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.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
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
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(613
+ ,0
+ ,611
+ ,594
+ ,543
+ ,537
+ ,611
+ ,0
+ ,613
+ ,611
+ ,594
+ ,543
+ ,594
+ ,0
+ ,611
+ ,613
+ ,611
+ ,594
+ ,595
+ ,0
+ ,594
+ ,611
+ ,613
+ ,611
+ ,591
+ ,0
+ ,595
+ ,594
+ ,611
+ ,613
+ ,589
+ ,0
+ ,591
+ ,595
+ ,594
+ ,611
+ ,584
+ ,0
+ ,589
+ ,591
+ ,595
+ ,594
+ ,573
+ ,0
+ ,584
+ ,589
+ ,591
+ ,595
+ ,567
+ ,0
+ ,573
+ ,584
+ ,589
+ ,591
+ ,569
+ ,0
+ ,567
+ ,573
+ ,584
+ ,589
+ ,621
+ ,0
+ ,569
+ ,567
+ ,573
+ ,584
+ ,629
+ ,0
+ ,621
+ ,569
+ ,567
+ ,573
+ ,628
+ ,0
+ ,629
+ ,621
+ ,569
+ ,567
+ ,612
+ ,0
+ ,628
+ ,629
+ ,621
+ ,569
+ ,595
+ ,0
+ ,612
+ ,628
+ ,629
+ ,621
+ ,597
+ ,0
+ ,595
+ ,612
+ ,628
+ ,629
+ ,593
+ ,0
+ ,597
+ ,595
+ ,612
+ ,628
+ ,590
+ ,0
+ ,593
+ ,597
+ ,595
+ ,612
+ ,580
+ ,0
+ ,590
+ ,593
+ ,597
+ ,595
+ ,574
+ ,0
+ ,580
+ ,590
+ ,593
+ ,597
+ ,573
+ ,0
+ ,574
+ ,580
+ ,590
+ ,593
+ ,573
+ ,0
+ ,573
+ ,574
+ ,580
+ ,590
+ ,620
+ ,0
+ ,573
+ ,573
+ ,574
+ ,580
+ ,626
+ ,0
+ ,620
+ ,573
+ ,573
+ ,574
+ ,620
+ ,0
+ ,626
+ ,620
+ ,573
+ ,573
+ ,588
+ ,0
+ ,620
+ ,626
+ ,620
+ ,573
+ ,566
+ ,0
+ ,588
+ ,620
+ ,626
+ ,620
+ ,557
+ ,0
+ ,566
+ ,588
+ ,620
+ ,626
+ ,561
+ ,0
+ ,557
+ ,566
+ ,588
+ ,620
+ ,549
+ ,0
+ ,561
+ ,557
+ ,566
+ ,588
+ ,532
+ ,0
+ ,549
+ ,561
+ ,557
+ ,566
+ ,526
+ ,0
+ ,532
+ ,549
+ ,561
+ ,557
+ ,511
+ ,0
+ ,526
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+ ,549
+ ,561
+ ,499
+ ,0
+ ,511
+ ,526
+ ,532
+ ,549
+ ,555
+ ,0
+ ,499
+ ,511
+ ,526
+ ,532
+ ,565
+ ,0
+ ,555
+ ,499
+ ,511
+ ,526
+ ,542
+ ,0
+ ,565
+ ,555
+ ,499
+ ,511
+ ,527
+ ,0
+ ,542
+ ,565
+ ,555
+ ,499
+ ,510
+ ,0
+ ,527
+ ,542
+ ,565
+ ,555
+ ,514
+ ,0
+ ,510
+ ,527
+ ,542
+ ,565
+ ,517
+ ,0
+ ,514
+ ,510
+ ,527
+ ,542
+ ,508
+ ,0
+ ,517
+ ,514
+ ,510
+ ,527
+ ,493
+ ,0
+ ,508
+ ,517
+ ,514
+ ,510
+ ,490
+ ,0
+ ,493
+ ,508
+ ,517
+ ,514
+ ,469
+ ,0
+ ,490
+ ,493
+ ,508
+ ,517
+ ,478
+ ,0
+ ,469
+ ,490
+ ,493
+ ,508
+ ,528
+ ,0
+ ,478
+ ,469
+ ,490
+ ,493
+ ,534
+ ,0
+ ,528
+ ,478
+ ,469
+ ,490
+ ,518
+ ,1
+ ,534
+ ,528
+ ,478
+ ,469
+ ,506
+ ,1
+ ,518
+ ,534
+ ,528
+ ,478
+ ,502
+ ,1
+ ,506
+ ,518
+ ,534
+ ,528
+ ,516
+ ,1
+ ,502
+ ,506
+ ,518
+ ,534
+ ,528
+ ,1
+ ,516
+ ,502
+ ,506
+ ,518
+ ,533
+ ,1
+ ,528
+ ,516
+ ,502
+ ,506
+ ,536
+ ,1
+ ,533
+ ,528
+ ,516
+ ,502
+ ,537
+ ,1
+ ,536
+ ,533
+ ,528
+ ,516
+ ,524
+ ,1
+ ,537
+ ,536
+ ,533
+ ,528
+ ,536
+ ,1
+ ,524
+ ,537
+ ,536
+ ,533
+ ,587
+ ,1
+ ,536
+ ,524
+ ,537
+ ,536
+ ,597
+ ,1
+ ,587
+ ,536
