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(543
+ ,0
+ ,537
+ ,544
+ ,555
+ ,561
+ ,562
+ ,555
+ ,594
+ ,0
+ ,543
+ ,537
+ ,544
+ ,555
+ ,561
+ ,562
+ ,611
+ ,0
+ ,594
+ ,543
+ ,537
+ ,544
+ ,555
+ ,561
+ ,613
+ ,0
+ ,611
+ ,594
+ ,543
+ ,537
+ ,544
+ ,555
+ ,611
+ ,0
+ ,613
+ ,611
+ ,594
+ ,543
+ ,537
+ ,544
+ ,594
+ ,0
+ ,611
+ ,613
+ ,611
+ ,594
+ ,543
+ ,537
+ ,595
+ ,0
+ ,594
+ ,611
+ ,613
+ ,611
+ ,594
+ ,543
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+ ,0
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+ ,611
+ ,613
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+ ,594
+ ,589
+ ,0
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+ ,611
+ ,584
+ ,0
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+ ,0
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+ ,611
+ ,567
+ ,0
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+ ,0
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+ ,589
+ ,628
+ ,0
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+ ,569
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+ ,584
+ ,612
+ ,0
+ ,628
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+ ,621
+ ,569
+ ,567
+ ,573
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+ ,0
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+ ,628
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+ ,0
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+ ,612
+ ,628
+ ,629
+ ,580
+ ,0
+ ,590
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+ ,0
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+ ,0
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+ ,0
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+ ,620
+ ,0
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+ ,573
+ ,573
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+ ,580
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+ ,0
+ ,620
+ ,626
+ ,620
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+ ,566
+ ,0
+ ,588
+ ,620
+ ,626
+ ,620
+ ,573
+ ,573
+ ,557
+ ,0
+ ,566
+ ,588
+ ,620
+ ,626
+ ,620
+ ,573
+ ,561
+ ,0
+ ,557
+ ,566
+ ,588
+ ,620
+ ,626
+ ,620
+ ,549
+ ,0
+ ,561
+ ,557
+ ,566
+ ,588
+ ,620
+ ,626
+ ,532
+ ,0
+ ,549
+ ,561
+ ,557
+ ,566
+ ,588
+ ,620
+ ,526
+ ,0
+ ,532
+ ,549
+ ,561
+ ,557
+ ,566
+ ,588
+ ,511
+ ,0
+ ,526
+ ,532
+ ,549
+ ,561
+ ,557
+ ,566
+ ,499
+ ,0
+ ,511
+ ,526
+ ,532
+ ,549
+ ,561
+ ,557
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+ ,0
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+ ,511
+ ,526
+ ,532
+ ,549
+ ,561
+ ,565
+ ,0
+ ,555
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+ ,511
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+ ,532
+ ,549
+ ,542
+ ,0
+ ,565
+ ,555
+ ,499
+ ,511
+ ,526
+ ,532
+ ,527
+ ,0
+ ,542
+ ,565
+ ,555
+ ,499
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+ ,526
+ ,510
+ ,0
+ ,527
+ ,542
+ ,565
+ ,555
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+ ,0
+ ,510
+ ,527
+ ,542
+ ,565
+ ,555
+ ,499
+ ,517
+ ,0
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+ ,527
+ ,542
+ ,565
+ ,555
+ ,508
+ ,0
+ ,517
+ ,514
+ ,510
