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 '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(300,2.26,302,2.57,400,3.07,392,2.76,373,2.51,379,2.87,303,3.14,324,3.11,353,3.16,392,2.47,327,2.57,376,2.89,329,2.63,359,2.38,413,1.69,338,1.96,422,2.19,390,1.87,370,1.60,367,1.63,406,1.22,418,1.21,346,1.49,350,1.64,330,1.66,318,1.77,382,1.82,337,1.78,372,1.28,422,1.29,428,1.37,426,1.12,396,1.51,458,2.24,315,2.94,337,3.09,386,3.46,352,3.64,383,4.39,439,4.15,397,5.21,453,5.80,363,5.91,365,5.39,474,5.46,373,4.72,403,3.14,384,2.63,364,2.32,361,1.93,419,0.62,352,0.60,363,-0.37,410,-1.10,361,-1.68,383,-0.78,342,-1.19,369,-0.79,361,-0.12,317,0.26,386,0.62,318,0.70,407,1.66,393,1.80,404,2.27,498,2.46,438,2.57),dim=c(2,67),dimnames=list(c('Aantal_vergunningen','Inflatie'),1:67))
> y <- array(NA,dim=c(2,67),dimnames=list(c('Aantal_vergunningen','Inflatie'),1:67))
> 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
Aantal_vergunningen Inflatie M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 300 2.26 1 0 0 0 0 0 0 0 0 0 0
2 302 2.57 0 1 0 0 0 0 0 0 0 0 0
3 400 3.07 0 0 1 0 0 0 0 0 0 0 0
4 392 2.76 0 0 0 1 0 0 0 0 0 0 0
5 373 2.51 0 0 0 0 1 0 0 0 0 0 0
6 379 2.87 0 0 0 0 0 1 0 0 0 0 0
7 303 3.14 0 0 0 0 0 0 1 0 0 0 0
8 324 3.11 0 0 0 0 0 0 0 1 0 0 0
9 353 3.16 0 0 0 0 0 0 0 0 1 0 0
10 392 2.47 0 0 0 0 0 0 0 0 0 1 0
11 327 2.57 0 0 0 0 0 0 0 0 0 0 1
12 376 2.89 0 0 0 0 0 0 0 0 0 0 0
13 329 2.63 1 0 0 0 0 0 0 0 0 0 0
14 359 2.38 0 1 0 0 0 0 0 0 0 0 0
15 413 1.69 0 0 1 0 0 0 0 0 0 0 0
16 338 1.96 0 0 0 1 0 0 0 0 0 0 0
17 422 2.19 0 0 0 0 1 0 0 0 0 0 0
18 390 1.87 0 0 0 0 0 1 0 0 0 0 0
19 370 1.60 0 0 0 0 0 0 1 0 0 0 0
20 367 1.63 0 0 0 0 0 0 0 1 0 0 0
21 406 1.22 0 0 0 0 0 0 0 0 1 0 0
22 418 1.21 0 0 0 0 0 0 0 0 0 1 0
23 346 1.49 0 0 0 0 0 0 0 0 0 0 1
24 350 1.64 0 0 0 0 0 0 0 0 0 0 0
25 330 1.66 1 0 0 0 0 0 0 0 0 0 0
26 318 1.77 0 1 0 0 0 0 0 0 0 0 0
27 382 1.82 0 0 1 0 0 0 0 0 0 0 0
28 337 1.78 0 0 0 1 0 0 0 0 0 0 0
29 372 1.28 0 0 0 0 1 0 0 0 0 0 0
