R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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(349
+ ,0
+ ,336
+ ,349
+ ,331
+ ,336
+ ,327
+ ,331
+ ,323
+ ,327
+ ,322
+ ,323
+ ,385
+ ,322
+ ,405
+ ,385
+ ,412
+ ,405
+ ,411
+ ,412
+ ,410
+ ,411
+ ,415
+ ,410
+ ,414
+ ,415
+ ,411
+ ,414
+ ,408
+ ,411
+ ,410
+ ,408
+ ,411
+ ,410
+ ,416
+ ,411
+ ,479
+ ,416
+ ,498
+ ,479
+ ,502
+ ,498
+ ,498
+ ,502
+ ,499
+ ,498
+ ,506
+ ,499
+ ,510
+ ,506
+ ,509
+ ,510
+ ,502
+ ,509
+ ,495
+ ,502
+ ,490
+ ,495
+ ,490
+ ,490
+ ,553
+ ,490
+ ,570
+ ,553
+ ,573
+ ,570
+ ,572
+ ,573
+ ,575
+ ,572
+ ,580
+ ,575
+ ,580
+ ,580
+ ,574
+ ,580
+ ,563
+ ,574
+ ,556
+ ,563
+ ,546
+ ,556
+ ,545
+ ,546
+ ,605
+ ,545
+ ,628
+ ,605
+ ,631
+ ,628
+ ,626
+ ,631
+ ,614
+ ,626
+ ,606
+ ,614
+ ,602
+ ,606
+ ,589
+ ,602
+ ,574
+ ,589
+ ,558
+ ,574
+ ,552
+ ,558
+ ,546
+ ,552
+ ,607
+ ,546
+ ,636
+ ,607
+ ,631
+ ,636
+ ,623
+ ,631
+ ,618
+ ,623
+ ,605
+ ,618
+ ,619
+ ,605
+ ,596
+ ,619
+ ,570
+ ,596
+ ,546
+ ,570
+ ,528
+ ,546
+ ,506
+ ,528
+ ,555
+ ,506
+ ,568
+ ,555
+ ,564
+ ,568
+ ,553
+ ,564
+ ,541
+ ,553
+ ,542
+ ,541
+ ,540
+ ,542
+ ,521
+ ,540
+ ,505
+ ,521
+ ,491
+ ,505
+ ,482
+ ,491
+ ,478
+ ,482
+ ,523
+ ,478
+ ,531
+ ,523
+ ,532
+ ,531
+ ,540
+ ,532
+ ,525
+ ,540
+ ,533
+ ,525
+ ,531
+ ,533
+ ,508
+ ,531
+ ,495
+ ,508
+ ,482
+ ,495
+ ,470
+ ,482
+ ,466
+ ,470
+ ,515
+ ,466
+ ,518
+ ,515
+ ,516
+ ,518
+ ,511
+ ,516
+ ,500
+ ,511
+ ,498
+ ,500
+ ,494
+ ,498
+ ,476
+ ,494
+ ,458
+ ,476
+ ,443
+ ,458
+ ,430
+ ,443
+ ,424
+ ,430
+ ,476
+ ,424
+ ,481
+ ,476
+ ,470
+ ,481
+ ,460
+ ,470
+ ,451
+ ,460
+ ,450
+ ,451
+ ,444
+ ,450
+ ,429
+ ,444
+ ,421
+ ,429
+ ,400
+ ,421
+ ,389
+ ,400
+ ,384
+ ,389
+ ,432
+ ,384
+ ,446
+ ,432
+ ,431
+ ,446
+ ,423
+ ,431
+ ,416
+ ,423
+ ,416
+ ,416
+ ,413
+ ,416
+ ,399
+ ,413
+ ,386
+ ,399
+ ,374
+ ,386
+ ,365
+ ,374
+ ,365
+ ,365
+ ,418
+ ,365
+ ,428
+ ,418
+ ,424
+ ,428
+ ,421
+ ,424
+ ,417
+ ,421
+ ,423
+ ,417
+ ,423
+ ,423
+ ,419
+ ,423
+ ,406
+ ,419
+ ,398
+ ,406
+ ,390
+ ,398
+ ,391
+ ,390
+ ,444
+ ,391
+ ,460
+ ,444
+ ,455
+ ,460
+ ,456
+ ,455
+ ,452
+ ,456
+ ,459
+ ,452
+ ,461
+ ,459
+ ,451
+ ,461
+ ,443
+ ,451
+ ,439
+ ,443
+ ,430
+ ,439
+ ,436
+ ,430
+ ,488
+ ,436
+ ,506
+ ,488
+ ,502
+ ,506
+ ,501
+ ,502
+ ,501
+ ,501
+ ,515
+ ,501
+ ,521
+ ,515
+ ,520
+ ,521
+ ,512
+ ,520
+ ,509
+ ,512
+ ,505
+ ,509
+ ,511
+ ,505
+ ,570
+ ,511
+ ,592
+ ,570
+ ,594
+ ,592
+ ,586
+ ,594
+ ,586
+ ,586
+ ,592
+ ,586
+ ,594
+ ,592
+ ,594
+ ,594
+ ,586
+ ,594
+ ,586
+ ,586
+ ,572
+ ,586
+ ,572
+ ,572
+ ,563
+ ,572
+ ,563
+ ,563
+ ,555
+ ,563
+ ,555
+ ,555
+ ,554
+ ,555
+ ,554
+ ,554
+ ,601
+ ,554
+ ,601
+ ,601
+ ,622
+ ,601
+ ,622
+ ,622
+ ,617
+ ,622
+ ,617
+ ,617
+ ,606
+ ,617
+ ,606
+ ,606
+ ,595
+ ,606
+ ,595
+ ,595
+ ,599
+ ,595
+ ,599
+ ,599
+ ,600
+ ,599
+ ,600
+ ,600
+ ,592
+ ,600
+ ,592
+ ,592
+ ,575
+ ,592
+ ,575
+ ,575
+ ,567
+ ,575
+ ,567
+ ,567
+ ,555
+ ,567
+ ,555
+ ,555
+ ,555
+ ,555
+ ,555
+ ,555
+ ,608
+ ,555
+ ,608
+ ,608
+ ,631
+ ,608
+ ,631
+ ,631
+ ,629
+ ,631
+ ,629
+ ,629
+ ,624
+ ,629
+ ,624
+ ,624
+ ,610
+ ,624
+ ,610
+ ,610
+ ,616
+ ,610
+ ,616
+ ,616
+ ,621
+ ,616
+ ,621
+ ,621
+ ,604
+ ,621
+ ,604
+ ,604
+ ,584
+ ,604
+ ,584
+ ,584
+ ,574
+ ,584
+ ,574
+ ,574
+ ,555
+ ,574
+ ,555
+ ,555
+ ,545
+ ,555
+ ,545
+ ,545
+ ,599
+ ,545
+ ,599
+ ,599
+ ,620
+ ,599
+ ,620
+ ,620
+ ,608
+ ,620
+ ,608
+ ,608
+ ,590
+ ,608
+ ,590
+ ,590
+ ,579
+ ,590
+ ,579
+ ,579
+ ,580
+ ,579
+ ,580
+ ,580
+ ,579
+ ,580
+ ,579
+ ,579
+ ,572
+ ,579
+ ,572
+ ,572
+ ,560
+ ,572
+ ,560
+ ,560
+ ,551
+ ,560
+ ,551
+ ,551
+ ,537
+ ,551
+ ,537
+ ,537
+ ,541
+ ,537
+ ,541
+ ,541
+ ,588
+ ,541
+ ,588
+ ,588
+ ,607
+ ,588
+ ,607
+ ,607
+ ,599
+ ,607
+ ,599
+ ,599
+ ,578
+ ,599
+ ,578
+ ,578
+ ,563
+ ,578
+ ,563
+ ,563
+ ,566
+ ,563
+ ,566
+ ,566
+ ,561
+ ,566
+ ,561
+ ,561
+ ,554
+ ,561
+ ,554
+ ,554
+ ,540
+ ,554
+ ,540
+ ,540
+ ,526
+ ,540
+ ,526
+ ,526
+ ,512
+ ,526
+ ,512
+ ,512
+ ,505
+ ,512
+ ,505
+ ,505
+ ,554
+ ,505
+ ,554
+ ,554
+ ,584
+ ,554
+ ,584
+ ,584
+ ,569
+ ,584
+ ,569
+ ,569
+ ,540
+ ,569
+ ,540
+ ,540
+ ,522
+ ,540
+ ,522
+ ,522
+ ,526
+ ,522
+ ,526
+ ,526
+ ,527
+ ,526
+ ,527
+ ,527
+ ,516
+ ,527
+ ,516
+ ,516
+ ,503
+ ,516
+ ,503
+ ,503
+ ,489
+ ,503
+ ,489
+ ,489
+ ,479
+ ,489
+ ,479
+ ,479
+ ,475
+ ,479
+ ,475
+ ,475
+ ,524
+ ,475
+ ,524
+ ,524
+ ,552
+ ,524
+ ,552
+ ,552
+ ,532
+ ,552
+ ,532
+ ,532
+ ,511
+ ,532
+ ,511
+ ,511
+ ,492
+ ,511
+ ,492
+ ,492
+ ,492
+ ,492
+ ,492
+ ,492
+ ,493
+ ,492
+ ,493
+ ,493
+ ,481
+ ,493
+ ,481
+ ,481
+ ,462
+ ,481
+ ,462
+ ,462
+ ,457
+ ,462
+ ,457
+ ,457
+ ,442
+ ,457
+ ,442
+ ,442
+ ,439
+ ,442
+ ,439
+ ,439
+ ,488
+ ,439
+ ,488
+ ,488
+ ,521
+ ,488
+ ,521
+ ,521
+ ,501
+ ,521
+ ,501
+ ,501
+ ,485
+ ,501
+ ,485
+ ,485
+ ,464
+ ,485
+ ,464
+ ,464
+ ,460
+ ,464
+ ,460
+ ,460
+ ,467
+ ,460
+ ,467
+ ,467
+ ,460
+ ,467
+ ,460
+ ,460
+ ,448
+ ,460
+ ,448
+ ,448
+ ,443
+ ,448
+ ,443
+ ,443
+ ,436
+ ,443
+ ,436
+ ,436
+ ,431
+ ,436
+ ,431
+ ,431
+ ,484
+ ,431
+ ,484
+ ,484
+ ,510
+ ,484
+ ,510
+ ,510
+ ,513
+ ,510
+ ,513
+ ,513
+ ,503
+ ,513
+ ,503
+ ,503
+ ,471
+ ,503
+ ,471
+ ,471
+ ,471
+ ,471
+ ,471
+ ,471
+ ,476
+ ,471
+ ,476
+ ,476
+ ,475
+ ,476
+ ,475
+ ,475
+ ,470
+ ,475
+ ,470
+ ,470
+ ,461
+ ,470
+ ,461
+ ,461
+ ,455
+ ,461
+ ,455
+ ,455
+ ,456
+ ,455
+ ,456
+ ,456
+ ,517
+ ,456
+ ,517
+ ,517
+ ,525
+ ,517
+ ,525
+ ,525
+ ,523
+ ,525
+ ,523
+ ,523
+ ,519
+ ,523
+ ,519
+ ,519
+ ,509
+ ,519
+ ,509
+ ,509
+ ,512
+ ,509
+ ,512
+ ,512
+ ,519
+ ,512
+ ,519
+ ,519
+ ,517
+ ,519
+ ,517
+ ,517
+ ,510
+ ,517
+ ,510
+ ,510
+ ,509
+ ,510
+ ,509
+ ,509
+ ,501
+ ,509
+ ,501
+ ,501
+ ,507
+ ,501
+ ,507
+ ,507
+ ,569
+ ,507
+ ,569
+ ,569
+ ,580
+ ,569
+ ,580
+ ,580
+ ,578
+ ,580
+ ,578
+ ,578
+ ,565
+ ,578
+ ,565
+ ,565
+ ,547
+ ,565
+ ,547
+ ,547
+ ,555
+ ,547
+ ,555
+ ,555
+ ,562
+ ,555
+ ,561
+ ,562
+ ,555
+ ,561
+ ,544
+ ,555
+ ,537
+ ,544
+ ,543
+ ,537
+ ,594
+ ,543
+ ,611
+ ,594
+ ,613
+ ,611
+ ,611
+ ,613
+ ,594
+ ,611
+ ,595
+ ,594
+ ,591
+ ,595
+ ,589
+ ,591
+ ,584
+ ,589
+ ,573
+ ,584
+ ,567
+ ,573
+ ,569
+ ,567
+ ,621
+ ,569
+ ,629
+ ,621
+ ,628
+ ,629
+ ,612
+ ,628
+ ,595
+ ,612
+ ,597
+ ,595
+ ,593
+ ,597
+ ,590
+ ,593
+ ,580
+ ,590
+ ,574
+ ,580
+ ,573
+ ,574
+ ,573
+ ,573
+ ,620
+ ,573
+ ,626
+ ,620
+ ,620
+ ,626
+ ,588
+ ,620
+ ,566
+ ,588
+ ,557
+ ,566
+ ,561
+ ,557
+ ,549
+ ,561
+ ,532
+ ,549
+ ,526
+ ,532
+ ,511
+ ,526
+ ,499
+ ,511
+ ,555
+ ,499
+ ,565
+ ,555
+ ,542
+ ,565
+ ,527
+ ,542
+ ,510
+ ,527
+ ,514
+ ,510
+ ,517
+ ,514
+ ,508
+ ,517
+ ,493
+ ,508
+ ,490
+ ,493
+ ,469
+ ,490
+ ,478
+ ,469
+ ,528
+ ,478
+ ,534
+ ,528
+ ,518
+ ,534
+ ,506
+ ,518
+ ,502
+ ,506
+ ,516
+ ,502
+ ,528
+ ,516
+ ,533
+ ,528
+ ,536
+ ,533
+ ,537
+ ,536
+ ,524
+ ,537
+ ,536
+ ,524
+ ,587
+ ,536
+ ,597
+ ,587
+ ,581
+ ,597
+ ,564
+ ,581
+ ,558
+ ,564
+ ,575
+ ,558
+ ,580
+ ,575
+ ,575
+ ,580
+ ,563
+ ,575
+ ,552
+ ,563
+ ,537
+ ,552
+ ,545
+ ,537
+ ,601
+ ,545
+ ,604
+ ,601
+ ,586
+ ,604
+ ,564
+ ,586
+ ,549
+ ,564
+ ,551
+ ,549)
+ ,dim=c(2
+ ,492)
+ ,dimnames=list(c('werkloosheid'
+ ,'y1')
+ ,1:492))
> y <- array(NA,dim=c(2,492),dimnames=list(c('werkloosheid','y1'),1:492))
> 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'
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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
werkloosheid y1 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 349 0 1 0 0 0 0 0 0 0 0 0 0
2 336 349 0 1 0 0 0 0 0 0 0 0 0
3 331 336 0 0 1 0 0 0 0 0 0 0 0
4 327 331 0 0 0 1 0 0 0 0 0 0 0
5 323 327 0 0 0 0 1 0 0 0 0 0 0
6 322 323 0 0 0 0 0 1 0 0 0 0 0
7 385 322 0 0 0 0 0 0 1 0 0 0 0
8 405 385 0 0 0 0 0 0 0 1 0 0 0
9 412 405 0 0 0 0 0 0 0 0 1 0 0
10 411 412 0 0 0 0 0 0 0 0 0 1 0
11 410 411 0 0 0 0 0 0 0 0 0 0 1
12 415 410 0 0 0 0 0 0 0 0 0 0 0
13 414 415 1 0 0 0 0 0 0 0 0 0 0
14 411 414 0 1 0 0 0 0 0 0 0 0 0
15 408 411 0 0 1 0 0 0 0 0 0 0 0
16 410 408 0 0 0 1 0 0 0 0 0 0 0
17 411 410 0 0 0 0 1 0 0 0 0 0 0
18 416 411 0 0 0 0 0 1 0 0 0 0 0
19 479 416 0 0 0 0 0 0 1 0 0 0 0
20 498 479 0 0 0 0 0 0 0 1 0 0 0
21 502 498 0 0 0 0 0 0 0 0 1 0 0
22 498 502 0 0 0 0 0 0 0 0 0 1 0
23 499 498 0 0 0 0 0 0 0 0 0 0 1
24 506 499 0 0 0 0 0 0 0 0 0 0 0
25 510 506 1 0 0 0 0 0 0 0 0 0 0
26 509 510 0 1 0 0 0 0 0 0 0 0 0
27 502 509 0 0 1 0 0 0 0 0 0 0 0
28 495 502 0 0 0 1 0 0 0 0 0 0 0
29 490 495 0 0 0 0 1 0 0 0 0 0 0
30 490 490 0 0 0 0 0 1 0 0 0 0 0
31 553 490 0 0 0 0 0 0 1 0 0 0 0
32 570 553 0 0 0 0 0 0 0 1 0 0 0
33 573 570 0 0 0 0 0 0 0 0 1 0 0
34 572 573 0 0 0 0 0 0 0 0 0 1 0
35 575 572 0 0 0 0 0 0 0 0 0 0 1
36 580 575 0 0 0 0 0 0 0 0 0 0 0
37 580 580 1 0 0 0 0 0 0 0 0 0 0
38 574 580 0 1 0 0 0 0 0 0 0 0 0
39 563 574 0 0 1 0 0 0 0 0 0 0 0
40 556 563 0 0 0 1 0 0 0 0 0 0 0
41 546 556 0 0 0 0 1 0 0 0 0 0 0
42 545 546 0 0 0 0 0 1 0 0 0 0 0
43 605 545 0 0 0 0 0 0 1 0 0 0 0
44 628 605 0 0 0 0 0 0 0 1 0 0 0
45 631 628 0 0 0 0 0 0 0 0 1 0 0
46 626 631 0 0 0 0 0 0 0 0 0 1 0
47 614 626 0 0 0 0 0 0 0 0 0 0 1
48 606 614 0 0 0 0 0 0 0 0 0 0 0
49 602 606 1 0 0 0 0 0 0 0 0 0 0
50 589 602 0 1 0 0 0 0 0 0 0 0 0
51 574 589 0 0 1 0 0 0 0 0 0 0 0
52 558 574 0 0 0 1 0 0 0 0 0 0 0
53 552 558 0 0 0 0 1 0 0 0 0 0 0
54 546 552 0 0 0 0 0 1 0 0 0 0 0
55 607 546 0 0 0 0 0 0 1 0 0 0 0
56 636 607 0 0 0 0 0 0 0 1 0 0 0
57 631 636 0 0 0 0 0 0 0 0 1 0 0
58 623 631 0 0 0 0 0 0 0 0 0 1 0
59 618 623 0 0 0 0 0 0 0 0 0 0 1
60 605 618 0 0 0 0 0 0 0 0 0 0 0
61 619 605 1 0 0 0 0 0 0 0 0 0 0
62 596 619 0 1 0 0 0 0 0 0 0 0 0
63 570 596 0 0 1 0 0 0 0 0 0 0 0
64 546 570 0 0 0 1 0 0 0 0 0 0 0
65 528 546 0 0 0 0 1 0 0 0 0 0 0
66 506 528 0 0 0 0 0 1 0 0 0 0 0
67 555 506 0 0 0 0 0 0 1 0 0 0 0
68 568 555 0 0 0 0 0 0 0 1 0 0 0
69 564 568 0 0 0 0 0 0 0 0 1 0 0
70 553 564 0 0 0 0 0 0 0 0 0 1 0
71 541 553 0 0 0 0 0 0 0 0 0 0 1
72 542 541 0 0 0 0 0 0 0 0 0 0 0
73 540 542 1 0 0 0 0 0 0 0 0 0 0
74 521 540 0 1 0 0 0 0 0 0 0 0 0
75 505 521 0 0 1 0 0 0 0 0 0 0 0
76 491 505 0 0 0 1 0 0 0 0 0 0 0
77 482 491 0 0 0 0 1 0 0 0 0 0 0
78 478 482 0 0 0 0 0 1 0 0 0 0 0
79 523 478 0 0 0 0 0 0 1 0 0 0 0
80 531 523 0 0 0 0 0 0 0 1 0 0 0
81 532 531 0 0 0 0 0 0 0 0 1 0 0
82 540 532 0 0 0 0 0 0 0 0 0 1 0
83 525 540 0 0 0 0 0 0 0 0 0 0 1
84 533 525 0 0 0 0 0 0 0 0 0 0 0
85 531 533 1 0 0 0 0 0 0 0 0 0 0
86 508 531 0 1 0 0 0 0 0 0 0 0 0
87 495 508 0 0 1 0 0 0 0 0 0 0 0
88 482 495 0 0 0 1 0 0 0 0 0 0 0
89 470 482 0 0 0 0 1 0 0 0 0 0 0
90 466 470 0 0 0 0 0 1 0 0 0 0 0
91 515 466 0 0 0 0 0 0 1 0 0 0 0
92 518 515 0 0 0 0 0 0 0 1 0 0 0
93 516 518 0 0 0 0 0 0 0 0 1 0 0
94 511 516 0 0 0 0 0 0 0 0 0 1 0
95 500 511 0 0 0 0 0 0 0 0 0 0 1
96 498 500 0 0 0 0 0 0 0 0 0 0 0
97 494 498 1 0 0 0 0 0 0 0 0 0 0
98 476 494 0 1 0 0 0 0 0 0 0 0 0
99 458 476 0 0 1 0 0 0 0 0 0 0 0
100 443 458 0 0 0 1 0 0 0 0 0 0 0
101 430 443 0 0 0 0 1 0 0 0 0 0 0
102 424 430 0 0 0 0 0 1 0 0 0 0 0
103 476 424 0 0 0 0 0 0 1 0 0 0 0
104 481 476 0 0 0 0 0 0 0 1 0 0 0
105 470 481 0 0 0 0 0 0 0 0 1 0 0
106 460 470 0 0 0 0 0 0 0 0 0 1 0
107 451 460 0 0 0 0 0 0 0 0 0 0 1
108 450 451 0 0 0 0 0 0 0 0 0 0 0
109 444 450 1 0 0 0 0 0 0 0 0 0 0
110 429 444 0 1 0 0 0 0 0 0 0 0 0
111 421 429 0 0 1 0 0 0 0 0 0 0 0
112 400 421 0 0 0 1 0 0 0 0 0 0 0
113 389 400 0 0 0 0 1 0 0 0 0 0 0
114 384 389 0 0 0 0 0 1 0 0 0 0 0
115 432 384 0 0 0 0 0 0 1 0 0 0 0
116 446 432 0 0 0 0 0 0 0 1 0 0 0
117 431 446 0 0 0 0 0 0 0 0 1 0 0
118 423 431 0 0 0 0 0 0 0 0 0 1 0
119 416 423 0 0 0 0 0 0 0 0 0 0 1
120 416 416 0 0 0 0 0 0 0 0 0 0 0
121 413 416 1 0 0 0 0 0 0 0 0 0 0
122 399 413 0 1 0 0 0 0 0 0 0 0 0
123 386 399 0 0 1 0 0 0 0 0 0 0 0
124 374 386 0 0 0 1 0 0 0 0 0 0 0
125 365 374 0 0 0 0 1 0 0 0 0 0 0
126 365 365 0 0 0 0 0 1 0 0 0 0 0
127 418 365 0 0 0 0 0 0 1 0 0 0 0
128 428 418 0 0 0 0 0 0 0 1 0 0 0
129 424 428 0 0 0 0 0 0 0 0 1 0 0
130 421 424 0 0 0 0 0 0 0 0 0 1 0
131 417 421 0 0 0 0 0 0 0 0 0 0 1
