R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'q()' to quit R.
> 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 = '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 t
1 95.1 93.8 111.7 1 0 0 0 0 0 0 0 0 0 0 1
2 97.0 93.8 98.6 0 1 0 0 0 0 0 0 0 0 0 2
3 112.7 107.6 96.9 0 0 1 0 0 0 0 0 0 0 0 3
4 102.9 101.0 95.1 0 0 0 1 0 0 0 0 0 0 0 4
5 97.4 95.4 97.0 0 0 0 0 1 0 0 0 0 0 0 5
6 111.4 96.5 112.7 0 0 0 0 0 1 0 0 0 0 0 6
7 87.4 89.2 102.9 0 0 0 0 0 0 1 0 0 0 0 7
8 96.8 87.1 97.4 0 0 0 0 0 0 0 1 0 0 0 8
9 114.1 110.5 111.4 0 0 0 0 0 0 0 0 1 0 0 9
10 110.3 110.8 87.4 0 0 0 0 0 0 0 0 0 1 0 10
11 103.9 104.2 96.8 0 0 0 0 0 0 0 0 0 0 1 11
12 101.6 88.9 114.1 0 0 0 0 0 0 0 0 0 0 0 12
13 94.6 89.8 110.3 1 0 0 0 0 0 0 0 0 0 0 13
14 95.9 90.0 103.9 0 1 0 0 0 0 0 0 0 0 0 14
15 104.7 93.9 101.6 0 0 1 0 0 0 0 0 0 0 0 15
16 102.8 91.3 94.6 0 0 0 1 0 0 0 0 0 0 0 16
17 98.1 87.8 95.9 0 0 0 0 1 0 0 0 0 0 0 17
18 113.9 99.7 104.7 0 0 0 0 0 1 0 0 0 0 0 18
19 80.9 73.5 102.8 0 0 0 0 0 0 1 0 0 0 0 19
20 95.7 79.2 98.1 0 0 0 0 0 0 0 1 0 0 0 20
21 113.2 96.9 113.9 0 0 0 0 0 0 0 0 1 0 0 21
22 105.9 95.2 80.9 0 0 0 0 0 0 0 0 0 1 0 22
23 108.8 95.6 95.7 0 0 0 0 0 0 0 0 0 0 1 23
24 102.3 89.7 113.2 0 0 0 0 0 0 0 0 0 0 0 24
25 99.0 92.8 105.9 1 0 0 0 0 0 0 0 0 0 0 25
26 100.7 88.0 108.8 0 1 0 0 0 0 0 0 0 0 0 26
27 115.5 101.1 102.3 0 0 1 0 0 0 0 0 0 0 0 27
28 100.7 92.7 99.0 0 0 0 1 0 0 0 0 0 0 0 28
29 109.9 95.8 100.7 0 0 0 0 1 0 0 0 0 0 0 29
30 114.6 103.8 115.5 0 0 0 0 0 1 0 0 0 0 0 30
31 85.4 81.8 100.7 0 0 0 0 0 0 1 0 0 0 0 31
32 100.5 87.1 109.9 0 0 0 0 0 0 0 1 0 0 0 32
33 114.8 105.9 114.6 0 0 0 0 0 0 0 0 1 0 0 33
34 116.5 108.1 85.4 0 0 0 0 0 0 0 0 0 1 0 34
35 112.9 102.6 100.5 0 0 0 0 0 0 0 0 0 0 1 35
36 102.0 93.7 114.8 0 0 0 0 0 0 0 0 0 0 0 36
37 106.0 103.5 116.5 1 0 0 0 0 0 0 0 0 0 0 37
38 105.3 100.6 112.9 0 1 0 0 0 0 0 0 0 0 0 38
39 118.8 113.3 102.0 0 0 1 0 0 0 0 0 0 0 0 39
40 106.1 102.4 106.0 0 0 0 1 0 0 0 0 0 0 0 40
41 109.3 102.1 105.3 0 0 0 0 1 0 0 0 0 0 0 41
42 117.2 106.9 118.8 0 0 0 0 0 1 0 0 0 0 0 42
43 92.5 87.3 106.1 0 0 0 0 0 0 1 0 0 0 0 43
44 104.2 93.1 109.3 0 0 0 0 0 0 0 1 0 0 0 44
45 112.5 109.1 117.2 0 0 0 0 0 0 0 0 1 0 0 45
46 122.4 120.3 92.5 0 0 0 0 0 0 0 0 0 1 0 46
47 113.3 104.9 104.2 0 0 0 0 0 0 0 0 0 0 1 47
48 100.0 92.6 112.5 0 0 0 0 0 0 0 0 0 0 0 48
49 110.7 109.8 122.4 1 0 0 0 0 0 0 0 0 0 0 49
50 112.8 111.4 113.3 0 1 0 0 0 0 0 0 0 0 0 50
51 109.8 117.9 100.0 0 0 1 0 0 0 0 0 0 0 0 51
52 117.3 121.6 110.7 0 0 0 1 0 0 0 0 0 0 0 52
53 109.1 117.8 112.8 0 0 0 0 1 0 0 0 0 0 0 53
54 115.9 124.2 109.8 0 0 0 0 0 1 0 0 0 0 0 54
55 96.0 106.8 117.3 0 0 0 0 0 0 1 0 0 0 0 55
56 99.8 102.7 109.1 0 0 0 0 0 0 0 1 0 0 0 56
57 116.8 116.8 115.9 0 0 0 0 0 0 0 0 1 0 0 57
58 115.7 113.6 96.0 0 0 0 0 0 0 0 0 0 1 0 58
59 99.4 96.1 99.8 0 0 0 0 0 0 0 0 0 0 1 59
60 94.3 85.0 116.8 0 0 0 0 0 0 0 0 0 0 0 60
> 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
32.504936 0.303639 0.354779 -1.151563 2.554919 11.949880
M4 M5 M6 M7 M8 M9
6.940625 5.916135 10.276281 -8.007920 2.743283 8.675938
M10 M11 t
17.311741 9.640999 -0.009181
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-6.7909 -2.1551 0.0484 2.3272 6.9303
