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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> x <- array(list(95.1
+ ,93.8
+ ,111.7
+ ,97
+ ,93.8
+ ,98.6
+ ,112.7
+ ,107.6
+ ,96.9
+ ,102.9
+ ,101
+ ,95.1
+ ,97.4
+ ,95.4
+ ,97
+ ,111.4
+ ,96.5
+ ,112.7
+ ,87.4
+ ,89.2
+ ,102.9
+ ,96.8
+ ,87.1
+ ,97.4
+ ,114.1
+ ,110.5
+ ,111.4
+ ,110.3
+ ,110.8
+ ,87.4
+ ,103.9
+ ,104.2
+ ,96.8
+ ,101.6
+ ,88.9
+ ,114.1
+ ,94.6
+ ,89.8
+ ,110.3
+ ,95.9
+ ,90
+ ,103.9
+ ,104.7
+ ,93.9
+ ,101.6
+ ,102.8
+ ,91.3
+ ,94.6
+ ,98.1
+ ,87.8
+ ,95.9
+ ,113.9
+ ,99.7
+ ,104.7
+ ,80.9
+ ,73.5
+ ,102.8
+ ,95.7
+ ,79.2
+ ,98.1
+ ,113.2
+ ,96.9
+ ,113.9
+ ,105.9
+ ,95.2
+ ,80.9
+ ,108.8
+ ,95.6
+ ,95.7
+ ,102.3
+ ,89.7
+ ,113.2
+ ,99
+ ,92.8
+ ,105.9
+ ,100.7
+ ,88
+ ,108.8
+ ,115.5
+ ,101.1
+ ,102.3
+ ,100.7
+ ,92.7
+ ,99
+ ,109.9
+ ,95.8
+ ,100.7
+ ,114.6
+ ,103.8
+ ,115.5
+ ,85.4
+ ,81.8
+ ,100.7
+ ,100.5
+ ,87.1
+ ,109.9
+ ,114.8
+ ,105.9
+ ,114.6
+ ,116.5
+ ,108.1
+ ,85.4
+ ,112.9
+ ,102.6
+ ,100.5
+ ,102
+ ,93.7
+ ,114.8
+ ,106
+ ,103.5
+ ,116.5
+ ,105.3
+ ,100.6
+ ,112.9
+ ,118.8
+ ,113.3
+ ,102
+ ,106.1
+ ,102.4
+ ,106
+ ,109.3
+ ,102.1
+ ,105.3
+ ,117.2
+ ,106.9
+ ,118.8
+ ,92.5
+ ,87.3
+ ,106.1
+ ,104.2
+ ,93.1
+ ,109.3
+ ,112.5
+ ,109.1
+ ,117.2
+ ,122.4
+ ,120.3
+ ,92.5
+ ,113.3
+ ,104.9
+ ,104.2
+ ,100
+ ,92.6
+ ,112.5
+ ,110.7
+ ,109.8
+ ,122.4
+ ,112.8
+ ,111.4
+ ,113.3
+ ,109.8
+ ,117.9
+ ,100
+ ,117.3
+ ,121.6
+ ,110.7
+ ,109.1
+ ,117.8
+ ,112.8
+ ,115.9
+ ,124.2
+ ,109.8
+ ,96
+ ,106.8
+ ,117.3
+ ,99.8
+ ,102.7
+ ,109.1
+ ,116.8
+ ,116.8
+ ,115.9
+ ,115.7
+ ,113.6
+ ,96
+ ,99.4
+ ,96.1
+ ,99.8
+ ,94.3
+ ,85
+ ,116.8)
+ ,dim=c(3
+ ,60)
+ ,dimnames=list(c('TIA'
+ ,'IAidM'
+ ,'TIA(t-3)')
+ ,1:60))
> y <- array(NA,dim=c(3,60),dimnames=list(c('TIA','IAidM','TIA(t-3)'),1:60))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No 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
TIA IAidM TIA(t-3) M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 95.1 93.8 111.7 1 0 0 0 0 0 0 0 0 0 0
2 97.0 93.8 98.6 0 1 0 0 0 0 0 0 0 0 0
3 112.7 107.6 96.9 0 0 1 0 0 0 0 0 0 0 0
4 102.9 101.0 95.1 0 0 0 1 0 0 0 0 0 0 0
5 97.4 95.4 97.0 0 0 0 0 1 0 0 0 0 0 0
6 111.4 96.5 112.7 0 0 0 0 0 1 0 0 0 0 0
7 87.4 89.2 102.9 0 0 0 0 0 0 1 0 0 0 0
8 96.8 87.1 97.4 0 0 0 0 0 0 0 1 0 0 0
9 114.1 110.5 111.4 0 0 0 0 0 0 0 0 1 0 0
10 110.3 110.8 87.4 0 0 0 0 0 0 0 0 0 1 0
11 103.9 104.2 96.8 0 0 0 0 0 0 0 0 0 0 1
12 101.6 88.9 114.1 0 0 0 0 0 0 0 0 0 0 0
13 94.6 89.8 110.3 1 0 0 0 0 0 0 0 0 0 0
14 95.9 90.0 103.9 0 1 0 0 0 0 0 0 0 0 0