+ ,524
+ ,537
+ ,581
+ ,1
+ ,597
+ ,587
+ ,536
+ ,524)
+ ,dim=c(6
+ ,61)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:61))
> y <- array(NA,dim=c(6,61),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:61))
> 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
Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 613 0 611 594 543 537 1 0 0 0 0 0 0 0 0 0 0 1
2 611 0 613 611 594 543 0 1 0 0 0 0 0 0 0 0 0 2
3 594 0 611 613 611 594 0 0 1 0 0 0 0 0 0 0 0 3
4 595 0 594 611 613 611 0 0 0 1 0 0 0 0 0 0 0 4
5 591 0 595 594 611 613 0 0 0 0 1 0 0 0 0 0 0 5
6 589 0 591 595 594 611 0 0 0 0 0 1 0 0 0 0 0 6
7 584 0 589 591 595 594 0 0 0 0 0 0 1 0 0 0 0 7
8 573 0 584 589 591 595 0 0 0 0 0 0 0 1 0 0 0 8
9 567 0 573 584 589 591 0 0 0 0 0 0 0 0 1 0 0 9
10 569 0 567 573 584 589 0 0 0 0 0 0 0 0 0 1 0 10
11 621 0 569 567 573 584 0 0 0 0 0 0 0 0 0 0 1 11
12 629 0 621 569 567 573 0 0 0 0 0 0 0 0 0 0 0 12
13 628 0 629 621 569 567 1 0 0 0 0 0 0 0 0 0 0 13
14 612 0 628 629 621 569 0 1 0 0 0 0 0 0 0 0 0 14
15 595 0 612 628 629 621 0 0 1 0 0 0 0 0 0 0 0 15
16 597 0 595 612 628 629 0 0 0 1 0 0 0 0 0 0 0 16
17 593 0 597 595 612 628 0 0 0 0 1 0 0 0 0 0 0 17
18 590 0 593 597 595 612 0 0 0 0 0 1 0 0 0 0 0 18
19 580 0 590 593 597 595 0 0 0 0 0 0 1 0 0 0 0 19
20 574 0 580 590 593 597 0 0 0 0 0 0 0 1 0 0 0 20
21 573 0 574 580 590 593 0 0 0 0 0 0 0 0 1 0 0 21
22 573 0 573 574 580 590 0 0 0 0 0 0 0 0 0 1 0 22
23 620 0 573 573 574 580 0 0 0 0 0 0 0 0 0 0 1 23
24 626 0 620 573 573 574 0 0 0 0 0 0 0 0 0 0 0 24
25 620 0 626 620 573 573 1 0 0 0 0 0 0 0 0 0 0 25
26 588 0 620 626 620 573 0 1 0 0 0 0 0 0 0 0 0 26
27 566 0 588 620 626 620 0 0 1 0 0 0 0 0 0 0 0 27
28 557 0 566 588 620 626 0 0 0 1 0 0 0 0 0 0 0 28
29 561 0 557 566 588 620 0 0 0 0 1 0 0 0 0 0 0 29
30 549 0 561 557 566 588 0 0 0 0 0 1 0 0 0 0 0 30
31 532 0 549 561 557 566 0 0 0 0 0 0 1 0 0 0 0 31
32 526 0 532 549 561 557 0 0 0 0 0 0 0 1 0 0 0 32
33 511 0 526 532 549 561 0 0 0 0 0 0 0 0 1 0 0 33
34 499 0 511 526 532 549 0 0 0 0 0 0 0 0 0 1 0 34
35 555 0 499 511 526 532 0 0 0 0 0 0 0 0 0 0 1 35
36 565 0 555 499 511 526 0 0 0 0 0 0 0 0 0 0 0 36
37 542 0 565 555 499 511 1 0 0 0 0 0 0 0 0 0 0 37
38 527 0 542 565 555 499 0 1 0 0 0 0 0 0 0 0 0 38
39 510 0 527 542 565 555 0 0 1 0 0 0 0 0 0 0 0 39
40 514 0 510 527 542 565 0 0 0 1 0 0 0 0 0 0 0 40
41 517 0 514 510 527 542 0 0 0 0 1 0 0 0 0 0 0 41
42 508 0 517 514 510 527 0 0 0 0 0 1 0 0 0 0 0 42
43 493 0 508 517 514 510 0 0 0 0 0 0 1 0 0 0 0 43
44 490 0 493 508 517 514 0 0 0 0 0 0 0 1 0 0 0 44
45 469 0 490 493 508 517 0 0 0 0 0 0 0 0 1 0 0 45
46 478 0 469 490 493 508 0 0 0 0 0 0 0 0 0 1 0 46
47 528 0 478 469 490 493 0 0 0 0 0 0 0 0 0 0 1 47
