R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-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(14
+ ,501
+ ,11
+ ,20
+ ,91.81
+ ,77585
+ ,1303.2
+ ,2000
+ ,14
+ ,485
+ ,11
+ ,19
+ ,91.98
+ ,77585
+ ,-58.7
+ ,2000
+ ,15
+ ,464
+ ,11
+ ,18
+ ,91.72
+ ,77585
+ ,-378.9
+ ,2000
+ ,13
+ ,460
+ ,11
+ ,13
+ ,90.27
+ ,78302
+ ,175.6
+ ,2001
+ ,8
+ ,467
+ ,11
+ ,17
+ ,91.89
+ ,78302
+ ,233.7
+ ,2001
+ ,7
+ ,460
+ ,9
+ ,17
+ ,92.07
+ ,78302
+ ,706.8
+ ,2001
+ ,3
+ ,448
+ ,8
+ ,13
+ ,92.92
+ ,78224
+ ,-23.6
+ ,2001
+ ,3
+ ,443
+ ,6
+ ,14
+ ,93.34
+ ,78224
+ ,420.9
+ ,2001
+ ,4
+ ,436
+ ,7
+ ,13
+ ,93.6
+ ,78224
+ ,722.1
+ ,2001
+ ,4
+ ,431
+ ,8
+ ,17
+ ,92.41
+ ,78178
+ ,1401.3
+ ,2001
+ ,0
+ ,484
+ ,6
+ ,17
+ ,93.6
+ ,78178
+ ,-94.9
+ ,2001
+ ,-4
+ ,510
+ ,5
+ ,15
+ ,93.77
+ ,78178
+ ,1043.6
+ ,2001
+ ,-14
+ ,513
+ ,2
+ ,9
+ ,93.6
+ ,77988
+ ,1300.1
+ ,2001
+ ,-18
+ ,503
+ ,3
+ ,10
+ ,93.6
+ ,77988
+ ,721.1
+ ,2001
+ ,-8
+ ,471
+ ,3
+ ,9
+ ,93.51
+ ,77988
+ ,-45.6
+ ,2001
+ ,-1
+ ,471
+ ,7
+ ,14
+ ,92.66
+ ,77876
+ ,787.5
+ ,2002
+ ,1
+ ,476
+ ,8
+ ,18
+ ,94.2
+ ,77876
+ ,694.3
+ ,2002
+ ,2
+ ,475
+ ,7
+ ,18
+ ,94.37
+ ,77876
+ ,1054.7
+ ,2002
+ ,0
+ ,470
+ ,7
+ ,12
+ ,94.45
+ ,78432
+ ,821.9
+ ,2002
+ ,1
+ ,461
+ ,6
+ ,16
+ ,94.62
+ ,78432
+ ,1100.7
+ ,2002
+ ,0
+ ,455
+ ,6
+ ,12
+ ,94.37
+ ,78432
+ ,862.4
+ ,2002
+ ,-1
+ ,456
+ ,7
+ ,19
+ ,93.43
+ ,79025
+ ,1656.1
+ ,2002
+ ,-3
+ ,517
+ ,5
+ ,13
+ ,94.79
+ ,79025
+ ,-174
+ ,2002
+ ,-3
+ ,525
+ ,5
+ ,12
+ ,94.88
+ ,79025
+ ,1337.6
+ ,2002
+ ,-3
+ ,523
+ ,5
+ ,13
+ ,94.79
+ ,79407
+ ,1394.9
+ ,2002
+ ,-4
+ ,519
+ ,4
+ ,11
+ ,94.62
+ ,79407
+ ,915.7
+ ,2002
+ ,-8
+ ,509
+ ,4
+ ,10
+ ,94.71
+ ,79407
+ ,-481.1
+ ,2002
+ ,-9
+ ,512
+ ,4
+ ,16
+ ,93.77
+ ,79644
+ ,167.9
+ ,2003
+ ,-13
+ ,519
+ ,1
+ ,12
+ ,95.73
+ ,79644
+ ,208.2
+ ,2003
+ ,-18
+ ,517
+ ,-1
+ ,6
+ ,95.99
+ ,79644
+ ,382.2
+ ,2003
+ ,-11
+ ,510
+ ,3
+ ,8
+ ,95.82
+ ,79381
+ ,1004
+ ,2003
+ ,-9
+ ,509
+ ,4
+ ,6
+ ,95.47
+ ,79381
+ ,864.7
+ ,2003
+ ,-10
+ ,501
+ ,3
+ ,8
+ ,95.82
+ ,79381
+ ,1052.9
+ ,2003
+ ,-13
+ ,507
+ ,2
+ ,8
+ ,94.71
+ ,79536
+ ,1417.6
+ ,2003
+ ,-11
+ ,569
+ ,1
+ ,9
+ ,96.33
+ ,79536
+ ,-197.7
+ ,2003
+ ,-5
+ ,580
+ ,4
+ ,13
+ ,96.5
+ ,79536
+ ,1262.1
+ ,2003
+ ,-15
+ ,578
+ ,3
+ ,8
+ ,96.16
+ ,79813
+ ,1147.2
+ ,2003
+ ,-6
+ ,565
+ ,5
+ ,11
+ ,96.33
+ ,79813
+ ,700.2
+ ,2003
+ ,-6
+ ,547
+ ,6
+ ,8
+ ,96.33
+ ,79813
+ ,45.3
+ ,2003
+ ,-3
+ ,555
+ ,6
+ ,10
+ ,95.05
+ ,80332
+ ,458.5
+ ,2004
+ ,-1
+ ,562
+ ,6
+ ,15
+ ,96.84
+ ,80332
+ ,610.2
+ ,2004
+ ,-3
+ ,561
+ ,6
+ ,12
+ ,96.92
+ ,80332
+ ,786.4
+ ,2004
+ ,-4
+ ,555
+ ,6
+ ,13
+ ,97.44
+ ,81434
+ ,787.2
+ ,2004
+ ,-6
+ ,544
+ ,5
+ ,12
+ ,97.78
+ ,81434
+ ,1040
+ ,2004
+ ,0
+ ,537
+ ,6
+ ,15
+ ,97.69
+ ,81434
+ ,324.1
+ ,2004
+ ,-4
+ ,543
+ ,5
+ ,13
+ ,96.67
+ ,82167
+ ,1343
+ ,2004
+ ,-2
+ ,594
+ ,6
+ ,13
+ ,98.29
+ ,82167
+ ,-501.2
+ ,2004
+ ,-2
+ ,611
+ ,5
+ ,16
+ ,98.2
+ ,82167
+ ,800.4
+ ,2004
+ ,-6
+ ,613
+ ,7
+ ,14
+ ,98.71
+ ,82816
+ ,916.7
+ ,2004
+ ,-7
+ ,611
+ ,4
+ ,12
+ ,98.54
+ ,82816
+ ,695.8
+ ,2004
+ ,-6
+ ,594
+ ,5
+ ,15
+ ,98.2
+ ,82816
+ ,28
+ ,2004
+ ,-6
+ ,595
+ ,6
+ ,14
+ ,96.92
+ ,83000
+ ,495.6
+ ,2005
+ ,-3
+ ,591
+ ,6
+ ,19
+ ,99.06
+ ,83000
+ ,366.2
+ ,2005
+ ,-2
+ ,589
+ ,5
+ ,16
+ ,99.65
+ ,83000
+ ,633
+ ,2005
+ ,-5
+ ,584
+ ,3
+ ,16
+ ,99.82
+ ,83251
+ ,848.3
+ ,2005
+ ,-11
+ ,573
+ ,2
+ ,11
+ ,99.99
+ ,83251
+ ,472.2
+ ,2005
+ ,-11
+ ,567
+ ,3
+ ,13
+ ,100.33
+ ,83251
+ ,357.8
+ ,2005
+ ,-11
+ ,569
+ ,3
+ ,12
+ ,99.31
+ ,83591
+ ,824.3
+ ,2005
+ ,-10
+ ,621
+ ,2
+ ,11
+ ,101.1
+ ,83591
+ ,-880.1
+ ,2005
+ ,-14
+ ,629
+ ,0
+ ,6
+ ,101.1
+ ,83591
+ ,1066.8