132 423 417 0 0 0 0 0 0 0 0 0 0 0
133 423 423 1 0 0 0 0 0 0 0 0 0 0
134 419 423 0 1 0 0 0 0 0 0 0 0 0
135 406 419 0 0 1 0 0 0 0 0 0 0 0
136 398 406 0 0 0 1 0 0 0 0 0 0 0
137 390 398 0 0 0 0 1 0 0 0 0 0 0
138 391 390 0 0 0 0 0 1 0 0 0 0 0
139 444 391 0 0 0 0 0 0 1 0 0 0 0
140 460 444 0 0 0 0 0 0 0 1 0 0 0
141 455 460 0 0 0 0 0 0 0 0 1 0 0
142 456 455 0 0 0 0 0 0 0 0 0 1 0
143 452 456 0 0 0 0 0 0 0 0 0 0 1
144 459 452 0 0 0 0 0 0 0 0 0 0 0
145 461 459 1 0 0 0 0 0 0 0 0 0 0
146 451 461 0 1 0 0 0 0 0 0 0 0 0
147 443 451 0 0 1 0 0 0 0 0 0 0 0
148 439 443 0 0 0 1 0 0 0 0 0 0 0
149 430 439 0 0 0 0 1 0 0 0 0 0 0
150 436 430 0 0 0 0 0 1 0 0 0 0 0
151 488 436 0 0 0 0 0 0 1 0 0 0 0
152 506 488 0 0 0 0 0 0 0 1 0 0 0
153 502 506 0 0 0 0 0 0 0 0 1 0 0
154 501 502 0 0 0 0 0 0 0 0 0 1 0
155 501 501 0 0 0 0 0 0 0 0 0 0 1
156 515 501 0 0 0 0 0 0 0 0 0 0 0
157 521 515 1 0 0 0 0 0 0 0 0 0 0
158 520 521 0 1 0 0 0 0 0 0 0 0 0
159 512 520 0 0 1 0 0 0 0 0 0 0 0
160 509 512 0 0 0 1 0 0 0 0 0 0 0
161 505 509 0 0 0 0 1 0 0 0 0 0 0
162 511 505 0 0 0 0 0 1 0 0 0 0 0
163 570 511 0 0 0 0 0 0 1 0 0 0 0
164 592 570 0 0 0 0 0 0 0 1 0 0 0
165 594 592 0 0 0 0 0 0 0 0 1 0 0
166 586 594 0 0 0 0 0 0 0 0 0 1 0
167 586 586 0 0 0 0 0 0 0 0 0 0 1
168 592 586 0 0 0 0 0 0 0 0 0 0 0
169 594 592 1 0 0 0 0 0 0 0 0 0 0
170 594 594 0 1 0 0 0 0 0 0 0 0 0
171 586 594 0 0 1 0 0 0 0 0 0 0 0
172 586 586 0 0 0 1 0 0 0 0 0 0 0
173 572 586 0 0 0 0 1 0 0 0 0 0 0
174 572 572 0 0 0 0 0 1 0 0 0 0 0
175 563 572 0 0 0 0 0 0 1 0 0 0 0
176 563 563 0 0 0 0 0 0 0 1 0 0 0
177 555 563 0 0 0 0 0 0 0 0 1 0 0
178 555 555 0 0 0 0 0 0 0 0 0 1 0
179 554 555 0 0 0 0 0 0 0 0 0 0 1
180 554 554 0 0 0 0 0 0 0 0 0 0 0
181 601 554 1 0 0 0 0 0 0 0 0 0 0
182 601 601 0 1 0 0 0 0 0 0 0 0 0
183 622 601 0 0 1 0 0 0 0 0 0 0 0
184 622 622 0 0 0 1 0 0 0 0 0 0 0
185 617 622 0 0 0 0 1 0 0 0 0 0 0
186 617 617 0 0 0 0 0 1 0 0 0 0 0
187 606 617 0 0 0 0 0 0 1 0 0 0 0
188 606 606 0 0 0 0 0 0 0 1 0 0 0
189 595 606 0 0 0 0 0 0 0 0 1 0 0
190 595 595 0 0 0 0 0 0 0 0 0 1 0
191 599 595 0 0 0 0 0 0 0 0 0 0 1
192 599 599 0 0 0 0 0 0 0 0 0 0 0
193 600 599 1 0 0 0 0 0 0 0 0 0 0
194 600 600 0 1 0 0 0 0 0 0 0 0 0
195 592 600 0 0 1 0 0 0 0 0 0 0 0
196 592 592 0 0 0 1 0 0 0 0 0 0 0
197 575 592 0 0 0 0 1 0 0 0 0 0 0
198 575 575 0 0 0 0 0 1 0 0 0 0 0
199 567 575 0 0 0 0 0 0 1 0 0 0 0
200 567 567 0 0 0 0 0 0 0 1 0 0 0
201 555 567 0 0 0 0 0 0 0 0 1 0 0
202 555 555 0 0 0 0 0 0 0 0 0 1 0
203 555 555 0 0 0 0 0 0 0 0 0 0 1
204 555 555 0 0 0 0 0 0 0 0 0 0 0
205 608 555 1 0 0 0 0 0 0 0 0 0 0
206 608 608 0 1 0 0 0 0 0 0 0 0 0
207 631 608 0 0 1 0 0 0 0 0 0 0 0
208 631 631 0 0 0 1 0 0 0 0 0 0 0
209 629 631 0 0 0 0 1 0 0 0 0 0 0
210 629 629 0 0 0 0 0 1 0 0 0 0 0
211 624 629 0 0 0 0 0 0 1 0 0 0 0
212 624 624 0 0 0 0 0 0 0 1 0 0 0
213 610 624 0 0 0 0 0 0 0 0 1 0 0
214 610 610 0 0 0 0 0 0 0 0 0 1 0
215 616 610 0 0 0 0 0 0 0 0 0 0 1
216 616 616 0 0 0 0 0 0 0 0 0 0 0
217 621 616 1 0 0 0 0 0 0 0 0 0 0
218 621 621 0 1 0 0 0 0 0 0 0 0 0
219 604 621 0 0 1 0 0 0 0 0 0 0 0
220 604 604 0 0 0 1 0 0 0 0 0 0 0
221 584 604 0 0 0 0 1 0 0 0 0 0 0
222 584 584 0 0 0 0 0 1 0 0 0 0 0
223 574 584 0 0 0 0 0 0 1 0 0 0 0
224 574 574 0 0 0 0 0 0 0 1 0 0 0
225 555 574 0 0 0 0 0 0 0 0 1 0 0
226 555 555 0 0 0 0 0 0 0 0 0 1 0
227 545 555 0 0 0 0 0 0 0 0 0 0 1
228 545 545 0 0 0 0 0 0 0 0 0 0 0
229 599 545 1 0 0 0 0 0 0 0 0 0 0
230 599 599 0 1 0 0 0 0 0 0 0 0 0
231 620 599 0 0 1 0 0 0 0 0 0 0 0
232 620 620 0 0 0 1 0 0 0 0 0 0 0
233 608 620 0 0 0 0 1 0 0 0 0 0 0
234 608 608 0 0 0 0 0 1 0 0 0 0 0
235 590 608 0 0 0 0 0 0 1 0 0 0 0
236 590 590 0 0 0 0 0 0 0 1 0 0 0
237 579 590 0 0 0 0 0 0 0 0 1 0 0
238 579 579 0 0 0 0 0 0 0 0 0 1 0
239 580 579 0 0 0 0 0 0 0 0 0 0 1
240 580 580 0 0 0 0 0 0 0 0 0 0 0
241 579 580 1 0 0 0 0 0 0 0 0 0 0
242 579 579 0 1 0 0 0 0 0 0 0 0 0
243 572 579 0 0 1 0 0 0 0 0 0 0 0
244 572 572 0 0 0 1 0 0 0 0 0 0 0
245 560 572 0 0 0 0 1 0 0 0 0 0 0
246 560 560 0 0 0 0 0 1 0 0 0 0 0
247 551 560 0 0 0 0 0 0 1 0 0 0 0
248 551 551 0 0 0 0 0 0 0 1 0 0 0
249 537 551 0 0 0 0 0 0 0 0 1 0 0
250 537 537 0 0 0 0 0 0 0 0 0 1 0
251 541 537 0 0 0 0 0 0 0 0 0 0 1
252 541 541 0 0 0 0 0 0 0 0 0 0 0
253 588 541 1 0 0 0 0 0 0 0 0 0 0
254 588 588 0 1 0 0 0 0 0 0 0 0 0
255 607 588 0 0 1 0 0 0 0 0 0 0 0
256 607 607 0 0 0 1 0 0 0 0 0 0 0
257 599 607 0 0 0 0 1 0 0 0 0 0 0
258 599 599 0 0 0 0 0 1 0 0 0 0 0
259 578 599 0 0 0 0 0 0 1 0 0 0 0
260 578 578 0 0 0 0 0 0 0 1 0 0 0
261 563 578 0 0 0 0 0 0 0 0 1 0 0
262 563 563 0 0 0 0 0 0 0 0 0 1 0
263 566 563 0 0 0 0 0 0 0 0 0 0 1
264 566 566 0 0 0 0 0 0 0 0 0 0 0
265 561 566 1 0 0 0 0 0 0 0 0 0 0
266 561 561 0 1 0 0 0 0 0 0 0 0 0
267 554 561 0 0 1 0 0 0 0 0 0 0 0
268 554 554 0 0 0 1 0 0 0 0 0 0 0
269 540 554 0 0 0 0 1 0 0 0 0 0 0
270 540 540 0 0 0 0 0 1 0 0 0 0 0
271 526 540 0 0 0 0 0 0 1 0 0 0 0
272 526 526 0 0 0 0 0 0 0 1 0 0 0
273 512 526 0 0 0 0 0 0 0 0 1 0 0
274 512 512 0 0 0 0 0 0 0 0 0 1 0
275 505 512 0 0 0 0 0 0 0 0 0 0 1
276 505 505 0 0 0 0 0 0 0 0 0 0 0
277 554 505 1 0 0 0 0 0 0 0 0 0 0
278 554 554 0 1 0 0 0 0 0 0 0 0 0
279 584 554 0 0 1 0 0 0 0 0 0 0 0
280 584 584 0 0 0 1 0 0 0 0 0 0 0
281 569 584 0 0 0 0 1 0 0 0 0 0 0
282 569 569 0 0 0 0 0 1 0 0 0 0 0
283 540 569 0 0 0 0 0 0 1 0 0 0 0
284 540 540 0 0 0 0 0 0 0 1 0 0 0
285 522 540 0 0 0 0 0 0 0 0 1 0 0
286 522 522 0 0 0 0 0 0 0 0 0 1 0
287 526 522 0 0 0 0 0 0 0 0 0 0 1
288 526 526 0 0 0 0 0 0 0 0 0 0 0
289 527 526 1 0 0 0 0 0 0 0 0 0 0
290 527 527 0 1 0 0 0 0 0 0 0 0 0
291 516 527 0 0 1 0 0 0 0 0 0 0 0
292 516 516 0 0 0 1 0 0 0 0 0 0 0
293 503 516 0 0 0 0 1 0 0 0 0 0 0
294 503 503 0 0 0 0 0 1 0 0 0 0 0
295 489 503 0 0 0 0 0 0 1 0 0 0 0
296 489 489 0 0 0 0 0 0 0 1 0 0 0
297 479 489 0 0 0 0 0 0 0 0 1 0 0
298 479 479 0 0 0 0 0 0 0 0 0 1 0
299 475 479 0 0 0 0 0 0 0 0 0 0 1
300 475 475 0 0 0 0 0 0 0 0 0 0 0
301 524 475 1 0 0 0 0 0 0 0 0 0 0
302 524 524 0 1 0 0 0 0 0 0 0 0 0
303 552 524 0 0 1 0 0 0 0 0 0 0 0
304 552 552 0 0 0 1 0 0 0 0 0 0 0
305 532 552 0 0 0 0 1 0 0 0 0 0 0
306 532 532 0 0 0 0 0 1 0 0 0 0 0
307 511 532 0 0 0 0 0 0 1 0 0 0 0
308 511 511 0 0 0 0 0 0 0 1 0 0 0
309 492 511 0 0 0 0 0 0 0 0 1 0 0
310 492 492 0 0 0 0 0 0 0 0 0 1 0
311 492 492 0 0 0 0 0 0 0 0 0 0 1
312 492 492 0 0 0 0 0 0 0 0 0 0 0
313 493 492 1 0 0 0 0 0 0 0 0 0 0
314 493 493 0 1 0 0 0 0 0 0 0 0 0
315 481 493 0 0 1 0 0 0 0 0 0 0 0
316 481 481 0 0 0 1 0 0 0 0 0 0 0
317 462 481 0 0 0 0 1 0 0 0 0 0 0
318 462 462 0 0 0 0 0 1 0 0 0 0 0
319 457 462 0 0 0 0 0 0 1 0 0 0 0
320 457 457 0 0 0 0 0 0 0 1 0 0 0
321 442 457 0 0 0 0 0 0 0 0 1 0 0
322 442 442 0 0 0 0 0 0 0 0 0 1 0
323 439 442 0 0 0 0 0 0 0 0 0 0 1
324 439 439 0 0 0 0 0 0 0 0 0 0 0
325 488 439 1 0 0 0 0 0 0 0 0 0 0
326 488 488 0 1 0 0 0 0 0 0 0 0 0
327 521 488 0 0 1 0 0 0 0 0 0 0 0
328 521 521 0 0 0 1 0 0 0 0 0 0 0
329 501 521 0 0 0 0 1 0 0 0 0 0 0
330 501 501 0 0 0 0 0 1 0 0 0 0 0
331 485 501 0 0 0 0 0 0 1 0 0 0 0
332 485 485 0 0 0 0 0 0 0 1 0 0 0
333 464 485 0 0 0 0 0 0 0 0 1 0 0
334 464 464 0 0 0 0 0 0 0 0 0 1 0
335 460 464 0 0 0 0 0 0 0 0 0 0 1
336 460 460 0 0 0 0 0 0 0 0 0 0 0
337 467 460 1 0 0 0 0 0 0 0 0 0 0
338 467 467 0 1 0 0 0 0 0 0 0 0 0
339 460 467 0 0 1 0 0 0 0 0 0 0 0
340 460 460 0 0 0 1 0 0 0 0 0 0 0
341 448 460 0 0 0 0 1 0 0 0 0 0 0
342 448 448 0 0 0 0 0 1 0 0 0 0 0
343 443 448 0 0 0 0 0 0 1 0 0 0 0
344 443 443 0 0 0 0 0 0 0 1 0 0 0
345 436 443 0 0 0 0 0 0 0 0 1 0 0
346 436 436 0 0 0 0 0 0 0 0 0 1 0
347 431 436 0 0 0 0 0 0 0 0 0 0 1
348 431 431 0 0 0 0 0 0 0 0 0 0 0
349 484 431 1 0 0 0 0 0 0 0 0 0 0
350 484 484 0 1 0 0 0 0 0 0 0 0 0
351 510 484 0 0 1 0 0 0 0 0 0 0 0
352 510 510 0 0 0 1 0 0 0 0 0 0 0
353 513 510 0 0 0 0 1 0 0 0 0 0 0
354 513 513 0 0 0 0 0 1 0 0 0 0 0
355 503 513 0 0 0 0 0 0 1 0 0 0 0
356 503 503 0 0 0 0 0 0 0 1 0 0 0
357 471 503 0 0 0 0 0 0 0 0 1 0 0
358 471 471 0 0 0 0 0 0 0 0 0 1 0
359 471 471 0 0 0 0 0 0 0 0 0 0 1
360 471 471 0 0 0 0 0 0 0 0 0 0 0
361 476 471 1 0 0 0 0 0 0 0 0 0 0
362 476 476 0 1 0 0 0 0 0 0 0 0 0
363 475 476 0 0 1 0 0 0 0 0 0 0 0
364 475 475 0 0 0 1 0 0 0 0 0 0 0
365 470 475 0 0 0 0 1 0 0 0 0 0 0
366 470 470 0 0 0 0 0 1 0 0 0 0 0
367 461 470 0 0 0 0 0 0 1 0 0 0 0
368 461 461 0 0 0 0 0 0 0 1 0 0 0
369 455 461 0 0 0 0 0 0 0 0 1 0 0
370 455 455 0 0 0 0 0 0 0 0 0 1 0
371 456 455 0 0 0 0 0 0 0 0 0 0 1
372 456 456 0 0 0 0 0 0 0 0 0 0 0
373 517 456 1 0 0 0 0 0 0 0 0 0 0
374 517 517 0 1 0 0 0 0 0 0 0 0 0
375 525 517 0 0 1 0 0 0 0 0 0 0 0
376 525 525 0 0 0 1 0 0 0 0 0 0 0
377 523 525 0 0 0 0 1 0 0 0 0 0 0
378 523 523 0 0 0 0 0 1 0 0 0 0 0
379 519 523 0 0 0 0 0 0 1 0 0 0 0
380 519 519 0 0 0 0 0 0 0 1 0 0 0
381 509 519 0 0 0 0 0 0 0 0 1 0 0
382 509 509 0 0 0 0 0 0 0 0 0 1 0
383 512 509 0 0 0 0 0 0 0 0 0 0 1
384 512 512 0 0 0 0 0 0 0 0 0 0 0
385 519 512 1 0 0 0 0 0 0 0 0 0 0
386 519 519 0 1 0 0 0 0 0 0 0 0 0
387 517 519 0 0 1 0 0 0 0 0 0 0 0
388 517 517 0 0 0 1 0 0 0 0 0 0 0
389 510 517 0 0 0 0 1 0 0 0 0 0 0
390 510 510 0 0 0 0 0 1 0 0 0 0 0
391 509 510 0 0 0 0 0 0 1 0 0 0 0
392 509 509 0 0 0 0 0 0 0 1 0 0 0
393 501 509 0 0 0 0 0 0 0 0 1 0 0
394 501 501 0 0 0 0 0 0 0 0 0 1 0
395 507 501 0 0 0 0 0 0 0 0 0 0 1
396 507 507 0 0 0 0 0 0 0 0 0 0 0
397 569 507 1 0 0 0 0 0 0 0 0 0 0
398 569 569 0 1 0 0 0 0 0 0 0 0 0
399 580 569 0 0 1 0 0 0 0 0 0 0 0
400 580 580 0 0 0 1 0 0 0 0 0 0 0
401 578 580 0 0 0 0 1 0 0 0 0 0 0
402 578 578 0 0 0 0 0 1 0 0 0 0 0
403 565 578 0 0 0 0 0 0 1 0 0 0 0
404 565 565 0 0 0 0 0 0 0 1 0 0 0
405 547 565 0 0 0 0 0 0 0 0 1 0 0
406 547 547 0 0 0 0 0 0 0 0 0 1 0
407 555 547 0 0 0 0 0 0 0 0 0 0 1
408 555 555 0 0 0 0 0 0 0 0 0 0 0
409 562 555 1 0 0 0 0 0 0 0 0 0 0
410 561 562 0 1 0 0 0 0 0 0 0 0 0
411 555 561 0 0 1 0 0 0 0 0 0 0 0
412 544 555 0 0 0 1 0 0 0 0 0 0 0
413 537 544 0 0 0 0 1 0 0 0 0 0 0
414 543 537 0 0 0 0 0 1 0 0 0 0 0
415 594 543 0 0 0 0 0 0 1 0 0 0 0
416 611 594 0 0 0 0 0 0 0 1 0 0 0
417 613 611 0 0 0 0 0 0 0 0 1 0 0
418 611 613 0 0 0 0 0 0 0 0 0 1 0
419 594 611 0 0 0 0 0 0 0 0 0 0 1
420 595 594 0 0 0 0 0 0 0 0 0 0 0
421 591 595 1 0 0 0 0 0 0 0 0 0 0
422 589 591 0 1 0 0 0 0 0 0 0 0 0
423 584 589 0 0 1 0 0 0 0 0 0 0 0
424 573 584 0 0 0 1 0 0 0 0 0 0 0
425 567 573 0 0 0 0 1 0 0 0 0 0 0
426 569 567 0 0 0 0 0 1 0 0 0 0 0
427 621 569 0 0 0 0 0 0 1 0 0 0 0
428 629 621 0 0 0 0 0 0 0 1 0 0 0
429 628 629 0 0 0 0 0 0 0 0 1 0 0
430 612 628 0 0 0 0 0 0 0 0 0 1 0
431 595 612 0 0 0 0 0 0 0 0 0 0 1
432 597 595 0 0 0 0 0 0 0 0 0 0 0
433 593 597 1 0 0 0 0 0 0 0 0 0 0
434 590 593 0 1 0 0 0 0 0 0 0 0 0
435 580 590 0 0 1 0 0 0 0 0 0 0 0
436 574 580 0 0 0 1 0 0 0 0 0 0 0
437 573 574 0 0 0 0 1 0 0 0 0 0 0
438 573 573 0 0 0 0 0 1 0 0 0 0 0
439 620 573 0 0 0 0 0 0 1 0 0 0 0
440 626 620 0 0 0 0 0 0 0 1 0 0 0
441 620 626 0 0 0 0 0 0 0 0 1 0 0
442 588 620 0 0 0 0 0 0 0 0 0 1 0
443 566 588 0 0 0 0 0 0 0 0 0 0 1
444 557 566 0 0 0 0 0 0 0 0 0 0 0
445 561 557 1 0 0 0 0 0 0 0 0 0 0
446 549 561 0 1 0 0 0 0 0 0 0 0 0
447 532 549 0 0 1 0 0 0 0 0 0 0 0
448 526 532 0 0 0 1 0 0 0 0 0 0 0
449 511 526 0 0 0 0 1 0 0 0 0 0 0
450 499 511 0 0 0 0 0 1 0 0 0 0 0
451 555 499 0 0 0 0 0 0 1 0 0 0 0
452 565 555 0 0 0 0 0 0 0 1 0 0 0
453 542 565 0 0 0 0 0 0 0 0 1 0 0
454 527 542 0 0 0 0 0 0 0 0 0 1 0
455 510 527 0 0 0 0 0 0 0 0 0 0 1
456 514 510 0 0 0 0 0 0 0 0 0 0 0
457 517 514 1 0 0 0 0 0 0 0 0 0 0
458 508 517 0 1 0 0 0 0 0 0 0 0 0
459 493 508 0 0 1 0 0 0 0 0 0 0 0
460 490 493 0 0 0 1 0 0 0 0 0 0 0
461 469 490 0 0 0 0 1 0 0 0 0 0 0
462 478 469 0 0 0 0 0 1 0 0 0 0 0
463 528 478 0 0 0 0 0 0 1 0 0 0 0
464 534 528 0 0 0 0 0 0 0 1 0 0 0
465 518 534 0 0 0 0 0 0 0 0 1 0 0
466 506 518 0 0 0 0 0 0 0 0 0 1 0
467 502 506 0 0 0 0 0 0 0 0 0 0 1
468 516 502 0 0 0 0 0 0 0 0 0 0 0
469 528 516 1 0 0 0 0 0 0 0 0 0 0
470 533 528 0 1 0 0 0 0 0 0 0 0 0
471 536 533 0 0 1 0 0 0 0 0 0 0 0
472 537 536 0 0 0 1 0 0 0 0 0 0 0
473 524 537 0 0 0 0 1 0 0 0 0 0 0
474 536 524 0 0 0 0 0 1 0 0 0 0 0
475 587 536 0 0 0 0 0 0 1 0 0 0 0
476 597 587 0 0 0 0 0 0 0 1 0 0 0
