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 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.
> x <- array(list(461
+ ,1870
+ ,455
+ ,462
+ ,461
+ ,2263
+ ,461
+ ,455
+ ,463
+ ,1802
+ ,461
+ ,461
+ ,462
+ ,1863
+ ,463
+ ,461
+ ,456
+ ,1989
+ ,462
+ ,463
+ ,455
+ ,2197
+ ,456
+ ,462
+ ,456
+ ,2409
+ ,455
+ ,456
+ ,472
+ ,2502
+ ,456
+ ,455
+ ,472
+ ,2593
+ ,472
+ ,456
+ ,471
+ ,2598
+ ,472
+ ,472
+ ,465
+ ,2053
+ ,471
+ ,472
+ ,459
+ ,2213
+ ,465
+ ,471
+ ,465
+ ,2238
+ ,459
+ ,465
+ ,468
+ ,2359
+ ,465
+ ,459
+ ,467
+ ,2151
+ ,468
+ ,465
+ ,463
+ ,2474
+ ,467
+ ,468
+ ,460
+ ,3079
+ ,463
+ ,467
+ ,462
+ ,2312
+ ,460
+ ,463
+ ,461
+ ,2565
+ ,462
+ ,460
+ ,476
+ ,1972
+ ,461
+ ,462
+ ,476
+ ,2484
+ ,476
+ ,461
+ ,471
+ ,2202
+ ,476
+ ,476
+ ,453
+ ,2151
+ ,471
+ ,476
+ ,443
+ ,1976
+ ,453
+ ,471
+ ,442
+ ,2012
+ ,443
+ ,453
+ ,444
+ ,2114
+ ,442
+ ,443
+ ,438
+ ,1772
+ ,444
+ ,442
+ ,427
+ ,1957
+ ,438
+ ,444
+ ,424
+ ,2070
+ ,427
+ ,438
+ ,416
+ ,1990
+ ,424
+ ,427
+ ,406
+ ,2182
+ ,416
+ ,424
+ ,431
+ ,2008
+ ,406
+ ,416
+ ,434
+ ,1916
+ ,431
+ ,406
+ ,418
+ ,2397
+ ,434
+ ,431
+ ,412
+ ,2114
+ ,418
+ ,434
+ ,404
+ ,1778
+ ,412
+ ,418
+ ,409
+ ,1641
+ ,404
+ ,412
+ ,412
+ ,2186
+ ,409
+ ,404
+ ,406
+ ,1773
+ ,412
+ ,409
+ ,398
+ ,1785
+ ,406
+ ,412
+ ,397
+ ,2217
+ ,398
+ ,406
+ ,385
+ ,2153
+ ,397
+ ,398
+ ,390
+ ,1895
+ ,385
+ ,397
+ ,413
+ ,2475
+ ,390
+ ,385
+ ,413
+ ,1793
+ ,413
+ ,390
+ ,401
+ ,2308
+ ,413
+ ,413
+ ,397
+ ,2051
+ ,401
+ ,413
+ ,397
+ ,1898
+ ,397
+ ,401
+ ,409
+ ,2142
+ ,397
+ ,397
+ ,419
+ ,1874
+ ,409
+ ,397
+ ,424
+ ,1560
+ ,419
+ ,409
+ ,428
+ ,1808
+ ,424
+ ,419
+ ,430
+ ,1575
+ ,428
+ ,424
+ ,424
+ ,1525
+ ,430
+ ,428
+ ,433
+ ,1997
+ ,424
+ ,430
+ ,456
+ ,1753
+ ,433
+ ,424
+ ,459
+ ,1623
+ ,456
+ ,433
+ ,446
+ ,2251
+ ,459
+ ,456
+ ,441
+ ,1890
+ ,446
+ ,459)
+ ,dim=c(4
+ ,59)
+ ,dimnames=list(c('wkl'
+ ,'bvg'
+ ,'Y1'
+ ,'Y2')
+ ,1:59))
> y <- array(NA,dim=c(4,59),dimnames=list(c('wkl','bvg','Y1','Y2'),1:59))
> 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
wkl bvg Y1 Y2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 461 1870 455 462 1 0 0 0 0 0 0 0 0 0 0 1
2 461 2263 461 455 0 1 0 0 0 0 0 0 0 0 0 2
3 463 1802 461 461 0 0 1 0 0 0 0 0 0 0 0 3
4 462 1863 463 461 0 0 0 1 0 0 0 0 0 0 0 4
5 456 1989 462 463 0 0 0 0 1 0 0 0 0 0 0 5
6 455 2197 456 462 0 0 0 0 0 1 0 0 0 0 0 6
7 456 2409 455 456 0 0 0 0 0 0 1 0 0 0 0 7
8 472 2502 456 455 0 0 0 0 0 0 0 1 0 0 0 8
9 472 2593 472 456 0 0 0 0 0 0 0 0 1 0 0 9
10 471 2598 472 472 0 0 0 0 0 0 0 0 0 1 0 10
11 465 2053 471 472 0 0 0 0 0 0 0 0 0 0 1 11
12 459 2213 465 471 0 0 0 0 0 0 0 0 0 0 0 12
13 465 2238 459 465 1 0 0 0 0 0 0 0 0 0 0 13