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+ ,565
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+ ,0
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+ ,1
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+ ,1
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+ ,510
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+ ,1
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+ ,493
+ ,508
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+ ,1
+ ,478
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+ ,1
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+ ,1
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+ ,1
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+ ,518
+ ,534
+ ,528
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+ ,1
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+ ,506
+ ,518
+ ,534
+ ,528
+ ,478
+ ,528
+ ,1
+ ,516
+ ,502
+ ,506
+ ,518
+ ,534
+ ,528
+ ,533
+ ,1
+ ,528
+ ,516
+ ,502
+ ,506
+ ,518
+ ,534
+ ,536
+ ,1
+ ,533
+ ,528
+ ,516
+ ,502
+ ,506
+ ,518
+ ,537
+ ,1
+ ,536
+ ,533
+ ,528
+ ,516
+ ,502
+ ,506
+ ,524
+ ,1
+ ,537
+ ,536
+ ,533
+ ,528
+ ,516
+ ,502
+ ,536
+ ,1
+ ,524
+ ,537
+ ,536
+ ,533
+ ,528
+ ,516
+ ,587
+ ,1
+ ,536
+ ,524
+ ,537
+ ,536
+ ,533
+ ,528
+ ,597
+ ,1
+ ,587
+ ,536
+ ,524
+ ,537
+ ,536
+ ,533
+ ,581
+ ,1
+ ,597
+ ,587
+ ,536
+ ,524
+ ,537
+ ,536)
+ ,dim=c(8
+ ,64)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4'
+ ,'Y5'
+ ,'Y6')
+ ,1:64))
> y <- array(NA,dim=c(8,64),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4','Y5','Y6'),1:64))
> 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 Y5 Y6 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 543 0 537 544 555 561 562 555 1 0 0 0 0 0 0 0 0 0 0 1
2 594 0 543 537 544 555 561 562 0 1 0 0 0 0 0 0 0 0 0 2
3 611 0 594 543 537 544 555 561 0 0 1 0 0 0 0 0 0 0 0 3
4 613 0 611 594 543 537 544 555 0 0 0 1 0 0 0 0 0 0 0 4
5 611 0 613 611 594 543 537 544 0 0 0 0 1 0 0 0 0 0 0 5
6 594 0 611 613 611 594 543 537 0 0 0 0 0 1 0 0 0 0 0 6
7 595 0 594 611 613 611 594 543 0 0 0 0 0 0 1 0 0 0 0 7
8 591 0 595 594 611 613 611 594 0 0 0 0 0 0 0 1 0 0 0 8
9 589 0 591 595 594 611 613 611 0 0 0 0 0 0 0 0 1 0 0 9
10 584 0 589 591 595 594 611 613 0 0 0 0 0 0 0 0 0 1 0 10
11 573 0 584 589 591 595 594 611 0 0 0 0 0 0 0 0 0 0 1 11
12 567 0 573 584 589 591 595 594 0 0 0 0 0 0 0 0 0 0 0 12
13 569 0 567 573 584 589 591 595 1 0 0 0 0 0 0 0 0 0 0 13
14 621 0 569 567 573 584 589 591 0 1 0 0 0 0 0 0 0 0 0 14
15 629 0 621 569 567 573 584 589 0 0 1 0 0 0 0 0 0 0 0 15
16 628 0 629 621 569 567 573 584 0 0 0 1 0 0 0 0 0 0 0 16
17 612 0 628 629 621 569 567 573 0 0 0 0 1 0 0 0 0 0 0 17
18 595 0 612 628 629 621 569 567 0 0 0 0 0 1 0 0 0 0 0 18
19 597 0 595 612 628 629 621 569 0 0 0 0 0 0 1 0 0 0 0 19
20 593 0 597 595 612 628 629 621 0 0 0 0 0 0 0 1 0 0 0 20
21 590 0 593 597 595 612 628 629 0 0 0 0 0 0 0 0 1 0 0 21
22 580 0 590 593 597 595 612 628 0 0 0 0 0 0 0 0 0 1 0 22
23 574 0 580 590 593 597 595 612 0 0 0 0 0 0 0 0 0 0 1 23
24 573 0 574 580 590 593 597 595 0 0 0 0 0 0 0 0 0 0 0 24
25 573 0 573 574 580 590 593 597 1 0 0 0 0 0 0 0 0 0 0 25