+ ,2005
+ ,-8
+ ,628
+ ,4
+ ,9
+ ,100.93
+ ,83910
+ ,1052.8
+ ,2005
+ ,-9
+ ,612
+ ,4
+ ,6
+ ,100.85
+ ,83910
+ ,-32.1
+ ,2005
+ ,-5
+ ,595
+ ,5
+ ,15
+ ,100.93
+ ,83910
+ ,-1331.4
+ ,2005
+ ,-1
+ ,597
+ ,6
+ ,17
+ ,99.6
+ ,84599
+ ,-767.1
+ ,2006
+ ,-2
+ ,593
+ ,6
+ ,13
+ ,101.88
+ ,84599
+ ,-236.7
+ ,2006
+ ,-5
+ ,590
+ ,5
+ ,12
+ ,101.81
+ ,84599
+ ,-184.9
+ ,2006
+ ,-4
+ ,580
+ ,5
+ ,13
+ ,102.38
+ ,85275
+ ,-143.4
+ ,2006
+ ,-6
+ ,574
+ ,3
+ ,10
+ ,102.74
+ ,85275
+ ,493.9
+ ,2006
+ ,-2
+ ,573
+ ,5
+ ,14
+ ,102.82
+ ,85275
+ ,549.7
+ ,2006
+ ,-2
+ ,573
+ ,5
+ ,13
+ ,101.72
+ ,85608
+ ,982.7
+ ,2006
+ ,-2
+ ,620
+ ,5
+ ,10
+ ,103.47
+ ,85608
+ ,-856.3
+ ,2006
+ ,-2
+ ,626
+ ,3
+ ,11
+ ,102.98
+ ,85608
+ ,967
+ ,2006
+ ,2
+ ,620
+ ,6
+ ,12
+ ,102.68
+ ,86303
+ ,659.4
+ ,2006
+ ,1
+ ,588
+ ,6
+ ,7
+ ,102.9
+ ,86303
+ ,577.2
+ ,2006
+ ,-8
+ ,566
+ ,4
+ ,11
+ ,103.03
+ ,86303
+ ,-213.1
+ ,2006
+ ,-1
+ ,557
+ ,6
+ ,9
+ ,101.29
+ ,87115
+ ,17.7
+ ,2007
+ ,1
+ ,561
+ ,5
+ ,13
+ ,103.69
+ ,87115
+ ,390.1
+ ,2007
+ ,-1
+ ,549
+ ,4
+ ,12
+ ,103.68
+ ,87115
+ ,509.3
+ ,2007
+ ,2
+ ,532
+ ,5
+ ,5
+ ,104.2
+ ,87931
+ ,410
+ ,2007
+ ,2
+ ,526
+ ,5
+ ,13
+ ,104.08
+ ,87931
+ ,212.5
+ ,2007
+ ,1
+ ,511
+ ,4
+ ,11
+ ,104.16
+ ,87931
+ ,818
+ ,2007
+ ,-1
+ ,499
+ ,3
+ ,8
+ ,103.05
+ ,88164
+ ,422.7
+ ,2007
+ ,-2
+ ,555
+ ,2
+ ,8
+ ,104.66
+ ,88164
+ ,-158
+ ,2007
+ ,-2
+ ,565
+ ,3
+ ,8
+ ,104.46
+ ,88164
+ ,427.2
+ ,2007
+ ,-1
+ ,542
+ ,2
+ ,8
+ ,104.95
+ ,88792
+ ,243.4
+ ,2007
+ ,-8
+ ,527
+ ,-1
+ ,0
+ ,105.85
+ ,88792
+ ,-419.3
+ ,2007
+ ,-4
+ ,510
+ ,0
+ ,3
+ ,106.23
+ ,88792
+ ,-1459.8
+ ,2007
+ ,-6
+ ,514
+ ,-2
+ ,0
+ ,104.86
+ ,89263
+ ,-1389.8
+ ,2008
+ ,-3
+ ,517
+ ,1
+ ,-1
+ ,107.44
+ ,89263
+ ,-2.1
+ ,2008
+ ,-3
+ ,508
+ ,-2
+ ,-1
+ ,108.23
+ ,89263
+ ,-938.6
+ ,2008
+ ,-7
+ ,493
+ ,-2
+ ,-4
+ ,108.45
+ ,89881
+ ,-839.9
+ ,2008
+ ,-9
+ ,490
+ ,-2
+ ,1
+ ,109.39
+ ,89881
+ ,-297.6
+ ,2008
+ ,-11
+ ,469
+ ,-6
+ ,-1
+ ,110.15
+ ,89881
+ ,-376.3
+ ,2008
+ ,-13
+ ,478
+ ,-4
+ ,0
+ ,109.13
+ ,90120
+ ,-79.4
+ ,2008
+ ,-11
+ ,528
+ ,-2
+ ,-1
+ ,110.28
+ ,90120
+ ,-2091.3
+ ,2008
+ ,-9
+ ,534
+ ,0
+ ,6
+ ,110.17
+ ,90120
+ ,-1023
+ ,2008
+ ,-17
+ ,518
+ ,-5
+ ,0
+ ,109.99
+ ,89703
+ ,-765.6
+ ,2008
+ ,-22
+ ,506
+ ,-4
+ ,-3
+ ,109.26
+ ,89703
+ ,-1592.3
+ ,2008
+ ,-25
+ ,502
+ ,-5
+ ,-3
+ ,109.11
+ ,89703
+ ,-1588.8
+ ,2008
+ ,-20
+ ,516
+ ,-1
+ ,4
+ ,107.06
+ ,87818
+ ,-1318
+ ,2009
+ ,-24
+ ,528
+ ,-2
+ ,1
+ ,109.53
+ ,87818
+ ,-402.4
+ ,2009
+ ,-24
+ ,533
+ ,-4
+ ,0
+ ,108.92
+ ,87818
+ ,-814.5
+ ,2009
+ ,-22
+ ,536
+ ,-1
+ ,-4
+ ,109.24
+ ,86273
+ ,-98.4
+ ,2009
+ ,-19
+ ,537
+ ,1
+ ,-2
+ ,109.12
+ ,86273
+ ,-305.9
+ ,2009
+ ,-18
+ ,524
+ ,1
+ ,3
+ ,109
+ ,86273
+ ,-18.4
+ ,2009
+ ,-17
+ ,536
+ ,-2
+ ,2
+ ,107.23
+ ,86316
+ ,610.3
+ ,2009
+ ,-11
+ ,587
+ ,1
+ ,5
+ ,109.49
+ ,86316
+ ,-917.3
+ ,2009
+ ,-11
+ ,597
+ ,1
+ ,6
+ ,109.04
+ ,86316
+ ,88.4
+ ,2009
+ ,-12
+ ,581
+ ,3
+ ,6
+ ,109.02
+ ,87234
+ ,-740.2
+ ,2009
+ ,-10
+ ,564
+ ,3
+ ,3
+ ,109.23
+ ,87234
+ ,29.3
+ ,2009
+ ,-15
+ ,558
+ ,1
+ ,4
+ ,109.46
+ ,87234
+ ,-893.2
+ ,2009
+ ,-15
+ ,575
+ ,1
+ ,7
+ ,107.9
+ ,87885
+ ,-1030.2
+ ,2010
+ ,-15
+ ,580
+ ,0
+ ,5
+ ,110.42
+ ,87885
+ ,-403.4
+ ,2010
+ ,-13
+ ,575
+ ,2
+ ,6
+ ,110.98
+ ,87885
+ ,-46.9
+ ,2010
+ ,-8
+ ,563
+ ,2
+ ,1
+ ,111.48
+ ,88003
+ ,-321.2
+ ,2010
+ ,-13
+ ,552
+ ,-1
+ ,3
+ ,111.88
+ ,88003
+ ,-239.9
+ ,2010
+ ,-9
+ ,537
+ ,1
+ ,6
+ ,111.89
+ ,88003
+ ,640.9
+ ,2010
+ ,-7
+ ,545
+ ,0
+ ,0
+ ,109.85
+ ,88910
+ ,511.6
+ ,2010
+ ,-4
+ ,601
+ ,1
+ ,3
+ ,112.1
+ ,88910
+ ,-665.1
+ ,2010
+ ,-4
+ ,604
+ ,1
+ ,4
+ ,112.24
+ ,88910
+ ,657.7
+ ,2010
+ ,-2