14 468 2359 465 459 0 1 0 0 0 0 0 0 0 0 0 14
15 467 2151 468 465 0 0 1 0 0 0 0 0 0 0 0 15
16 463 2474 467 468 0 0 0 1 0 0 0 0 0 0 0 16
17 460 3079 463 467 0 0 0 0 1 0 0 0 0 0 0 17
18 462 2312 460 463 0 0 0 0 0 1 0 0 0 0 0 18
19 461 2565 462 460 0 0 0 0 0 0 1 0 0 0 0 19
20 476 1972 461 462 0 0 0 0 0 0 0 1 0 0 0 20
21 476 2484 476 461 0 0 0 0 0 0 0 0 1 0 0 21
22 471 2202 476 476 0 0 0 0 0 0 0 0 0 1 0 22
23 453 2151 471 476 0 0 0 0 0 0 0 0 0 0 1 23
24 443 1976 453 471 0 0 0 0 0 0 0 0 0 0 0 24
25 442 2012 443 453 1 0 0 0 0 0 0 0 0 0 0 25
26 444 2114 442 443 0 1 0 0 0 0 0 0 0 0 0 26
27 438 1772 444 442 0 0 1 0 0 0 0 0 0 0 0 27
28 427 1957 438 444 0 0 0 1 0 0 0 0 0 0 0 28
29 424 2070 427 438 0 0 0 0 1 0 0 0 0 0 0 29
30 416 1990 424 427 0 0 0 0 0 1 0 0 0 0 0 30
31 406 2182 416 424 0 0 0 0 0 0 1 0 0 0 0 31
32 431 2008 406 416 0 0 0 0 0 0 0 1 0 0 0 32
33 434 1916 431 406 0 0 0 0 0 0 0 0 1 0 0 33
34 418 2397 434 431 0 0 0 0 0 0 0 0 0 1 0 34
35 412 2114 418 434 0 0 0 0 0 0 0 0 0 0 1 35
36 404 1778 412 418 0 0 0 0 0 0 0 0 0 0 0 36
37 409 1641 404 412 1 0 0 0 0 0 0 0 0 0 0 37
38 412 2186 409 404 0 1 0 0 0 0 0 0 0 0 0 38
39 406 1773 412 409 0 0 1 0 0 0 0 0 0 0 0 39
40 398 1785 406 412 0 0 0 1 0 0 0 0 0 0 0 40
41 397 2217 398 406 0 0 0 0 1 0 0 0 0 0 0 41
42 385 2153 397 398 0 0 0 0 0 1 0 0 0 0 0 42
43 390 1895 385 397 0 0 0 0 0 0 1 0 0 0 0 43
44 413 2475 390 385 0 0 0 0 0 0 0 1 0 0 0 44
45 413 1793 413 390 0 0 0 0 0 0 0 0 1 0 0 45
46 401 2308 413 413 0 0 0 0 0 0 0 0 0 1 0 46
47 397 2051 401 413 0 0 0 0 0 0 0 0 0 0 1 47
48 397 1898 397 401 0 0 0 0 0 0 0 0 0 0 0 48
49 409 2142 397 397 1 0 0 0 0 0 0 0 0 0 0 49
50 419 1874 409 397 0 1 0 0 0 0 0 0 0 0 0 50
51 424 1560 419 409 0 0 1 0 0 0 0 0 0 0 0 51
52 428 1808 424 419 0 0 0 1 0 0 0 0 0 0 0 52
53 430 1575 428 424 0 0 0 0 1 0 0 0 0 0 0 53
54 424 1525 430 428 0 0 0 0 0 1 0 0 0 0 0 54
55 433 1997 424 430 0 0 0 0 0 0 1 0 0 0 0 55
56 456 1753 433 424 0 0 0 0 0 0 0 1 0 0 0 56
57 459 1623 456 433 0 0 0 0 0 0 0 0 1 0 0 57
58 446 2251 459 456 0 0 0 0 0 0 0 0 0 1 0 58
59 441 1890 446 459 0 0 0 0 0 0 0 0 0 0 1 59
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) bvg Y1 Y2 M1 M2
-4.0121588 -0.0002801 1.1548015 -0.1579077 11.4480705 7.6106411
M3 M4 M5 M6 M7 M8
2.9987317 0.9578624 3.2044692 0.0296764 6.2635413 24.8896854
M9 M10 M11 t
2.5996572 -4.9308674 -1.8116497 0.0415409
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-10.3725 -2.8647 0.3459 3.1596 9.7215
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -4.0121588 20.4546208 -0.196 0.84542
bvg -0.0002801 0.0030063 -0.093 0.92620
Y1 1.1548015 0.1509836 7.649 1.50e-09 ***
Y2 -0.1579077 0.1569175 -1.006 0.31990
M1 11.4480705 3.4317278 3.336 0.00176 **
M2 7.6106411 4.0994681 1.856 0.07024 .
