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(8.2
+ ,103.9
+ ,8.7
+ ,9.3
+ ,9.3
+ ,8.3
+ ,101.6
+ ,8.2
+ ,8.7
+ ,9.3
+ ,8.5
+ ,94.6
+ ,8.3
+ ,8.2
+ ,8.7
+ ,8.6
+ ,95.9
+ ,8.5
+ ,8.3
+ ,8.2
+ ,8.5
+ ,104.7
+ ,8.6
+ ,8.5
+ ,8.3
+ ,8.2
+ ,102.8
+ ,8.5
+ ,8.6
+ ,8.5
+ ,8.1
+ ,98.1
+ ,8.2
+ ,8.5
+ ,8.6
+ ,7.9
+ ,113.9
+ ,8.1
+ ,8.2
+ ,8.5
+ ,8.6
+ ,80.9
+ ,7.9
+ ,8.1
+ ,8.2
+ ,8.7
+ ,95.7
+ ,8.6
+ ,7.9
+ ,8.1
+ ,8.7
+ ,113.2
+ ,8.7
+ ,8.6
+ ,7.9
+ ,8.5
+ ,105.9
+ ,8.7
+ ,8.7
+ ,8.6
+ ,8.4
+ ,108.8
+ ,8.5
+ ,8.7
+ ,8.7
+ ,8.5
+ ,102.3
+ ,8.4
+ ,8.5
+ ,8.7
+ ,8.7
+ ,99
+ ,8.5
+ ,8.4
+ ,8.5
+ ,8.7
+ ,100.7
+ ,8.7
+ ,8.5
+ ,8.4
+ ,8.6
+ ,115.5
+ ,8.7
+ ,8.7
+ ,8.5
+ ,8.5
+ ,100.7
+ ,8.6
+ ,8.7
+ ,8.7
+ ,8.3
+ ,109.9
+ ,8.5
+ ,8.6
+ ,8.7
+ ,8
+ ,114.6
+ ,8.3
+ ,8.5
+ ,8.6
+ ,8.2
+ ,85.4
+ ,8
+ ,8.3
+ ,8.5
+ ,8.1
+ ,100.5
+ ,8.2
+ ,8
+ ,8.3
+ ,8.1
+ ,114.8
+ ,8.1
+ ,8.2
+ ,8
+ ,8
+ ,116.5
+ ,8.1
+ ,8.1
+ ,8.2
+ ,7.9
+ ,112.9
+ ,8
+ ,8.1
+ ,8.1
+ ,7.9
+ ,102
+ ,7.9
+ ,8
+ ,8.1
+ ,8
+ ,106
+ ,7.9
+ ,7.9
+ ,8
+ ,8
+ ,105.3
+ ,8
+ ,7.9
+ ,7.9
+ ,7.9
+ ,118.8
+ ,8
+ ,8
+ ,7.9
+ ,8
+ ,106.1
+ ,7.9
+ ,8
+ ,8
+ ,7.7
+ ,109.3
+ ,8
+ ,7.9
+ ,8
+ ,7.2
+ ,117.2
+ ,7.7
+ ,8
+ ,7.9
+ ,7.5
+ ,92.5
+ ,7.2
+ ,7.7
+ ,8
+ ,7.3
+ ,104.2
+ ,7.5
+ ,7.2
+ ,7.7
+ ,7
+ ,112.5
+ ,7.3
+ ,7.5
+ ,7.2
+ ,7
+ ,122.4
+ ,7
+ ,7.3
+ ,7.5
+ ,7
+ ,113.3
+ ,7
+ ,7
+ ,7.3
+ ,7.2
+ ,100
+ ,7
+ ,7
+ ,7
+ ,7.3
+ ,110.7
+ ,7.2
+ ,7
+ ,7
+ ,7.1
+ ,112.8
+ ,7.3
+ ,7.2
+ ,7
+ ,6.8
+ ,109.8
+ ,7.1
+ ,7.3
+ ,7.2
+ ,6.4
+ ,117.3
+ ,6.8
+ ,7.1
+ ,7.3
+ ,6.1
+ ,109.1
+ ,6.4
+ ,6.8
+ ,7.1
+ ,6.5
+ ,115.9
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.7
+ ,96
+ ,6.5
+ ,6.1
+ ,6.4
+ ,7.9
+ ,99.8
+ ,7.7
+ ,6.5
+ ,6.1
+ ,7.5
+ ,116.8
+ ,7.9
+ ,7.7
+ ,6.5
+ ,6.9
+ ,115.7
+ ,7.5
+ ,7.9
+ ,7.7
+ ,6.6
+ ,99.4
+ ,6.9
+ ,7.5
+ ,7.9
+ ,6.9
+ ,94.3
+ ,6.6
+ ,6.9
+ ,7.5
+ ,7.7
+ ,91
+ ,6.9
+ ,6.6
+ ,6.9
+ ,8
+ ,93.2
+ ,7.7
+ ,6.9
+ ,6.6
+ ,8
+ ,103.1
+ ,8
+ ,7.7
+ ,6.9
+ ,7.7
+ ,94.1
+ ,8
+ ,8
+ ,7.7
+ ,7.3
+ ,91.8
+ ,7.7
+ ,8
+ ,8
+ ,7.4
+ ,102.7
+ ,7.3
+ ,7.7
+ ,8
+ ,8.1
+ ,82.6
+ ,7.4
+ ,7.3
+ ,7.7)
+ ,dim=c(5
+ ,57)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3')
+ ,1:57))
> y <- array(NA,dim=c(5,57),dimnames=list(c('Y','X','Y1','Y2','Y3'),1:57))
> 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 = 'Do not include Seasonal 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 t
1 8.2 103.9 8.7 9.3 9.3 1
2 8.3 101.6 8.2 8.7 9.3 2
3 8.5 94.6 8.3 8.2 8.7 3
4 8.6 95.9 8.5 8.3 8.2 4
5 8.5 104.7 8.6 8.5 8.3 5
6 8.2 102.8 8.5 8.6 8.5 6
7 8.1 98.1 8.2 8.5 8.6 7
8 7.9 113.9 8.1 8.2 8.5 8
9 8.6 80.9 7.9 8.1 8.2 9
10 8.7 95.7 8.6 7.9 8.1 10
11 8.7 113.2 8.7 8.6 7.9 11
12 8.5 105.9 8.7 8.7 8.6 12
13 8.4 108.8 8.5 8.7 8.7 13
14 8.5 102.3 8.4 8.5 8.7 14
15 8.7 99.0 8.5 8.4 8.5 15
16 8.7 100.7 8.7 8.5 8.4 16
17 8.6 115.5 8.7 8.7 8.5 17
18 8.5 100.7 8.6 8.7 8.7 18
19 8.3 109.9 8.5 8.6 8.7 19