+ ,586
+ ,3
+ ,7
+ ,112.39
+ ,89397
+ ,-207.7
+ ,2010
+ ,0
+ ,564
+ ,2
+ ,6
+ ,112.52
+ ,89397
+ ,-885.2
+ ,2010
+ ,-2
+ ,549
+ ,0
+ ,6
+ ,113.16
+ ,89397
+ ,-1595.8
+ ,2010
+ ,-3
+ ,551
+ ,0
+ ,6
+ ,111.84
+ ,89813
+ ,-1374.9
+ ,2011
+ ,1
+ ,556
+ ,3
+ ,6
+ ,114.33
+ ,89813
+ ,-316.6
+ ,2011
+ ,-2
+ ,548
+ ,-2
+ ,2
+ ,114.82
+ ,89813
+ ,-283.4
+ ,2011
+ ,-1
+ ,540
+ ,0
+ ,2
+ ,115.2
+ ,90539
+ ,-175.8
+ ,2011
+ ,1
+ ,531
+ ,1
+ ,2
+ ,115.4
+ ,90539
+ ,-694.2
+ ,2011
+ ,-3
+ ,521
+ ,-1
+ ,3
+ ,115.74
+ ,90539
+ ,-249.9
+ ,2011
+ ,-4
+ ,519
+ ,-2
+ ,-1
+ ,114.19
+ ,90688
+ ,268.2
+ ,2011
+ ,-9
+ ,572
+ ,-1
+ ,-4
+ ,115.94
+ ,90688
+ ,-2105.1
+ ,2011
+ ,-9
+ ,581
+ ,-1
+ ,4
+ ,116.03
+ ,90688
+ ,-762.8
+ ,2011
+ ,-7
+ ,563
+ ,1
+ ,5
+ ,116.24
+ ,90691
+ ,-117.1
+ ,2011
+ ,-14
+ ,548
+ ,-2
+ ,3
+ ,116.66
+ ,90691
+ ,-1094.4
+ ,2011
+ ,-12
+ ,539
+ ,-5
+ ,-1
+ ,116.79
+ ,90691
+ ,-2095.2
+ ,2011
+ ,-16
+ ,541
+ ,-5
+ ,-4
+ ,115.48
+ ,90645
+ ,-1587.6
+ ,2012
+ ,-20
+ ,562
+ ,-6
+ ,0
+ ,118.16
+ ,90645
+ ,-528
+ ,2012
+ ,-12
+ ,559
+ ,-4
+ ,-1
+ ,118.38
+ ,90645
+ ,-324.2
+ ,2012
+ ,-12
+ ,546
+ ,-3
+ ,-1
+ ,118.51
+ ,90861
+ ,-276.1
+ ,2012
+ ,-10
+ ,536
+ ,-3
+ ,3
+ ,118.42
+ ,90861
+ ,-139.1
+ ,2012
+ ,-10
+ ,528
+ ,-1
+ ,2
+ ,118.24
+ ,90861
+ ,268
+ ,2012
+ ,-13
+ ,530
+ ,-2
+ ,-4
+ ,116.47
+ ,90401
+ ,570.5
+ ,2012
+ ,-16
+ ,582
+ ,-3
+ ,-3
+ ,118.96
+ ,90401
+ ,-316.5
+ ,2012)
+ ,dim=c(8
+ ,143)
+ ,dimnames=list(c('i'
+ ,'w'
+ ,'f'
+ ,'s'
+ ,'c'
+ ,'b'
+ ,'h'
+ ,'t')
+ ,1:143))
> y <- array(NA,dim=c(8,143),dimnames=list(c('i','w','f','s','c','b','h','t'),1:143))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
i w f s c b h t
1 14 501 11 20 91.81 77585 1303.2 2000
2 14 485 11 19 91.98 77585 -58.7 2000
3 15 464 11 18 91.72 77585 -378.9 2000
4 13 460 11 13 90.27 78302 175.6 2001
5 8 467 11 17 91.89 78302 233.7 2001
6 7 460 9 17 92.07 78302 706.8 2001
7 3 448 8 13 92.92 78224 -23.6 2001
8 3 443 6 14 93.34 78224 420.9 2001
9 4 436 7 13 93.60 78224 722.1 2001
10 4 431 8 17 92.41 78178 1401.3 2001
11 0 484 6 17 93.60 78178 -94.9 2001
12 -4 510 5 15 93.77 78178 1043.6 2001
13 -14 513 2 9 93.60 77988 1300.1 2001
14 -18 503 3 10 93.60 77988 721.1 2001
15 -8 471 3 9 93.51 77988 -45.6 2001
16 -1 471 7 14 92.66 77876 787.5 2002
17 1 476 8 18 94.20 77876 694.3 2002
18 2 475 7 18 94.37 77876 1054.7 2002
19 0 470 7 12 94.45 78432 821.9 2002
20 1 461 6 16 94.62 78432 1100.7 2002
21 0 455 6 12 94.37 78432 862.4 2002
22 -1 456 7 19 93.43 79025 1656.1 2002
23 -3 517 5 13 94.79 79025 -174.0 2002
24 -3 525 5 12 94.88 79025 1337.6 2002
25 -3 523 5 13 94.79 79407 1394.9 2002
26 -4 519 4 11 94.62 79407 915.7 2002
27 -8 509 4 10 94.71 79407 -481.1 2002
28 -9 512 4 16 93.77 79644 167.9 2003
29 -13 519 1 12 95.73 79644 208.2 2003
30 -18 517 -1 6 95.99 79644 382.2 2003
31 -11 510 3 8 95.82 79381 1004.0 2003
32 -9 509 4 6 95.47 79381 864.7 2003
33 -10 501 3 8 95.82 79381 1052.9 2003
34 -13 507 2 8 94.71 79536 1417.6 2003
35 -11 569 1 9 96.33 79536 -197.7 2003
36 -5 580 4 13 96.50 79536 1262.1 2003
37 -15 578 3 8 96.16 79813 1147.2 2003
38 -6 565 5 11 96.33 79813 700.2 2003
39 -6 547 6 8 96.33 79813 45.3 2003
40 -3 555 6 10 95.05 80332 458.5 2004
41 -1 562 6 15 96.84 80332 610.2 2004
42 -3 561 6 12 96.92 80332 786.4 2004
43 -4 555 6 13 97.44 81434 787.2 2004
44 -6 544 5 12 97.78 81434 1040.0 2004
45 0 537 6 15 97.69 81434 324.1 2004
46 -4 543 5 13 96.67 82167 1343.0 2004
47 -2 594 6 13 98.29 82167 -501.2 2004
48 -2 611 5 16 98.20 82167 800.4 2004
49 -6 613 7 14 98.71 82816 916.7 2004
50 -7 611 4 12 98.54 82816 695.8 2004
51 -6 594 5 15 98.20 82816 28.0 2004
52 -6 595 6 14 96.92 83000 495.6 2005