30 422 1.29 0 0 0 0 0 1 0 0 0 0 0
31 428 1.37 0 0 0 0 0 0 1 0 0 0 0
32 426 1.12 0 0 0 0 0 0 0 1 0 0 0
33 396 1.51 0 0 0 0 0 0 0 0 1 0 0
34 458 2.24 0 0 0 0 0 0 0 0 0 1 0
35 315 2.94 0 0 0 0 0 0 0 0 0 0 1
36 337 3.09 0 0 0 0 0 0 0 0 0 0 0
37 386 3.46 1 0 0 0 0 0 0 0 0 0 0
38 352 3.64 0 1 0 0 0 0 0 0 0 0 0
39 383 4.39 0 0 1 0 0 0 0 0 0 0 0
40 439 4.15 0 0 0 1 0 0 0 0 0 0 0
41 397 5.21 0 0 0 0 1 0 0 0 0 0 0
42 453 5.80 0 0 0 0 0 1 0 0 0 0 0
43 363 5.91 0 0 0 0 0 0 1 0 0 0 0
44 365 5.39 0 0 0 0 0 0 0 1 0 0 0
45 474 5.46 0 0 0 0 0 0 0 0 1 0 0
46 373 4.72 0 0 0 0 0 0 0 0 0 1 0
47 403 3.14 0 0 0 0 0 0 0 0 0 0 1
48 384 2.63 0 0 0 0 0 0 0 0 0 0 0
49 364 2.32 1 0 0 0 0 0 0 0 0 0 0
50 361 1.93 0 1 0 0 0 0 0 0 0 0 0
51 419 0.62 0 0 1 0 0 0 0 0 0 0 0
52 352 0.60 0 0 0 1 0 0 0 0 0 0 0
53 363 -0.37 0 0 0 0 1 0 0 0 0 0 0
54 410 -1.10 0 0 0 0 0 1 0 0 0 0 0
55 361 -1.68 0 0 0 0 0 0 1 0 0 0 0
56 383 -0.78 0 0 0 0 0 0 0 1 0 0 0
57 342 -1.19 0 0 0 0 0 0 0 0 1 0 0
58 369 -0.79 0 0 0 0 0 0 0 0 0 1 0
59 361 -0.12 0 0 0 0 0 0 0 0 0 0 1
60 317 0.26 0 0 0 0 0 0 0 0 0 0 0
61 386 0.62 1 0 0 0 0 0 0 0 0 0 0
62 318 0.70 0 1 0 0 0 0 0 0 0 0 0
63 407 1.66 0 0 1 0 0 0 0 0 0 0 0
64 393 1.80 0 0 0 1 0 0 0 0 0 0 0
65 404 2.27 0 0 0 0 1 0 0 0 0 0 0
66 498 2.46 0 0 0 0 0 1 0 0 0 0 0
67 438 2.57 0 0 0 0 0 0 1 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Inflatie M1 M2 M3 M4
344.888 3.764 -3.845 -18.037 47.466 22.092
M5 M6 M7 M8 M9 M10
35.400 72.171 24.180 20.230 41.663 49.697
M11
-2.031
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-77.887 -22.277 -2.899 19.739 71.682
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 344.888 17.130 20.133 < 2e-16 ***
Inflatie 3.764 2.747 1.370 0.17622
M1 -3.845 21.838 -0.176 0.86088
M2 -18.037 21.838 -0.826 0.41246
M3 47.466 21.839 2.173 0.03415 *
M4 22.092 21.838 1.012 0.31623
M5 35.400 21.838 1.621 0.11084
M6 72.171 21.839 3.305 0.00169 **
M7 24.180 21.838 1.107 0.27309
M8 20.230 22.808 0.887 0.37903
M9 41.663 22.809 1.827 0.07329 .