M3 2.9987317 3.8983248 0.769 0.44596
M4 0.9578624 3.5679714 0.268 0.78963
M5 3.2044692 3.5201169 0.910 0.36772
M6 0.0296764 3.5321603 0.008 0.99334
M7 6.2635413 3.5229851 1.778 0.08249 .
M8 24.8896854 3.7395345 6.656 4.06e-08 ***
M9 2.5996572 5.5509703 0.468 0.64192
M10 -4.9308674 3.9498668 -1.248 0.21865
M11 -1.8116497 3.4815306 -0.520 0.60548
t 0.0415409 0.0673180 0.617 0.54043
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.048 on 43 degrees of freedom
Multiple R-squared: 0.9728, Adjusted R-squared: 0.9634
F-statistic: 102.7 on 15 and 43 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,] 0.0117706822 0.023541364 0.988229318
[2,] 0.0022613514 0.004522703 0.997738649
[3,] 0.0005171232 0.001034246 0.999482877
[4,] 0.0190381692 0.038076338 0.980961831
[5,] 0.3100823309 0.620164662 0.689917669
[6,] 0.2294768874 0.458953775 0.770523113
[7,] 0.1750893664 0.350178733 0.824910634
[8,] 0.1920543712 0.384108742 0.807945629
[9,] 0.1542290451 0.308458090 0.845770955
[10,] 0.1128400686 0.225680137 0.887159931
[11,] 0.1524158795 0.304831759 0.847584120
[12,] 0.1736818658 0.347363732 0.826318134
[13,] 0.3561647622 0.712329524 0.643835238
[14,] 0.9564077371 0.087184526 0.043592263
[15,] 0.9562470989 0.087505802 0.043752901
[16,] 0.9583909648 0.083218070 0.041609035
[17,] 0.9838071589 0.032385682 0.016192841
[18,] 0.9650010548 0.069997890 0.034998945
[19,] 0.9704613332 0.059077334 0.029538667
[20,] 0.9862474218 0.027505156 0.013752578
[21,] 0.9927653287 0.014469343 0.007234671
[22,] 0.9696938941 0.060612212 0.030306106
> postscript(file="/var/www/html/rcomp/tmp/1hzav1258745870.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2kwib1258745870.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/34d2h1258745870.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ndjy1258745870.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5twyv1258745870.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 = 59
Frequency = 1
1 2 3 4 5 6
1.56501188 -2.56317935 4.82550471 3.53231676 -3.24992026 5.71249582
7 8 9 10 11 12
0.70382876 -3.25051523 0.70454552 9.72145257 1.56283576 0.52536408
13 14 15 16 17 18
1.02411843 -0.02235495 0.97279233 0.69112066 0.03373766 7.78491928
19 20 21 22 23 24
-2.20294478 -4.56611795 0.34585512 5.12446303 -10.27657358 -2.18189459
25 26 27 28 29 30
-5.95574510 -0.55556070 -4.54850033 -6.25272726 0.24614797 -2.91558880
31 32 33 34 35 36
-10.37252446 6.19580514 0.96940782 -6.92358839 2.78692918 -2.75809201
37 38 39 40 41 42
-0.99511240 -1.08383313 -5.30401601 -3.89879423 1.22503146 -7.76810356
43 44 45 46 47 48
4.58393282 1.40981177 -2.30363210 -3.03851540 3.58635596 4.41462252
49 50 51 52 53 54
4.36172718 4.22492814 4.05421929 5.92808407 1.74500317 -2.81372274
55 56 57 58 59
7.28770766 0.21101627 0.28382363 -4.88381181 2.34045268
> postscript(file="/var/www/html/rcomp/tmp/6tjj11258745870.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 = 59
Frequency = 1
lag(myerror, k = 1) myerror
0 1.56501188 NA
1 -2.56317935 1.56501188
2 4.82550471 -2.56317935
3 3.53231676 4.82550471
4 -3.24992026 3.53231676