26 620 0 573 573 574 580 590 593 0 1 0 0 0 0 0 0 0 0 0 26
27 626 0 620 573 573 574 580 590 0 0 1 0 0 0 0 0 0 0 0 27
28 620 0 626 620 573 573 574 580 0 0 0 1 0 0 0 0 0 0 0 28
29 588 0 620 626 620 573 573 574 0 0 0 0 1 0 0 0 0 0 0 29
30 566 0 588 620 626 620 573 573 0 0 0 0 0 1 0 0 0 0 0 30
31 557 0 566 588 620 626 620 573 0 0 0 0 0 0 1 0 0 0 0 31
32 561 0 557 566 588 620 626 620 0 0 0 0 0 0 0 1 0 0 0 32
33 549 0 561 557 566 588 620 626 0 0 0 0 0 0 0 0 1 0 0 33
34 532 0 549 561 557 566 588 620 0 0 0 0 0 0 0 0 0 1 0 34
35 526 0 532 549 561 557 566 588 0 0 0 0 0 0 0 0 0 0 1 35
36 511 0 526 532 549 561 557 566 0 0 0 0 0 0 0 0 0 0 0 36
37 499 0 511 526 532 549 561 557 1 0 0 0 0 0 0 0 0 0 0 37
38 555 0 499 511 526 532 549 561 0 1 0 0 0 0 0 0 0 0 0 38
39 565 0 555 499 511 526 532 549 0 0 1 0 0 0 0 0 0 0 0 39
40 542 0 565 555 499 511 526 532 0 0 0 1 0 0 0 0 0 0 0 40
41 527 0 542 565 555 499 511 526 0 0 0 0 1 0 0 0 0 0 0 41
42 510 0 527 542 565 555 499 511 0 0 0 0 0 1 0 0 0 0 0 42
43 514 0 510 527 542 565 555 499 0 0 0 0 0 0 1 0 0 0 0 43
44 517 0 514 510 527 542 565 555 0 0 0 0 0 0 0 1 0 0 0 44
45 508 0 517 514 510 527 542 565 0 0 0 0 0 0 0 0 1 0 0 45
46 493 0 508 517 514 510 527 542 0 0 0 0 0 0 0 0 0 1 0 46
47 490 1 493 508 517 514 510 527 0 0 0 0 0 0 0 0 0 0 1 47
48 469 1 490 493 508 517 514 510 0 0 0 0 0 0 0 0 0 0 0 48
49 478 1 469 490 493 508 517 514 1 0 0 0 0 0 0 0 0 0 0 49
50 528 1 478 469 490 493 508 517 0 1 0 0 0 0 0 0 0 0 0 50
51 534 1 528 478 469 490 493 508 0 0 1 0 0 0 0 0 0 0 0 51
52 518 1 534 528 478 469 490 493 0 0 0 1 0 0 0 0 0 0 0 52
53 506 1 518 534 528 478 469 490 0 0 0 0 1 0 0 0 0 0 0 53
54 502 1 506 518 534 528 478 469 0 0 0 0 0 1 0 0 0 0 0 54
55 516 1 502 506 518 534 528 478 0 0 0 0 0 0 1 0 0 0 0 55
56 528 1 516 502 506 518 534 528 0 0 0 0 0 0 0 1 0 0 0 56
57 533 1 528 516 502 506 518 534 0 0 0 0 0 0 0 0 1 0 0 57
58 536 1 533 528 516 502 506 518 0 0 0 0 0 0 0 0 0 1 0 58
59 537 1 536 533 528 516 502 506 0 0 0 0 0 0 0 0 0 0 1 59
60 524 1 537 536 533 528 516 502 0 0 0 0 0 0 0 0 0 0 0 60
61 536 1 524 537 536 533 528 516 1 0 0 0 0 0 0 0 0 0 0 61
62 587 1 536 524 537 536 533 528 0 1 0 0 0 0 0 0 0 0 0 62
63 597 1 587 536 524 537 536 533 0 0 1 0 0 0 0 0 0 0 0 63
64 581 1 597 587 536 524 537 536 0 0 0 1 0 0 0 0 0 0 0 64
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
2.879e+01 6.155e+00 1.040e+00 5.291e-02 1.733e-04 -3.125e-02
Y5 Y6 M1 M2 M3 M4
-1.984e-01 7.572e-02 1.436e+01 6.212e+01 1.688e+01 -6.391e+00
M5 M6 M7 M8 M9 M10
-1.345e+01 -9.609e+00 2.021e+01 1.865e+01 9.298e+00 2.083e+00
M11 t
3.618e+00 -2.036e-01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-12.5650 -4.4988 -0.1568 3.9528 13.1096
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.879e+01 2.685e+01 1.072 0.28941
X 6.155e+00 4.210e+00 1.462 0.15088
Y1 1.040e+00 1.489e-01 6.988 1.19e-08 ***
Y2 5.291e-02 2.135e-01 0.248 0.80545
Y3 1.733e-04 2.115e-01 0.001 0.99935
Y4 -3.125e-02 2.139e-01 -0.146 0.88451
Y5 -1.984e-01 2.185e-01 -0.908 0.36869
Y6 7.572e-02 1.570e-01 0.482 0.63209
M1 1.436e+01 4.401e+00 3.262 0.00214 **
M2 6.212e+01 4.713e+00 13.182 < 2e-16 ***
M3 1.688e+01 9.936e+00 1.699 0.09634 .