15 104.7 93.9 101.6 0 0 1 0 0 0 0 0 0 0 0
16 102.8 91.3 94.6 0 0 0 1 0 0 0 0 0 0 0
17 98.1 87.8 95.9 0 0 0 0 1 0 0 0 0 0 0
18 113.9 99.7 104.7 0 0 0 0 0 1 0 0 0 0 0
19 80.9 73.5 102.8 0 0 0 0 0 0 1 0 0 0 0
20 95.7 79.2 98.1 0 0 0 0 0 0 0 1 0 0 0
21 113.2 96.9 113.9 0 0 0 0 0 0 0 0 1 0 0
22 105.9 95.2 80.9 0 0 0 0 0 0 0 0 0 1 0
23 108.8 95.6 95.7 0 0 0 0 0 0 0 0 0 0 1
24 102.3 89.7 113.2 0 0 0 0 0 0 0 0 0 0 0
25 99.0 92.8 105.9 1 0 0 0 0 0 0 0 0 0 0
26 100.7 88.0 108.8 0 1 0 0 0 0 0 0 0 0 0
27 115.5 101.1 102.3 0 0 1 0 0 0 0 0 0 0 0
28 100.7 92.7 99.0 0 0 0 1 0 0 0 0 0 0 0
29 109.9 95.8 100.7 0 0 0 0 1 0 0 0 0 0 0
30 114.6 103.8 115.5 0 0 0 0 0 1 0 0 0 0 0
31 85.4 81.8 100.7 0 0 0 0 0 0 1 0 0 0 0
32 100.5 87.1 109.9 0 0 0 0 0 0 0 1 0 0 0
33 114.8 105.9 114.6 0 0 0 0 0 0 0 0 1 0 0
34 116.5 108.1 85.4 0 0 0 0 0 0 0 0 0 1 0
35 112.9 102.6 100.5 0 0 0 0 0 0 0 0 0 0 1
36 102.0 93.7 114.8 0 0 0 0 0 0 0 0 0 0 0
37 106.0 103.5 116.5 1 0 0 0 0 0 0 0 0 0 0
38 105.3 100.6 112.9 0 1 0 0 0 0 0 0 0 0 0
39 118.8 113.3 102.0 0 0 1 0 0 0 0 0 0 0 0
40 106.1 102.4 106.0 0 0 0 1 0 0 0 0 0 0 0
41 109.3 102.1 105.3 0 0 0 0 1 0 0 0 0 0 0
42 117.2 106.9 118.8 0 0 0 0 0 1 0 0 0 0 0
43 92.5 87.3 106.1 0 0 0 0 0 0 1 0 0 0 0
44 104.2 93.1 109.3 0 0 0 0 0 0 0 1 0 0 0
45 112.5 109.1 117.2 0 0 0 0 0 0 0 0 1 0 0
46 122.4 120.3 92.5 0 0 0 0 0 0 0 0 0 1 0
47 113.3 104.9 104.2 0 0 0 0 0 0 0 0 0 0 1
48 100.0 92.6 112.5 0 0 0 0 0 0 0 0 0 0 0
49 110.7 109.8 122.4 1 0 0 0 0 0 0 0 0 0 0
50 112.8 111.4 113.3 0 1 0 0 0 0 0 0 0 0 0
51 109.8 117.9 100.0 0 0 1 0 0 0 0 0 0 0 0
52 117.3 121.6 110.7 0 0 0 1 0 0 0 0 0 0 0
53 109.1 117.8 112.8 0 0 0 0 1 0 0 0 0 0 0
54 115.9 124.2 109.8 0 0 0 0 0 1 0 0 0 0 0
55 96.0 106.8 117.3 0 0 0 0 0 0 1 0 0 0 0
56 99.8 102.7 109.1 0 0 0 0 0 0 0 1 0 0 0
57 116.8 116.8 115.9 0 0 0 0 0 0 0 0 1 0 0
58 115.7 113.6 96.0 0 0 0 0 0 0 0 0 0 1 0
59 99.4 96.1 99.8 0 0 0 0 0 0 0 0 0 0 1
60 94.3 85.0 116.8 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) IAidM `TIA(t-3)` M1 M2 M3
34.5998 0.2982 0.3378 -1.0230 2.5685 11.8908
M4 M5 M6 M7 M8 M9
6.8543 5.8310 10.3858 -8.1153 2.6178 8.8057
M10 M11
16.9982 9.4558
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7.0293 -2.2131 0.1442 2.3253 6.8809
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 34.59975 11.15105 3.103 0.003273 **
IAidM 0.29822 0.07112 4.193 0.000124 ***
`TIA(t-3)` 0.33782 0.12263 2.755 0.008386 **
M1 -1.02304 2.31085 -0.443 0.660048
M2 2.56850 2.52281 1.018 0.313951
M3 11.89077 3.42996 3.467 0.001153 **
M4 6.85428 3.16283 2.167 0.035438 *
M5 5.83103 2.97795 1.958 0.056303 .