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 32.504936 14.565839 2.232 0.030668 *
IAidM 0.303639 0.075723 4.010 0.000226 ***
`TIA(t-3)` 0.354779 0.144699 2.452 0.018158 *
M1 -1.151563 2.402733 -0.479 0.634066
M2 2.554919 2.549927 1.002 0.321722
M3 11.949880 3.475651 3.438 0.001272 **
M4 6.940625 3.218519 2.156 0.036428 *
M5 5.916135 3.032412 1.951 0.057304 .
M6 10.276281 2.655537 3.870 0.000349 ***
M7 -8.007920 2.475079 -3.235 0.002280 **
M8 2.743283 2.590436 1.059 0.295249
M9 8.675938 2.634067 3.294 0.001931 **
M10 17.311741 4.998995 3.463 0.001183 **
M11 9.640999 3.392720 2.842 0.006721 **
t -0.009181 0.040456 -0.227 0.821492
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.546 on 45 degrees of freedom
Multiple R-squared: 0.8816, Adjusted R-squared: 0.8448
F-statistic: 23.94 on 14 and 45 DF, p-value: 2.898e-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,] 0.24040277 0.4808055 0.7595972
[2,] 0.15606932 0.3121386 0.8439307
[3,] 0.08037441 0.1607488 0.9196256
[4,] 0.08921720 0.1784344 0.9107828
[5,] 0.05828384 0.1165677 0.9417162
[6,] 0.18436607 0.3687321 0.8156339
[7,] 0.12719375 0.2543875 0.8728062
[8,] 0.07997637 0.1599527 0.9200236
[9,] 0.07802156 0.1560431 0.9219784
[10,] 0.06032998 0.1206600 0.9396700
[11,] 0.10414072 0.2082814 0.8958593
[12,] 0.20477569 0.4095514 0.7952243
[13,] 0.24696106 0.4939221 0.7530389
[14,] 0.22402694 0.4480539 0.7759731
[15,] 0.16850391 0.3370078 0.8314961
[16,] 0.13922168 0.2784434 0.8607783
[17,] 0.10632712 0.2126542 0.8936729
[18,] 0.06886467 0.1377293 0.9311353
[19,] 0.08892015 0.1778403 0.9110798
[20,] 0.07531025 0.1506205 0.9246898
[21,] 0.12575436 0.2515087 0.8742456
[22,] 0.12276687 0.2455337 0.8772331
[23,] 0.27049270 0.5409854 0.7295073
[24,] 0.19474028 0.3894806 0.8052597
[25,] 0.11370186 0.2274037 0.8862981
> postscript(file="/var/www/html/rcomp/tmp/1r1eo1258747802.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2kdjo1258747802.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3qjl01258747802.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/497bw1258747802.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/527hh1258747802.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
-4.35435572 -1.50404744 1.22308173 -0.91586272 -4.35589464 -0.61089667
7 8 9 10 11 12
-0.62411466 0.62279193 -0.07273932 -4.07574996 -4.12673624 1.73143626
13 14 15 16 17 18
-3.03293266 -3.22037336 -4.17435270 2.21700002 -0.84780575 3.86587049
19 20 21 22 23 24
-2.21133095 1.78336973 2.37997680 -1.32274269 3.88499142 2.61800355
25 26 27 28 29 30
2.12735682 0.55866263 4.30127953 -1.75894619 6.93032037 -0.40048788
31 32 33 34 35 36
0.62368063 0.10840471 1.10905923 3.87398721 4.26675633 0.64597851
37 38 39 40 41 42
2.22793837 -0.01160412 4.11349715 -1.67752042 2.89558828 0.19763720
43 44 45 46 47 48
4.24803613 2.30961656 -2.97483407 3.66083810 2.76588071 -0.09384952
49 50 51 52 53 54
3.03199320 4.17736229 -5.46350571 2.13532931 -4.62220827 -3.05212314
55 56 57 58 59 60
-2.03627115 -4.82418292 -0.44146265 -2.13633265 -6.79089222 -4.90156880
> postscript(file="/var/www/html/rcomp/tmp/6gt7b1258747802.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 -4.35435572 NA
