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.
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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
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> x <- array(list(8.9,1.4,8.8,1.2,8.3,1,7.5,1.7,7.2,2.4,7.4,2,8.8,2.1,9.3,2,9.3,1.8,8.7,2.7,8.2,2.3,8.3,1.9,8.5,2,8.6,2.3,8.5,2.8,8.2,2.4,8.1,2.3,7.9,2.7,8.6,2.7,8.7,2.9,8.7,3,8.5,2.2,8.4,2.3,8.5,2.8,8.7,2.8,8.7,2.8,8.6,2.2,8.5,2.6,8.3,2.8,8,2.5,8.2,2.4,8.1,2.3,8.1,1.9,8,1.7,7.9,2,7.9,2.1,8,1.7,8,1.8,7.9,1.8,8,1.8,7.7,1.3,7.2,1.3,7.5,1.3,7.3,1.2,7,1.4,7,2.2,7,2.9,7.2,3.1,7.3,3.5,7.1,3.6,6.8,4.4,6.4,4.1,6.1,5.1,6.5,5.8,7.7,5.9,7.9,5.4,7.5,5.5,6.9,4.8,6.6,3.2,6.9,2.7),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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 = '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
1 8.9 1.4
2 8.8 1.2
3 8.3 1.0
4 7.5 1.7
5 7.2 2.4
6 7.4 2.0
7 8.8 2.1
8 9.3 2.0
9 9.3 1.8
10 8.7 2.7
11 8.2 2.3
12 8.3 1.9
13 8.5 2.0
14 8.6 2.3
15 8.5 2.8
16 8.2 2.4
17 8.1 2.3
18 7.9 2.7
19 8.6 2.7
20 8.7 2.9
21 8.7 3.0
22 8.5 2.2
23 8.4 2.3
24 8.5 2.8
25 8.7 2.8
26 8.7 2.8
27 8.6 2.2
28 8.5 2.6
29 8.3 2.8
30 8.0 2.5
31 8.2 2.4
32 8.1 2.3
33 8.1 1.9
34 8.0 1.7
35 7.9 2.0
36 7.9 2.1
37 8.0 1.7
38 8.0 1.8
39 7.9 1.8
40 8.0 1.8
41 7.7 1.3
42 7.2 1.3
43 7.5 1.3
44 7.3 1.2
45 7.0 1.4
46 7.0 2.2
47 7.0 2.9
48 7.2 3.1
49 7.3 3.5
50 7.1 3.6
51 6.8 4.4
52 6.4 4.1
53 6.1 5.1
54 6.5 5.8
55 7.7 5.9
56 7.9 5.4
57 7.5 5.5
58 6.9 4.8
59 6.6 3.2
60 6.9 2.7
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
8.6159 -0.2714
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.23594 -0.56596 0.03971 0.59436 1.22689
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.61588 0.21625 39.842 < 2e-16 ***
X -0.27138 0.07566 -3.587 0.000688 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.6782 on 58 degrees of freedom
Multiple R-squared: 0.1815, Adjusted R-squared: 0.1674
F-statistic: 12.86 on 1 and 58 DF, p-value: 0.0006882
> 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,] 0.3843696 0.7687393 0.6156304
[2,] 0.2442667 0.4885333 0.7557333
[3,] 0.5503377 0.8993245 0.4496623
[4,] 0.7928563 0.4142875 0.2071437
[5,] 0.8603273 0.2793455 0.1396727
[6,] 0.8517294 0.2965413 0.1482706
[7,] 0.7869210 0.4261580 0.2130790
[8,] 0.7111681 0.5776638 0.2888319
[9,] 0.6371330 0.7257341 0.3628670
[10,] 0.5808908 0.8382184 0.4191092
[11,] 0.5242787 0.9514427 0.4757213
[12,] 0.4441409 0.8882818 0.5558591
[13,] 0.3704088 0.7408176 0.6295912
[14,] 0.3073341 0.6146681 0.6926659
[15,] 0.2849498 0.5698997 0.7150502
[16,] 0.2890421 0.5780841 0.7109579
[17,] 0.2973898 0.5947797 0.7026102
[18,] 0.2592583 0.5185165 0.7407417
[19,] 0.2205277 0.4410553 0.7794723
[20,] 0.2060250 0.4120500 0.7939750
[21,] 0.2317167 0.4634334 0.7682833
[22,] 0.2738815 0.5477629 0.7261185
[23,] 0.2921901 0.5843802 0.7078099
[24,] 0.3191530 0.6383060 0.6808470
[25,] 0.3324285 0.6648570 0.6675715
[26,] 0.3214435 0.6428870 0.6785565
[27,] 0.3246239 0.6492478 0.6753761
[28,] 0.3229750 0.6459500 0.6770250
[29,] 0.3180423 0.6360846 0.6819577
[30,] 0.3071652 0.6143305 0.6928348