477 581 597 0 0 0 0 0 0 0 0 1 0 0
478 564 581 0 0 0 0 0 0 0 0 0 1 0
479 558 564 0 0 0 0 0 0 0 0 0 0 1
480 575 558 0 0 0 0 0 0 0 0 0 0 0
481 580 575 1 0 0 0 0 0 0 0 0 0 0
482 575 580 0 1 0 0 0 0 0 0 0 0 0
483 563 575 0 0 1 0 0 0 0 0 0 0 0
484 552 563 0 0 0 1 0 0 0 0 0 0 0
485 537 552 0 0 0 0 1 0 0 0 0 0 0
486 545 537 0 0 0 0 0 1 0 0 0 0 0
487 601 545 0 0 0 0 0 0 1 0 0 0 0
488 604 601 0 0 0 0 0 0 0 1 0 0 0
489 586 604 0 0 0 0 0 0 0 0 1 0 0
490 564 586 0 0 0 0 0 0 0 0 0 1 0
491 549 564 0 0 0 0 0 0 0 0 0 0 1
492 551 549 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) y1 M1 M2 M3 M4
54.733 0.898 19.696 -5.155 -3.091 -5.914
M5 M6 M7 M8 M9 M10
-11.711 -2.855 19.252 6.273 -9.307 -4.959
M11
-5.290
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-44.975 -9.411 -0.828 7.797 274.570
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 54.73309 7.29558 7.502 3.07e-13 ***
y1 0.89805 0.01275 70.435 < 2e-16 ***
M1 19.69645 4.26556 4.618 5.00e-06 ***
M2 -5.15478 4.26507 -1.209 0.22741
M3 -3.09064 4.26359 -0.725 0.46887
M4 -5.91425 4.26319 -1.387 0.16600
M5 -11.71123 4.26290 -2.747 0.00624 **
M6 -2.85517 4.26511 -0.669 0.50355
M7 19.25187 4.26517 4.514 8.03e-06 ***
M8 6.27276 4.26522 1.471 0.14203
M9 -9.30675 4.26893 -2.180 0.02974 *
M10 -4.95944 4.26420 -1.163 0.24539
M11 -5.28957 4.26321 -1.241 0.21531
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19.3 on 479 degrees of freedom
Multiple R-squared: 0.9133, Adjusted R-squared: 0.9112
F-statistic: 420.7 on 12 and 479 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,] 0.9999992 1.543348e-06 7.716741e-07
[2,] 1.0000000 3.151341e-08 1.575670e-08
[3,] 1.0000000 5.520279e-10 2.760140e-10
[4,] 1.0000000 1.312287e-11 6.561434e-12
[5,] 1.0000000 8.329055e-13 4.164527e-13
[6,] 1.0000000 1.023901e-13 5.119504e-14
[7,] 1.0000000 2.152051e-14 1.076026e-14
[8,] 1.0000000 3.986589e-15 1.993294e-15
[9,] 1.0000000 8.086560e-16 4.043280e-16
[10,] 1.0000000 2.472412e-15 1.236206e-15
[11,] 1.0000000 3.876858e-18 1.938429e-18
[12,] 1.0000000 4.990817e-20 2.495409e-20
[13,] 1.0000000 2.568883e-21 1.284441e-21
[14,] 1.0000000 2.232031e-22 1.116015e-22
[15,] 1.0000000 2.895856e-23 1.447928e-23
[16,] 1.0000000 1.222814e-24 6.114070e-25
[17,] 1.0000000 2.855184e-25 1.427592e-25
[18,] 1.0000000 8.593327e-26 4.296664e-26
[19,] 1.0000000 2.620094e-26 1.310047e-26
[20,] 1.0000000 7.447702e-27 3.723851e-27
[21,] 1.0000000 3.415757e-27 1.707878e-27
[22,] 1.0000000 6.280154e-27 3.140077e-27
[23,] 1.0000000 5.418342e-28 2.709171e-28
[24,] 1.0000000 1.250283e-28 6.251413e-29
[25,] 1.0000000 3.922225e-29 1.961112e-29
[26,] 1.0000000 2.278356e-29 1.139178e-29
[27,] 1.0000000 1.200508e-29 6.002542e-30
[28,] 1.0000000 1.550295e-30 7.751476e-31
[29,] 1.0000000 4.598563e-31 2.299282e-31
[30,] 1.0000000 2.541122e-31 1.270561e-31
[31,] 1.0000000 2.241888e-31 1.120944e-31
[32,] 1.0000000 3.892175e-31 1.946087e-31
[33,] 1.0000000 7.951979e-31 3.975989e-31
[34,] 1.0000000 6.370727e-31 3.185363e-31
[35,] 1.0000000 6.518989e-31 3.259494e-31
[36,] 1.0000000 7.713314e-31 3.856657e-31
[37,] 1.0000000 1.293311e-30 6.466555e-31
[38,] 1.0000000 1.628110e-30 8.140548e-31
[39,] 1.0000000 2.797272e-30 1.398636e-30
[40,] 1.0000000 5.657142e-31 2.828571e-31
[41,] 1.0000000 2.256611e-31 1.128305e-31
[42,] 1.0000000 4.164104e-31 2.082052e-31
[43,] 1.0000000 7.796122e-31 3.898061e-31
[44,] 1.0000000 1.384136e-30 6.920681e-31
[45,] 1.0000000 3.085541e-30 1.542771e-30
[46,] 1.0000000 7.080476e-30 3.540238e-30
[47,] 1.0000000 1.123149e-29 5.615747e-30
[48,] 1.0000000 1.556125e-29 7.780625e-30
[49,] 1.0000000 2.760046e-29 1.380023e-29
[50,] 1.0000000 6.629899e-29 3.314949e-29
[51,] 1.0000000 9.909278e-29 4.954639e-29
[52,] 1.0000000 8.176090e-29 4.088045e-29
[53,] 1.0000000 1.894586e-28 9.472931e-29
[54,] 1.0000000 4.424114e-28 2.212057e-28
[55,] 1.0000000 1.042608e-27 5.213040e-28
[56,] 1.0000000 2.293807e-27 1.146903e-27
[57,] 1.0000000 5.571615e-27 2.785807e-27
[58,] 1.0000000 1.666092e-27 8.330462e-28
[59,] 1.0000000 3.133994e-27 1.566997e-27
[60,] 1.0000000 5.775299e-27 2.887649e-27
[61,] 1.0000000 1.213653e-26 6.068264e-27
[62,] 1.0000000 2.864432e-26 1.432216e-26
[63,] 1.0000000 6.474837e-26 3.237418e-26
[64,] 1.0000000 5.320114e-26 2.660057e-26
[65,] 1.0000000 9.965062e-26 4.982531e-26
[66,] 1.0000000 1.902857e-25 9.514287e-26
[67,] 1.0000000 3.463936e-25 1.731968e-25
[68,] 1.0000000 5.988455e-25 2.994228e-25
[69,] 1.0000000 1.270367e-24 6.351837e-25
[70,] 1.0000000 5.018625e-25 2.509313e-25
[71,] 1.0000000 6.894139e-25 3.447069e-25
[72,] 1.0000000 1.263250e-24 6.316252e-25
[73,] 1.0000000 2.479099e-24 1.239550e-24
[74,] 1.0000000 5.273385e-24 2.636692e-24
[75,] 1.0000000 1.106343e-23 5.531714e-24
[76,] 1.0000000 6.745030e-24 3.372515e-24
[77,] 1.0000000 1.022120e-23 5.110600e-24
[78,] 1.0000000 1.800431e-23 9.002157e-24
[79,] 1.0000000 3.500609e-23 1.750305e-23
[80,] 1.0000000 5.860955e-23 2.930478e-23
[81,] 1.0000000 1.048823e-22 5.244114e-23
[82,] 1.0000000 2.283963e-23 1.141982e-23
[83,] 1.0000000 3.212271e-23 1.606135e-23
[84,] 1.0000000 3.760843e-23 1.880421e-23
[85,] 1.0000000 5.471463e-23 2.735732e-23
[86,] 1.0000000 9.082653e-23 4.541326e-23
[87,] 1.0000000 1.479717e-22 7.398586e-23
[88,] 1.0000000 5.844385e-23 2.922192e-23
[89,] 1.0000000 7.121411e-23 3.560705e-23
[90,] 1.0000000 7.544932e-23 3.772466e-23
[91,] 1.0000000 8.585432e-23 4.292716e-23
[92,] 1.0000000 1.096911e-22 5.484556e-23
[93,] 1.0000000 1.486125e-22 7.430627e-23
[94,] 1.0000000 1.296506e-23 6.482532e-24
[95,] 1.0000000 1.527663e-23 7.638317e-24
[96,] 1.0000000 2.365269e-23 1.182634e-23
[97,] 1.0000000 1.588002e-23 7.940008e-24
[98,] 1.0000000 2.227832e-23 1.113916e-23
[99,] 1.0000000 2.976620e-23 1.488310e-23
[100,] 1.0000000 1.041141e-23 5.205704e-24
[101,] 1.0000000 1.389572e-23 6.947859e-24
[102,] 1.0000000 9.884740e-24 4.942370e-24
[103,] 1.0000000 1.060168e-23 5.300839e-24
[104,] 1.0000000 1.303645e-23 6.518227e-24
[105,] 1.0000000 1.654429e-23 8.272145e-24
[106,] 1.0000000 1.921834e-24 9.609171e-25
[107,] 1.0000000 2.037682e-24 1.018841e-24
[108,] 1.0000000 1.907540e-24 9.537700e-25
[109,] 1.0000000 2.145017e-24 1.072509e-24
[110,] 1.0000000 3.144003e-24 1.572002e-24
[111,] 1.0000000 5.041916e-24 2.520958e-24
[112,] 1.0000000 1.451289e-24 7.256446e-25
[113,] 1.0000000 1.898415e-24 9.492077e-25
[114,] 1.0000000 2.652600e-24 1.326300e-24
[115,] 1.0000000 4.176343e-24 2.088171e-24
[116,] 1.0000000 6.764026e-24 3.382013e-24
[117,] 1.0000000 1.216533e-23 6.082665e-24
[118,] 1.0000000 3.451698e-24 1.725849e-24
[119,] 1.0000000 6.452580e-24 3.226290e-24
[120,] 1.0000000 6.965185e-24 3.482592e-24
[121,] 1.0000000 1.113774e-23 5.568869e-24
[122,] 1.0000000 2.005887e-23 1.002943e-23
[123,] 1.0000000 3.684954e-23 1.842477e-23
[124,] 1.0000000 1.037903e-23 5.189517e-24
[125,] 1.0000000 1.763851e-23 8.819253e-24
[126,] 1.0000000 2.989680e-23 1.494840e-23
[127,] 1.0000000 5.757165e-23 2.878582e-23
[128,] 1.0000000 1.072458e-22 5.362290e-23
[129,] 1.0000000 2.076515e-22 1.038258e-22
[130,] 1.0000000 1.281381e-22 6.406904e-23
[131,] 1.0000000 2.059706e-22 1.029853e-22
[132,] 1.0000000 3.108176e-22 1.554088e-22
[133,] 1.0000000 5.673858e-22 2.836929e-22
[134,] 1.0000000 1.076401e-21 5.382006e-22
[135,] 1.0000000 2.008276e-21 1.004138e-21
[136,] 1.0000000 4.781619e-22 2.390809e-22
[137,] 1.0000000 7.501030e-22 3.750515e-22
[138,] 1.0000000 1.345543e-21 6.727714e-22
[139,] 1.0000000 2.563345e-21 1.281672e-21
[140,] 1.0000000 4.768574e-21 2.384287e-21
[141,] 1.0000000 6.794993e-21 3.397496e-21
[142,] 1.0000000 8.566141e-21 4.283070e-21
[143,] 1.0000000 1.310549e-20 6.552746e-21
[144,] 1.0000000 1.883323e-20 9.416613e-21
[145,] 1.0000000 2.903911e-20 1.451956e-20
[146,] 1.0000000 4.547472e-20 2.273736e-20
[147,] 1.0000000 6.425428e-20 3.212714e-20
[148,] 1.0000000 2.877020e-21 1.438510e-21
[149,] 1.0000000 2.378631e-21 1.189316e-21
[150,] 1.0000000 2.457685e-21 1.228842e-21
[151,] 1.0000000 4.341223e-21 2.170611e-21
[152,] 1.0000000 6.068164e-21 3.034082e-21
[153,] 1.0000000 8.535155e-21 4.267577e-21
[154,] 1.0000000 1.061813e-20 5.309064e-21
[155,] 1.0000000 1.109623e-20 5.548117e-21
[156,] 1.0000000 1.299131e-20 6.495655e-21
[157,] 1.0000000 1.322549e-20 6.612744e-21
[158,] 1.0000000 2.132268e-20 1.066134e-20
[159,] 1.0000000 2.916528e-20 1.458264e-20
[160,] 1.0000000 1.064805e-20 5.324027e-21
[161,] 1.0000000 1.935145e-20 9.675726e-21
[162,] 1.0000000 3.436294e-20 1.718147e-20
[163,] 1.0000000 5.752704e-20 2.876352e-20
[164,] 1.0000000 9.645624e-20 4.822812e-20
[165,] 1.0000000 1.747818e-19 8.739088e-20
[166,] 1.0000000 5.299182e-20 2.649591e-20
[167,] 1.0000000 6.048042e-20 3.024021e-20
[168,] 1.0000000 1.274409e-20 6.372044e-21
[169,] 1.0000000 1.227361e-20 6.136804e-21
[170,] 1.0000000 1.331239e-20 6.656197e-21
[171,] 1.0000000 1.681919e-20 8.409596e-21
[172,] 1.0000000 9.000659e-21 4.500329e-21
[173,] 1.0000000 1.682195e-20 8.410973e-21
[174,] 1.0000000 3.008862e-20 1.504431e-20
[175,] 1.0000000 4.574481e-20 2.287241e-20
[176,] 1.0000000 5.650829e-20 2.825414e-20
[177,] 1.0000000 9.737447e-20 4.868724e-20
[178,] 1.0000000 1.135076e-19 5.675379e-20
[179,] 1.0000000 1.465276e-19 7.326381e-20
[180,] 1.0000000 2.061437e-19 1.030719e-19
[181,] 1.0000000 2.631573e-19 1.315787e-19
[182,] 1.0000000 4.522983e-19 2.261492e-19
[183,] 1.0000000 6.990584e-19 3.495292e-19
[184,] 1.0000000 3.894174e-19 1.947087e-19
[185,] 1.0000000 6.896009e-19 3.448005e-19
[186,] 1.0000000 1.229716e-18 6.148578e-19
[187,] 1.0000000 2.053411e-18 1.026706e-18
[188,] 1.0000000 3.397970e-18 1.698985e-18
[189,] 1.0000000 6.040777e-18 3.020388e-18
[190,] 1.0000000 1.052746e-18 5.263732e-19
[191,] 1.0000000 1.391035e-18 6.955175e-19
[192,] 1.0000000 3.555235e-19 1.777617e-19
[193,] 1.0000000 4.156448e-19 2.078224e-19
[194,] 1.0000000 4.174280e-19 2.087140e-19
[195,] 1.0000000 5.835086e-19 2.917543e-19
[196,] 1.0000000 6.103084e-19 3.051542e-19
[197,] 1.0000000 1.104379e-18 5.521894e-19
[198,] 1.0000000 1.964674e-18 9.823371e-19
[199,] 1.0000000 2.889916e-18 1.444958e-18
[200,] 1.0000000 3.117963e-18 1.558981e-18
[201,] 1.0000000 5.222783e-18 2.611391e-18
[202,] 1.0000000 7.706871e-18 3.853436e-18
[203,] 1.0000000 1.031117e-17 5.155587e-18
[204,] 1.0000000 1.272438e-17 6.362188e-18
[205,] 1.0000000 1.746785e-17 8.733925e-18
[206,] 1.0000000 2.915047e-17 1.457524e-17
[207,] 1.0000000 4.640771e-17 2.320385e-17
[208,] 1.0000000 2.809690e-17 1.404845e-17
[209,] 1.0000000 4.862952e-17 2.431476e-17
[210,] 1.0000000 7.943613e-17 3.971807e-17
[211,] 1.0000000 1.295265e-16 6.476324e-17
[212,] 1.0000000 2.191167e-16 1.095583e-16
[213,] 1.0000000 3.802247e-16 1.901124e-16
[214,] 1.0000000 7.044722e-17 3.522361e-17
[215,] 1.0000000 1.033420e-16 5.167098e-17
[216,] 1.0000000 4.634744e-17 2.317372e-17
[217,] 1.0000000 6.246803e-17 3.123402e-17
[218,] 1.0000000 1.019268e-16 5.096341e-17
[219,] 1.0000000 1.573262e-16 7.866308e-17
[220,] 1.0000000 5.789300e-17 2.894650e-17
[221,] 1.0000000 1.011296e-16 5.056478e-17
[222,] 1.0000000 1.718875e-16 8.594376e-17
[223,] 1.0000000 2.673350e-16 1.336675e-16
[224,] 1.0000000 4.044409e-16 2.022204e-16
[225,] 1.0000000 6.920141e-16 3.460070e-16
[226,] 1.0000000 6.711760e-16 3.355880e-16
[227,] 1.0000000 1.040378e-15 5.201891e-16
[228,] 1.0000000 1.625472e-15 8.127359e-16
[229,] 1.0000000 2.491622e-15 1.245811e-15
[230,] 1.0000000 4.205454e-15 2.102727e-15
[231,] 1.0000000 6.895794e-15 3.447897e-15
[232,] 1.0000000 4.471552e-15 2.235776e-15
[233,] 1.0000000 7.350568e-15 3.675284e-15
[234,] 1.0000000 1.218457e-14 6.092286e-15
[235,] 1.0000000 1.952123e-14 9.760616e-15
[236,] 1.0000000 2.851969e-14 1.425984e-14
[237,] 1.0000000 4.786020e-14 2.393010e-14
[238,] 1.0000000 2.103647e-14 1.051824e-14
[239,] 1.0000000 3.175945e-14 1.587973e-14