1 -1.50404744 -4.35435572
2 1.22308173 -1.50404744
3 -0.91586272 1.22308173
4 -4.35589464 -0.91586272
5 -0.61089667 -4.35589464
6 -0.62411466 -0.61089667
7 0.62279193 -0.62411466
8 -0.07273932 0.62279193
9 -4.07574996 -0.07273932
10 -4.12673624 -4.07574996
11 1.73143626 -4.12673624
12 -3.03293266 1.73143626
13 -3.22037336 -3.03293266
14 -4.17435270 -3.22037336
15 2.21700002 -4.17435270
16 -0.84780575 2.21700002
17 3.86587049 -0.84780575
18 -2.21133095 3.86587049
19 1.78336973 -2.21133095
20 2.37997680 1.78336973
21 -1.32274269 2.37997680
22 3.88499142 -1.32274269
23 2.61800355 3.88499142
24 2.12735682 2.61800355
25 0.55866263 2.12735682
26 4.30127953 0.55866263
27 -1.75894619 4.30127953
28 6.93032037 -1.75894619
29 -0.40048788 6.93032037
30 0.62368063 -0.40048788
31 0.10840471 0.62368063
32 1.10905923 0.10840471
33 3.87398721 1.10905923
34 4.26675633 3.87398721
35 0.64597851 4.26675633
36 2.22793837 0.64597851
37 -0.01160412 2.22793837
38 4.11349715 -0.01160412
39 -1.67752042 4.11349715
40 2.89558828 -1.67752042
41 0.19763720 2.89558828
42 4.24803613 0.19763720
43 2.30961656 4.24803613
44 -2.97483407 2.30961656
45 3.66083810 -2.97483407
46 2.76588071 3.66083810
47 -0.09384952 2.76588071
48 3.03199320 -0.09384952
49 4.17736229 3.03199320
50 -5.46350571 4.17736229
51 2.13532931 -5.46350571
52 -4.62220827 2.13532931
53 -3.05212314 -4.62220827
54 -2.03627115 -3.05212314
55 -4.82418292 -2.03627115
56 -0.44146265 -4.82418292
57 -2.13633265 -0.44146265
58 -6.79089222 -2.13633265
59 -4.90156880 -6.79089222
60 NA -4.90156880
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.50404744 -4.35435572
[2,] 1.22308173 -1.50404744
[3,] -0.91586272 1.22308173
[4,] -4.35589464 -0.91586272
[5,] -0.61089667 -4.35589464
[6,] -0.62411466 -0.61089667
[7,] 0.62279193 -0.62411466
[8,] -0.07273932 0.62279193
[9,] -4.07574996 -0.07273932
[10,] -4.12673624 -4.07574996
[11,] 1.73143626 -4.12673624
[12,] -3.03293266 1.73143626
[13,] -3.22037336 -3.03293266
[14,] -4.17435270 -3.22037336
[15,] 2.21700002 -4.17435270
[16,] -0.84780575 2.21700002
[17,] 3.86587049 -0.84780575
[18,] -2.21133095 3.86587049
[19,] 1.78336973 -2.21133095
[20,] 2.37997680 1.78336973
[21,] -1.32274269 2.37997680
[22,] 3.88499142 -1.32274269
[23,] 2.61800355 3.88499142
[24,] 2.12735682 2.61800355
[25,] 0.55866263 2.12735682
[26,] 4.30127953 0.55866263
[27,] -1.75894619 4.30127953
[28,] 6.93032037 -1.75894619
[29,] -0.40048788 6.93032037
[30,] 0.62368063 -0.40048788
[31,] 0.10840471 0.62368063
[32,] 1.10905923 0.10840471
[33,] 3.87398721 1.10905923
[34,] 4.26675633 3.87398721
[35,] 0.64597851 4.26675633
[36,] 2.22793837 0.64597851
[37,] -0.01160412 2.22793837
[38,] 4.11349715 -0.01160412
[39,] -1.67752042 4.11349715
[40,] 2.89558828 -1.67752042
[41,] 0.19763720 2.89558828
[42,] 4.24803613 0.19763720
[43,] 2.30961656 4.24803613
[44,] -2.97483407 2.30961656
[45,] 3.66083810 -2.97483407
[46,] 2.76588071 3.66083810
[47,] -0.09384952 2.76588071
[48,] 3.03199320 -0.09384952
[49,] 4.17736229 3.03199320
[50,] -5.46350571 4.17736229
[51,] 2.13532931 -5.46350571
[52,] -4.62220827 2.13532931
[53,] -3.05212314 -4.62220827
[54,] -2.03627115 -3.05212314