53 -3 591 6 19 99.06 83000 366.2 2005
54 -2 589 5 16 99.65 83000 633.0 2005
55 -5 584 3 16 99.82 83251 848.3 2005
56 -11 573 2 11 99.99 83251 472.2 2005
57 -11 567 3 13 100.33 83251 357.8 2005
58 -11 569 3 12 99.31 83591 824.3 2005
59 -10 621 2 11 101.10 83591 -880.1 2005
60 -14 629 0 6 101.10 83591 1066.8 2005
61 -8 628 4 9 100.93 83910 1052.8 2005
62 -9 612 4 6 100.85 83910 -32.1 2005
63 -5 595 5 15 100.93 83910 -1331.4 2005
64 -1 597 6 17 99.60 84599 -767.1 2006
65 -2 593 6 13 101.88 84599 -236.7 2006
66 -5 590 5 12 101.81 84599 -184.9 2006
67 -4 580 5 13 102.38 85275 -143.4 2006
68 -6 574 3 10 102.74 85275 493.9 2006
69 -2 573 5 14 102.82 85275 549.7 2006
70 -2 573 5 13 101.72 85608 982.7 2006
71 -2 620 5 10 103.47 85608 -856.3 2006
72 -2 626 3 11 102.98 85608 967.0 2006
73 2 620 6 12 102.68 86303 659.4 2006
74 1 588 6 7 102.90 86303 577.2 2006
75 -8 566 4 11 103.03 86303 -213.1 2006
76 -1 557 6 9 101.29 87115 17.7 2007
77 1 561 5 13 103.69 87115 390.1 2007
78 -1 549 4 12 103.68 87115 509.3 2007
79 2 532 5 5 104.20 87931 410.0 2007
80 2 526 5 13 104.08 87931 212.5 2007
81 1 511 4 11 104.16 87931 818.0 2007
82 -1 499 3 8 103.05 88164 422.7 2007
83 -2 555 2 8 104.66 88164 -158.0 2007
84 -2 565 3 8 104.46 88164 427.2 2007
85 -1 542 2 8 104.95 88792 243.4 2007
86 -8 527 -1 0 105.85 88792 -419.3 2007
87 -4 510 0 3 106.23 88792 -1459.8 2007
88 -6 514 -2 0 104.86 89263 -1389.8 2008
89 -3 517 1 -1 107.44 89263 -2.1 2008
90 -3 508 -2 -1 108.23 89263 -938.6 2008
91 -7 493 -2 -4 108.45 89881 -839.9 2008
92 -9 490 -2 1 109.39 89881 -297.6 2008
93 -11 469 -6 -1 110.15 89881 -376.3 2008
94 -13 478 -4 0 109.13 90120 -79.4 2008
95 -11 528 -2 -1 110.28 90120 -2091.3 2008
96 -9 534 0 6 110.17 90120 -1023.0 2008
97 -17 518 -5 0 109.99 89703 -765.6 2008
98 -22 506 -4 -3 109.26 89703 -1592.3 2008
99 -25 502 -5 -3 109.11 89703 -1588.8 2008
100 -20 516 -1 4 107.06 87818 -1318.0 2009
101 -24 528 -2 1 109.53 87818 -402.4 2009
102 -24 533 -4 0 108.92 87818 -814.5 2009
103 -22 536 -1 -4 109.24 86273 -98.4 2009
104 -19 537 1 -2 109.12 86273 -305.9 2009
105 -18 524 1 3 109.00 86273 -18.4 2009
106 -17 536 -2 2 107.23 86316 610.3 2009
107 -11 587 1 5 109.49 86316 -917.3 2009
108 -11 597 1 6 109.04 86316 88.4 2009
109 -12 581 3 6 109.02 87234 -740.2 2009
110 -10 564 3 3 109.23 87234 29.3 2009
111 -15 558 1 4 109.46 87234 -893.2 2009
112 -15 575 1 7 107.90 87885 -1030.2 2010
113 -15 580 0 5 110.42 87885 -403.4 2010
114 -13 575 2 6 110.98 87885 -46.9 2010
115 -8 563 2 1 111.48 88003 -321.2 2010
116 -13 552 -1 3 111.88 88003 -239.9 2010
117 -9 537 1 6 111.89 88003 640.9 2010
118 -7 545 0 0 109.85 88910 511.6 2010
119 -4 601 1 3 112.10 88910 -665.1 2010
120 -4 604 1 4 112.24 88910 657.7 2010
121 -2 586 3 7 112.39 89397 -207.7 2010
122 0 564 2 6 112.52 89397 -885.2 2010
123 -2 549 0 6 113.16 89397 -1595.8 2010
124 -3 551 0 6 111.84 89813 -1374.9 2011
125 1 556 3 6 114.33 89813 -316.6 2011
126 -2 548 -2 2 114.82 89813 -283.4 2011
127 -1 540 0 2 115.20 90539 -175.8 2011
128 1 531 1 2 115.40 90539 -694.2 2011
129 -3 521 -1 3 115.74 90539 -249.9 2011
130 -4 519 -2 -1 114.19 90688 268.2 2011
131 -9 572 -1 -4 115.94 90688 -2105.1 2011
132 -9 581 -1 4 116.03 90688 -762.8 2011
133 -7 563 1 5 116.24 90691 -117.1 2011
134 -14 548 -2 3 116.66 90691 -1094.4 2011
135 -12 539 -5 -1 116.79 90691 -2095.2 2011
136 -16 541 -5 -4 115.48 90645 -1587.6 2012
137 -20 562 -6 0 118.16 90645 -528.0 2012
138 -12 559 -4 -1 118.38 90645 -324.2 2012
139 -12 546 -3 -1 118.51 90861 -276.1 2012
140 -10 536 -3 3 118.42 90861 -139.1 2012
141 -10 528 -1 2 118.24 90861 268.0 2012
142 -13 530 -2 -4 116.47 90401 570.5 2012