M4 -6.391e+00 1.023e+01 -0.625 0.53526
M5 -1.345e+01 9.742e+00 -1.381 0.17428
M6 -9.609e+00 9.057e+00 -1.061 0.29451
M7 2.021e+01 9.165e+00 2.205 0.03272 *
M8 1.865e+01 5.357e+00 3.480 0.00114 **
M9 9.298e+00 6.194e+00 1.501 0.14045
M10 2.083e+00 6.226e+00 0.335 0.73953
M11 3.618e+00 5.390e+00 0.671 0.50560
t -2.036e-01 9.105e-02 -2.236 0.03049 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.889 on 44 degrees of freedom
Multiple R-squared: 0.9811, Adjusted R-squared: 0.9729
F-statistic: 120.1 on 19 and 44 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,] 0.30075819 0.601516382 0.699241809
[2,] 0.25895955 0.517919101 0.741040449
[3,] 0.17751461 0.355029225 0.822485387
[4,] 0.09728540 0.194570805 0.902714597
[5,] 0.05114262 0.102285250 0.948857375
[6,] 0.09285437 0.185708732 0.907145634
[7,] 0.42919919 0.858398374 0.570800813
[8,] 0.33038120 0.660762397 0.669618801
[9,] 0.47484953 0.949699060 0.525150470
[10,] 0.39670589 0.793411777 0.603294111
[11,] 0.30632625 0.612652499 0.693673750
[12,] 0.38270239 0.765404779 0.617297610
[13,] 0.37330416 0.746608321 0.626695840
[14,] 0.42338153 0.846763064 0.576618468
[15,] 0.77670658 0.446586849 0.223293424
[16,] 0.98554603 0.028907941 0.014453970
[17,] 0.99515206 0.009695888 0.004847944
[18,] 0.98536973 0.029260536 0.014630268
[19,] 0.95405057 0.091898855 0.045949428
> postscript(file="/var/www/html/rcomp/tmp/1rhdx1258730363.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/295b61258730363.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3dwd41258730363.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4t7eb1258730363.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5s5qp1258730363.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 = 64
Frequency = 1
1 2 3 4 5 6
-0.44244181 -3.78855771 3.82147406 6.96812724 8.87618999 -6.47785191
7 8 9 10 11 12
-7.10506612 -9.90571062 0.80463754 4.43529633 -5.77798413 5.11196958
13 14 15 16 17 18
-1.14770098 1.28021612 -0.66443520 8.74818421 0.32658719 -1.14117128
19 20 21 22 23 24
0.19296166 -5.60078068 3.70541217 0.82550530 1.95795771 13.10958428
25 26 27 28 29 30
-0.72222385 -1.83380149 -1.23214526 7.05290770 -11.50953689 -1.99935164
31 32 33 34 35 36
-6.51943532 7.22292739 -1.55097304 -5.44193346 3.32311817 -0.70731734
37 38 39 40 41 42
-9.83474003 8.66771641 3.83664519 -9.42104005 3.33549443 0.01978278
43 44 45 46 47 48
5.22108159 3.75305734 -4.81402816 -4.95860738 -1.47691183 -12.56499734
49 50 51 52 53 54
4.30122281 -3.99209918 -7.42808427 -8.95443795 -1.02873472 9.59859205
55 56 57 58 59 60
8.21045820 4.53050657 1.85495149 5.13973922 1.97382008 -4.94923917
61 62 63 64
7.84588387 -0.33347414 1.66654547 -4.39374115
> postscript(file="/var/www/html/rcomp/tmp/635cr1258730363.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 = 64
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.44244181 NA
1 -3.78855771 -0.44244181
2 3.82147406 -3.78855771
3 6.96812724 3.82147406
4 8.87618999 6.96812724
5 -6.47785191 8.87618999
6 -7.10506612 -6.47785191
7 -9.90571062 -7.10506612
8 0.80463754 -9.90571062
9 4.43529633 0.80463754
10 -5.77798413 4.43529633
11 5.11196958 -5.77798413
12 -1.14770098 5.11196958