[31,] 0.3020356 0.6040711 0.6979644
[32,] 0.3019366 0.6038732 0.6980634
[33,] 0.3068518 0.6137036 0.6931482
[34,] 0.3287150 0.6574300 0.6712850
[35,] 0.3523391 0.7046781 0.6476609
[36,] 0.4279994 0.8559988 0.5720006
[37,] 0.4549093 0.9098186 0.5450907
[38,] 0.4683009 0.9366017 0.5316991
[39,] 0.4723615 0.9447231 0.5276385
[40,] 0.4660638 0.9321277 0.5339362
[41,] 0.4644949 0.9289898 0.5355051
[42,] 0.4933522 0.9867044 0.5066478
[43,] 0.5313157 0.9373686 0.4686843
[44,] 0.5400269 0.9199461 0.4599731
[45,] 0.5495244 0.9009513 0.4504756
[46,] 0.5238078 0.9523844 0.4761922
[47,] 0.4618510 0.9237019 0.5381490
[48,] 0.4516709 0.9033419 0.5483291
[49,] 0.6716752 0.6566496 0.3283248
[50,] 0.9088520 0.1822960 0.0911480
[51,] 0.8051367 0.3897267 0.1948633
> postscript(file="/var/www/html/rcomp/tmp/16tqi1258481145.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2qbkk1258481145.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3duvu1258481145.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4da2t1258481145.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xa8x1258481145.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
0.6640569513 0.5097806246 -0.0444957021 -0.6545285586 -0.7645614152
6 7 8 9 10
-0.6731140686 0.7540240948 1.2268859314 1.1726096047 0.8168530749
11 12 13 14 15
0.2083004215 0.1997477681 0.4268859314 0.6083004215 0.6439912383
16 17 18 19 20
0.2354385848 0.1083004215 0.0168530749 0.7168530749 0.8711294016
21 22 23 24 25
0.8982675650 0.4811622581 0.4083004215 0.6439912383 0.8439912383
26 27 28 29 30
0.8439912383 0.5811622581 0.5897149116 0.4439912383 0.0625767482
31 32 33 34 35
0.2354385848 0.1083004215 -0.0002522319 -0.1545285586 -0.1731140686
36 37 38 39 40
-0.1459759052 -0.1545285586 -0.1273903953 -0.2273903953 -0.1273903953
41 42 43 44 45
-0.5630812120 -1.0630812120 -0.7630812120 -0.9902193754 -1.2359430487
46 47 48 49 50
-1.0188377419 -0.8288705984 -0.5745942717 -0.3660416183 -0.5389034549
51 52 53 54 55
-0.6217981481 -1.1032126381 -1.1318310046 -0.5418638611 0.6852743022
56 57 58 59 60
0.7495834854 0.3767216488 -0.4132454947 -1.1474561083 -0.9831469251
> postscript(file="/var/www/html/rcomp/tmp/6q51s1258481145.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 0.6640569513 NA
1 0.5097806246 0.6640569513
2 -0.0444957021 0.5097806246
3 -0.6545285586 -0.0444957021
4 -0.7645614152 -0.6545285586
5 -0.6731140686 -0.7645614152
6 0.7540240948 -0.6731140686
7 1.2268859314 0.7540240948
8 1.1726096047 1.2268859314
9 0.8168530749 1.1726096047
10 0.2083004215 0.8168530749
11 0.1997477681 0.2083004215
12 0.4268859314 0.1997477681
13 0.6083004215 0.4268859314
14 0.6439912383 0.6083004215
15 0.2354385848 0.6439912383
16 0.1083004215 0.2354385848
17 0.0168530749 0.1083004215
18 0.7168530749 0.0168530749
19 0.8711294016 0.7168530749
20 0.8982675650 0.8711294016
21 0.4811622581 0.8982675650
22 0.4083004215 0.4811622581
23 0.6439912383 0.4083004215
24 0.8439912383 0.6439912383
25 0.8439912383 0.8439912383
26 0.5811622581 0.8439912383
27 0.5897149116 0.5811622581
28 0.4439912383 0.5897149116
29 0.0625767482 0.4439912383