[240,] 1.0000000 2.067342e-14 1.033671e-14
[241,] 1.0000000 2.931062e-14 1.465531e-14
[242,] 1.0000000 4.375620e-14 2.187810e-14
[243,] 1.0000000 6.789313e-14 3.394656e-14
[244,] 1.0000000 1.924991e-14 9.624953e-15
[245,] 1.0000000 3.220889e-14 1.610444e-14
[246,] 1.0000000 5.371669e-14 2.685834e-14
[247,] 1.0000000 8.220009e-14 4.110005e-14
[248,] 1.0000000 1.158290e-13 5.791450e-14
[249,] 1.0000000 1.923011e-13 9.615056e-14
[250,] 1.0000000 1.356830e-13 6.784152e-14
[251,] 1.0000000 2.138831e-13 1.069415e-13
[252,] 1.0000000 3.278659e-13 1.639330e-13
[253,] 1.0000000 5.109226e-13 2.554613e-13
[254,] 1.0000000 8.362042e-13 4.181021e-13
[255,] 1.0000000 1.354687e-12 6.773433e-13
[256,] 1.0000000 5.330645e-13 2.665322e-13
[257,] 1.0000000 8.310352e-13 4.155176e-13
[258,] 1.0000000 1.317948e-12 6.589738e-13
[259,] 1.0000000 2.067232e-12 1.033616e-12
[260,] 1.0000000 3.306974e-12 1.653487e-12
[261,] 1.0000000 5.308912e-12 2.654456e-12
[262,] 1.0000000 2.399369e-12 1.199685e-12
[263,] 1.0000000 3.759329e-12 1.879665e-12
[264,] 1.0000000 1.168646e-12 5.843232e-13
[265,] 1.0000000 1.740071e-12 8.700357e-13
[266,] 1.0000000 2.829347e-12 1.414674e-12
[267,] 1.0000000 4.492004e-12 2.246002e-12
[268,] 1.0000000 3.187167e-13 1.593583e-13
[269,] 1.0000000 5.126213e-13 2.563107e-13
[270,] 1.0000000 7.915692e-13 3.957846e-13
[271,] 1.0000000 1.237218e-12 6.186092e-13
[272,] 1.0000000 1.783040e-12 8.915201e-13
[273,] 1.0000000 2.929331e-12 1.464665e-12
[274,] 1.0000000 2.693376e-12 1.346688e-12
[275,] 1.0000000 4.359709e-12 2.179855e-12
[276,] 1.0000000 5.796997e-12 2.898499e-12
[277,] 1.0000000 9.311197e-12 4.655599e-12
[278,] 1.0000000 1.489472e-11 7.447359e-12
[279,] 1.0000000 2.399021e-11 1.199511e-11
[280,] 1.0000000 6.411672e-12 3.205836e-12
[281,] 1.0000000 9.470493e-12 4.735247e-12
[282,] 1.0000000 1.499775e-11 7.498877e-12
[283,] 1.0000000 2.335268e-11 1.167634e-11
[284,] 1.0000000 3.717511e-11 1.858756e-11
[285,] 1.0000000 5.798000e-11 2.899000e-11
[286,] 1.0000000 2.760569e-11 1.380284e-11
[287,] 1.0000000 4.415764e-11 2.207882e-11
[288,] 1.0000000 1.915599e-11 9.577996e-12
[289,] 1.0000000 2.976428e-11 1.488214e-11
[290,] 1.0000000 4.261191e-11 2.130595e-11
[291,] 1.0000000 6.844296e-11 3.422148e-11
[292,] 1.0000000 7.664615e-12 3.832308e-12
[293,] 1.0000000 1.181984e-11 5.909918e-12
[294,] 1.0000000 1.698109e-11 8.490545e-12
[295,] 1.0000000 2.629017e-11 1.314508e-11
[296,] 1.0000000 4.144139e-11 2.072069e-11
[297,] 1.0000000 6.614549e-11 3.307274e-11
[298,] 1.0000000 5.587342e-11 2.793671e-11
[299,] 1.0000000 9.066480e-11 4.533240e-11
[300,] 1.0000000 1.097033e-10 5.485165e-11
[301,] 1.0000000 1.766210e-10 8.831049e-11
[302,] 1.0000000 2.263690e-10 1.131845e-10
[303,] 1.0000000 3.545874e-10 1.772937e-10
[304,] 1.0000000 1.421159e-10 7.105797e-11
[305,] 1.0000000 1.963084e-10 9.815418e-11
[306,] 1.0000000 2.797463e-10 1.398732e-10
[307,] 1.0000000 4.319335e-10 2.159667e-10
[308,] 1.0000000 6.735079e-10 3.367539e-10
[309,] 1.0000000 9.971292e-10 4.985646e-10
[310,] 1.0000000 5.152440e-10 2.576220e-10
[311,] 1.0000000 8.253522e-10 4.126761e-10
[312,] 1.0000000 2.365638e-10 1.182819e-10
[313,] 1.0000000 3.755548e-10 1.877774e-10
[314,] 1.0000000 4.861850e-10 2.430925e-10
[315,] 1.0000000 7.762877e-10 3.881439e-10
[316,] 1.0000000 8.077358e-11 4.038679e-11
[317,] 1.0000000 1.192072e-10 5.960360e-11
[318,] 1.0000000 1.487205e-10 7.436024e-11
[319,] 1.0000000 2.310441e-10 1.155221e-10
[320,] 1.0000000 3.720427e-10 1.860213e-10
[321,] 1.0000000 5.759390e-10 2.879695e-10
[322,] 1.0000000 6.442494e-10 3.221247e-10
[323,] 1.0000000 1.043130e-09 5.215652e-10
[324,] 1.0000000 1.482012e-09 7.410058e-10
[325,] 1.0000000 2.381205e-09 1.190602e-09
[326,] 1.0000000 3.478207e-09 1.739104e-09
[327,] 1.0000000 5.280336e-09 2.640168e-09
[328,] 1.0000000 1.126257e-09 5.631283e-10
[329,] 1.0000000 1.427042e-09 7.135211e-10
[330,] 1.0000000 2.267681e-09 1.133841e-09
[331,] 1.0000000 3.559934e-09 1.779967e-09
[332,] 1.0000000 5.406749e-09 2.703374e-09
[333,] 1.0000000 7.603650e-09 3.801825e-09
[334,] 1.0000000 2.527494e-09 1.263747e-09
[335,] 1.0000000 4.090735e-09 2.045368e-09
[336,] 1.0000000 2.025354e-09 1.012677e-09
[337,] 1.0000000 3.250503e-09 1.625251e-09
[338,] 1.0000000 4.346383e-09 2.173191e-09
[339,] 1.0000000 6.942732e-09 3.471366e-09
[340,] 1.0000000 7.499305e-10 3.749653e-10
[341,] 1.0000000 1.101976e-09 5.509878e-10
[342,] 1.0000000 6.158288e-10 3.079144e-10
[343,] 1.0000000 9.688830e-10 4.844415e-10
[344,] 1.0000000 1.582457e-09 7.912286e-10
[345,] 1.0000000 2.450321e-09 1.225161e-09
[346,] 1.0000000 2.663008e-09 1.331504e-09
[347,] 1.0000000 4.380199e-09 2.190099e-09
[348,] 1.0000000 7.160414e-09 3.580207e-09
[349,] 1.0000000 1.169512e-08 5.847562e-09
[350,] 1.0000000 1.900003e-08 9.500014e-09
[351,] 1.0000000 2.903940e-08 1.451970e-08
[352,] 1.0000000 1.079467e-09 5.397336e-10
[353,] 1.0000000 1.239843e-09 6.199213e-10
[354,] 1.0000000 2.039162e-09 1.019581e-09
[355,] 1.0000000 3.378746e-09 1.689373e-09
[356,] 1.0000000 5.641031e-09 2.820516e-09
[357,] 1.0000000 7.782092e-09 3.891046e-09
[358,] 1.0000000 3.600557e-10 1.800278e-10
[359,] 1.0000000 6.261216e-10 3.130608e-10
[360,] 1.0000000 8.314101e-10 4.157050e-10
[361,] 1.0000000 1.394139e-09 6.970695e-10
[362,] 1.0000000 2.180638e-09 1.090319e-09
[363,] 1.0000000 3.657586e-09 1.828793e-09
[364,] 1.0000000 1.452690e-10 7.263449e-11
[365,] 1.0000000 2.078768e-10 1.039384e-10
[366,] 1.0000000 3.677455e-10 1.838728e-10
[367,] 1.0000000 5.557050e-10 2.778525e-10
[368,] 1.0000000 8.203404e-10 4.101702e-10
[369,] 1.0000000 1.363065e-09 6.815325e-10
[370,] 1.0000000 2.113171e-09 1.056585e-09
[371,] 1.0000000 3.690074e-09 1.845037e-09
[372,] 1.0000000 6.385465e-09 3.192733e-09
[373,] 1.0000000 1.073917e-08 5.369585e-09
[374,] 1.0000000 1.839739e-08 9.198694e-09
[375,] 1.0000000 3.017903e-08 1.508952e-08
[376,] 1.0000000 5.835314e-10 2.917657e-10
[377,] 1.0000000 7.138841e-10 3.569420e-10
[378,] 1.0000000 1.285183e-09 6.425915e-10
[379,] 1.0000000 1.991889e-09 9.959444e-10
[380,] 1.0000000 2.496185e-09 1.248092e-09
[381,] 1.0000000 4.033527e-09 2.016763e-09
[382,] 1.0000000 1.595250e-12 7.976252e-13
[383,] 1.0000000 3.064152e-12 1.532076e-12
[384,] 1.0000000 1.562360e-12 7.811799e-13
[385,] 1.0000000 2.557448e-12 1.278724e-12
[386,] 1.0000000 3.419335e-12 1.709668e-12
[387,] 1.0000000 6.989227e-12 3.494614e-12
[388,] 1.0000000 1.074335e-19 5.371673e-20
[389,] 1.0000000 1.684770e-19 8.423848e-20
[390,] 1.0000000 3.101922e-19 1.550961e-19
[391,] 1.0000000 1.561515e-19 7.807576e-20
[392,] 1.0000000 1.236028e-20 6.180142e-21
[393,] 1.0000000 3.145648e-20 1.572824e-20
[394,] 1.0000000 7.830259e-20 3.915129e-20
[395,] 1.0000000 2.095220e-19 1.047610e-19
[396,] 1.0000000 5.615384e-19 2.807692e-19
[397,] 1.0000000 1.364546e-18 6.822728e-19
[398,] 1.0000000 3.287894e-18 1.643947e-18
[399,] 1.0000000 8.708306e-18 4.354153e-18
[400,] 1.0000000 1.920833e-17 9.604166e-18
[401,] 1.0000000 2.511455e-17 1.255728e-17
[402,] 1.0000000 1.055408e-17 5.277041e-18
[403,] 1.0000000 2.301116e-18 1.150558e-18
[404,] 1.0000000 6.754803e-18 3.377402e-18
[405,] 1.0000000 1.904351e-17 9.521755e-18
[406,] 1.0000000 3.684756e-17 1.842378e-17
[407,] 1.0000000 9.808961e-17 4.904481e-17
[408,] 1.0000000 2.159989e-16 1.079994e-16
[409,] 1.0000000 5.337987e-16 2.668993e-16
[410,] 1.0000000 9.485658e-16 4.742829e-16
[411,] 1.0000000 2.764167e-15 1.382084e-15
[412,] 1.0000000 6.328994e-15 3.164497e-15
[413,] 1.0000000 1.738698e-14 8.693492e-15
[414,] 1.0000000 6.434251e-15 3.217125e-15
[415,] 1.0000000 1.440513e-14 7.202566e-15
[416,] 1.0000000 4.184247e-14 2.092123e-14
[417,] 1.0000000 1.203547e-13 6.017737e-14
[418,] 1.0000000 2.156477e-13 1.078239e-13
[419,] 1.0000000 5.560867e-13 2.780434e-13
[420,] 1.0000000 1.549086e-12 7.745428e-13
[421,] 1.0000000 4.382154e-12 2.191077e-12
[422,] 1.0000000 1.498683e-12 7.493414e-13
[423,] 1.0000000 4.351552e-12 2.175776e-12
[424,] 1.0000000 1.027453e-11 5.137267e-12
[425,] 1.0000000 2.900167e-11 1.450084e-11
[426,] 1.0000000 1.560308e-11 7.801539e-12
[427,] 1.0000000 1.527729e-11 7.638645e-12
[428,] 1.0000000 2.272564e-11 1.136282e-11
[429,] 1.0000000 5.701599e-12 2.850799e-12
[430,] 1.0000000 1.734972e-11 8.674860e-12
[431,] 1.0000000 2.968284e-11 1.484142e-11
[432,] 1.0000000 4.830798e-11 2.415399e-11
[433,] 1.0000000 1.522630e-10 7.613149e-11
[434,] 1.0000000 4.755396e-10 2.377698e-10
[435,] 1.0000000 1.780458e-11 8.902289e-12
[436,] 1.0000000 5.179701e-11 2.589851e-11
[437,] 1.0000000 1.635263e-10 8.176313e-11
[438,] 1.0000000 3.666408e-10 1.833204e-10
[439,] 1.0000000 1.250266e-09 6.251329e-10
[440,] 1.0000000 1.880528e-09 9.402642e-10
[441,] 1.0000000 3.637001e-09 1.818501e-09
[442,] 1.0000000 8.690453e-09 4.345227e-09
[443,] 1.0000000 1.125973e-08 5.629863e-09
[444,] 1.0000000 7.625324e-09 3.812662e-09
[445,] 1.0000000 2.942002e-08 1.471001e-08
[446,] 1.0000000 3.343009e-08 1.671505e-08
[447,] 1.0000000 9.277185e-08 4.638593e-08
[448,] 0.9999999 1.320853e-07 6.604264e-08
[449,] 0.9999999 2.532689e-07 1.266345e-07
[450,] 0.9999998 4.646392e-07 2.323196e-07
[451,] 0.9999991 1.844735e-06 9.223674e-07
[452,] 0.9999966 6.883162e-06 3.441581e-06
[453,] 0.9999898 2.039613e-05 1.019806e-05
[454,] 0.9999710 5.797798e-05 2.898899e-05
[455,] 0.9999004 1.991673e-04 9.958364e-05
[456,] 0.9996531 6.937385e-04 3.468692e-04
[457,] 0.9991768 1.646403e-03 8.232013e-04
[458,] 0.9970066 5.986817e-03 2.993408e-03
[459,] 0.9907881 1.842388e-02 9.211938e-03
[460,] 0.9730170 5.396591e-02 2.698295e-02
[461,] 0.9478509 1.042982e-01 5.214911e-02
> postscript(file="/var/www/rcomp/tmp/1ck5i1296734019.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/rcomp/tmp/28jgw1296734019.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3bgjv1296734019.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/475c31296734019.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5l22c1296734019.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 492
Frequency = 1
1 2 3 4 5 6
274.5704656 -26.9978103 -22.3872932 -19.0734403 -13.6842563 -19.9481194
7 8 9 10 11 12
21.8428990 -1.7551584 2.8633482 -8.7703092 -8.5421280 -7.9336491
13 14 15 16 17 18
-33.1203468 -10.3710701 -12.7410545 -5.2233019 -0.2224188 -4.9765326
19 20 21 22 23 24
31.4261849 6.8281275 9.3446842 -2.5948227 2.3275090 3.1398875
25 26 27 28 29 30
-18.8429105 1.4161155 -6.7499692 -4.6400160 2.4433184 -1.9224945
31 32 33 34 35 36
38.9704738 12.3724164 15.6850734 7.6436166 11.8717978 8.8880760
37 38 39 40 41 42
-15.2986216 3.5526049 -4.1232290 1.5789248 3.6622593 2.7866971
43 44 45 46 47 48
41.5777155 23.6738086 21.5981646 9.5567079 2.3770897 -0.1358798
49 50 51 52 53 54
-16.6479255 -1.2044984 -6.5939813 -6.2996269 7.8661590 -1.6016038
55 56 57 58 59 60
42.6796653 29.8777083 14.4137634 6.5567079 9.0712402 -4.7280804
61 62 63 64 65 66
1.2501246 -9.4713509 -16.8803323 -14.7074263 -5.3572392 -20.0484002
67 68 69 70 71 72
26.6016714 8.5763161 8.4811737 -3.2739320 -5.0652493 1.4217811
73 74 75 76 77 78
-21.1727159 -13.5253890 -14.5265710 -11.3341665 -1.9644810 -6.7380933
79 80 81 82 83 84
19.7470756 0.3139209 9.7090292 12.4636728 -9.3905974 6.7905836
85 86 87 88 89 90
-22.0902645 -18.4429377 -12.8519191 -11.3536650 -5.8820296 -7.9614915
91 92 93 94 95 96
22.5236774 -5.5016779 5.3836812 -2.1675248 -8.3471430 -5.7581627
97 98 99 100 101 102
-27.6585093 -17.2150821 -21.1143143 -17.1258094 -10.8580737 -14.0394855
103 104 105 106 107 108
21.2417837 -7.4777220 -7.3884632 -11.8572179 -11.5465853 -9.7537053
109 110 111 112 113 114
-34.5521021 -19.3125746 -15.9059572 -26.8979539 -13.2419173 -17.2194293
115 116 117 118 119 120
13.1637897 -2.9635154 -14.9567080 -13.8332620 -13.3187298 -12.3219501
121 122 123 124 125 126
-35.0183970 -21.4730199 -23.9644527 -21.4661986 -13.8926134 -14.6662257