13 1.28021612 -1.14770098
14 -0.66443520 1.28021612
15 8.74818421 -0.66443520
16 0.32658719 8.74818421
17 -1.14117128 0.32658719
18 0.19296166 -1.14117128
19 -5.60078068 0.19296166
20 3.70541217 -5.60078068
21 0.82550530 3.70541217
22 1.95795771 0.82550530
23 13.10958428 1.95795771
24 -0.72222385 13.10958428
25 -1.83380149 -0.72222385
26 -1.23214526 -1.83380149
27 7.05290770 -1.23214526
28 -11.50953689 7.05290770
29 -1.99935164 -11.50953689
30 -6.51943532 -1.99935164
31 7.22292739 -6.51943532
32 -1.55097304 7.22292739
33 -5.44193346 -1.55097304
34 3.32311817 -5.44193346
35 -0.70731734 3.32311817
36 -9.83474003 -0.70731734
37 8.66771641 -9.83474003
38 3.83664519 8.66771641
39 -9.42104005 3.83664519
40 3.33549443 -9.42104005
41 0.01978278 3.33549443
42 5.22108159 0.01978278
43 3.75305734 5.22108159
44 -4.81402816 3.75305734
45 -4.95860738 -4.81402816
46 -1.47691183 -4.95860738
47 -12.56499734 -1.47691183
48 4.30122281 -12.56499734
49 -3.99209918 4.30122281
50 -7.42808427 -3.99209918
51 -8.95443795 -7.42808427
52 -1.02873472 -8.95443795
53 9.59859205 -1.02873472
54 8.21045820 9.59859205
55 4.53050657 8.21045820
56 1.85495149 4.53050657
57 5.13973922 1.85495149
58 1.97382008 5.13973922
59 -4.94923917 1.97382008
60 7.84588387 -4.94923917
61 -0.33347414 7.84588387
62 1.66654547 -0.33347414
63 -4.39374115 1.66654547
64 NA -4.39374115
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.78855771 -0.44244181
[2,] 3.82147406 -3.78855771
[3,] 6.96812724 3.82147406
[4,] 8.87618999 6.96812724
[5,] -6.47785191 8.87618999
[6,] -7.10506612 -6.47785191
[7,] -9.90571062 -7.10506612
[8,] 0.80463754 -9.90571062
[9,] 4.43529633 0.80463754
[10,] -5.77798413 4.43529633
[11,] 5.11196958 -5.77798413
[12,] -1.14770098 5.11196958
[13,] 1.28021612 -1.14770098
[14,] -0.66443520 1.28021612
[15,] 8.74818421 -0.66443520
[16,] 0.32658719 8.74818421
[17,] -1.14117128 0.32658719
[18,] 0.19296166 -1.14117128
[19,] -5.60078068 0.19296166
[20,] 3.70541217 -5.60078068
[21,] 0.82550530 3.70541217
[22,] 1.95795771 0.82550530
[23,] 13.10958428 1.95795771
[24,] -0.72222385 13.10958428
[25,] -1.83380149 -0.72222385
[26,] -1.23214526 -1.83380149
[27,] 7.05290770 -1.23214526
[28,] -11.50953689 7.05290770
[29,] -1.99935164 -11.50953689
[30,] -6.51943532 -1.99935164
[31,] 7.22292739 -6.51943532
[32,] -1.55097304 7.22292739
[33,] -5.44193346 -1.55097304
[34,] 3.32311817 -5.44193346
[35,] -0.70731734 3.32311817
[36,] -9.83474003 -0.70731734
[37,] 8.66771641 -9.83474003
[38,] 3.83664519 8.66771641
[39,] -9.42104005 3.83664519
[40,] 3.33549443 -9.42104005
[41,] 0.01978278 3.33549443
[42,] 5.22108159 0.01978278
[43,] 3.75305734 5.22108159
[44,] -4.81402816 3.75305734
[45,] -4.95860738 -4.81402816
[46,] -1.47691183 -4.95860738
[47,] -12.56499734 -1.47691183
[48,] 4.30122281 -12.56499734
[49,] -3.99209918 4.30122281
[50,] -7.42808427 -3.99209918
[51,] -8.95443795 -7.42808427
[52,] -1.02873472 -8.95443795
[53,] 9.59859205 -1.02873472
[54,] 8.21045820 9.59859205
[55,] 4.53050657 8.21045820
[56,] 1.85495149 4.53050657
[57,] 5.13973922 1.85495149
[58,] 1.97382008 5.13973922
[59,] -4.94923917 1.97382008
[60,] 7.84588387 -4.94923917
[61,] -0.33347414 7.84588387
[62,] 1.66654547 -0.33347414