143 -16 582 -3 -3 118.96 90401 -316.5 2012
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) w f s c b
4.403e+03 -4.349e-02 2.129e+00 2.826e-01 8.835e-01 1.410e-03
h t
3.437e-04 -2.295e+00
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-9.6622 -1.6906 -0.0062 2.0253 9.9879
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.403e+03 1.080e+03 4.078 7.71e-05 ***
w -4.349e-02 8.056e-03 -5.398 2.94e-07 ***
f 2.129e+00 1.791e-01 11.890 < 2e-16 ***
s 2.826e-01 1.160e-01 2.436 0.016145 *
c 8.835e-01 2.347e-01 3.764 0.000249 ***
b 1.410e-03 2.313e-04 6.095 1.08e-08 ***
h 3.437e-04 4.854e-04 0.708 0.480111
t -2.295e+00 5.522e-01 -4.156 5.71e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.632 on 135 degrees of freedom
Multiple R-squared: 0.7769, Adjusted R-squared: 0.7653
F-statistic: 67.14 on 7 and 135 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,] 2.692015e-02 5.384029e-02 0.9730799
[2,] 2.490341e-02 4.980682e-02 0.9750966
[3,] 1.841393e-02 3.682787e-02 0.9815861
[4,] 7.114683e-02 1.422937e-01 0.9288532
[5,] 1.147504e-01 2.295008e-01 0.8852496
[6,] 3.835415e-01 7.670830e-01 0.6164585
[7,] 2.855458e-01 5.710915e-01 0.7144542
[8,] 2.467588e-01 4.935175e-01 0.7532412
[9,] 1.984699e-01 3.969399e-01 0.8015301
[10,] 1.724399e-01 3.448799e-01 0.8275601
[11,] 1.384509e-01 2.769019e-01 0.8615491
[12,] 1.101201e-01 2.202402e-01 0.8898799
[13,] 1.065984e-01 2.131968e-01 0.8934016
[14,] 9.227595e-02 1.845519e-01 0.9077240
[15,] 6.556393e-02 1.311279e-01 0.9344361
[16,] 5.638054e-02 1.127611e-01 0.9436195
[17,] 4.627827e-02 9.255654e-02 0.9537217
[18,] 3.106155e-02 6.212309e-02 0.9689385
[19,] 2.625375e-02 5.250750e-02 0.9737463
[20,] 2.309107e-02 4.618214e-02 0.9769089
[21,] 1.578347e-02 3.156694e-02 0.9842165
[22,] 1.062154e-02 2.124307e-02 0.9893785
[23,] 6.641805e-03 1.328361e-02 0.9933582
[24,] 4.281396e-03 8.562792e-03 0.9957186
[25,] 6.784667e-03 1.356933e-02 0.9932153
[26,] 5.274357e-03 1.054871e-02 0.9947256
[27,] 9.518807e-03 1.903761e-02 0.9904812
[28,] 7.546206e-03 1.509241e-02 0.9924538
[29,] 9.272145e-03 1.854429e-02 0.9907279
[30,] 8.719271e-03 1.743854e-02 0.9912807
[31,] 7.764672e-03 1.552934e-02 0.9922353
[32,] 6.792912e-03 1.358582e-02 0.9932071
[33,] 6.999820e-03 1.399964e-02 0.9930002
[34,] 5.462231e-03 1.092446e-02 0.9945378
[35,] 5.649750e-03 1.129950e-02 0.9943502
[36,] 4.271786e-03 8.543571e-03 0.9957282
[37,] 4.024836e-03 8.049672e-03 0.9959752
[38,] 3.619052e-03 7.238104e-03 0.9963809
[39,] 1.085207e-02 2.170414e-02 0.9891479
[40,] 7.728554e-03 1.545711e-02 0.9922714
[41,] 6.063352e-03 1.212670e-02 0.9939366
[42,] 4.718469e-03 9.436938e-03 0.9952815
[43,] 3.372120e-03 6.744240e-03 0.9966279
[44,] 3.596657e-03 7.193314e-03 0.9964033
[45,] 4.714145e-03 9.428289e-03 0.9952859
[46,] 3.527960e-03 7.055920e-03 0.9964720
[47,] 3.037540e-03 6.075081e-03 0.9969625
[48,] 2.088147e-03 4.176293e-03 0.9979119
[49,] 1.701647e-03 3.403294e-03 0.9982984
[50,] 2.489404e-03 4.978808e-03 0.9975106
[51,] 1.639965e-03 3.279930e-03 0.9983600
[52,] 1.132530e-03 2.265060e-03 0.9988675
[53,] 1.042651e-03 2.085302e-03 0.9989573
[54,] 7.830871e-04 1.566174e-03 0.9992169
[55,] 5.699267e-04 1.139853e-03 0.9994301
[56,] 3.968281e-04 7.936563e-04 0.9996032
[57,] 2.524025e-04 5.048050e-04 0.9997476
[58,] 2.415299e-04 4.830598e-04 0.9997585
[59,] 1.712272e-04 3.424543e-04 0.9998288
[60,] 1.174546e-04 2.349092e-04 0.9998825
[61,] 1.001034e-04 2.002068e-04 0.9998999
[62,] 4.877816e-04 9.755633e-04 0.9995122
[63,] 4.120660e-04 8.241320e-04 0.9995879
[64,] 3.124966e-04 6.249932e-04 0.9996875
[65,] 3.772519e-04 7.545039e-04 0.9996227
[66,] 2.828506e-04 5.657012e-04 0.9997171