48 534 0 528 478 469 490 0 0 0 0 0 0 0 0 0 0 0 48
49 518 1 534 528 478 469 1 0 0 0 0 0 0 0 0 0 0 49
50 506 1 518 534 528 478 0 1 0 0 0 0 0 0 0 0 0 50
51 502 1 506 518 534 528 0 0 1 0 0 0 0 0 0 0 0 51
52 516 1 502 506 518 534 0 0 0 1 0 0 0 0 0 0 0 52
53 528 1 516 502 506 518 0 0 0 0 1 0 0 0 0 0 0 53
54 533 1 528 516 502 506 0 0 0 0 0 1 0 0 0 0 0 54
55 536 1 533 528 516 502 0 0 0 0 0 0 1 0 0 0 0 55
56 537 1 536 533 528 516 0 0 0 0 0 0 0 1 0 0 0 56
57 524 1 537 536 533 528 0 0 0 0 0 0 0 0 1 0 0 57
58 536 1 524 537 536 533 0 0 0 0 0 0 0 0 0 1 0 58
59 587 1 536 524 537 536 0 0 0 0 0 0 0 0 0 0 1 59
60 597 1 587 536 524 537 0 0 0 0 0 0 0 0 0 0 0 60
61 581 1 597 587 536 524 1 0 0 0 0 0 0 0 0 0 0 61
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
79.36076 12.40285 0.94872 0.04522 -0.04083 -0.06149
M1 M2 M3 M4 M5 M6
-23.73716 -27.99893 -24.49201 -6.19986 -6.38345 -13.98806
M7 M8 M9 M10 M11 t
-19.38499 -15.24211 -20.96998 -8.16896 41.07192 -0.36681
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-14.192 -3.478 0.483 3.200 12.070
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 79.36076 28.75189 2.760 0.00846 **
X 12.40285 4.15452 2.985 0.00466 **
Y1 0.94872 0.14712 6.449 8.13e-08 ***
Y2 0.04522 0.20578 0.220 0.82710
Y3 -0.04083 0.20551 -0.199 0.84344
Y4 -0.06149 0.14714 -0.418 0.67812
M1 -23.73716 10.35688 -2.292 0.02687 *
M2 -27.99893 13.53603 -2.068 0.04464 *
M3 -24.49201 11.11501 -2.204 0.03296 *
M4 -6.19986 10.77971 -0.575 0.56819
M5 -6.38345 8.57903 -0.744 0.46088
M6 -13.98806 8.32830 -1.680 0.10029
M7 -19.38499 9.40856 -2.060 0.04545 *
M8 -15.24211 9.98553 -1.526 0.13423
M9 -20.96998 9.37540 -2.237 0.03054 *
M10 -8.16896 10.06906 -0.811 0.42167
M11 41.07192 8.56490 4.795 1.97e-05 ***
t -0.36681 0.12007 -3.055 0.00386 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.573 on 43 degrees of freedom
Multiple R-squared: 0.9825, Adjusted R-squared: 0.9756
F-statistic: 141.9 on 17 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,] 0.31146181 0.62292363 0.68853819
[2,] 0.16621253 0.33242506 0.83378747
[3,] 0.08539045 0.17078090 0.91460955
[4,] 0.03789657 0.07579313 0.96210343
[5,] 0.09352744 0.18705488 0.90647256
[6,] 0.71842379 0.56315242 0.28157621
[7,] 0.61524503 0.76950995 0.38475497
[8,] 0.63286340 0.73427320 0.36713660
[9,] 0.57264969 0.85470063 0.42735031
[10,] 0.51551055 0.96897889 0.48448945
[11,] 0.51285287 0.97429425 0.48714713
[12,] 0.50717428 0.98565145 0.49282572
[13,] 0.56734909 0.86530183 0.43265091
[14,] 0.89978550 0.20042899 0.10021450
[15,] 0.93598480 0.12803040 0.06401520
[16,] 0.94547929 0.10904143 0.05452071
[17,] 0.94503873 0.10992253 0.05496127