20 8.0 114.6 8.3 8.5 8.6 20
21 8.2 85.4 8.0 8.3 8.5 21
22 8.1 100.5 8.2 8.0 8.3 22
23 8.1 114.8 8.1 8.2 8.0 23
24 8.0 116.5 8.1 8.1 8.2 24
25 7.9 112.9 8.0 8.1 8.1 25
26 7.9 102.0 7.9 8.0 8.1 26
27 8.0 106.0 7.9 7.9 8.0 27
28 8.0 105.3 8.0 7.9 7.9 28
29 7.9 118.8 8.0 8.0 7.9 29
30 8.0 106.1 7.9 8.0 8.0 30
31 7.7 109.3 8.0 7.9 8.0 31
32 7.2 117.2 7.7 8.0 7.9 32
33 7.5 92.5 7.2 7.7 8.0 33
34 7.3 104.2 7.5 7.2 7.7 34
35 7.0 112.5 7.3 7.5 7.2 35
36 7.0 122.4 7.0 7.3 7.5 36
37 7.0 113.3 7.0 7.0 7.3 37
38 7.2 100.0 7.0 7.0 7.0 38
39 7.3 110.7 7.2 7.0 7.0 39
40 7.1 112.8 7.3 7.2 7.0 40
41 6.8 109.8 7.1 7.3 7.2 41
42 6.4 117.3 6.8 7.1 7.3 42
43 6.1 109.1 6.4 6.8 7.1 43
44 6.5 115.9 6.1 6.4 6.8 44
45 7.7 96.0 6.5 6.1 6.4 45
46 7.9 99.8 7.7 6.5 6.1 46
47 7.5 116.8 7.9 7.7 6.5 47
48 6.9 115.7 7.5 7.9 7.7 48
49 6.6 99.4 6.9 7.5 7.9 49
50 6.9 94.3 6.6 6.9 7.5 50
51 7.7 91.0 6.9 6.6 6.9 51
52 8.0 93.2 7.7 6.9 6.6 52
53 8.0 103.1 8.0 7.7 6.9 53
54 7.7 94.1 8.0 8.0 7.7 54
55 7.3 91.8 7.7 8.0 8.0 55
56 7.4 102.7 7.3 7.7 8.0 56
57 8.1 82.6 7.4 7.3 7.7 57
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 t
4.562634 -0.017538 1.112872 -0.505979 0.074444 -0.008285
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.430218 -0.158363 -0.005221 0.153089 0.570173
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.562634 0.932637 4.892 1.04e-05 ***
X -0.017538 0.003539 -4.956 8.33e-06 ***
Y1 1.112872 0.125019 8.902 5.83e-12 ***
Y2 -0.505979 0.182097 -2.779 0.00762 **
Y3 0.074444 0.127874 0.582 0.56302
t -0.008285 0.003277 -2.528 0.01462 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2228 on 51 degrees of freedom
Multiple R-squared: 0.8967, Adjusted R-squared: 0.8866
F-statistic: 88.54 on 5 and 51 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,] 0.136037830 0.272075661 0.8639622
[2,] 0.127742922 0.255485845 0.8722571
[3,] 0.469709635 0.939419269 0.5302904
[4,] 0.342688889 0.685377777 0.6573111
[5,] 0.248493382 0.496986764 0.7515066
[6,] 0.168846468 0.337692936 0.8311535
[7,] 0.110363116 0.220726233 0.8896369
[8,] 0.067395928 0.134791857 0.9326041
[9,] 0.053230723 0.106461446 0.9467693
[10,] 0.041857515 0.083715029 0.9581425
[11,] 0.029530484 0.059060968 0.9704695
[12,] 0.027748878 0.055497755 0.9722511
[13,] 0.030351602 0.060703205 0.9696484
[14,] 0.041290034 0.082580067 0.9587100
[15,] 0.030949944 0.061899889 0.9690501
[16,] 0.019778625 0.039557250 0.9802214
[17,] 0.013247751 0.026495502 0.9867522
[18,] 0.009485855 0.018971710 0.9905141
[19,] 0.005672759 0.011345519 0.9943272
[20,] 0.003481739 0.006963477 0.9965183
[21,] 0.003462671 0.006925342 0.9965373
[22,] 0.004095613 0.008191226 0.9959044
[23,] 0.006695918 0.013391835 0.9933041
[24,] 0.014538056 0.029076112 0.9854619
[25,] 0.019142709 0.038285417 0.9808573
[26,] 0.026779411 0.053558822 0.9732206
[27,] 0.027893567 0.055787134 0.9721064
[28,] 0.063567761 0.127135522 0.9364322