[67,] 2.177719e-04 4.355437e-04 0.9997822
[68,] 1.650368e-04 3.300735e-04 0.9998350
[69,] 1.286550e-04 2.573100e-04 0.9998713
[70,] 8.058574e-05 1.611715e-04 0.9999194
[71,] 5.286963e-05 1.057393e-04 0.9999471
[72,] 3.926956e-05 7.853912e-05 0.9999607
[73,] 4.215524e-05 8.431047e-05 0.9999578
[74,] 2.846665e-05 5.693330e-05 0.9999715
[75,] 2.265809e-05 4.531617e-05 0.9999773
[76,] 1.688392e-05 3.376784e-05 0.9999831
[77,] 1.674135e-05 3.348269e-05 0.9999833
[78,] 5.764476e-05 1.152895e-04 0.9999424
[79,] 3.870047e-05 7.740095e-05 0.9999613
[80,] 3.790103e-04 7.580206e-04 0.9996210
[81,] 3.846345e-04 7.692690e-04 0.9996154
[82,] 2.951325e-04 5.902649e-04 0.9997049
[83,] 1.036969e-03 2.073939e-03 0.9989630
[84,] 9.561382e-04 1.912276e-03 0.9990439
[85,] 1.034967e-03 2.069933e-03 0.9989650
[86,] 1.367709e-03 2.735417e-03 0.9986323
[87,] 1.225621e-03 2.451241e-03 0.9987744
[88,] 3.334917e-03 6.669835e-03 0.9966651
[89,] 1.107110e-02 2.214220e-02 0.9889289
[90,] 2.233560e-02 4.467121e-02 0.9776644
[91,] 7.770671e-02 1.554134e-01 0.9222933
[92,] 1.237915e-01 2.475830e-01 0.8762085
[93,] 1.023444e-01 2.046887e-01 0.8976556
[94,] 8.908305e-02 1.781661e-01 0.9109169
[95,] 9.123883e-02 1.824777e-01 0.9087612
[96,] 8.528516e-02 1.705703e-01 0.9147148
[97,] 1.321982e-01 2.643964e-01 0.8678018
[98,] 2.048386e-01 4.096772e-01 0.7951614
[99,] 1.937417e-01 3.874834e-01 0.8062583
[100,] 1.694934e-01 3.389868e-01 0.8305066
[101,] 1.946455e-01 3.892910e-01 0.8053545
[102,] 2.527041e-01 5.054082e-01 0.7472959
[103,] 2.585771e-01 5.171542e-01 0.7414229
[104,] 3.644799e-01 7.289597e-01 0.6355201
[105,] 3.326531e-01 6.653063e-01 0.6673469
[106,] 3.339945e-01 6.679890e-01 0.6660055
[107,] 5.196545e-01 9.606910e-01 0.4803455
[108,] 7.260560e-01 5.478880e-01 0.2739440
[109,] 7.125259e-01 5.749482e-01 0.2874741
[110,] 6.771880e-01 6.456240e-01 0.3228120
[111,] 6.592167e-01 6.815666e-01 0.3407833
[112,] 6.396251e-01 7.207498e-01 0.3603749
[113,] 6.880738e-01 6.238523e-01 0.3119262
[114,] 6.502526e-01 6.994949e-01 0.3497474
[115,] 5.889855e-01 8.220290e-01 0.4110145
[116,] 6.217699e-01 7.564603e-01 0.3782301
[117,] 6.206603e-01 7.586793e-01 0.3793397
[118,] 7.090018e-01 5.819964e-01 0.2909982
[119,] 8.336129e-01 3.327743e-01 0.1663871
[120,] 7.720518e-01 4.558964e-01 0.2279482
[121,] 6.466484e-01 7.067032e-01 0.3533516
[122,] 5.120713e-01 9.758574e-01 0.4879287
> postscript(file="/var/wessaorg/rcomp/tmp/13noz1355497170.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/wessaorg/rcomp/tmp/2v0fr1355497170.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3wbsg1355497170.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4ttdo1355497170.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5ivuh1355497170.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 143
Frequency = 1
1 2 3 4 5 6
2.955230897 2.859918310 3.569037523 5.183048216 -2.094352140 0.537871167
7 8 9 10 11 12
-1.114239840 2.120104681 0.635953435 -1.958448387 0.067668496 -0.648640863
13 14 15 16 17 18
-2.104932375 -8.752624861 0.481368272 0.469257770 -1.901583519 0.910007056
19 20 21 22 23 24
-0.386133612 0.974987732 1.147418946 -4.195154342 1.839338053 1.870868606
25 26 27 28 29 30
1.022472501 2.857842704 -0.893855607 -0.890853111 1.186088561 1.763771937
31 32 33 34 35 36
-0.315223925 0.434542670 0.276560144 0.303442402 5.970208189 4.278664438
37 38 39 40 41 42
-2.316598607 1.015238541 -0.823692459 4.511189173 3.768776002 2.441994085
43 44 45 46 47 48
-1.115018255 -1.568891881 1.475154083 -0.051956348 1.239457046 2.892148140
49 50 51 52 53 54
-6.119449353 -0.027592000 -2.214102474 -1.011219650 -1.444634969 1.832512149
55 56 57 58 59 60