[18,] 0.92327571 0.15344858 0.07672429
[19,] 0.84176180 0.31647640 0.15823820
[20,] 0.78452968 0.43094064 0.21547032
> postscript(file="/var/www/html/rcomp/tmp/10gya1258727391.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/26adn1258727391.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/397x91258727391.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4r7ty1258727391.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5dgr21258727391.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 = 61
Frequency = 1
1 2 3 4 5 6
6.40273035 8.81647264 -5.68674883 -5.26649347 -8.85473035 0.04921501
7 8 9 10 11 12
1.88686615 -8.15700306 2.27209934 -2.29948111 -1.55624652 -2.46275821
13 14 15 16 17 18
10.41264435 1.87444081 0.48296138 1.86046434 -3.43260785 3.56532396
19 20 21 22 23 24
1.39252833 1.19896849 12.06974746 0.26280437 -2.42589293 0.01323154
25 26 27 28 29 30
10.23794608 -9.79334524 -1.16827800 -5.65075091 6.75746195 -3.52484998
31 32 33 34 35 36
-5.27752684 1.22728327 -1.46099655 -12.82504968 5.07361408 2.94526267
37 38 39 40 41 42
-9.38269013 3.16305060 2.14534694 4.70227553 3.19992338 -2.47214708
43 44 45 46 47 48
-4.18751061 4.04266522 -7.52120696 7.93751641 0.42985412 -1.01638445
49 50 51 52 53 54
-14.19239580 -4.06061881 4.22671851 4.35450452 2.32995287 2.38245810
55 56 57 58 59 60
6.18564296 1.68808608 -5.35964328 6.92421000 -1.52132875 0.52064845
61
-3.47823485
> postscript(file="/var/www/html/rcomp/tmp/69l2q1258727391.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 6.40273035 NA
1 8.81647264 6.40273035
2 -5.68674883 8.81647264
3 -5.26649347 -5.68674883
4 -8.85473035 -5.26649347
5 0.04921501 -8.85473035
6 1.88686615 0.04921501
7 -8.15700306 1.88686615
8 2.27209934 -8.15700306
9 -2.29948111 2.27209934
10 -1.55624652 -2.29948111
11 -2.46275821 -1.55624652
12 10.41264435 -2.46275821
13 1.87444081 10.41264435
14 0.48296138 1.87444081
15 1.86046434 0.48296138
16 -3.43260785 1.86046434
17 3.56532396 -3.43260785
18 1.39252833 3.56532396
19 1.19896849 1.39252833
20 12.06974746 1.19896849
21 0.26280437 12.06974746
22 -2.42589293 0.26280437
23 0.01323154 -2.42589293
24 10.23794608 0.01323154
25 -9.79334524 10.23794608
26 -1.16827800 -9.79334524
27 -5.65075091 -1.16827800
28 6.75746195 -5.65075091
29 -3.52484998 6.75746195
30 -5.27752684 -3.52484998
31 1.22728327 -5.27752684
32 -1.46099655 1.22728327
33 -12.82504968 -1.46099655
34 5.07361408 -12.82504968
35 2.94526267 5.07361408
36 -9.38269013 2.94526267
37 3.16305060 -9.38269013
38 2.14534694 3.16305060
39 4.70227553 2.14534694
40 3.19992338 4.70227553
41 -2.47214708 3.19992338
42 -4.18751061 -2.47214708
43 4.04266522 -4.18751061