5 5.71249582 -3.24992026
6 0.70382876 5.71249582
7 -3.25051523 0.70382876
8 0.70454552 -3.25051523
9 9.72145257 0.70454552
10 1.56283576 9.72145257
11 0.52536408 1.56283576
12 1.02411843 0.52536408
13 -0.02235495 1.02411843
14 0.97279233 -0.02235495
15 0.69112066 0.97279233
16 0.03373766 0.69112066
17 7.78491928 0.03373766
18 -2.20294478 7.78491928
19 -4.56611795 -2.20294478
20 0.34585512 -4.56611795
21 5.12446303 0.34585512
22 -10.27657358 5.12446303
23 -2.18189459 -10.27657358
24 -5.95574510 -2.18189459
25 -0.55556070 -5.95574510
26 -4.54850033 -0.55556070
27 -6.25272726 -4.54850033
28 0.24614797 -6.25272726
29 -2.91558880 0.24614797
30 -10.37252446 -2.91558880
31 6.19580514 -10.37252446
32 0.96940782 6.19580514
33 -6.92358839 0.96940782
34 2.78692918 -6.92358839
35 -2.75809201 2.78692918
36 -0.99511240 -2.75809201
37 -1.08383313 -0.99511240
38 -5.30401601 -1.08383313
39 -3.89879423 -5.30401601
40 1.22503146 -3.89879423
41 -7.76810356 1.22503146
42 4.58393282 -7.76810356
43 1.40981177 4.58393282
44 -2.30363210 1.40981177
45 -3.03851540 -2.30363210
46 3.58635596 -3.03851540
47 4.41462252 3.58635596
48 4.36172718 4.41462252
49 4.22492814 4.36172718
50 4.05421929 4.22492814
51 5.92808407 4.05421929
52 1.74500317 5.92808407
53 -2.81372274 1.74500317
54 7.28770766 -2.81372274
55 0.21101627 7.28770766
56 0.28382363 0.21101627
57 -4.88381181 0.28382363
58 2.34045268 -4.88381181
59 NA 2.34045268
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.56317935 1.56501188
[2,] 4.82550471 -2.56317935
[3,] 3.53231676 4.82550471
[4,] -3.24992026 3.53231676
[5,] 5.71249582 -3.24992026
[6,] 0.70382876 5.71249582
[7,] -3.25051523 0.70382876
[8,] 0.70454552 -3.25051523
[9,] 9.72145257 0.70454552
[10,] 1.56283576 9.72145257
[11,] 0.52536408 1.56283576
[12,] 1.02411843 0.52536408
[13,] -0.02235495 1.02411843
[14,] 0.97279233 -0.02235495
[15,] 0.69112066 0.97279233
[16,] 0.03373766 0.69112066
[17,] 7.78491928 0.03373766
[18,] -2.20294478 7.78491928
[19,] -4.56611795 -2.20294478
[20,] 0.34585512 -4.56611795
[21,] 5.12446303 0.34585512
[22,] -10.27657358 5.12446303
[23,] -2.18189459 -10.27657358
[24,] -5.95574510 -2.18189459
[25,] -0.55556070 -5.95574510
[26,] -4.54850033 -0.55556070
[27,] -6.25272726 -4.54850033
[28,] 0.24614797 -6.25272726
[29,] -2.91558880 0.24614797
[30,] -10.37252446 -2.91558880
[31,] 6.19580514 -10.37252446
[32,] 0.96940782 6.19580514
[33,] -6.92358839 0.96940782
[34,] 2.78692918 -6.92358839
[35,] -2.75809201 2.78692918
[36,] -0.99511240 -2.75809201
[37,] -1.08383313 -0.99511240
[38,] -5.30401601 -1.08383313
[39,] -3.89879423 -5.30401601
[40,] 1.22503146 -3.89879423
[41,] -7.76810356 1.22503146
[42,] 4.58393282 -7.76810356
[43,] 1.40981177 4.58393282
[44,] -2.30363210 1.40981177
[45,] -3.03851540 -2.30363210
[46,] 3.58635596 -3.03851540
[47,] 4.41462252 3.58635596
[48,] 4.36172718 4.41462252
[49,] 4.22492814 4.36172718
[50,] 4.05421929 4.22492814
[51,] 5.92808407 4.05421929
[52,] 1.74500317 5.92808407
[53,] -2.81372274 1.74500317
[54,] 7.28770766 -2.81372274
[55,] 0.21101627 7.28770766