2.295264251 -0.661672768 -3.878122208 -3.247029716 1.430562311 2.780876570
61 62 63 64 65 66
-0.921882353 -1.326225348 -2.362656582 1.334701219 -0.905332462 -1.579970595
67 68 69 70 71 72
-2.768480547 -0.460284782 -1.982509954 -1.346334440 0.631564724 4.674400939
73 74 75 76 77 78
1.134264036 -0.010288595 -6.682615525 -1.158758442 -0.234637690 -0.376859906
79 80 81 82 83 84
0.157426995 -2.190803731 -1.427498649 -0.184257846 2.157469600 0.438799487
85 86 87 88 89 90
1.312499765 1.741380004 2.046844555 8.144438154 2.413768603 8.033686010
91 92 93 94 95 96
3.129661670 -1.430923256 4.093240657 -1.594125589 -1.719813753 -5.965677741
97 98 99 100 101 102
-1.661418380 -7.535410201 -8.448906898 -6.664215519 -9.662171862 -4.223222195
103 104 105 106 107 108
-5.700093638 -7.302848146 -8.274252283 1.204786055 0.715719567 0.919894562
109 110 111 112 113 114
-6.026080096 -4.367467469 -5.538923089 -2.844911912 -2.374863570 -5.750529137
115 116 117 118 119 120
-0.373009788 -0.410613910 -2.480749493 4.260182568 5.135082268 4.404579595
121 122 123 124 125 126
-0.006193083 3.566813982 4.851535419 6.737428091 2.003816231 9.987873534
127 128 129 130 131 132
4.985360326 4.466279259 3.553922654 6.707956713 2.001288166 -0.409342978
133 134 135 136 137 138
-4.144778595 -4.879586576 4.476133646 4.753983688 -0.066130259 3.563352354
139 140 141 142 143
0.432913217 0.899848131 -3.404592107 -0.384191267 -1.171278003
> postscript(file="/var/wessaorg/rcomp/tmp/6dbp21355497170.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 = 143
Frequency = 1
lag(myerror, k = 1) myerror
0 2.955230897 NA
1 2.859918310 2.955230897
2 3.569037523 2.859918310
3 5.183048216 3.569037523
4 -2.094352140 5.183048216
5 0.537871167 -2.094352140
6 -1.114239840 0.537871167
7 2.120104681 -1.114239840
8 0.635953435 2.120104681
9 -1.958448387 0.635953435
10 0.067668496 -1.958448387
11 -0.648640863 0.067668496
12 -2.104932375 -0.648640863
13 -8.752624861 -2.104932375
14 0.481368272 -8.752624861
15 0.469257770 0.481368272
16 -1.901583519 0.469257770
17 0.910007056 -1.901583519
18 -0.386133612 0.910007056
19 0.974987732 -0.386133612
20 1.147418946 0.974987732
21 -4.195154342 1.147418946
22 1.839338053 -4.195154342
23 1.870868606 1.839338053
24 1.022472501 1.870868606
25 2.857842704 1.022472501
26 -0.893855607 2.857842704
27 -0.890853111 -0.893855607
28 1.186088561 -0.890853111
29 1.763771937 1.186088561
30 -0.315223925 1.763771937
31 0.434542670 -0.315223925
32 0.276560144 0.434542670
33 0.303442402 0.276560144
34 5.970208189 0.303442402
35 4.278664438 5.970208189
36 -2.316598607 4.278664438
37 1.015238541 -2.316598607
38 -0.823692459 1.015238541
39 4.511189173 -0.823692459
40 3.768776002 4.511189173
41 2.441994085 3.768776002
42 -1.115018255 2.441994085
43 -1.568891881 -1.115018255
44 1.475154083 -1.568891881
45 -0.051956348 1.475154083
46 1.239457046 -0.051956348
47 2.892148140 1.239457046
48 -6.119449353 2.892148140
49 -0.027592000 -6.119449353
50 -2.214102474 -0.027592000
51 -1.011219650 -2.214102474
52 -1.444634969 -1.011219650
53 1.832512149 -1.444634969
54 2.295264251 1.832512149
55 -0.661672768 2.295264251
56 -3.878122208 -0.661672768
57 -3.247029716 -3.878122208
58 1.430562311 -3.247029716
59 2.780876570 1.430562311
60 -0.921882353 2.780876570
61 -1.326225348 -0.921882353
62 -2.362656582 -1.326225348
63 1.334701219 -2.362656582
64 -0.905332462 1.334701219
65 -1.579970595 -0.905332462
66 -2.768480547 -1.579970595
67 -0.460284782 -2.768480547
68 -1.982509954 -0.460284782
69 -1.346334440 -1.982509954
70 0.631564724 -1.346334440
71 4.674400939 0.631564724
72 1.134264036 4.674400939
73 -0.010288595 1.134264036