30 0.2354385848 0.0625767482
31 0.1083004215 0.2354385848
32 -0.0002522319 0.1083004215
33 -0.1545285586 -0.0002522319
34 -0.1731140686 -0.1545285586
35 -0.1459759052 -0.1731140686
36 -0.1545285586 -0.1459759052
37 -0.1273903953 -0.1545285586
38 -0.2273903953 -0.1273903953
39 -0.1273903953 -0.2273903953
40 -0.5630812120 -0.1273903953
41 -1.0630812120 -0.5630812120
42 -0.7630812120 -1.0630812120
43 -0.9902193754 -0.7630812120
44 -1.2359430487 -0.9902193754
45 -1.0188377419 -1.2359430487
46 -0.8288705984 -1.0188377419
47 -0.5745942717 -0.8288705984
48 -0.3660416183 -0.5745942717
49 -0.5389034549 -0.3660416183
50 -0.6217981481 -0.5389034549
51 -1.1032126381 -0.6217981481
52 -1.1318310046 -1.1032126381
53 -0.5418638611 -1.1318310046
54 0.6852743022 -0.5418638611
55 0.7495834854 0.6852743022
56 0.3767216488 0.7495834854
57 -0.4132454947 0.3767216488
58 -1.1474561083 -0.4132454947
59 -0.9831469251 -1.1474561083
60 NA -0.9831469251
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.5097806246 0.6640569513
[2,] -0.0444957021 0.5097806246
[3,] -0.6545285586 -0.0444957021
[4,] -0.7645614152 -0.6545285586
[5,] -0.6731140686 -0.7645614152
[6,] 0.7540240948 -0.6731140686
[7,] 1.2268859314 0.7540240948
[8,] 1.1726096047 1.2268859314
[9,] 0.8168530749 1.1726096047
[10,] 0.2083004215 0.8168530749
[11,] 0.1997477681 0.2083004215
[12,] 0.4268859314 0.1997477681
[13,] 0.6083004215 0.4268859314
[14,] 0.6439912383 0.6083004215
[15,] 0.2354385848 0.6439912383
[16,] 0.1083004215 0.2354385848
[17,] 0.0168530749 0.1083004215
[18,] 0.7168530749 0.0168530749
[19,] 0.8711294016 0.7168530749
[20,] 0.8982675650 0.8711294016
[21,] 0.4811622581 0.8982675650
[22,] 0.4083004215 0.4811622581
[23,] 0.6439912383 0.4083004215
[24,] 0.8439912383 0.6439912383
[25,] 0.8439912383 0.8439912383
[26,] 0.5811622581 0.8439912383
[27,] 0.5897149116 0.5811622581
[28,] 0.4439912383 0.5897149116
[29,] 0.0625767482 0.4439912383
[30,] 0.2354385848 0.0625767482
[31,] 0.1083004215 0.2354385848
[32,] -0.0002522319 0.1083004215
[33,] -0.1545285586 -0.0002522319
[34,] -0.1731140686 -0.1545285586
[35,] -0.1459759052 -0.1731140686
[36,] -0.1545285586 -0.1459759052
[37,] -0.1273903953 -0.1545285586
[38,] -0.2273903953 -0.1273903953
[39,] -0.1273903953 -0.2273903953
[40,] -0.5630812120 -0.1273903953
[41,] -1.0630812120 -0.5630812120
[42,] -0.7630812120 -1.0630812120
[43,] -0.9902193754 -0.7630812120
[44,] -1.2359430487 -0.9902193754
[45,] -1.0188377419 -1.2359430487
[46,] -0.8288705984 -1.0188377419
[47,] -0.5745942717 -0.8288705984
[48,] -0.3660416183 -0.5745942717
[49,] -0.5389034549 -0.3660416183
[50,] -0.6217981481 -0.5389034549
[51,] -1.1032126381 -0.6217981481
[52,] -1.1318310046 -1.1032126381
[53,] -0.5418638611 -1.1318310046
[54,] 0.6852743022 -0.5418638611
[55,] 0.7495834854 0.6852743022
[56,] 0.3767216488 0.7495834854
[57,] -0.4132454947 0.3767216488
[58,] -1.1474561083 -0.4132454947
[59,] -0.9831469251 -1.1474561083
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.5097806246 0.6640569513
2 -0.0444957021 0.5097806246
3 -0.6545285586 -0.0444957021
4 -0.7645614152 -0.6545285586