[29,] 0.050747915 0.101495830 0.9492521
[30,] 0.043431624 0.086863249 0.9565684
[31,] 0.065642741 0.131285481 0.9343573
[32,] 0.099391425 0.198782851 0.9006086
[33,] 0.191813012 0.383626024 0.8081870
[34,] 0.184014982 0.368029963 0.8159850
[35,] 0.295186682 0.590373364 0.7048133
[36,] 0.392811891 0.785623782 0.6071881
[37,] 0.849322881 0.301354239 0.1506771
[38,] 0.758540814 0.482918373 0.2414592
[39,] 0.630603368 0.738793265 0.3693966
[40,] 0.655637035 0.688725929 0.3443630
> postscript(file="/var/www/html/rcomp/tmp/1m3wb1261080527.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2frsw1261080527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3m5zw1261080527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/42gga1261080527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5v66c1261080527.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 = 57
Frequency = 1
1 2 3 4 5 6
-0.200869420 0.119926175 -0.114164834 -0.117835201 -0.072752743 -0.250794077
7 8 9 10 11 12
-0.149118664 -0.096797146 0.227045727 -0.277870025 0.295115255 -0.026140220
13 14 15 16 17 18
0.148134148 0.152513513 0.155926708 0.029493740 0.291090880 0.036212454
19 20 21 22 23 24
0.066535088 0.036668681 -0.027043991 -0.213416051 0.280477056 0.153089243
25 26 27 28 29 30
0.116968854 -0.005220714 0.130062017 0.022227281 0.217871650 0.207267299
31 32 33 34 35 36
-0.190211907 -0.151473976 0.120821510 -0.430218030 -0.164778486 0.227463765
37 38 39 40 41 42
-0.060751655 -0.063388146 0.009977811 -0.154999356 -0.241045244 -0.276005118
43 44 45 46 47 48
-0.403287776 0.278057741 0.570173032 -0.265619251 -0.004367157 -0.158363186
49 50 51 52 53 54
-0.285504369 -0.006611499 0.302809315 -0.066492924 0.164005549 -0.193312998
55 56 57
-0.313837543 0.278965196 0.343392018
> postscript(file="/var/www/html/rcomp/tmp/6qfsi1261080527.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 = 57
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.200869420 NA
1 0.119926175 -0.200869420
2 -0.114164834 0.119926175
3 -0.117835201 -0.114164834
4 -0.072752743 -0.117835201
5 -0.250794077 -0.072752743
6 -0.149118664 -0.250794077
7 -0.096797146 -0.149118664
8 0.227045727 -0.096797146
9 -0.277870025 0.227045727
10 0.295115255 -0.277870025
11 -0.026140220 0.295115255
12 0.148134148 -0.026140220
13 0.152513513 0.148134148
14 0.155926708 0.152513513
15 0.029493740 0.155926708
16 0.291090880 0.029493740
17 0.036212454 0.291090880
18 0.066535088 0.036212454
19 0.036668681 0.066535088
20 -0.027043991 0.036668681
21 -0.213416051 -0.027043991
22 0.280477056 -0.213416051
23 0.153089243 0.280477056
24 0.116968854 0.153089243
25 -0.005220714 0.116968854
26 0.130062017 -0.005220714
27 0.022227281 0.130062017
28 0.217871650 0.022227281
29 0.207267299 0.217871650
30 -0.190211907 0.207267299
31 -0.151473976 -0.190211907
32 0.120821510 -0.151473976
33 -0.430218030 0.120821510
34 -0.164778486 -0.430218030