[56,] 0.28382363 0.21101627
[57,] -4.88381181 0.28382363
[58,] 2.34045268 -4.88381181
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.56317935 1.56501188
2 4.82550471 -2.56317935
3 3.53231676 4.82550471
4 -3.24992026 3.53231676
5 5.71249582 -3.24992026
6 0.70382876 5.71249582
7 -3.25051523 0.70382876
8 0.70454552 -3.25051523
9 9.72145257 0.70454552
10 1.56283576 9.72145257
11 0.52536408 1.56283576
12 1.02411843 0.52536408
13 -0.02235495 1.02411843
14 0.97279233 -0.02235495
15 0.69112066 0.97279233
16 0.03373766 0.69112066
17 7.78491928 0.03373766
18 -2.20294478 7.78491928
19 -4.56611795 -2.20294478
20 0.34585512 -4.56611795
21 5.12446303 0.34585512
22 -10.27657358 5.12446303
23 -2.18189459 -10.27657358
24 -5.95574510 -2.18189459
25 -0.55556070 -5.95574510
26 -4.54850033 -0.55556070
27 -6.25272726 -4.54850033
28 0.24614797 -6.25272726
29 -2.91558880 0.24614797
30 -10.37252446 -2.91558880
31 6.19580514 -10.37252446
32 0.96940782 6.19580514
33 -6.92358839 0.96940782
34 2.78692918 -6.92358839
35 -2.75809201 2.78692918
36 -0.99511240 -2.75809201
37 -1.08383313 -0.99511240
38 -5.30401601 -1.08383313
39 -3.89879423 -5.30401601
40 1.22503146 -3.89879423
41 -7.76810356 1.22503146
42 4.58393282 -7.76810356
43 1.40981177 4.58393282
44 -2.30363210 1.40981177
45 -3.03851540 -2.30363210
46 3.58635596 -3.03851540
47 4.41462252 3.58635596
48 4.36172718 4.41462252
49 4.22492814 4.36172718
50 4.05421929 4.22492814
51 5.92808407 4.05421929
52 1.74500317 5.92808407
53 -2.81372274 1.74500317
54 7.28770766 -2.81372274
55 0.21101627 7.28770766
56 0.28382363 0.21101627
57 -4.88381181 0.28382363
58 2.34045268 -4.88381181
> 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/7w4fi1258745870.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8kzqc1258745870.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9bpxp1258745870.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10wv8k1258745870.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11w48e1258745870.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/12s0us1258745870.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/13lu011258745870.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/14t2zs1258745870.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/154k681258745870.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/16xj9y1258745870.tab")
+ }
>
> system("convert tmp/1hzav1258745870.ps tmp/1hzav1258745870.png")
> system("convert tmp/2kwib1258745870.ps tmp/2kwib1258745870.png")
> system("convert tmp/34d2h1258745870.ps tmp/34d2h1258745870.png")
> system("convert tmp/4ndjy1258745870.ps tmp/4ndjy1258745870.png")
> system("convert tmp/5twyv1258745870.ps tmp/5twyv1258745870.png")
> system("convert tmp/6tjj11258745870.ps tmp/6tjj11258745870.png")
> system("convert tmp/7w4fi1258745870.ps tmp/7w4fi1258745870.png")
> system("convert tmp/8kzqc1258745870.ps tmp/8kzqc1258745870.png")
> system("convert tmp/9bpxp1258745870.ps tmp/9bpxp1258745870.png")
> system("convert tmp/10wv8k1258745870.ps tmp/10wv8k1258745870.png")
>
>
> proc.time()
user system elapsed
2.387 1.576 2.766