127 128 129 130 131 132
16.2267426 -8.3908133 -5.7918053 -9.5469110 -10.5226295 -6.2200002
133 134 135 136 137 138
-31.3047480 -10.4535214 -21.9254557 -15.4272016 -10.4458170 -11.1174795
139 140 141 142 143 144
18.8774386 0.2598828 -3.5294101 -2.3864656 -6.9543847 -1.6517555
145 146 147 148 149 150
-25.6345534 -12.5794272 -13.6630605 -7.6550572 -7.2658731 -2.0394855
151 152 153 154 155 156
22.4651819 6.7456761 2.1602830 0.4051773 1.6333585 10.3437872
157 158 159 160 161 162
-15.9253618 2.5375638 -6.6285209 0.3794824 4.8706163 5.6067532
163 164 165 166 167 168
37.1114206 19.1055638 16.9279701 2.7845635 10.2990957 11.0095244
169 170 171 172 173 174
-12.0752234 10.9799028 0.9157680 10.9237713 2.7207548 6.4373932
175 176 177 178 179 180
-24.6696386 -3.6080851 3.9714244 6.8085193 6.1386504 1.7471292
181 182 183 184 185 186
29.0506823 11.6935518 30.6294169 14.5939659 15.3909493 11.0251364
187 188 189 190 191 192
-22.0818953 0.7757584 5.3552680 10.8865133 15.2166444 6.3348724
193 194 195 196 197 198
-12.3615745 11.5916019 1.5274671 11.5354704 0.3324539 6.7432427
199 200 201 202 203 204
-23.3637890 -3.2002857 0.3792238 6.8085193 7.1386504 1.8490790
205 206 207 208 209 210
35.1526321 12.4072007 33.3430659 15.5115146 19.3084980 12.2485346
211 212 213 214 215 216
-14.8584971 2.6108557 4.1903652 12.4157610 18.7458921 8.0680199
217 218 219 220 221 222
-6.6284270 13.7325488 -5.3315861 12.7588686 -1.4441480 7.6607914
223 224 225 226 227 228
-24.4462404 -2.4866368 -5.9071272 6.8085193 -2.8613496 0.8295805
229 230 231 232 233 234
35.1331336 11.4896521 30.4255172 14.3900662 8.1870496 10.1075877
235 236 237 238 239 240
-29.9994440 -0.8554392 3.7240704 9.2553157 10.5854468 4.3978253
241 242 243 244 245 246
-16.2986216 9.4506551 0.3865202 9.4964734 3.2934569 5.2139950
247 248 249 250 251 252
-25.8930368 -4.8314833 -3.2519738 4.9734220 9.3035531 0.4217811
253 254 255 256 257 258
27.7253342 10.3682037 27.3040689 13.0647182 10.8617016 9.1900391
259 260 261 262 263 264
-33.9169926 -2.0788374 -1.4993278 7.6241181 10.9542492 2.9705274
265 266 267 268 269 270
-21.7259195 7.6155578 -1.4485770 7.6613761 -0.5416404 3.1749980
271 272 273 274 275 276
-32.9320338 -7.3802296 -5.8007200 2.4246758 -4.2451931 -3.2484134
277 278 279 280 281 282
26.0551397 6.9019088 34.8377740 10.7198716 1.5168551 6.1315436
283 284 285 286 287 288
-44.9754881 -5.9529317 -8.3734221 3.4441743 7.7743054 -1.1074666
289 290 291 292 293 294
-19.8039135 4.1492629 -8.9148719 3.7872818 -3.4157347 -0.5971465
295 296 297 298 299 300
-36.7041782 -11.1523740 -5.5728645 -0.9396693 -4.6095382 -6.3069089
301 302 303 304 305 306
22.9966442 3.8434134 29.7792785 7.4574764 -6.7455401 2.3593992
307 308 309 310 311 312
-40.7476326 -8.9094773 -12.3299678 0.3856788 0.7158099 -4.5737615
313 314 315 316 317 318
-23.2702084 0.6829680 -13.3811668 0.2190371 -12.9839795 -4.7770903
319 320 321 322 323 324
-31.8841220 -14.4147692 -13.8352596 -4.7118137 -7.3816826 -9.9771035
325 326 327 328 329 330
19.3264496 0.1732188 31.1090839 4.2970311 -9.9059855 -0.8010462
331 332 333 334 335 336
-38.9080779 -11.5601734 -16.9806638 -2.4689170 -6.1387859 -7.8361567
337 338 339 340 341 342
-20.5326036 -1.9677281 -11.0318629 -1.9219097 -8.1249263 -6.2043882
343 344 345 346 347 348
-33.3114199 -15.8420671 -7.2625575 -5.3235128 -9.9933817 -10.7927023
349 350 351 352 353 354
22.5108508 -0.2345806 23.7012845 3.1755827 11.9725662 0.4223520
355 356 357 358 359 360
-31.6846797 -9.7250761 -26.1455666 -1.7552681 -1.4251370 -6.7147083
361 362 363 364 365 366
-21.4111552 -1.0501794 -4.1143143 -0.3926620 0.4043214 -3.9614915
367 368 369 370 371 372
-35.0685232 -14.0069698 -4.4274602 -3.3864656 -2.0563346 -8.2439561
373 374 375 376 377 378
33.0595970 3.1297644 9.0656296 4.7048305 8.5018139 1.4418505
379 380 381 382 383 384
-24.6651812 -8.0938785 -2.5143690 2.1188262 5.4489573 -2.5347645
385 386 387 388 389 390
-15.2312114 3.3336641 -0.7304707 3.8892317 2.6862151 0.1165025
391 392 393 394 395 396
-22.9905292 -9.1133770 -1.5338675 1.3032274 7.6333585 -3.0445137
397 398 399 400 401 402
39.2590394 8.4311566 17.3670218 10.3120722 14.1090557 7.0490923
403 404 405 406 407 408
-28.0579395 -3.4041854 -5.8246759 5.9929205 14.3230516 1.8490790
409 410 411 412 413 414
-10.8473679 6.7175076 -0.4485770 -3.2366740 5.4388611 8.8691484
415 416 417 418 419 420
32.3738158 16.5523602 18.8650172 10.7216106 -4.1521580 6.8251232
421 422 423 424 425 426
-17.7693739 8.6740533 3.4060187 -0.2801284 9.3954067 7.9276439
427 428 429 430 431 432
36.0245119 10.3050061 17.7001145 -1.7491417 -4.0502082 7.9270730
433 434 435 436 437 438
-17.5654742 7.8779530 -1.4920314 4.3120722 14.4973566 6.5393430
439 440 441 442 443 444
31.4323113 8.2030563 12.3942649 -18.5647405 -11.4970046 -6.0294726
445 446 447 448 449 450
-13.6434682 -4.3844422 -12.6719752 -0.5815206 -4.3962362 -11.7815477
451 452 453 454 455 456
32.8880224 5.5763161 -10.8246759 -9.5168287 -12.7159454 1.2613358
457 458 459 460 461 462
-19.0273117 -5.8702356 -14.8519191 -1.5575647 -14.0664308 4.9365586
463 464 465 466 467 468
24.7470756 -1.1763299 -6.9851212 -8.9636251 -1.8568922 10.4457370
469 470 471 472 473 474
-9.8234120 9.2512128 5.6968272 6.8262788 -1.2747879 13.5438004
475 476 477 478 479 480
31.6601668 8.8387113 -0.5622807 -7.5407846 2.0561990 19.1549286
481 482 483 484 485 486
-10.8083709 4.5526049 -5.0212792 -2.4210752 -1.7455401 10.8691484
487 488 489 490 491 492
37.5777155 3.2660092 -1.8486317 -12.0310353 -6.9438010 3.2373799
> postscript(file="/var/www/rcomp/tmp/60hyi1296734019.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 = 492
Frequency = 1
lag(myerror, k = 1) myerror
0 274.5704656 NA
1 -26.9978103 274.5704656
2 -22.3872932 -26.9978103
3 -19.0734403 -22.3872932
4 -13.6842563 -19.0734403
5 -19.9481194 -13.6842563
6 21.8428990 -19.9481194
7 -1.7551584 21.8428990
8 2.8633482 -1.7551584
9 -8.7703092 2.8633482
10 -8.5421280 -8.7703092
11 -7.9336491 -8.5421280
12 -33.1203468 -7.9336491
13 -10.3710701 -33.1203468
14 -12.7410545 -10.3710701
15 -5.2233019 -12.7410545
16 -0.2224188 -5.2233019
17 -4.9765326 -0.2224188
18 31.4261849 -4.9765326
19 6.8281275 31.4261849
20 9.3446842 6.8281275
21 -2.5948227 9.3446842
22 2.3275090 -2.5948227
23 3.1398875 2.3275090
24 -18.8429105 3.1398875
25 1.4161155 -18.8429105
26 -6.7499692 1.4161155
27 -4.6400160 -6.7499692
28 2.4433184 -4.6400160
29 -1.9224945 2.4433184
30 38.9704738 -1.9224945
31 12.3724164 38.9704738
32 15.6850734 12.3724164
33 7.6436166 15.6850734
34 11.8717978 7.6436166
35 8.8880760 11.8717978
36 -15.2986216 8.8880760
37 3.5526049 -15.2986216
38 -4.1232290 3.5526049
39 1.5789248 -4.1232290
40 3.6622593 1.5789248
41 2.7866971 3.6622593
42 41.5777155 2.7866971
43 23.6738086 41.5777155
44 21.5981646 23.6738086
45 9.5567079 21.5981646
46 2.3770897 9.5567079
47 -0.1358798 2.3770897
48 -16.6479255 -0.1358798
49 -1.2044984 -16.6479255
50 -6.5939813 -1.2044984
51 -6.2996269 -6.5939813
52 7.8661590 -6.2996269
53 -1.6016038 7.8661590
54 42.6796653 -1.6016038
55 29.8777083 42.6796653
56 14.4137634 29.8777083
57 6.5567079 14.4137634
58 9.0712402 6.5567079
59 -4.7280804 9.0712402
60 1.2501246 -4.7280804
61 -9.4713509 1.2501246
62 -16.8803323 -9.4713509
63 -14.7074263 -16.8803323
64 -5.3572392 -14.7074263
65 -20.0484002 -5.3572392
66 26.6016714 -20.0484002
67 8.5763161 26.6016714
68 8.4811737 8.5763161
69 -3.2739320 8.4811737
70 -5.0652493 -3.2739320
71 1.4217811 -5.0652493
72 -21.1727159 1.4217811
73 -13.5253890 -21.1727159
74 -14.5265710 -13.5253890
75 -11.3341665 -14.5265710
76 -1.9644810 -11.3341665
77 -6.7380933 -1.9644810
78 19.7470756 -6.7380933
79 0.3139209 19.7470756
80 9.7090292 0.3139209
81 12.4636728 9.7090292
82 -9.3905974 12.4636728
83 6.7905836 -9.3905974
84 -22.0902645 6.7905836
85 -18.4429377 -22.0902645
86 -12.8519191 -18.4429377
87 -11.3536650 -12.8519191
88 -5.8820296 -11.3536650
89 -7.9614915 -5.8820296
90 22.5236774 -7.9614915
91 -5.5016779 22.5236774
92 5.3836812 -5.5016779
93 -2.1675248 5.3836812
94 -8.3471430 -2.1675248
95 -5.7581627 -8.3471430
96 -27.6585093 -5.7581627
97 -17.2150821 -27.6585093
98 -21.1143143 -17.2150821
99 -17.1258094 -21.1143143
100 -10.8580737 -17.1258094
101 -14.0394855 -10.8580737
102 21.2417837 -14.0394855
103 -7.4777220 21.2417837
104 -7.3884632 -7.4777220
105 -11.8572179 -7.3884632
106 -11.5465853 -11.8572179
107 -9.7537053 -11.5465853
108 -34.5521021 -9.7537053
109 -19.3125746 -34.5521021
110 -15.9059572 -19.3125746
111 -26.8979539 -15.9059572
112 -13.2419173 -26.8979539
113 -17.2194293 -13.2419173
114 13.1637897 -17.2194293
115 -2.9635154 13.1637897
116 -14.9567080 -2.9635154
117 -13.8332620 -14.9567080
118 -13.3187298 -13.8332620
119 -12.3219501 -13.3187298
120 -35.0183970 -12.3219501
121 -21.4730199 -35.0183970
122 -23.9644527 -21.4730199
123 -21.4661986 -23.9644527
124 -13.8926134 -21.4661986
125 -14.6662257 -13.8926134
126 16.2267426 -14.6662257
127 -8.3908133 16.2267426
128 -5.7918053 -8.3908133
129 -9.5469110 -5.7918053
130 -10.5226295 -9.5469110
131 -6.2200002 -10.5226295
132 -31.3047480 -6.2200002
133 -10.4535214 -31.3047480
134 -21.9254557 -10.4535214
135 -15.4272016 -21.9254557
136 -10.4458170 -15.4272016
137 -11.1174795 -10.4458170
138 18.8774386 -11.1174795
139 0.2598828 18.8774386
140 -3.5294101 0.2598828
141 -2.3864656 -3.5294101
142 -6.9543847 -2.3864656
143 -1.6517555 -6.9543847
144 -25.6345534 -1.6517555
145 -12.5794272 -25.6345534
146 -13.6630605 -12.5794272
147 -7.6550572 -13.6630605
148 -7.2658731 -7.6550572
149 -2.0394855 -7.2658731
150 22.4651819 -2.0394855
151 6.7456761 22.4651819
152 2.1602830 6.7456761
153 0.4051773 2.1602830
154 1.6333585 0.4051773
155 10.3437872 1.6333585
156 -15.9253618 10.3437872
157 2.5375638 -15.9253618
158 -6.6285209 2.5375638
159 0.3794824 -6.6285209
160 4.8706163 0.3794824
161 5.6067532 4.8706163
162 37.1114206 5.6067532
163 19.1055638 37.1114206
164 16.9279701 19.1055638
165 2.7845635 16.9279701
166 10.2990957 2.7845635
167 11.0095244 10.2990957
168 -12.0752234 11.0095244
169 10.9799028 -12.0752234
170 0.9157680 10.9799028
171 10.9237713 0.9157680
172 2.7207548 10.9237713
173 6.4373932 2.7207548
174 -24.6696386 6.4373932
175 -3.6080851 -24.6696386
176 3.9714244 -3.6080851
177 6.8085193 3.9714244
178 6.1386504 6.8085193
179 1.7471292 6.1386504
180 29.0506823 1.7471292
181 11.6935518 29.0506823
182 30.6294169 11.6935518
183 14.5939659 30.6294169
184 15.3909493 14.5939659
185 11.0251364 15.3909493
186 -22.0818953 11.0251364
187 0.7757584 -22.0818953
188 5.3552680 0.7757584
189 10.8865133 5.3552680
190 15.2166444 10.8865133
191 6.3348724 15.2166444
192 -12.3615745 6.3348724
193 11.5916019 -12.3615745
194 1.5274671 11.5916019
195 11.5354704 1.5274671
196 0.3324539 11.5354704
197 6.7432427 0.3324539
198 -23.3637890 6.7432427
199 -3.2002857 -23.3637890
200 0.3792238 -3.2002857
201 6.8085193 0.3792238
202 7.1386504 6.8085193
203 1.8490790 7.1386504
204 35.1526321 1.8490790
205 12.4072007 35.1526321
206 33.3430659 12.4072007
207 15.5115146 33.3430659
208 19.3084980 15.5115146
209 12.2485346 19.3084980
210 -14.8584971 12.2485346
211 2.6108557 -14.8584971
212 4.1903652 2.6108557
213 12.4157610 4.1903652
214 18.7458921 12.4157610
215 8.0680199 18.7458921
216 -6.6284270 8.0680199
217 13.7325488 -6.6284270
218 -5.3315861 13.7325488
219 12.7588686 -5.3315861
220 -1.4441480 12.7588686
221 7.6607914 -1.4441480
222 -24.4462404 7.6607914
223 -2.4866368 -24.4462404
224 -5.9071272 -2.4866368
225 6.8085193 -5.9071272
226 -2.8613496 6.8085193
227 0.8295805 -2.8613496
228 35.1331336 0.8295805
229 11.4896521 35.1331336
230 30.4255172 11.4896521
231 14.3900662 30.4255172
232 8.1870496 14.3900662
233 10.1075877 8.1870496
234 -29.9994440 10.1075877
235 -0.8554392 -29.9994440
236 3.7240704 -0.8554392
237 9.2553157 3.7240704
238 10.5854468 9.2553157