M10 49.697 22.811 2.179 0.03374 *
M11 -2.031 22.810 -0.089 0.92937
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 36.06 on 54 degrees of freedom
Multiple R-squared: 0.401, Adjusted R-squared: 0.2679
F-statistic: 3.013 on 12 and 54 DF, p-value: 0.002719
> 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,] 0.59908612 0.80182776 0.40091388
[2,] 0.59835340 0.80329319 0.40164660
[3,] 0.48769606 0.97539212 0.51230394
[4,] 0.50179435 0.99641129 0.49820565
[5,] 0.39246273 0.78492547 0.60753727
[6,] 0.28693229 0.57386458 0.71306771
[7,] 0.20002660 0.40005320 0.79997340
[8,] 0.13115474 0.26230948 0.86884526
[9,] 0.14016942 0.28033884 0.85983058
[10,] 0.10196619 0.20393238 0.89803381
[11,] 0.07853746 0.15707492 0.92146254
[12,] 0.06814857 0.13629715 0.93185143
[13,] 0.07697076 0.15394151 0.92302924
[14,] 0.07090103 0.14180205 0.92909897
[15,] 0.05481382 0.10962763 0.94518618
[16,] 0.13518330 0.27036659 0.86481670
[17,] 0.18843870 0.37687740 0.81156130
[18,] 0.13411018 0.26822036 0.86588982
[19,] 0.26185715 0.52371430 0.73814285
[20,] 0.30988541 0.61977082 0.69011459
[21,] 0.24933514 0.49867027 0.75066486
[22,] 0.37317267 0.74634535 0.62682733
[23,] 0.33336501 0.66673002 0.66663499
[24,] 0.32113725 0.64227449 0.67886275
[25,] 0.49277124 0.98554247 0.50722876
[26,] 0.40980920 0.81961840 0.59019080
[27,] 0.41181270 0.82362541 0.58818730
[28,] 0.59648401 0.80703198 0.40351599
[29,] 0.82143132 0.35713736 0.17856868
[30,] 0.85570457 0.28859086 0.14429543
[31,] 0.96861490 0.06277021 0.03138510
[32,] 0.95560274 0.08879453 0.04439726
[33,] 0.92978795 0.14042410 0.07021205
[34,] 0.97595562 0.04808876 0.02404438
[35,] 0.95283216 0.09433568 0.04716784
[36,] 0.96217508 0.07564984 0.03782492
> postscript(file="/var/www/html/rcomp/tmp/15l8r1292502832.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/25l8r1292502832.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/35l8r1292502832.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4gdpc1292502832.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5gdpc1292502832.ps",horizontal=F,onefile=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 = 67
Frequency = 1
1 2 3 4 5 6
-49.54934977 -34.52445892 -3.91006281 14.63133711 -16.73587822 -48.86155122
7 8 9 10 11 12
-77.88684831 -52.82432164 -45.44590040 -11.88204805 -25.53047839 20.23389227
13 14 15 16 17 18
-21.94206533 23.19071934 14.28438981 -36.35738600 33.46863253 -34.09745511
19 20 21 22 23 24
-5.09014032 -4.25345941 14.85644603 18.86071304 -2.46525460 -1.06098760
25 26 27 28 29 30
-17.29089211 -15.51318204 -17.20494268 -36.67984871 -13.10604001 0.08572063
31 32 33 34 35 36
53.77560179 56.66622960 3.76485817 54.98369405 -38.92319395 -19.51892695
37 38 39 40 41 42
31.93373491 11.44795825 -25.87866966 56.39924353 -2.89893770 14.10964721
43 44 45 46 47 48
-28.31339452 -20.40646075 66.89667856 -39.35126428 48.32398683 29.21255726
49 50 51 52 53 54
14.22480446 26.88456258 24.31197264 -17.23821531 -15.89528145 -2.91808969
55 56 57 58 59 60
-1.74390510 20.81801220 -40.07208236 -22.61109476 18.59494012 -28.86653498
61 62 63 64 65 66
42.62376784 -11.48559921 8.39731270 19.24486937 15.16750484 71.68172819
67
59.25868646
> postscript(file="/var/www/html/rcomp/tmp/6gdpc1292502832.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 67
Frequency = 1
lag(myerror, k = 1) myerror
0 -49.54934977 NA
1 -34.52445892 -49.54934977
2 -3.91006281 -34.52445892
3 14.63133711 -3.91006281
4 -16.73587822 14.63133711
5 -48.86155122 -16.73587822
6 -77.88684831 -48.86155122
7 -52.82432164 -77.88684831
8 -45.44590040 -52.82432164
9 -11.88204805 -45.44590040
10 -25.53047839 -11.88204805