[55,] -4.82418292 -2.03627115
[56,] -0.44146265 -4.82418292
[57,] -2.13633265 -0.44146265
[58,] -6.79089222 -2.13633265
[59,] -4.90156880 -6.79089222
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.50404744 -4.35435572
2 1.22308173 -1.50404744
3 -0.91586272 1.22308173
4 -4.35589464 -0.91586272
5 -0.61089667 -4.35589464
6 -0.62411466 -0.61089667
7 0.62279193 -0.62411466
8 -0.07273932 0.62279193
9 -4.07574996 -0.07273932
10 -4.12673624 -4.07574996
11 1.73143626 -4.12673624
12 -3.03293266 1.73143626
13 -3.22037336 -3.03293266
14 -4.17435270 -3.22037336
15 2.21700002 -4.17435270
16 -0.84780575 2.21700002
17 3.86587049 -0.84780575
18 -2.21133095 3.86587049
19 1.78336973 -2.21133095
20 2.37997680 1.78336973
21 -1.32274269 2.37997680
22 3.88499142 -1.32274269
23 2.61800355 3.88499142
24 2.12735682 2.61800355
25 0.55866263 2.12735682
26 4.30127953 0.55866263
27 -1.75894619 4.30127953
28 6.93032037 -1.75894619
29 -0.40048788 6.93032037
30 0.62368063 -0.40048788
31 0.10840471 0.62368063
32 1.10905923 0.10840471
33 3.87398721 1.10905923
34 4.26675633 3.87398721
35 0.64597851 4.26675633
36 2.22793837 0.64597851
37 -0.01160412 2.22793837
38 4.11349715 -0.01160412
39 -1.67752042 4.11349715
40 2.89558828 -1.67752042
41 0.19763720 2.89558828
42 4.24803613 0.19763720
43 2.30961656 4.24803613
44 -2.97483407 2.30961656
45 3.66083810 -2.97483407
46 2.76588071 3.66083810
47 -0.09384952 2.76588071
48 3.03199320 -0.09384952
49 4.17736229 3.03199320
50 -5.46350571 4.17736229
51 2.13532931 -5.46350571
52 -4.62220827 2.13532931
53 -3.05212314 -4.62220827
54 -2.03627115 -3.05212314
55 -4.82418292 -2.03627115
56 -0.44146265 -4.82418292
57 -2.13633265 -0.44146265
58 -6.79089222 -2.13633265
59 -4.90156880 -6.79089222
> 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/7chso1258747802.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8sqak1258747802.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9g2j21258747802.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10qm161258747802.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11c0891258747802.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/12dmpm1258747802.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/13vw9e1258747802.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/14ya5y1258747802.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/15o8531258747802.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/16ykpn1258747802.tab")
+ }
>
> system("convert tmp/1r1eo1258747802.ps tmp/1r1eo1258747802.png")
> system("convert tmp/2kdjo1258747802.ps tmp/2kdjo1258747802.png")
> system("convert tmp/3qjl01258747802.ps tmp/3qjl01258747802.png")
> system("convert tmp/497bw1258747802.ps tmp/497bw1258747802.png")
> system("convert tmp/527hh1258747802.ps tmp/527hh1258747802.png")
> system("convert tmp/6gt7b1258747802.ps tmp/6gt7b1258747802.png")
> system("convert tmp/7chso1258747802.ps tmp/7chso1258747802.png")
> system("convert tmp/8sqak1258747802.ps tmp/8sqak1258747802.png")
> system("convert tmp/9g2j21258747802.ps tmp/9g2j21258747802.png")
> system("convert tmp/10qm161258747802.ps tmp/10qm161258747802.png")
>
>
> proc.time()
user system elapsed
2.489 1.596 4.189