239 4.3978253 10.5854468
240 -16.2986216 4.3978253
241 9.4506551 -16.2986216
242 0.3865202 9.4506551
243 9.4964734 0.3865202
244 3.2934569 9.4964734
245 5.2139950 3.2934569
246 -25.8930368 5.2139950
247 -4.8314833 -25.8930368
248 -3.2519738 -4.8314833
249 4.9734220 -3.2519738
250 9.3035531 4.9734220
251 0.4217811 9.3035531
252 27.7253342 0.4217811
253 10.3682037 27.7253342
254 27.3040689 10.3682037
255 13.0647182 27.3040689
256 10.8617016 13.0647182
257 9.1900391 10.8617016
258 -33.9169926 9.1900391
259 -2.0788374 -33.9169926
260 -1.4993278 -2.0788374
261 7.6241181 -1.4993278
262 10.9542492 7.6241181
263 2.9705274 10.9542492
264 -21.7259195 2.9705274
265 7.6155578 -21.7259195
266 -1.4485770 7.6155578
267 7.6613761 -1.4485770
268 -0.5416404 7.6613761
269 3.1749980 -0.5416404
270 -32.9320338 3.1749980
271 -7.3802296 -32.9320338
272 -5.8007200 -7.3802296
273 2.4246758 -5.8007200
274 -4.2451931 2.4246758
275 -3.2484134 -4.2451931
276 26.0551397 -3.2484134
277 6.9019088 26.0551397
278 34.8377740 6.9019088
279 10.7198716 34.8377740
280 1.5168551 10.7198716
281 6.1315436 1.5168551
282 -44.9754881 6.1315436
283 -5.9529317 -44.9754881
284 -8.3734221 -5.9529317
285 3.4441743 -8.3734221
286 7.7743054 3.4441743
287 -1.1074666 7.7743054
288 -19.8039135 -1.1074666
289 4.1492629 -19.8039135
290 -8.9148719 4.1492629
291 3.7872818 -8.9148719
292 -3.4157347 3.7872818
293 -0.5971465 -3.4157347
294 -36.7041782 -0.5971465
295 -11.1523740 -36.7041782
296 -5.5728645 -11.1523740
297 -0.9396693 -5.5728645
298 -4.6095382 -0.9396693
299 -6.3069089 -4.6095382
300 22.9966442 -6.3069089
301 3.8434134 22.9966442
302 29.7792785 3.8434134
303 7.4574764 29.7792785
304 -6.7455401 7.4574764
305 2.3593992 -6.7455401
306 -40.7476326 2.3593992
307 -8.9094773 -40.7476326
308 -12.3299678 -8.9094773
309 0.3856788 -12.3299678
310 0.7158099 0.3856788
311 -4.5737615 0.7158099
312 -23.2702084 -4.5737615
313 0.6829680 -23.2702084
314 -13.3811668 0.6829680
315 0.2190371 -13.3811668
316 -12.9839795 0.2190371
317 -4.7770903 -12.9839795
318 -31.8841220 -4.7770903
319 -14.4147692 -31.8841220
320 -13.8352596 -14.4147692
321 -4.7118137 -13.8352596
322 -7.3816826 -4.7118137
323 -9.9771035 -7.3816826
324 19.3264496 -9.9771035
325 0.1732188 19.3264496
326 31.1090839 0.1732188
327 4.2970311 31.1090839
328 -9.9059855 4.2970311
329 -0.8010462 -9.9059855
330 -38.9080779 -0.8010462
331 -11.5601734 -38.9080779
332 -16.9806638 -11.5601734
333 -2.4689170 -16.9806638
334 -6.1387859 -2.4689170
335 -7.8361567 -6.1387859
336 -20.5326036 -7.8361567
337 -1.9677281 -20.5326036
338 -11.0318629 -1.9677281
339 -1.9219097 -11.0318629
340 -8.1249263 -1.9219097
341 -6.2043882 -8.1249263
342 -33.3114199 -6.2043882
343 -15.8420671 -33.3114199
344 -7.2625575 -15.8420671
345 -5.3235128 -7.2625575
346 -9.9933817 -5.3235128
347 -10.7927023 -9.9933817
348 22.5108508 -10.7927023
349 -0.2345806 22.5108508
350 23.7012845 -0.2345806
351 3.1755827 23.7012845
352 11.9725662 3.1755827
353 0.4223520 11.9725662
354 -31.6846797 0.4223520
355 -9.7250761 -31.6846797
356 -26.1455666 -9.7250761
357 -1.7552681 -26.1455666
358 -1.4251370 -1.7552681
359 -6.7147083 -1.4251370
360 -21.4111552 -6.7147083
361 -1.0501794 -21.4111552
362 -4.1143143 -1.0501794
363 -0.3926620 -4.1143143
364 0.4043214 -0.3926620
365 -3.9614915 0.4043214
366 -35.0685232 -3.9614915
367 -14.0069698 -35.0685232
368 -4.4274602 -14.0069698
369 -3.3864656 -4.4274602
370 -2.0563346 -3.3864656
371 -8.2439561 -2.0563346
372 33.0595970 -8.2439561
373 3.1297644 33.0595970
374 9.0656296 3.1297644
375 4.7048305 9.0656296
376 8.5018139 4.7048305
377 1.4418505 8.5018139
378 -24.6651812 1.4418505
379 -8.0938785 -24.6651812
380 -2.5143690 -8.0938785
381 2.1188262 -2.5143690
382 5.4489573 2.1188262
383 -2.5347645 5.4489573
384 -15.2312114 -2.5347645
385 3.3336641 -15.2312114
386 -0.7304707 3.3336641
387 3.8892317 -0.7304707
388 2.6862151 3.8892317
389 0.1165025 2.6862151
390 -22.9905292 0.1165025
391 -9.1133770 -22.9905292
392 -1.5338675 -9.1133770
393 1.3032274 -1.5338675
394 7.6333585 1.3032274
395 -3.0445137 7.6333585
396 39.2590394 -3.0445137
397 8.4311566 39.2590394
398 17.3670218 8.4311566
399 10.3120722 17.3670218
400 14.1090557 10.3120722
401 7.0490923 14.1090557
402 -28.0579395 7.0490923
403 -3.4041854 -28.0579395
404 -5.8246759 -3.4041854
405 5.9929205 -5.8246759
406 14.3230516 5.9929205
407 1.8490790 14.3230516
408 -10.8473679 1.8490790
409 6.7175076 -10.8473679
410 -0.4485770 6.7175076
411 -3.2366740 -0.4485770
412 5.4388611 -3.2366740
413 8.8691484 5.4388611
414 32.3738158 8.8691484
415 16.5523602 32.3738158
416 18.8650172 16.5523602
417 10.7216106 18.8650172
418 -4.1521580 10.7216106
419 6.8251232 -4.1521580
420 -17.7693739 6.8251232
421 8.6740533 -17.7693739
422 3.4060187 8.6740533
423 -0.2801284 3.4060187
424 9.3954067 -0.2801284
425 7.9276439 9.3954067
426 36.0245119 7.9276439
427 10.3050061 36.0245119
428 17.7001145 10.3050061
429 -1.7491417 17.7001145
430 -4.0502082 -1.7491417
431 7.9270730 -4.0502082
432 -17.5654742 7.9270730
433 7.8779530 -17.5654742
434 -1.4920314 7.8779530
435 4.3120722 -1.4920314
436 14.4973566 4.3120722
437 6.5393430 14.4973566
438 31.4323113 6.5393430
439 8.2030563 31.4323113
440 12.3942649 8.2030563
441 -18.5647405 12.3942649
442 -11.4970046 -18.5647405
443 -6.0294726 -11.4970046
444 -13.6434682 -6.0294726
445 -4.3844422 -13.6434682
446 -12.6719752 -4.3844422
447 -0.5815206 -12.6719752
448 -4.3962362 -0.5815206
449 -11.7815477 -4.3962362
450 32.8880224 -11.7815477
451 5.5763161 32.8880224
452 -10.8246759 5.5763161
453 -9.5168287 -10.8246759
454 -12.7159454 -9.5168287
455 1.2613358 -12.7159454
456 -19.0273117 1.2613358
457 -5.8702356 -19.0273117
458 -14.8519191 -5.8702356
459 -1.5575647 -14.8519191
460 -14.0664308 -1.5575647
461 4.9365586 -14.0664308
462 24.7470756 4.9365586
463 -1.1763299 24.7470756
464 -6.9851212 -1.1763299
465 -8.9636251 -6.9851212
466 -1.8568922 -8.9636251
467 10.4457370 -1.8568922
468 -9.8234120 10.4457370
469 9.2512128 -9.8234120
470 5.6968272 9.2512128
471 6.8262788 5.6968272
472 -1.2747879 6.8262788
473 13.5438004 -1.2747879
474 31.6601668 13.5438004
475 8.8387113 31.6601668
476 -0.5622807 8.8387113
477 -7.5407846 -0.5622807
478 2.0561990 -7.5407846
479 19.1549286 2.0561990
480 -10.8083709 19.1549286
481 4.5526049 -10.8083709
482 -5.0212792 4.5526049
483 -2.4210752 -5.0212792
484 -1.7455401 -2.4210752
485 10.8691484 -1.7455401
486 37.5777155 10.8691484
487 3.2660092 37.5777155
488 -1.8486317 3.2660092
489 -12.0310353 -1.8486317
490 -6.9438010 -12.0310353
491 3.2373799 -6.9438010
492 NA 3.2373799
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -26.9978103 274.5704656
[2,] -22.3872932 -26.9978103
[3,] -19.0734403 -22.3872932
[4,] -13.6842563 -19.0734403
[5,] -19.9481194 -13.6842563
[6,] 21.8428990 -19.9481194
[7,] -1.7551584 21.8428990
[8,] 2.8633482 -1.7551584
[9,] -8.7703092 2.8633482
[10,] -8.5421280 -8.7703092
[11,] -7.9336491 -8.5421280
[12,] -33.1203468 -7.9336491
[13,] -10.3710701 -33.1203468
[14,] -12.7410545 -10.3710701
[15,] -5.2233019 -12.7410545
[16,] -0.2224188 -5.2233019
[17,] -4.9765326 -0.2224188
[18,] 31.4261849 -4.9765326
[19,] 6.8281275 31.4261849
[20,] 9.3446842 6.8281275
[21,] -2.5948227 9.3446842
[22,] 2.3275090 -2.5948227
[23,] 3.1398875 2.3275090
[24,] -18.8429105 3.1398875
[25,] 1.4161155 -18.8429105
[26,] -6.7499692 1.4161155
[27,] -4.6400160 -6.7499692
[28,] 2.4433184 -4.6400160
[29,] -1.9224945 2.4433184
[30,] 38.9704738 -1.9224945
[31,] 12.3724164 38.9704738
[32,] 15.6850734 12.3724164
[33,] 7.6436166 15.6850734
[34,] 11.8717978 7.6436166
[35,] 8.8880760 11.8717978
[36,] -15.2986216 8.8880760
[37,] 3.5526049 -15.2986216
[38,] -4.1232290 3.5526049
[39,] 1.5789248 -4.1232290
[40,] 3.6622593 1.5789248
[41,] 2.7866971 3.6622593
[42,] 41.5777155 2.7866971
[43,] 23.6738086 41.5777155
[44,] 21.5981646 23.6738086
[45,] 9.5567079 21.5981646
[46,] 2.3770897 9.5567079
[47,] -0.1358798 2.3770897
[48,] -16.6479255 -0.1358798
[49,] -1.2044984 -16.6479255
[50,] -6.5939813 -1.2044984
[51,] -6.2996269 -6.5939813
[52,] 7.8661590 -6.2996269
[53,] -1.6016038 7.8661590
[54,] 42.6796653 -1.6016038
[55,] 29.8777083 42.6796653
[56,] 14.4137634 29.8777083
[57,] 6.5567079 14.4137634
[58,] 9.0712402 6.5567079
[59,] -4.7280804 9.0712402
[60,] 1.2501246 -4.7280804
[61,] -9.4713509 1.2501246
[62,] -16.8803323 -9.4713509
[63,] -14.7074263 -16.8803323
[64,] -5.3572392 -14.7074263
[65,] -20.0484002 -5.3572392
[66,] 26.6016714 -20.0484002
[67,] 8.5763161 26.6016714
[68,] 8.4811737 8.5763161
[69,] -3.2739320 8.4811737
[70,] -5.0652493 -3.2739320
[71,] 1.4217811 -5.0652493
[72,] -21.1727159 1.4217811
[73,] -13.5253890 -21.1727159
[74,] -14.5265710 -13.5253890
[75,] -11.3341665 -14.5265710
[76,] -1.9644810 -11.3341665
[77,] -6.7380933 -1.9644810
[78,] 19.7470756 -6.7380933
[79,] 0.3139209 19.7470756
[80,] 9.7090292 0.3139209
[81,] 12.4636728 9.7090292
[82,] -9.3905974 12.4636728
[83,] 6.7905836 -9.3905974
[84,] -22.0902645 6.7905836
[85,] -18.4429377 -22.0902645
[86,] -12.8519191 -18.4429377
[87,] -11.3536650 -12.8519191
[88,] -5.8820296 -11.3536650
[89,] -7.9614915 -5.8820296
[90,] 22.5236774 -7.9614915
[91,] -5.5016779 22.5236774
[92,] 5.3836812 -5.5016779
[93,] -2.1675248 5.3836812
[94,] -8.3471430 -2.1675248
[95,] -5.7581627 -8.3471430
[96,] -27.6585093 -5.7581627
[97,] -17.2150821 -27.6585093
[98,] -21.1143143 -17.2150821
[99,] -17.1258094 -21.1143143
[100,] -10.8580737 -17.1258094
[101,] -14.0394855 -10.8580737
[102,] 21.2417837 -14.0394855
[103,] -7.4777220 21.2417837
[104,] -7.3884632 -7.4777220
[105,] -11.8572179 -7.3884632
[106,] -11.5465853 -11.8572179
[107,] -9.7537053 -11.5465853
[108,] -34.5521021 -9.7537053
[109,] -19.3125746 -34.5521021
[110,] -15.9059572 -19.3125746
[111,] -26.8979539 -15.9059572
[112,] -13.2419173 -26.8979539
[113,] -17.2194293 -13.2419173
[114,] 13.1637897 -17.2194293
[115,] -2.9635154 13.1637897
[116,] -14.9567080 -2.9635154
[117,] -13.8332620 -14.9567080
[118,] -13.3187298 -13.8332620
[119,] -12.3219501 -13.3187298
[120,] -35.0183970 -12.3219501
[121,] -21.4730199 -35.0183970
[122,] -23.9644527 -21.4730199
[123,] -21.4661986 -23.9644527
[124,] -13.8926134 -21.4661986
[125,] -14.6662257 -13.8926134
[126,] 16.2267426 -14.6662257
[127,] -8.3908133 16.2267426
[128,] -5.7918053 -8.3908133
[129,] -9.5469110 -5.7918053
[130,] -10.5226295 -9.5469110
[131,] -6.2200002 -10.5226295
[132,] -31.3047480 -6.2200002
[133,] -10.4535214 -31.3047480
[134,] -21.9254557 -10.4535214
[135,] -15.4272016 -21.9254557
[136,] -10.4458170 -15.4272016
[137,] -11.1174795 -10.4458170
[138,] 18.8774386 -11.1174795
[139,] 0.2598828 18.8774386
[140,] -3.5294101 0.2598828
[141,] -2.3864656 -3.5294101
[142,] -6.9543847 -2.3864656
[143,] -1.6517555 -6.9543847
[144,] -25.6345534 -1.6517555
[145,] -12.5794272 -25.6345534
[146,] -13.6630605 -12.5794272
[147,] -7.6550572 -13.6630605
[148,] -7.2658731 -7.6550572
[149,] -2.0394855 -7.2658731
[150,] 22.4651819 -2.0394855
[151,] 6.7456761 22.4651819
[152,] 2.1602830 6.7456761
[153,] 0.4051773 2.1602830
[154,] 1.6333585 0.4051773
[155,] 10.3437872 1.6333585
[156,] -15.9253618 10.3437872
[157,] 2.5375638 -15.9253618
[158,] -6.6285209 2.5375638
[159,] 0.3794824 -6.6285209
[160,] 4.8706163 0.3794824
[161,] 5.6067532 4.8706163
[162,] 37.1114206 5.6067532
[163,] 19.1055638 37.1114206
[164,] 16.9279701 19.1055638
[165,] 2.7845635 16.9279701
[166,] 10.2990957 2.7845635
[167,] 11.0095244 10.2990957
[168,] -12.0752234 11.0095244
[169,] 10.9799028 -12.0752234
[170,] 0.9157680 10.9799028
[171,] 10.9237713 0.9157680
[172,] 2.7207548 10.9237713
[173,] 6.4373932 2.7207548
[174,] -24.6696386 6.4373932
[175,] -3.6080851 -24.6696386
[176,] 3.9714244 -3.6080851
[177,] 6.8085193 3.9714244
[178,] 6.1386504 6.8085193
[179,] 1.7471292 6.1386504
[180,] 29.0506823 1.7471292