[63,] -4.39374115 1.66654547
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.78855771 -0.44244181
2 3.82147406 -3.78855771
3 6.96812724 3.82147406
4 8.87618999 6.96812724
5 -6.47785191 8.87618999
6 -7.10506612 -6.47785191
7 -9.90571062 -7.10506612
8 0.80463754 -9.90571062
9 4.43529633 0.80463754
10 -5.77798413 4.43529633
11 5.11196958 -5.77798413
12 -1.14770098 5.11196958
13 1.28021612 -1.14770098
14 -0.66443520 1.28021612
15 8.74818421 -0.66443520
16 0.32658719 8.74818421
17 -1.14117128 0.32658719
18 0.19296166 -1.14117128
19 -5.60078068 0.19296166
20 3.70541217 -5.60078068
21 0.82550530 3.70541217
22 1.95795771 0.82550530
23 13.10958428 1.95795771
24 -0.72222385 13.10958428
25 -1.83380149 -0.72222385
26 -1.23214526 -1.83380149
27 7.05290770 -1.23214526
28 -11.50953689 7.05290770
29 -1.99935164 -11.50953689
30 -6.51943532 -1.99935164
31 7.22292739 -6.51943532
32 -1.55097304 7.22292739
33 -5.44193346 -1.55097304
34 3.32311817 -5.44193346
35 -0.70731734 3.32311817
36 -9.83474003 -0.70731734
37 8.66771641 -9.83474003
38 3.83664519 8.66771641
39 -9.42104005 3.83664519
40 3.33549443 -9.42104005
41 0.01978278 3.33549443
42 5.22108159 0.01978278
43 3.75305734 5.22108159
44 -4.81402816 3.75305734
45 -4.95860738 -4.81402816
46 -1.47691183 -4.95860738
47 -12.56499734 -1.47691183
48 4.30122281 -12.56499734
49 -3.99209918 4.30122281
50 -7.42808427 -3.99209918
51 -8.95443795 -7.42808427
52 -1.02873472 -8.95443795
53 9.59859205 -1.02873472
54 8.21045820 9.59859205
55 4.53050657 8.21045820
56 1.85495149 4.53050657
57 5.13973922 1.85495149
58 1.97382008 5.13973922
59 -4.94923917 1.97382008
60 7.84588387 -4.94923917
61 -0.33347414 7.84588387
62 1.66654547 -0.33347414
63 -4.39374115 1.66654547
> 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/77yk51258730363.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8swka1258730363.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9r6lx1258730363.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10p6gj1258730363.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ujkx1258730363.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/12if3r1258730363.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/13jp741258730363.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/14uomg1258730363.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/152aek1258730363.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/16c9ag1258730363.tab")
+ }
>
> system("convert tmp/1rhdx1258730363.ps tmp/1rhdx1258730363.png")
> system("convert tmp/295b61258730363.ps tmp/295b61258730363.png")
> system("convert tmp/3dwd41258730363.ps tmp/3dwd41258730363.png")
> system("convert tmp/4t7eb1258730363.ps tmp/4t7eb1258730363.png")
> system("convert tmp/5s5qp1258730363.ps tmp/5s5qp1258730363.png")
> system("convert tmp/635cr1258730363.ps tmp/635cr1258730363.png")
> system("convert tmp/77yk51258730363.ps tmp/77yk51258730363.png")
> system("convert tmp/8swka1258730363.ps tmp/8swka1258730363.png")
> system("convert tmp/9r6lx1258730363.ps tmp/9r6lx1258730363.png")
> system("convert tmp/10p6gj1258730363.ps tmp/10p6gj1258730363.png")
>
>
> proc.time()
user system elapsed
2.424 1.567 2.801