44 -7.52120696 4.04266522
45 7.93751641 -7.52120696
46 0.42985412 7.93751641
47 -1.01638445 0.42985412
48 -14.19239580 -1.01638445
49 -4.06061881 -14.19239580
50 4.22671851 -4.06061881
51 4.35450452 4.22671851
52 2.32995287 4.35450452
53 2.38245810 2.32995287
54 6.18564296 2.38245810
55 1.68808608 6.18564296
56 -5.35964328 1.68808608
57 6.92421000 -5.35964328
58 -1.52132875 6.92421000
59 0.52064845 -1.52132875
60 -3.47823485 0.52064845
61 NA -3.47823485
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 8.81647264 6.40273035
[2,] -5.68674883 8.81647264
[3,] -5.26649347 -5.68674883
[4,] -8.85473035 -5.26649347
[5,] 0.04921501 -8.85473035
[6,] 1.88686615 0.04921501
[7,] -8.15700306 1.88686615
[8,] 2.27209934 -8.15700306
[9,] -2.29948111 2.27209934
[10,] -1.55624652 -2.29948111
[11,] -2.46275821 -1.55624652
[12,] 10.41264435 -2.46275821
[13,] 1.87444081 10.41264435
[14,] 0.48296138 1.87444081
[15,] 1.86046434 0.48296138
[16,] -3.43260785 1.86046434
[17,] 3.56532396 -3.43260785
[18,] 1.39252833 3.56532396
[19,] 1.19896849 1.39252833
[20,] 12.06974746 1.19896849
[21,] 0.26280437 12.06974746
[22,] -2.42589293 0.26280437
[23,] 0.01323154 -2.42589293
[24,] 10.23794608 0.01323154
[25,] -9.79334524 10.23794608
[26,] -1.16827800 -9.79334524
[27,] -5.65075091 -1.16827800
[28,] 6.75746195 -5.65075091
[29,] -3.52484998 6.75746195
[30,] -5.27752684 -3.52484998
[31,] 1.22728327 -5.27752684
[32,] -1.46099655 1.22728327
[33,] -12.82504968 -1.46099655
[34,] 5.07361408 -12.82504968
[35,] 2.94526267 5.07361408
[36,] -9.38269013 2.94526267
[37,] 3.16305060 -9.38269013
[38,] 2.14534694 3.16305060
[39,] 4.70227553 2.14534694
[40,] 3.19992338 4.70227553
[41,] -2.47214708 3.19992338
[42,] -4.18751061 -2.47214708
[43,] 4.04266522 -4.18751061
[44,] -7.52120696 4.04266522
[45,] 7.93751641 -7.52120696
[46,] 0.42985412 7.93751641
[47,] -1.01638445 0.42985412
[48,] -14.19239580 -1.01638445
[49,] -4.06061881 -14.19239580
[50,] 4.22671851 -4.06061881
[51,] 4.35450452 4.22671851
[52,] 2.32995287 4.35450452
[53,] 2.38245810 2.32995287
[54,] 6.18564296 2.38245810
[55,] 1.68808608 6.18564296
[56,] -5.35964328 1.68808608
[57,] 6.92421000 -5.35964328
[58,] -1.52132875 6.92421000
[59,] 0.52064845 -1.52132875
[60,] -3.47823485 0.52064845
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 8.81647264 6.40273035
2 -5.68674883 8.81647264
3 -5.26649347 -5.68674883
4 -8.85473035 -5.26649347
5 0.04921501 -8.85473035
6 1.88686615 0.04921501
7 -8.15700306 1.88686615
8 2.27209934 -8.15700306
9 -2.29948111 2.27209934
10 -1.55624652 -2.29948111
11 -2.46275821 -1.55624652
12 10.41264435 -2.46275821
13 1.87444081 10.41264435
14 0.48296138 1.87444081