11 20.23389227 -25.53047839
12 -21.94206533 20.23389227
13 23.19071934 -21.94206533
14 14.28438981 23.19071934
15 -36.35738600 14.28438981
16 33.46863253 -36.35738600
17 -34.09745511 33.46863253
18 -5.09014032 -34.09745511
19 -4.25345941 -5.09014032
20 14.85644603 -4.25345941
21 18.86071304 14.85644603
22 -2.46525460 18.86071304
23 -1.06098760 -2.46525460
24 -17.29089211 -1.06098760
25 -15.51318204 -17.29089211
26 -17.20494268 -15.51318204
27 -36.67984871 -17.20494268
28 -13.10604001 -36.67984871
29 0.08572063 -13.10604001
30 53.77560179 0.08572063
31 56.66622960 53.77560179
32 3.76485817 56.66622960
33 54.98369405 3.76485817
34 -38.92319395 54.98369405
35 -19.51892695 -38.92319395
36 31.93373491 -19.51892695
37 11.44795825 31.93373491
38 -25.87866966 11.44795825
39 56.39924353 -25.87866966
40 -2.89893770 56.39924353
41 14.10964721 -2.89893770
42 -28.31339452 14.10964721
43 -20.40646075 -28.31339452
44 66.89667856 -20.40646075
45 -39.35126428 66.89667856
46 48.32398683 -39.35126428
47 29.21255726 48.32398683
48 14.22480446 29.21255726
49 26.88456258 14.22480446
50 24.31197264 26.88456258
51 -17.23821531 24.31197264
52 -15.89528145 -17.23821531
53 -2.91808969 -15.89528145
54 -1.74390510 -2.91808969
55 20.81801220 -1.74390510
56 -40.07208236 20.81801220
57 -22.61109476 -40.07208236
58 18.59494012 -22.61109476
59 -28.86653498 18.59494012
60 42.62376784 -28.86653498
61 -11.48559921 42.62376784
62 8.39731270 -11.48559921
63 19.24486937 8.39731270
64 15.16750484 19.24486937
65 71.68172819 15.16750484
66 59.25868646 71.68172819
67 NA 59.25868646
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -34.52445892 -49.54934977
[2,] -3.91006281 -34.52445892
[3,] 14.63133711 -3.91006281
[4,] -16.73587822 14.63133711
[5,] -48.86155122 -16.73587822
[6,] -77.88684831 -48.86155122
[7,] -52.82432164 -77.88684831
[8,] -45.44590040 -52.82432164
[9,] -11.88204805 -45.44590040
[10,] -25.53047839 -11.88204805
[11,] 20.23389227 -25.53047839
[12,] -21.94206533 20.23389227
[13,] 23.19071934 -21.94206533
[14,] 14.28438981 23.19071934
[15,] -36.35738600 14.28438981
[16,] 33.46863253 -36.35738600
[17,] -34.09745511 33.46863253
[18,] -5.09014032 -34.09745511
[19,] -4.25345941 -5.09014032
[20,] 14.85644603 -4.25345941
[21,] 18.86071304 14.85644603
[22,] -2.46525460 18.86071304
[23,] -1.06098760 -2.46525460
[24,] -17.29089211 -1.06098760
[25,] -15.51318204 -17.29089211
[26,] -17.20494268 -15.51318204
[27,] -36.67984871 -17.20494268
[28,] -13.10604001 -36.67984871
[29,] 0.08572063 -13.10604001
[30,] 53.77560179 0.08572063
[31,] 56.66622960 53.77560179
[32,] 3.76485817 56.66622960
[33,] 54.98369405 3.76485817
[34,] -38.92319395 54.98369405
[35,] -19.51892695 -38.92319395
[36,] 31.93373491 -19.51892695
[37,] 11.44795825 31.93373491
[38,] -25.87866966 11.44795825
[39,] 56.39924353 -25.87866966
[40,] -2.89893770 56.39924353
[41,] 14.10964721 -2.89893770
[42,] -28.31339452 14.10964721
[43,] -20.40646075 -28.31339452
[44,] 66.89667856 -20.40646075
[45,] -39.35126428 66.89667856
[46,] 48.32398683 -39.35126428
[47,] 29.21255726 48.32398683
[48,] 14.22480446 29.21255726
[49,] 26.88456258 14.22480446
[50,] 24.31197264 26.88456258
[51,] -17.23821531 24.31197264
[52,] -15.89528145 -17.23821531
[53,] -2.91808969 -15.89528145
[54,] -1.74390510 -2.91808969
[55,] 20.81801220 -1.74390510
[56,] -40.07208236 20.81801220
[57,] -22.61109476 -40.07208236
[58,] 18.59494012 -22.61109476
[59,] -28.86653498 18.59494012
[60,] 42.62376784 -28.86653498
[61,] -11.48559921 42.62376784
[62,] 8.39731270 -11.48559921
[63,] 19.24486937 8.39731270
[64,] 15.16750484 19.24486937
[65,] 71.68172819 15.16750484