5 -0.6731140686 -0.7645614152
6 0.7540240948 -0.6731140686
7 1.2268859314 0.7540240948
8 1.1726096047 1.2268859314
9 0.8168530749 1.1726096047
10 0.2083004215 0.8168530749
11 0.1997477681 0.2083004215
12 0.4268859314 0.1997477681
13 0.6083004215 0.4268859314
14 0.6439912383 0.6083004215
15 0.2354385848 0.6439912383
16 0.1083004215 0.2354385848
17 0.0168530749 0.1083004215
18 0.7168530749 0.0168530749
19 0.8711294016 0.7168530749
20 0.8982675650 0.8711294016
21 0.4811622581 0.8982675650
22 0.4083004215 0.4811622581
23 0.6439912383 0.4083004215
24 0.8439912383 0.6439912383
25 0.8439912383 0.8439912383
26 0.5811622581 0.8439912383
27 0.5897149116 0.5811622581
28 0.4439912383 0.5897149116
29 0.0625767482 0.4439912383
30 0.2354385848 0.0625767482
31 0.1083004215 0.2354385848
32 -0.0002522319 0.1083004215
33 -0.1545285586 -0.0002522319
34 -0.1731140686 -0.1545285586
35 -0.1459759052 -0.1731140686
36 -0.1545285586 -0.1459759052
37 -0.1273903953 -0.1545285586
38 -0.2273903953 -0.1273903953
39 -0.1273903953 -0.2273903953
40 -0.5630812120 -0.1273903953
41 -1.0630812120 -0.5630812120
42 -0.7630812120 -1.0630812120
43 -0.9902193754 -0.7630812120
44 -1.2359430487 -0.9902193754
45 -1.0188377419 -1.2359430487
46 -0.8288705984 -1.0188377419
47 -0.5745942717 -0.8288705984
48 -0.3660416183 -0.5745942717
49 -0.5389034549 -0.3660416183
50 -0.6217981481 -0.5389034549
51 -1.1032126381 -0.6217981481
52 -1.1318310046 -1.1032126381
53 -0.5418638611 -1.1318310046
54 0.6852743022 -0.5418638611
55 0.7495834854 0.6852743022
56 0.3767216488 0.7495834854
57 -0.4132454947 0.3767216488
58 -1.1474561083 -0.4132454947
59 -0.9831469251 -1.1474561083
> 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/77w1y1258481145.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8q9z11258481145.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9g5rr1258481145.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10gl7x1258481145.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/114ng51258481145.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/12fvhs1258481145.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/13wkrc1258481145.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/1467io1258481145.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/15xjyr1258481145.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/16ivwm1258481145.tab")
+ }
>
> system("convert tmp/16tqi1258481145.ps tmp/16tqi1258481145.png")
> system("convert tmp/2qbkk1258481145.ps tmp/2qbkk1258481145.png")
> system("convert tmp/3duvu1258481145.ps tmp/3duvu1258481145.png")
> system("convert tmp/4da2t1258481145.ps tmp/4da2t1258481145.png")
> system("convert tmp/5xa8x1258481145.ps tmp/5xa8x1258481145.png")
> system("convert tmp/6q51s1258481145.ps tmp/6q51s1258481145.png")
> system("convert tmp/77w1y1258481145.ps tmp/77w1y1258481145.png")
> system("convert tmp/8q9z11258481145.ps tmp/8q9z11258481145.png")
> system("convert tmp/9g5rr1258481145.ps tmp/9g5rr1258481145.png")
> system("convert tmp/10gl7x1258481145.ps tmp/10gl7x1258481145.png")
>
>
> proc.time()
user system elapsed
2.492 1.596 2.946