15 1.86046434 0.48296138
16 -3.43260785 1.86046434
17 3.56532396 -3.43260785
18 1.39252833 3.56532396
19 1.19896849 1.39252833
20 12.06974746 1.19896849
21 0.26280437 12.06974746
22 -2.42589293 0.26280437
23 0.01323154 -2.42589293
24 10.23794608 0.01323154
25 -9.79334524 10.23794608
26 -1.16827800 -9.79334524
27 -5.65075091 -1.16827800
28 6.75746195 -5.65075091
29 -3.52484998 6.75746195
30 -5.27752684 -3.52484998
31 1.22728327 -5.27752684
32 -1.46099655 1.22728327
33 -12.82504968 -1.46099655
34 5.07361408 -12.82504968
35 2.94526267 5.07361408
36 -9.38269013 2.94526267
37 3.16305060 -9.38269013
38 2.14534694 3.16305060
39 4.70227553 2.14534694
40 3.19992338 4.70227553
41 -2.47214708 3.19992338
42 -4.18751061 -2.47214708
43 4.04266522 -4.18751061
44 -7.52120696 4.04266522
45 7.93751641 -7.52120696
46 0.42985412 7.93751641
47 -1.01638445 0.42985412
48 -14.19239580 -1.01638445
49 -4.06061881 -14.19239580
50 4.22671851 -4.06061881
51 4.35450452 4.22671851
52 2.32995287 4.35450452
53 2.38245810 2.32995287
54 6.18564296 2.38245810
55 1.68808608 6.18564296
56 -5.35964328 1.68808608
57 6.92421000 -5.35964328
58 -1.52132875 6.92421000
59 0.52064845 -1.52132875
60 -3.47823485 0.52064845
> 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/7piya1258727391.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8tpu41258727391.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9dnb01258727391.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10yq3l1258727391.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/111qod1258727391.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/122lgq1258727391.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/13hobi1258727391.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/14rdi01258727391.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/15vec21258727392.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/16os5g1258727392.tab")
+ }
>
> system("convert tmp/10gya1258727391.ps tmp/10gya1258727391.png")
> system("convert tmp/26adn1258727391.ps tmp/26adn1258727391.png")
> system("convert tmp/397x91258727391.ps tmp/397x91258727391.png")
> system("convert tmp/4r7ty1258727391.ps tmp/4r7ty1258727391.png")
> system("convert tmp/5dgr21258727391.ps tmp/5dgr21258727391.png")
> system("convert tmp/69l2q1258727391.ps tmp/69l2q1258727391.png")
> system("convert tmp/7piya1258727391.ps tmp/7piya1258727391.png")
> system("convert tmp/8tpu41258727391.ps tmp/8tpu41258727391.png")
> system("convert tmp/9dnb01258727391.ps tmp/9dnb01258727391.png")
> system("convert tmp/10yq3l1258727391.ps tmp/10yq3l1258727391.png")
>
>
> proc.time()
user system elapsed
2.423 1.572 2.807