M6 10.38578 2.58428 4.019 0.000215 ***
M7 -8.11534 2.40422 -3.375 0.001506 **
M8 2.61782 2.50453 1.045 0.301377
M9 8.80567 2.54464 3.460 0.001174 **
M10 16.99823 4.75454 3.575 0.000836 ***
M11 9.45583 3.25902 2.901 0.005682 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.509 on 46 degrees of freedom
Multiple R-squared: 0.8815, Adjusted R-squared: 0.848
F-statistic: 26.32 on 13 and 46 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,] 0.13001039 0.26002077 0.8699896
[2,] 0.06620626 0.13241253 0.9337937
[3,] 0.04006644 0.08013287 0.9599336
[4,] 0.01842166 0.03684333 0.9815783
[5,] 0.01817393 0.03634787 0.9818261
[6,] 0.01058148 0.02116297 0.9894185
[7,] 0.05032610 0.10065220 0.9496739
[8,] 0.02926803 0.05853606 0.9707320
[9,] 0.02070023 0.04140047 0.9792998
[10,] 0.05787740 0.11575480 0.9421226
[11,] 0.11831820 0.23663640 0.8816818
[12,] 0.08976043 0.17952087 0.9102396
[13,] 0.32753836 0.65507673 0.6724616
[14,] 0.24410011 0.48820023 0.7558999
[15,] 0.18480965 0.36961929 0.8151904
[16,] 0.12693668 0.25387336 0.8730633
[17,] 0.08547577 0.17095153 0.9145242
[18,] 0.09177752 0.18355504 0.9082225
[19,] 0.10593465 0.21186930 0.8940654
[20,] 0.07676989 0.15353978 0.9232301
[21,] 0.05589663 0.11179326 0.9441034
[22,] 0.03961512 0.07923025 0.9603849
[23,] 0.06598041 0.13196081 0.9340196
[24,] 0.06156397 0.12312793 0.9384360
[25,] 0.04394704 0.08789408 0.9560530
[26,] 0.03856003 0.07712007 0.9614400
[27,] 0.04335246 0.08670492 0.9566475
> postscript(file="/var/www/html/rcomp/tmp/1f80x1258748237.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2elau1258748237.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/34rbp1258748237.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4r2ie1258748237.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xm2w1258748237.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 = 60
Frequency = 1
1 2 3 4 5 6
-4.184580156 -1.450648402 1.385923508 -0.801246566 -4.249821500 -0.436420538
7 8 9 10 11 12
-0.447631252 0.703496821 0.107763047 -3.866530162 -3.931400338 1.942886695
13 14 15 16 17 18
-3.018745021 -3.207866056 -4.116212722 2.160408435 -0.911737339 3.811849606
19 20 21 22 23 24
-2.231778990 1.722967370 2.419013503 -1.418438072 3.904904845 2.708349837
25 26 27 28 29 30
1.973009491 0.533247322 4.300120396 -1.843518573 6.880948037 -0.359336093
31 32 33 34 35 36
0.502413099 0.180719612 1.098548782 3.814310950 4.295811244 0.674950267
37 38 39 40 41 42
2.201129483 -0.009408478 4.063170582 -1.701017723 2.848173586 0.201365556
43 44 45 46 47 48
4.137957724 2.294086786 -3.034096147 3.677477028 2.759960839 -0.220015603
49 50 51 52 53 54
3.029186203 4.134675614 -5.633001765 2.185374426 -4.567562783 -3.217458532
55 56 57 58 59 60
-1.960960582 -4.901270589 -0.591229186 -2.206819744 -7.029276590 -5.106171196
> postscript(file="/var/www/html/rcomp/tmp/660oq1258748237.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -4.184580156 NA
1 -1.450648402 -4.184580156
2 1.385923508 -1.450648402
3 -0.801246566 1.385923508
4 -4.249821500 -0.801246566
5 -0.436420538 -4.249821500
6 -0.447631252 -0.436420538
7 0.703496821 -0.447631252
8 0.107763047 0.703496821
9 -3.866530162 0.107763047
10 -3.931400338 -3.866530162