[181,] 11.6935518 29.0506823
[182,] 30.6294169 11.6935518
[183,] 14.5939659 30.6294169
[184,] 15.3909493 14.5939659
[185,] 11.0251364 15.3909493
[186,] -22.0818953 11.0251364
[187,] 0.7757584 -22.0818953
[188,] 5.3552680 0.7757584
[189,] 10.8865133 5.3552680
[190,] 15.2166444 10.8865133
[191,] 6.3348724 15.2166444
[192,] -12.3615745 6.3348724
[193,] 11.5916019 -12.3615745
[194,] 1.5274671 11.5916019
[195,] 11.5354704 1.5274671
[196,] 0.3324539 11.5354704
[197,] 6.7432427 0.3324539
[198,] -23.3637890 6.7432427
[199,] -3.2002857 -23.3637890
[200,] 0.3792238 -3.2002857
[201,] 6.8085193 0.3792238
[202,] 7.1386504 6.8085193
[203,] 1.8490790 7.1386504
[204,] 35.1526321 1.8490790
[205,] 12.4072007 35.1526321
[206,] 33.3430659 12.4072007
[207,] 15.5115146 33.3430659
[208,] 19.3084980 15.5115146
[209,] 12.2485346 19.3084980
[210,] -14.8584971 12.2485346
[211,] 2.6108557 -14.8584971
[212,] 4.1903652 2.6108557
[213,] 12.4157610 4.1903652
[214,] 18.7458921 12.4157610
[215,] 8.0680199 18.7458921
[216,] -6.6284270 8.0680199
[217,] 13.7325488 -6.6284270
[218,] -5.3315861 13.7325488
[219,] 12.7588686 -5.3315861
[220,] -1.4441480 12.7588686
[221,] 7.6607914 -1.4441480
[222,] -24.4462404 7.6607914
[223,] -2.4866368 -24.4462404
[224,] -5.9071272 -2.4866368
[225,] 6.8085193 -5.9071272
[226,] -2.8613496 6.8085193
[227,] 0.8295805 -2.8613496
[228,] 35.1331336 0.8295805
[229,] 11.4896521 35.1331336
[230,] 30.4255172 11.4896521
[231,] 14.3900662 30.4255172
[232,] 8.1870496 14.3900662
[233,] 10.1075877 8.1870496
[234,] -29.9994440 10.1075877
[235,] -0.8554392 -29.9994440
[236,] 3.7240704 -0.8554392
[237,] 9.2553157 3.7240704
[238,] 10.5854468 9.2553157
[239,] 4.3978253 10.5854468
[240,] -16.2986216 4.3978253
[241,] 9.4506551 -16.2986216
[242,] 0.3865202 9.4506551
[243,] 9.4964734 0.3865202
[244,] 3.2934569 9.4964734
[245,] 5.2139950 3.2934569
[246,] -25.8930368 5.2139950
[247,] -4.8314833 -25.8930368
[248,] -3.2519738 -4.8314833
[249,] 4.9734220 -3.2519738
[250,] 9.3035531 4.9734220
[251,] 0.4217811 9.3035531
[252,] 27.7253342 0.4217811
[253,] 10.3682037 27.7253342
[254,] 27.3040689 10.3682037
[255,] 13.0647182 27.3040689
[256,] 10.8617016 13.0647182
[257,] 9.1900391 10.8617016
[258,] -33.9169926 9.1900391
[259,] -2.0788374 -33.9169926
[260,] -1.4993278 -2.0788374
[261,] 7.6241181 -1.4993278
[262,] 10.9542492 7.6241181
[263,] 2.9705274 10.9542492
[264,] -21.7259195 2.9705274
[265,] 7.6155578 -21.7259195
[266,] -1.4485770 7.6155578
[267,] 7.6613761 -1.4485770
[268,] -0.5416404 7.6613761
[269,] 3.1749980 -0.5416404
[270,] -32.9320338 3.1749980
[271,] -7.3802296 -32.9320338
[272,] -5.8007200 -7.3802296
[273,] 2.4246758 -5.8007200
[274,] -4.2451931 2.4246758
[275,] -3.2484134 -4.2451931
[276,] 26.0551397 -3.2484134
[277,] 6.9019088 26.0551397
[278,] 34.8377740 6.9019088
[279,] 10.7198716 34.8377740
[280,] 1.5168551 10.7198716
[281,] 6.1315436 1.5168551
[282,] -44.9754881 6.1315436
[283,] -5.9529317 -44.9754881
[284,] -8.3734221 -5.9529317
[285,] 3.4441743 -8.3734221
[286,] 7.7743054 3.4441743
[287,] -1.1074666 7.7743054
[288,] -19.8039135 -1.1074666
[289,] 4.1492629 -19.8039135
[290,] -8.9148719 4.1492629
[291,] 3.7872818 -8.9148719
[292,] -3.4157347 3.7872818
[293,] -0.5971465 -3.4157347
[294,] -36.7041782 -0.5971465
[295,] -11.1523740 -36.7041782
[296,] -5.5728645 -11.1523740
[297,] -0.9396693 -5.5728645
[298,] -4.6095382 -0.9396693
[299,] -6.3069089 -4.6095382
[300,] 22.9966442 -6.3069089
[301,] 3.8434134 22.9966442
[302,] 29.7792785 3.8434134
[303,] 7.4574764 29.7792785
[304,] -6.7455401 7.4574764
[305,] 2.3593992 -6.7455401
[306,] -40.7476326 2.3593992
[307,] -8.9094773 -40.7476326
[308,] -12.3299678 -8.9094773
[309,] 0.3856788 -12.3299678
[310,] 0.7158099 0.3856788
[311,] -4.5737615 0.7158099
[312,] -23.2702084 -4.5737615
[313,] 0.6829680 -23.2702084
[314,] -13.3811668 0.6829680
[315,] 0.2190371 -13.3811668
[316,] -12.9839795 0.2190371
[317,] -4.7770903 -12.9839795
[318,] -31.8841220 -4.7770903
[319,] -14.4147692 -31.8841220
[320,] -13.8352596 -14.4147692
[321,] -4.7118137 -13.8352596
[322,] -7.3816826 -4.7118137
[323,] -9.9771035 -7.3816826
[324,] 19.3264496 -9.9771035
[325,] 0.1732188 19.3264496
[326,] 31.1090839 0.1732188
[327,] 4.2970311 31.1090839
[328,] -9.9059855 4.2970311
[329,] -0.8010462 -9.9059855
[330,] -38.9080779 -0.8010462
[331,] -11.5601734 -38.9080779
[332,] -16.9806638 -11.5601734
[333,] -2.4689170 -16.9806638
[334,] -6.1387859 -2.4689170
[335,] -7.8361567 -6.1387859
[336,] -20.5326036 -7.8361567
[337,] -1.9677281 -20.5326036
[338,] -11.0318629 -1.9677281
[339,] -1.9219097 -11.0318629
[340,] -8.1249263 -1.9219097
[341,] -6.2043882 -8.1249263
[342,] -33.3114199 -6.2043882
[343,] -15.8420671 -33.3114199
[344,] -7.2625575 -15.8420671
[345,] -5.3235128 -7.2625575
[346,] -9.9933817 -5.3235128
[347,] -10.7927023 -9.9933817
[348,] 22.5108508 -10.7927023
[349,] -0.2345806 22.5108508
[350,] 23.7012845 -0.2345806
[351,] 3.1755827 23.7012845
[352,] 11.9725662 3.1755827
[353,] 0.4223520 11.9725662
[354,] -31.6846797 0.4223520
[355,] -9.7250761 -31.6846797
[356,] -26.1455666 -9.7250761
[357,] -1.7552681 -26.1455666
[358,] -1.4251370 -1.7552681
[359,] -6.7147083 -1.4251370
[360,] -21.4111552 -6.7147083
[361,] -1.0501794 -21.4111552
[362,] -4.1143143 -1.0501794
[363,] -0.3926620 -4.1143143
[364,] 0.4043214 -0.3926620
[365,] -3.9614915 0.4043214
[366,] -35.0685232 -3.9614915
[367,] -14.0069698 -35.0685232
[368,] -4.4274602 -14.0069698
[369,] -3.3864656 -4.4274602
[370,] -2.0563346 -3.3864656
[371,] -8.2439561 -2.0563346
[372,] 33.0595970 -8.2439561
[373,] 3.1297644 33.0595970
[374,] 9.0656296 3.1297644
[375,] 4.7048305 9.0656296
[376,] 8.5018139 4.7048305
[377,] 1.4418505 8.5018139
[378,] -24.6651812 1.4418505
[379,] -8.0938785 -24.6651812
[380,] -2.5143690 -8.0938785
[381,] 2.1188262 -2.5143690
[382,] 5.4489573 2.1188262
[383,] -2.5347645 5.4489573
[384,] -15.2312114 -2.5347645
[385,] 3.3336641 -15.2312114
[386,] -0.7304707 3.3336641
[387,] 3.8892317 -0.7304707
[388,] 2.6862151 3.8892317
[389,] 0.1165025 2.6862151
[390,] -22.9905292 0.1165025
[391,] -9.1133770 -22.9905292
[392,] -1.5338675 -9.1133770
[393,] 1.3032274 -1.5338675
[394,] 7.6333585 1.3032274
[395,] -3.0445137 7.6333585
[396,] 39.2590394 -3.0445137
[397,] 8.4311566 39.2590394
[398,] 17.3670218 8.4311566
[399,] 10.3120722 17.3670218
[400,] 14.1090557 10.3120722
[401,] 7.0490923 14.1090557
[402,] -28.0579395 7.0490923
[403,] -3.4041854 -28.0579395
[404,] -5.8246759 -3.4041854
[405,] 5.9929205 -5.8246759
[406,] 14.3230516 5.9929205
[407,] 1.8490790 14.3230516
[408,] -10.8473679 1.8490790
[409,] 6.7175076 -10.8473679
[410,] -0.4485770 6.7175076
[411,] -3.2366740 -0.4485770
[412,] 5.4388611 -3.2366740
[413,] 8.8691484 5.4388611
[414,] 32.3738158 8.8691484
[415,] 16.5523602 32.3738158
[416,] 18.8650172 16.5523602
[417,] 10.7216106 18.8650172
[418,] -4.1521580 10.7216106
[419,] 6.8251232 -4.1521580
[420,] -17.7693739 6.8251232
[421,] 8.6740533 -17.7693739
[422,] 3.4060187 8.6740533
[423,] -0.2801284 3.4060187
[424,] 9.3954067 -0.2801284
[425,] 7.9276439 9.3954067
[426,] 36.0245119 7.9276439
[427,] 10.3050061 36.0245119
[428,] 17.7001145 10.3050061
[429,] -1.7491417 17.7001145
[430,] -4.0502082 -1.7491417
[431,] 7.9270730 -4.0502082
[432,] -17.5654742 7.9270730
[433,] 7.8779530 -17.5654742
[434,] -1.4920314 7.8779530
[435,] 4.3120722 -1.4920314
[436,] 14.4973566 4.3120722
[437,] 6.5393430 14.4973566
[438,] 31.4323113 6.5393430
[439,] 8.2030563 31.4323113
[440,] 12.3942649 8.2030563
[441,] -18.5647405 12.3942649
[442,] -11.4970046 -18.5647405
[443,] -6.0294726 -11.4970046
[444,] -13.6434682 -6.0294726
[445,] -4.3844422 -13.6434682
[446,] -12.6719752 -4.3844422
[447,] -0.5815206 -12.6719752
[448,] -4.3962362 -0.5815206
[449,] -11.7815477 -4.3962362
[450,] 32.8880224 -11.7815477
[451,] 5.5763161 32.8880224
[452,] -10.8246759 5.5763161
[453,] -9.5168287 -10.8246759
[454,] -12.7159454 -9.5168287
[455,] 1.2613358 -12.7159454
[456,] -19.0273117 1.2613358
[457,] -5.8702356 -19.0273117
[458,] -14.8519191 -5.8702356
[459,] -1.5575647 -14.8519191
[460,] -14.0664308 -1.5575647
[461,] 4.9365586 -14.0664308
[462,] 24.7470756 4.9365586
[463,] -1.1763299 24.7470756
[464,] -6.9851212 -1.1763299
[465,] -8.9636251 -6.9851212
[466,] -1.8568922 -8.9636251
[467,] 10.4457370 -1.8568922
[468,] -9.8234120 10.4457370
[469,] 9.2512128 -9.8234120
[470,] 5.6968272 9.2512128
[471,] 6.8262788 5.6968272
[472,] -1.2747879 6.8262788
[473,] 13.5438004 -1.2747879
[474,] 31.6601668 13.5438004
[475,] 8.8387113 31.6601668
[476,] -0.5622807 8.8387113
[477,] -7.5407846 -0.5622807
[478,] 2.0561990 -7.5407846
[479,] 19.1549286 2.0561990
[480,] -10.8083709 19.1549286
[481,] 4.5526049 -10.8083709
[482,] -5.0212792 4.5526049
[483,] -2.4210752 -5.0212792
[484,] -1.7455401 -2.4210752
[485,] 10.8691484 -1.7455401
[486,] 37.5777155 10.8691484
[487,] 3.2660092 37.5777155
[488,] -1.8486317 3.2660092
[489,] -12.0310353 -1.8486317
[490,] -6.9438010 -12.0310353
[491,] 3.2373799 -6.9438010
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -26.9978103 274.5704656
2 -22.3872932 -26.9978103
3 -19.0734403 -22.3872932
4 -13.6842563 -19.0734403
5 -19.9481194 -13.6842563
6 21.8428990 -19.9481194
7 -1.7551584 21.8428990
8 2.8633482 -1.7551584
9 -8.7703092 2.8633482
10 -8.5421280 -8.7703092
11 -7.9336491 -8.5421280
12 -33.1203468 -7.9336491
13 -10.3710701 -33.1203468
14 -12.7410545 -10.3710701
15 -5.2233019 -12.7410545
16 -0.2224188 -5.2233019
17 -4.9765326 -0.2224188
18 31.4261849 -4.9765326
19 6.8281275 31.4261849
20 9.3446842 6.8281275
21 -2.5948227 9.3446842
22 2.3275090 -2.5948227
23 3.1398875 2.3275090
24 -18.8429105 3.1398875
25 1.4161155 -18.8429105
26 -6.7499692 1.4161155
27 -4.6400160 -6.7499692
28 2.4433184 -4.6400160
29 -1.9224945 2.4433184
30 38.9704738 -1.9224945
31 12.3724164 38.9704738
32 15.6850734 12.3724164
33 7.6436166 15.6850734
34 11.8717978 7.6436166
35 8.8880760 11.8717978
36 -15.2986216 8.8880760
37 3.5526049 -15.2986216
38 -4.1232290 3.5526049
39 1.5789248 -4.1232290
40 3.6622593 1.5789248
41 2.7866971 3.6622593
42 41.5777155 2.7866971
43 23.6738086 41.5777155
44 21.5981646 23.6738086
45 9.5567079 21.5981646
46 2.3770897 9.5567079
47 -0.1358798 2.3770897
48 -16.6479255 -0.1358798
49 -1.2044984 -16.6479255
50 -6.5939813 -1.2044984
51 -6.2996269 -6.5939813
52 7.8661590 -6.2996269
53 -1.6016038 7.8661590
54 42.6796653 -1.6016038
55 29.8777083 42.6796653
56 14.4137634 29.8777083
57 6.5567079 14.4137634
58 9.0712402 6.5567079
59 -4.7280804 9.0712402
60 1.2501246 -4.7280804
61 -9.4713509 1.2501246
62 -16.8803323 -9.4713509
63 -14.7074263 -16.8803323
64 -5.3572392 -14.7074263
65 -20.0484002 -5.3572392
66 26.6016714 -20.0484002
67 8.5763161 26.6016714
68 8.4811737 8.5763161
69 -3.2739320 8.4811737
70 -5.0652493 -3.2739320
71 1.4217811 -5.0652493
72 -21.1727159 1.4217811
73 -13.5253890 -21.1727159
74 -14.5265710 -13.5253890
75 -11.3341665 -14.5265710
76 -1.9644810 -11.3341665
77 -6.7380933 -1.9644810
78 19.7470756 -6.7380933
79 0.3139209 19.7470756
80 9.7090292 0.3139209
81 12.4636728 9.7090292
82 -9.3905974 12.4636728
83 6.7905836 -9.3905974
84 -22.0902645 6.7905836
85 -18.4429377 -22.0902645
86 -12.8519191 -18.4429377
87 -11.3536650 -12.8519191
88 -5.8820296 -11.3536650
89 -7.9614915 -5.8820296
90 22.5236774 -7.9614915
91 -5.5016779 22.5236774
92 5.3836812 -5.5016779
93 -2.1675248 5.3836812
94 -8.3471430 -2.1675248
95 -5.7581627 -8.3471430
96 -27.6585093 -5.7581627
97 -17.2150821 -27.6585093
98 -21.1143143 -17.2150821
99 -17.1258094 -21.1143143
100 -10.8580737 -17.1258094
101 -14.0394855 -10.8580737
102 21.2417837 -14.0394855
103 -7.4777220 21.2417837
104 -7.3884632 -7.4777220
105 -11.8572179 -7.3884632
106 -11.5465853 -11.8572179
107 -9.7537053 -11.5465853
108 -34.5521021 -9.7537053