35 0.227463765 -0.164778486
36 -0.060751655 0.227463765
37 -0.063388146 -0.060751655
38 0.009977811 -0.063388146
39 -0.154999356 0.009977811
40 -0.241045244 -0.154999356
41 -0.276005118 -0.241045244
42 -0.403287776 -0.276005118
43 0.278057741 -0.403287776
44 0.570173032 0.278057741
45 -0.265619251 0.570173032
46 -0.004367157 -0.265619251
47 -0.158363186 -0.004367157
48 -0.285504369 -0.158363186
49 -0.006611499 -0.285504369
50 0.302809315 -0.006611499
51 -0.066492924 0.302809315
52 0.164005549 -0.066492924
53 -0.193312998 0.164005549
54 -0.313837543 -0.193312998
55 0.278965196 -0.313837543
56 0.343392018 0.278965196
57 NA 0.343392018
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.119926175 -0.200869420
[2,] -0.114164834 0.119926175
[3,] -0.117835201 -0.114164834
[4,] -0.072752743 -0.117835201
[5,] -0.250794077 -0.072752743
[6,] -0.149118664 -0.250794077
[7,] -0.096797146 -0.149118664
[8,] 0.227045727 -0.096797146
[9,] -0.277870025 0.227045727
[10,] 0.295115255 -0.277870025
[11,] -0.026140220 0.295115255
[12,] 0.148134148 -0.026140220
[13,] 0.152513513 0.148134148
[14,] 0.155926708 0.152513513
[15,] 0.029493740 0.155926708
[16,] 0.291090880 0.029493740
[17,] 0.036212454 0.291090880
[18,] 0.066535088 0.036212454
[19,] 0.036668681 0.066535088
[20,] -0.027043991 0.036668681
[21,] -0.213416051 -0.027043991
[22,] 0.280477056 -0.213416051
[23,] 0.153089243 0.280477056
[24,] 0.116968854 0.153089243
[25,] -0.005220714 0.116968854
[26,] 0.130062017 -0.005220714
[27,] 0.022227281 0.130062017
[28,] 0.217871650 0.022227281
[29,] 0.207267299 0.217871650
[30,] -0.190211907 0.207267299
[31,] -0.151473976 -0.190211907
[32,] 0.120821510 -0.151473976
[33,] -0.430218030 0.120821510
[34,] -0.164778486 -0.430218030
[35,] 0.227463765 -0.164778486
[36,] -0.060751655 0.227463765
[37,] -0.063388146 -0.060751655
[38,] 0.009977811 -0.063388146
[39,] -0.154999356 0.009977811
[40,] -0.241045244 -0.154999356
[41,] -0.276005118 -0.241045244
[42,] -0.403287776 -0.276005118
[43,] 0.278057741 -0.403287776
[44,] 0.570173032 0.278057741
[45,] -0.265619251 0.570173032
[46,] -0.004367157 -0.265619251
[47,] -0.158363186 -0.004367157
[48,] -0.285504369 -0.158363186
[49,] -0.006611499 -0.285504369
[50,] 0.302809315 -0.006611499
[51,] -0.066492924 0.302809315
[52,] 0.164005549 -0.066492924
[53,] -0.193312998 0.164005549
[54,] -0.313837543 -0.193312998
[55,] 0.278965196 -0.313837543
[56,] 0.343392018 0.278965196
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.119926175 -0.200869420
2 -0.114164834 0.119926175
3 -0.117835201 -0.114164834
4 -0.072752743 -0.117835201
5 -0.250794077 -0.072752743
6 -0.149118664 -0.250794077
7 -0.096797146 -0.149118664
8 0.227045727 -0.096797146
9 -0.277870025 0.227045727
10 0.295115255 -0.277870025
11 -0.026140220 0.295115255
12 0.148134148 -0.026140220
13 0.152513513 0.148134148
14 0.155926708 0.152513513
15 0.029493740 0.155926708