11 1.942886695 -3.931400338
12 -3.018745021 1.942886695
13 -3.207866056 -3.018745021
14 -4.116212722 -3.207866056
15 2.160408435 -4.116212722
16 -0.911737339 2.160408435
17 3.811849606 -0.911737339
18 -2.231778990 3.811849606
19 1.722967370 -2.231778990
20 2.419013503 1.722967370
21 -1.418438072 2.419013503
22 3.904904845 -1.418438072
23 2.708349837 3.904904845
24 1.973009491 2.708349837
25 0.533247322 1.973009491
26 4.300120396 0.533247322
27 -1.843518573 4.300120396
28 6.880948037 -1.843518573
29 -0.359336093 6.880948037
30 0.502413099 -0.359336093
31 0.180719612 0.502413099
32 1.098548782 0.180719612
33 3.814310950 1.098548782
34 4.295811244 3.814310950
35 0.674950267 4.295811244
36 2.201129483 0.674950267
37 -0.009408478 2.201129483
38 4.063170582 -0.009408478
39 -1.701017723 4.063170582
40 2.848173586 -1.701017723
41 0.201365556 2.848173586
42 4.137957724 0.201365556
43 2.294086786 4.137957724
44 -3.034096147 2.294086786
45 3.677477028 -3.034096147
46 2.759960839 3.677477028
47 -0.220015603 2.759960839
48 3.029186203 -0.220015603
49 4.134675614 3.029186203
50 -5.633001765 4.134675614
51 2.185374426 -5.633001765
52 -4.567562783 2.185374426
53 -3.217458532 -4.567562783
54 -1.960960582 -3.217458532
55 -4.901270589 -1.960960582
56 -0.591229186 -4.901270589
57 -2.206819744 -0.591229186
58 -7.029276590 -2.206819744
59 -5.106171196 -7.029276590
60 NA -5.106171196
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.450648402 -4.184580156
[2,] 1.385923508 -1.450648402
[3,] -0.801246566 1.385923508
[4,] -4.249821500 -0.801246566
[5,] -0.436420538 -4.249821500
[6,] -0.447631252 -0.436420538
[7,] 0.703496821 -0.447631252
[8,] 0.107763047 0.703496821
[9,] -3.866530162 0.107763047
[10,] -3.931400338 -3.866530162
[11,] 1.942886695 -3.931400338
[12,] -3.018745021 1.942886695
[13,] -3.207866056 -3.018745021
[14,] -4.116212722 -3.207866056
[15,] 2.160408435 -4.116212722
[16,] -0.911737339 2.160408435
[17,] 3.811849606 -0.911737339
[18,] -2.231778990 3.811849606
[19,] 1.722967370 -2.231778990
[20,] 2.419013503 1.722967370
[21,] -1.418438072 2.419013503
[22,] 3.904904845 -1.418438072
[23,] 2.708349837 3.904904845
[24,] 1.973009491 2.708349837
[25,] 0.533247322 1.973009491
[26,] 4.300120396 0.533247322
[27,] -1.843518573 4.300120396
[28,] 6.880948037 -1.843518573
[29,] -0.359336093 6.880948037
[30,] 0.502413099 -0.359336093
[31,] 0.180719612 0.502413099
[32,] 1.098548782 0.180719612
[33,] 3.814310950 1.098548782
[34,] 4.295811244 3.814310950
[35,] 0.674950267 4.295811244
[36,] 2.201129483 0.674950267
[37,] -0.009408478 2.201129483
[38,] 4.063170582 -0.009408478
[39,] -1.701017723 4.063170582
[40,] 2.848173586 -1.701017723
[41,] 0.201365556 2.848173586
[42,] 4.137957724 0.201365556
[43,] 2.294086786 4.137957724
[44,] -3.034096147 2.294086786
[45,] 3.677477028 -3.034096147
[46,] 2.759960839 3.677477028
[47,] -0.220015603 2.759960839
[48,] 3.029186203 -0.220015603
[49,] 4.134675614 3.029186203
[50,] -5.633001765 4.134675614
[51,] 2.185374426 -5.633001765
[52,] -4.567562783 2.185374426
[53,] -3.217458532 -4.567562783
[54,] -1.960960582 -3.217458532
[55,] -4.901270589 -1.960960582
[56,] -0.591229186 -4.901270589
[57,] -2.206819744 -0.591229186
