380409
[31,] -0.259794058 -0.020611614
[32,] -0.317547804 -0.259794058
[33,] -0.096194472 -0.317547804
[34,] -0.093859447 -0.096194472
[35,] 0.011095823 -0.093859447
[36,] 0.190970977 0.011095823
[37,] -0.039173817 0.190970977
[38,] -0.078773811 -0.039173817
[39,] -0.159143889 -0.078773811
[40,] -0.147919335 -0.159143889
[41,] -0.118666446 -0.147919335
[42,] 0.026792284 -0.118666446
[43,] -0.126860205 0.026792284
[44,] 0.253079938 -0.126860205
[45,] 0.168794387 0.253079938
[46,] 0.002534083 0.168794387
[47,] -0.177194135 0.002534083
[48,] -0.090170403 -0.177194135
[49,] -0.106030937 -0.090170403
[50,] 0.090137747 -0.106030937
[51,] 0.167327858 0.090137747
[52,] -0.007098855 0.167327858
[53,] 0.009376924 -0.007098855
[54,] 0.019066976 0.009376924
[55,] 0.015898378 0.019066976
[56,] 0.259223376 0.015898378
[57,] 0.095464811 0.259223376
[58,] 0.207952366 0.095464811
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.002415729 -0.150662663
2 0.128504817 -0.002415729
3 0.026761285 0.128504817
4 0.109954146 0.026761285
5 0.068441328 0.109954146
6 -0.079072679 0.068441328
7 0.261816648 -0.079072679
8 -0.053262469 0.261816648
9 0.042706992 -0.053262469
10 -0.074700429 0.042706992
11 0.160211745 -0.074700429
12 0.058936386 0.160211745
13 0.136417612 0.058936386
14 0.032108852 0.136417612
15 0.080849211 0.032108852
16 0.085170356 0.080849211
17 0.072228603 0.085170356
18 0.053825034 0.072228603
19 0.108939237 0.053825034
20 -0.141493041 0.108939237
21 -0.210771718 -0.141493041
22 -0.041926572 -0.210771718
23 0.005886567 -0.041926572
24 -0.009074297 0.005886567
25 0.011202871 -0.009074297
26 -0.171977604 0.011202871
27 -0.115794465 -0.171977604
28 -0.040106313 -0.115794465
29 -0.031380409 -0.040106313
30 -0.020611614 -0.031380409
31 -0.259794058 -0.020611614
32 -0.317547804 -0.259794058
33 -0.096194472 -0.317547804
34 -0.093859447 -0.096194472
35 0.011095823 -0.093859447
36 0.190970977 0.011095823
37 -0.039173817 0.190970977
38 -0.078773811 -0.039173817
39 -0.159143889 -0.078773811
40 -0.147919335 -0.159143889
41 -0.118666446 -0.147919335
42 0.026792284 -0.118666446
43 -0.126860205 0.026792284
44 0.253079938 -0.126860205
45 0.168794387 0.253079938
46 0.002534083 0.168794387
47 -0.177194135 0.002534083
48 -0.090170403 -0.177194135
49 -0.106030937 -0.090170403
50 0.090137747 -0.106030937
51 0.167327858 0.090137747
52 -0.007098855 0.167327858
53 0.009376924 -0.007098855
54 0.019066976 0.009376924
55 0.015898378 0.019066976
56 0.259223376 0.015898378
57 0.095464811 0.259223376
58 0.207952366 0.095464811
> 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/7sh9k1258723826.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/80j771258723826.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9t5uk1258723826.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10kk581258723826.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11fj2s1258723826.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/129mr41258723826.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/13vhc01258723826.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/14et0l1258723826.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/15rgxe1258723826.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/16vt111258723826.tab")
+ }
>
> system("convert tmp/1evt61258723826.ps tmp/1evt61258723826.png")
> system("convert tmp/2ir2j1258723826.ps tmp/2ir2j1258723826.png")
> system("convert tmp/3k0c71258723826.ps tmp/3k0c71258723826.png")
> system("convert tmp/4lexw1258723826.ps tmp/4lexw1258723826.png")
> system("convert tmp/509191258723826.ps tmp/509191258723826.png")
> system("convert tmp/6q15c1258723826.ps tmp/6q15c1258723826.png")
> system("convert tmp/7sh9k1258723826.ps tmp/7sh9k1258723826.png")
> system("convert tmp/80j771258723826.ps tmp/80j771258723826.png")
> system("convert tmp/9t5uk1258723826.ps tmp/9t5uk1258723826.png")
> system("convert tmp/10kk581258723826.ps tmp/10kk581258723826.png")
>
>
> proc.time()
user system elapsed
2.401 1.588 2.798