[66,] 59.25868646 71.68172819
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -34.52445892 -49.54934977
2 -3.91006281 -34.52445892
3 14.63133711 -3.91006281
4 -16.73587822 14.63133711
5 -48.86155122 -16.73587822
6 -77.88684831 -48.86155122
7 -52.82432164 -77.88684831
8 -45.44590040 -52.82432164
9 -11.88204805 -45.44590040
10 -25.53047839 -11.88204805
11 20.23389227 -25.53047839
12 -21.94206533 20.23389227
13 23.19071934 -21.94206533
14 14.28438981 23.19071934
15 -36.35738600 14.28438981
16 33.46863253 -36.35738600
17 -34.09745511 33.46863253
18 -5.09014032 -34.09745511
19 -4.25345941 -5.09014032
20 14.85644603 -4.25345941
21 18.86071304 14.85644603
22 -2.46525460 18.86071304
23 -1.06098760 -2.46525460
24 -17.29089211 -1.06098760
25 -15.51318204 -17.29089211
26 -17.20494268 -15.51318204
27 -36.67984871 -17.20494268
28 -13.10604001 -36.67984871
29 0.08572063 -13.10604001
30 53.77560179 0.08572063
31 56.66622960 53.77560179
32 3.76485817 56.66622960
33 54.98369405 3.76485817
34 -38.92319395 54.98369405
35 -19.51892695 -38.92319395
36 31.93373491 -19.51892695
37 11.44795825 31.93373491
38 -25.87866966 11.44795825
39 56.39924353 -25.87866966
40 -2.89893770 56.39924353
41 14.10964721 -2.89893770
42 -28.31339452 14.10964721
43 -20.40646075 -28.31339452
44 66.89667856 -20.40646075
45 -39.35126428 66.89667856
46 48.32398683 -39.35126428
47 29.21255726 48.32398683
48 14.22480446 29.21255726
49 26.88456258 14.22480446
50 24.31197264 26.88456258
51 -17.23821531 24.31197264
52 -15.89528145 -17.23821531
53 -2.91808969 -15.89528145
54 -1.74390510 -2.91808969
55 20.81801220 -1.74390510
56 -40.07208236 20.81801220
57 -22.61109476 -40.07208236
58 18.59494012 -22.61109476
59 -28.86653498 18.59494012
60 42.62376784 -28.86653498
61 -11.48559921 42.62376784
62 8.39731270 -11.48559921
63 19.24486937 8.39731270
64 15.16750484 19.24486937
65 71.68172819 15.16750484
66 59.25868646 71.68172819
> 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/7rm6f1292502832.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8jv6i1292502832.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9jv6i1292502832.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10jv6i1292502832.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ne4o1292502832.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/128e3u1292502832.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/13fxi61292502832.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/14qph91292502832.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/15tpfe1292502832.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/16phvn1292502832.tab")
+ }
>
> try(system("convert tmp/15l8r1292502832.ps tmp/15l8r1292502832.png",intern=TRUE))
character(0)
> try(system("convert tmp/25l8r1292502832.ps tmp/25l8r1292502832.png",intern=TRUE))
character(0)
> try(system("convert tmp/35l8r1292502832.ps tmp/35l8r1292502832.png",intern=TRUE))
character(0)
> try(system("convert tmp/4gdpc1292502832.ps tmp/4gdpc1292502832.png",intern=TRUE))
character(0)
> try(system("convert tmp/5gdpc1292502832.ps tmp/5gdpc1292502832.png",intern=TRUE))
character(0)
> try(system("convert tmp/6gdpc1292502832.ps tmp/6gdpc1292502832.png",intern=TRUE))
character(0)
> try(system("convert tmp/7rm6f1292502832.ps tmp/7rm6f1292502832.png",intern=TRUE))
character(0)
> try(system("convert tmp/8jv6i1292502832.ps tmp/8jv6i1292502832.png",intern=TRUE))
character(0)
> try(system("convert tmp/9jv6i1292502832.ps tmp/9jv6i1292502832.png",intern=TRUE))
character(0)
> try(system("convert tmp/10jv6i1292502832.ps tmp/10jv6i1292502832.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.551 1.664 6.161