[58,] -7.029276590 -2.206819744
[59,] -5.106171196 -7.029276590
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.450648402 -4.184580156
2 1.385923508 -1.450648402
3 -0.801246566 1.385923508
4 -4.249821500 -0.801246566
5 -0.436420538 -4.249821500
6 -0.447631252 -0.436420538
7 0.703496821 -0.447631252
8 0.107763047 0.703496821
9 -3.866530162 0.107763047
10 -3.931400338 -3.866530162
11 1.942886695 -3.931400338
12 -3.018745021 1.942886695
13 -3.207866056 -3.018745021
14 -4.116212722 -3.207866056
15 2.160408435 -4.116212722
16 -0.911737339 2.160408435
17 3.811849606 -0.911737339
18 -2.231778990 3.811849606
19 1.722967370 -2.231778990
20 2.419013503 1.722967370
21 -1.418438072 2.419013503
22 3.904904845 -1.418438072
23 2.708349837 3.904904845
24 1.973009491 2.708349837
25 0.533247322 1.973009491
26 4.300120396 0.533247322
27 -1.843518573 4.300120396
28 6.880948037 -1.843518573
29 -0.359336093 6.880948037
30 0.502413099 -0.359336093
31 0.180719612 0.502413099
32 1.098548782 0.180719612
33 3.814310950 1.098548782
34 4.295811244 3.814310950
35 0.674950267 4.295811244
36 2.201129483 0.674950267
37 -0.009408478 2.201129483
38 4.063170582 -0.009408478
39 -1.701017723 4.063170582
40 2.848173586 -1.701017723
41 0.201365556 2.848173586
42 4.137957724 0.201365556
43 2.294086786 4.137957724
44 -3.034096147 2.294086786
45 3.677477028 -3.034096147
46 2.759960839 3.677477028
47 -0.220015603 2.759960839
48 3.029186203 -0.220015603
49 4.134675614 3.029186203
50 -5.633001765 4.134675614
51 2.185374426 -5.633001765
52 -4.567562783 2.185374426
53 -3.217458532 -4.567562783
54 -1.960960582 -3.217458532
55 -4.901270589 -1.960960582
56 -0.591229186 -4.901270589
57 -2.206819744 -0.591229186
58 -7.029276590 -2.206819744
59 -5.106171196 -7.029276590
> 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/79uyz1258748237.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8mmvr1258748237.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9axdr1258748237.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/102l4y1258748237.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/112cl31258748237.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/12r8la1258748237.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/13edaq1258748237.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/14zsab1258748237.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/15znu41258748237.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/16f7tw1258748237.tab")
+ }
>
> system("convert tmp/1f80x1258748237.ps tmp/1f80x1258748237.png")
> system("convert tmp/2elau1258748237.ps tmp/2elau1258748237.png")
> system("convert tmp/34rbp1258748237.ps tmp/34rbp1258748237.png")
> system("convert tmp/4r2ie1258748237.ps tmp/4r2ie1258748237.png")
> system("convert tmp/5xm2w1258748237.ps tmp/5xm2w1258748237.png")
> system("convert tmp/660oq1258748237.ps tmp/660oq1258748237.png")
> system("convert tmp/79uyz1258748237.ps tmp/79uyz1258748237.png")
> system("convert tmp/8mmvr1258748237.ps tmp/8mmvr1258748237.png")
> system("convert tmp/9axdr1258748237.ps tmp/9axdr1258748237.png")
> system("convert tmp/102l4y1258748237.ps tmp/102l4y1258748237.png")
>
>
> proc.time()
user system elapsed
2.416 1.583 2.855