16 0.291090880 0.029493740
17 0.036212454 0.291090880
18 0.066535088 0.036212454
19 0.036668681 0.066535088
20 -0.027043991 0.036668681
21 -0.213416051 -0.027043991
22 0.280477056 -0.213416051
23 0.153089243 0.280477056
24 0.116968854 0.153089243
25 -0.005220714 0.116968854
26 0.130062017 -0.005220714
27 0.022227281 0.130062017
28 0.217871650 0.022227281
29 0.207267299 0.217871650
30 -0.190211907 0.207267299
31 -0.151473976 -0.190211907
32 0.120821510 -0.151473976
33 -0.430218030 0.120821510
34 -0.164778486 -0.430218030
35 0.227463765 -0.164778486
36 -0.060751655 0.227463765
37 -0.063388146 -0.060751655
38 0.009977811 -0.063388146
39 -0.154999356 0.009977811
40 -0.241045244 -0.154999356
41 -0.276005118 -0.241045244
42 -0.403287776 -0.276005118
43 0.278057741 -0.403287776
44 0.570173032 0.278057741
45 -0.265619251 0.570173032
46 -0.004367157 -0.265619251
47 -0.158363186 -0.004367157
48 -0.285504369 -0.158363186
49 -0.006611499 -0.285504369
50 0.302809315 -0.006611499
51 -0.066492924 0.302809315
52 0.164005549 -0.066492924
53 -0.193312998 0.164005549
54 -0.313837543 -0.193312998
55 0.278965196 -0.313837543
56 0.343392018 0.278965196
> 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/7vuut1261080527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8dizx1261080527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9nlty1261080527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10kkey1261080527.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11a1mi1261080528.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/12j1el1261080528.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/13ge9q1261080528.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/14iq5n1261080528.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/15fbfd1261080528.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/16w6551261080528.tab")
+ }
>
> try(system("convert tmp/1m3wb1261080527.ps tmp/1m3wb1261080527.png",intern=TRUE))
character(0)
> try(system("convert tmp/2frsw1261080527.ps tmp/2frsw1261080527.png",intern=TRUE))
character(0)
> try(system("convert tmp/3m5zw1261080527.ps tmp/3m5zw1261080527.png",intern=TRUE))
character(0)
> try(system("convert tmp/42gga1261080527.ps tmp/42gga1261080527.png",intern=TRUE))
character(0)
> try(system("convert tmp/5v66c1261080527.ps tmp/5v66c1261080527.png",intern=TRUE))
character(0)
> try(system("convert tmp/6qfsi1261080527.ps tmp/6qfsi1261080527.png",intern=TRUE))
character(0)
> try(system("convert tmp/7vuut1261080527.ps tmp/7vuut1261080527.png",intern=TRUE))
character(0)
> try(system("convert tmp/8dizx1261080527.ps tmp/8dizx1261080527.png",intern=TRUE))
character(0)
> try(system("convert tmp/9nlty1261080527.ps tmp/9nlty1261080527.png",intern=TRUE))
character(0)
> try(system("convert tmp/10kkey1261080527.ps tmp/10kkey1261080527.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.451 1.581 3.651