109 -19.3125746 -34.5521021
110 -15.9059572 -19.3125746
111 -26.8979539 -15.9059572
112 -13.2419173 -26.8979539
113 -17.2194293 -13.2419173
114 13.1637897 -17.2194293
115 -2.9635154 13.1637897
116 -14.9567080 -2.9635154
117 -13.8332620 -14.9567080
118 -13.3187298 -13.8332620
119 -12.3219501 -13.3187298
120 -35.0183970 -12.3219501
121 -21.4730199 -35.0183970
122 -23.9644527 -21.4730199
123 -21.4661986 -23.9644527
124 -13.8926134 -21.4661986
125 -14.6662257 -13.8926134
126 16.2267426 -14.6662257
127 -8.3908133 16.2267426
128 -5.7918053 -8.3908133
129 -9.5469110 -5.7918053
130 -10.5226295 -9.5469110
131 -6.2200002 -10.5226295
132 -31.3047480 -6.2200002
133 -10.4535214 -31.3047480
134 -21.9254557 -10.4535214
135 -15.4272016 -21.9254557
136 -10.4458170 -15.4272016
137 -11.1174795 -10.4458170
138 18.8774386 -11.1174795
139 0.2598828 18.8774386
140 -3.5294101 0.2598828
141 -2.3864656 -3.5294101
142 -6.9543847 -2.3864656
143 -1.6517555 -6.9543847
144 -25.6345534 -1.6517555
145 -12.5794272 -25.6345534
146 -13.6630605 -12.5794272
147 -7.6550572 -13.6630605
148 -7.2658731 -7.6550572
149 -2.0394855 -7.2658731
150 22.4651819 -2.0394855
151 6.7456761 22.4651819
152 2.1602830 6.7456761
153 0.4051773 2.1602830
154 1.6333585 0.4051773
155 10.3437872 1.6333585
156 -15.9253618 10.3437872
157 2.5375638 -15.9253618
158 -6.6285209 2.5375638
159 0.3794824 -6.6285209
160 4.8706163 0.3794824
161 5.6067532 4.8706163
162 37.1114206 5.6067532
163 19.1055638 37.1114206
164 16.9279701 19.1055638
165 2.7845635 16.9279701
166 10.2990957 2.7845635
167 11.0095244 10.2990957
168 -12.0752234 11.0095244
169 10.9799028 -12.0752234
170 0.9157680 10.9799028
171 10.9237713 0.9157680
172 2.7207548 10.9237713
173 6.4373932 2.7207548
174 -24.6696386 6.4373932
175 -3.6080851 -24.6696386
176 3.9714244 -3.6080851
177 6.8085193 3.9714244
178 6.1386504 6.8085193
179 1.7471292 6.1386504
180 29.0506823 1.7471292
181 11.6935518 29.0506823
182 30.6294169 11.6935518
183 14.5939659 30.6294169
184 15.3909493 14.5939659
185 11.0251364 15.3909493
186 -22.0818953 11.0251364
187 0.7757584 -22.0818953
188 5.3552680 0.7757584
189 10.8865133 5.3552680
190 15.2166444 10.8865133
191 6.3348724 15.2166444
192 -12.3615745 6.3348724
193 11.5916019 -12.3615745
194 1.5274671 11.5916019
195 11.5354704 1.5274671
196 0.3324539 11.5354704
197 6.7432427 0.3324539
198 -23.3637890 6.7432427
199 -3.2002857 -23.3637890
200 0.3792238 -3.2002857
201 6.8085193 0.3792238
202 7.1386504 6.8085193
203 1.8490790 7.1386504
204 35.1526321 1.8490790
205 12.4072007 35.1526321
206 33.3430659 12.4072007
207 15.5115146 33.3430659
208 19.3084980 15.5115146
209 12.2485346 19.3084980
210 -14.8584971 12.2485346
211 2.6108557 -14.8584971
212 4.1903652 2.6108557
213 12.4157610 4.1903652
214 18.7458921 12.4157610
215 8.0680199 18.7458921
216 -6.6284270 8.0680199
217 13.7325488 -6.6284270
218 -5.3315861 13.7325488
219 12.7588686 -5.3315861
220 -1.4441480 12.7588686
221 7.6607914 -1.4441480
222 -24.4462404 7.6607914
223 -2.4866368 -24.4462404
224 -5.9071272 -2.4866368
225 6.8085193 -5.9071272
226 -2.8613496 6.8085193
227 0.8295805 -2.8613496
228 35.1331336 0.8295805
229 11.4896521 35.1331336
230 30.4255172 11.4896521
231 14.3900662 30.4255172
232 8.1870496 14.3900662
233 10.1075877 8.1870496
234 -29.9994440 10.1075877
235 -0.8554392 -29.9994440
236 3.7240704 -0.8554392
237 9.2553157 3.7240704
238 10.5854468 9.2553157
239 4.3978253 10.5854468
240 -16.2986216 4.3978253
241 9.4506551 -16.2986216
242 0.3865202 9.4506551
243 9.4964734 0.3865202
244 3.2934569 9.4964734
245 5.2139950 3.2934569
246 -25.8930368 5.2139950
247 -4.8314833 -25.8930368
248 -3.2519738 -4.8314833
249 4.9734220 -3.2519738
250 9.3035531 4.9734220
251 0.4217811 9.3035531
252 27.7253342 0.4217811
253 10.3682037 27.7253342
254 27.3040689 10.3682037
255 13.0647182 27.3040689
256 10.8617016 13.0647182
257 9.1900391 10.8617016
258 -33.9169926 9.1900391
259 -2.0788374 -33.9169926
260 -1.4993278 -2.0788374
261 7.6241181 -1.4993278
262 10.9542492 7.6241181
263 2.9705274 10.9542492
264 -21.7259195 2.9705274
265 7.6155578 -21.7259195
266 -1.4485770 7.6155578
267 7.6613761 -1.4485770
268 -0.5416404 7.6613761
269 3.1749980 -0.5416404
270 -32.9320338 3.1749980
271 -7.3802296 -32.9320338
272 -5.8007200 -7.3802296
273 2.4246758 -5.8007200
274 -4.2451931 2.4246758
275 -3.2484134 -4.2451931
276 26.0551397 -3.2484134
277 6.9019088 26.0551397
278 34.8377740 6.9019088
279 10.7198716 34.8377740
280 1.5168551 10.7198716
281 6.1315436 1.5168551
282 -44.9754881 6.1315436
283 -5.9529317 -44.9754881
284 -8.3734221 -5.9529317
285 3.4441743 -8.3734221
286 7.7743054 3.4441743
287 -1.1074666 7.7743054
288 -19.8039135 -1.1074666
289 4.1492629 -19.8039135
290 -8.9148719 4.1492629
291 3.7872818 -8.9148719
292 -3.4157347 3.7872818
293 -0.5971465 -3.4157347
294 -36.7041782 -0.5971465
295 -11.1523740 -36.7041782
296 -5.5728645 -11.1523740
297 -0.9396693 -5.5728645
298 -4.6095382 -0.9396693
299 -6.3069089 -4.6095382
300 22.9966442 -6.3069089
301 3.8434134 22.9966442
302 29.7792785 3.8434134
303 7.4574764 29.7792785
304 -6.7455401 7.4574764
305 2.3593992 -6.7455401
306 -40.7476326 2.3593992
307 -8.9094773 -40.7476326
308 -12.3299678 -8.9094773
309 0.3856788 -12.3299678
310 0.7158099 0.3856788
311 -4.5737615 0.7158099
312 -23.2702084 -4.5737615
313 0.6829680 -23.2702084
314 -13.3811668 0.6829680
315 0.2190371 -13.3811668
316 -12.9839795 0.2190371
317 -4.7770903 -12.9839795
318 -31.8841220 -4.7770903
319 -14.4147692 -31.8841220
320 -13.8352596 -14.4147692
321 -4.7118137 -13.8352596
322 -7.3816826 -4.7118137
323 -9.9771035 -7.3816826
324 19.3264496 -9.9771035
325 0.1732188 19.3264496
326 31.1090839 0.1732188
327 4.2970311 31.1090839
328 -9.9059855 4.2970311
329 -0.8010462 -9.9059855
330 -38.9080779 -0.8010462
331 -11.5601734 -38.9080779
332 -16.9806638 -11.5601734
333 -2.4689170 -16.9806638
334 -6.1387859 -2.4689170
335 -7.8361567 -6.1387859
336 -20.5326036 -7.8361567
337 -1.9677281 -20.5326036
338 -11.0318629 -1.9677281
339 -1.9219097 -11.0318629
340 -8.1249263 -1.9219097
341 -6.2043882 -8.1249263
342 -33.3114199 -6.2043882
343 -15.8420671 -33.3114199
344 -7.2625575 -15.8420671
345 -5.3235128 -7.2625575
346 -9.9933817 -5.3235128
347 -10.7927023 -9.9933817
348 22.5108508 -10.7927023
349 -0.2345806 22.5108508
350 23.7012845 -0.2345806
351 3.1755827 23.7012845
352 11.9725662 3.1755827
353 0.4223520 11.9725662
354 -31.6846797 0.4223520
355 -9.7250761 -31.6846797
356 -26.1455666 -9.7250761
357 -1.7552681 -26.1455666
358 -1.4251370 -1.7552681
359 -6.7147083 -1.4251370
360 -21.4111552 -6.7147083
361 -1.0501794 -21.4111552
362 -4.1143143 -1.0501794
363 -0.3926620 -4.1143143
364 0.4043214 -0.3926620
365 -3.9614915 0.4043214
366 -35.0685232 -3.9614915
367 -14.0069698 -35.0685232
368 -4.4274602 -14.0069698
369 -3.3864656 -4.4274602
370 -2.0563346 -3.3864656
371 -8.2439561 -2.0563346
372 33.0595970 -8.2439561
373 3.1297644 33.0595970
374 9.0656296 3.1297644
375 4.7048305 9.0656296
376 8.5018139 4.7048305
377 1.4418505 8.5018139
378 -24.6651812 1.4418505
379 -8.0938785 -24.6651812
380 -2.5143690 -8.0938785
381 2.1188262 -2.5143690
382 5.4489573 2.1188262
383 -2.5347645 5.4489573
384 -15.2312114 -2.5347645
385 3.3336641 -15.2312114
386 -0.7304707 3.3336641
387 3.8892317 -0.7304707
388 2.6862151 3.8892317
389 0.1165025 2.6862151
390 -22.9905292 0.1165025
391 -9.1133770 -22.9905292
392 -1.5338675 -9.1133770
393 1.3032274 -1.5338675
394 7.6333585 1.3032274
395 -3.0445137 7.6333585
396 39.2590394 -3.0445137
397 8.4311566 39.2590394
398 17.3670218 8.4311566
399 10.3120722 17.3670218
400 14.1090557 10.3120722
401 7.0490923 14.1090557
402 -28.0579395 7.0490923
403 -3.4041854 -28.0579395
404 -5.8246759 -3.4041854
405 5.9929205 -5.8246759
406 14.3230516 5.9929205
407 1.8490790 14.3230516
408 -10.8473679 1.8490790
409 6.7175076 -10.8473679
410 -0.4485770 6.7175076
411 -3.2366740 -0.4485770
412 5.4388611 -3.2366740
413 8.8691484 5.4388611
414 32.3738158 8.8691484
415 16.5523602 32.3738158
416 18.8650172 16.5523602
417 10.7216106 18.8650172
418 -4.1521580 10.7216106
419 6.8251232 -4.1521580
420 -17.7693739 6.8251232
421 8.6740533 -17.7693739
422 3.4060187 8.6740533
423 -0.2801284 3.4060187
424 9.3954067 -0.2801284
425 7.9276439 9.3954067
426 36.0245119 7.9276439
427 10.3050061 36.0245119
428 17.7001145 10.3050061
429 -1.7491417 17.7001145
430 -4.0502082 -1.7491417
431 7.9270730 -4.0502082
432 -17.5654742 7.9270730
433 7.8779530 -17.5654742
434 -1.4920314 7.8779530
435 4.3120722 -1.4920314
436 14.4973566 4.3120722
437 6.5393430 14.4973566
438 31.4323113 6.5393430
439 8.2030563 31.4323113
440 12.3942649 8.2030563
441 -18.5647405 12.3942649
442 -11.4970046 -18.5647405
443 -6.0294726 -11.4970046
444 -13.6434682 -6.0294726
445 -4.3844422 -13.6434682
446 -12.6719752 -4.3844422
447 -0.5815206 -12.6719752
448 -4.3962362 -0.5815206
449 -11.7815477 -4.3962362
450 32.8880224 -11.7815477
451 5.5763161 32.8880224
452 -10.8246759 5.5763161
453 -9.5168287 -10.8246759
454 -12.7159454 -9.5168287
455 1.2613358 -12.7159454
456 -19.0273117 1.2613358
457 -5.8702356 -19.0273117
458 -14.8519191 -5.8702356
459 -1.5575647 -14.8519191
460 -14.0664308 -1.5575647
461 4.9365586 -14.0664308
462 24.7470756 4.9365586
463 -1.1763299 24.7470756
464 -6.9851212 -1.1763299
465 -8.9636251 -6.9851212
466 -1.8568922 -8.9636251
467 10.4457370 -1.8568922
468 -9.8234120 10.4457370
469 9.2512128 -9.8234120
470 5.6968272 9.2512128
471 6.8262788 5.6968272
472 -1.2747879 6.8262788
473 13.5438004 -1.2747879
474 31.6601668 13.5438004
475 8.8387113 31.6601668
476 -0.5622807 8.8387113
477 -7.5407846 -0.5622807
478 2.0561990 -7.5407846
479 19.1549286 2.0561990
480 -10.8083709 19.1549286
481 4.5526049 -10.8083709
482 -5.0212792 4.5526049
483 -2.4210752 -5.0212792
484 -1.7455401 -2.4210752
485 10.8691484 -1.7455401
486 37.5777155 10.8691484
487 3.2660092 37.5777155
488 -1.8486317 3.2660092
489 -12.0310353 -1.8486317
490 -6.9438010 -12.0310353
491 3.2373799 -6.9438010
> 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/rcomp/tmp/70h4j1296734019.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/rcomp/tmp/8ppyt1296734019.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/rcomp/tmp/9098c1296734019.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/rcomp/tmp/107olx1296734019.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/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/11gafd1296734019.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/124f5f1296734019.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/13o9oe1296734019.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/14vu7u1296734019.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/rcomp/tmp/15b16d1296734019.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/rcomp/tmp/16cgvx1296734019.tab")
+ }
>
> try(system("convert tmp/1ck5i1296734019.ps tmp/1ck5i1296734019.png",intern=TRUE))
character(0)
> try(system("convert tmp/28jgw1296734019.ps tmp/28jgw1296734019.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bgjv1296734019.ps tmp/3bgjv1296734019.png",intern=TRUE))
character(0)
> try(system("convert tmp/475c31296734019.ps tmp/475c31296734019.png",intern=TRUE))
character(0)
> try(system("convert tmp/5l22c1296734019.ps tmp/5l22c1296734019.png",intern=TRUE))
character(0)
> try(system("convert tmp/60hyi1296734019.ps tmp/60hyi1296734019.png",intern=TRUE))
character(0)
> try(system("convert tmp/70h4j1296734019.ps tmp/70h4j1296734019.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ppyt1296734019.ps tmp/8ppyt1296734019.png",intern=TRUE))
character(0)
> try(system("convert tmp/9098c1296734019.ps tmp/9098c1296734019.png",intern=TRUE))
character(0)
> try(system("convert tmp/107olx1296734019.ps tmp/107olx1296734019.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
14.010 0.550 14.537