74 -6.682615525 -0.010288595
75 -1.158758442 -6.682615525
76 -0.234637690 -1.158758442
77 -0.376859906 -0.234637690
78 0.157426995 -0.376859906
79 -2.190803731 0.157426995
80 -1.427498649 -2.190803731
81 -0.184257846 -1.427498649
82 2.157469600 -0.184257846
83 0.438799487 2.157469600
84 1.312499765 0.438799487
85 1.741380004 1.312499765
86 2.046844555 1.741380004
87 8.144438154 2.046844555
88 2.413768603 8.144438154
89 8.033686010 2.413768603
90 3.129661670 8.033686010
91 -1.430923256 3.129661670
92 4.093240657 -1.430923256
93 -1.594125589 4.093240657
94 -1.719813753 -1.594125589
95 -5.965677741 -1.719813753
96 -1.661418380 -5.965677741
97 -7.535410201 -1.661418380
98 -8.448906898 -7.535410201
99 -6.664215519 -8.448906898
100 -9.662171862 -6.664215519
101 -4.223222195 -9.662171862
102 -5.700093638 -4.223222195
103 -7.302848146 -5.700093638
104 -8.274252283 -7.302848146
105 1.204786055 -8.274252283
106 0.715719567 1.204786055
107 0.919894562 0.715719567
108 -6.026080096 0.919894562
109 -4.367467469 -6.026080096
110 -5.538923089 -4.367467469
111 -2.844911912 -5.538923089
112 -2.374863570 -2.844911912
113 -5.750529137 -2.374863570
114 -0.373009788 -5.750529137
115 -0.410613910 -0.373009788
116 -2.480749493 -0.410613910
117 4.260182568 -2.480749493
118 5.135082268 4.260182568
119 4.404579595 5.135082268
120 -0.006193083 4.404579595
121 3.566813982 -0.006193083
122 4.851535419 3.566813982
123 6.737428091 4.851535419
124 2.003816231 6.737428091
125 9.987873534 2.003816231
126 4.985360326 9.987873534
127 4.466279259 4.985360326
128 3.553922654 4.466279259
129 6.707956713 3.553922654
130 2.001288166 6.707956713
131 -0.409342978 2.001288166
132 -4.144778595 -0.409342978
133 -4.879586576 -4.144778595
134 4.476133646 -4.879586576
135 4.753983688 4.476133646
136 -0.066130259 4.753983688
137 3.563352354 -0.066130259
138 0.432913217 3.563352354
139 0.899848131 0.432913217
140 -3.404592107 0.899848131
141 -0.384191267 -3.404592107
142 -1.171278003 -0.384191267
143 NA -1.171278003
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.859918310 2.955230897
[2,] 3.569037523 2.859918310
[3,] 5.183048216 3.569037523
[4,] -2.094352140 5.183048216
[5,] 0.537871167 -2.094352140
[6,] -1.114239840 0.537871167
[7,] 2.120104681 -1.114239840
[8,] 0.635953435 2.120104681
[9,] -1.958448387 0.635953435
[10,] 0.067668496 -1.958448387
[11,] -0.648640863 0.067668496
[12,] -2.104932375 -0.648640863
[13,] -8.752624861 -2.104932375
[14,] 0.481368272 -8.752624861
[15,] 0.469257770 0.481368272
[16,] -1.901583519 0.469257770
[17,] 0.910007056 -1.901583519
[18,] -0.386133612 0.910007056
[19,] 0.974987732 -0.386133612
[20,] 1.147418946 0.974987732
[21,] -4.195154342 1.147418946
[22,] 1.839338053 -4.195154342
[23,] 1.870868606 1.839338053
[24,] 1.022472501 1.870868606
[25,] 2.857842704 1.022472501
[26,] -0.893855607 2.857842704
[27,] -0.890853111 -0.893855607
[28,] 1.186088561 -0.890853111
[29,] 1.763771937 1.186088561
[30,] -0.315223925 1.763771937
[31,] 0.434542670 -0.315223925
[32,] 0.276560144 0.434542670
[33,] 0.303442402 0.276560144
[34,] 5.970208189 0.303442402
[35,] 4.278664438 5.970208189
[36,] -2.316598607 4.278664438
[37,] 1.015238541 -2.316598607
[38,] -0.823692459 1.015238541
[39,] 4.511189173 -0.823692459
[40,] 3.768776002 4.511189173
[41,] 2.441994085 3.768776002
[42,] -1.115018255 2.441994085
[43,] -1.568891881 -1.115018255
[44,] 1.475154083 -1.568891881
[45,] -0.051956348 1.475154083
[46,] 1.239457046 -0.051956348
[47,] 2.892148140 1.239457046
[48,] -6.119449353 2.892148140
[49,] -0.027592000 -6.119449353
[50,] -2.214102474 -0.027592000
[51,] -1.011219650 -2.214102474
[52,] -1.444634969 -1.011219650
[53,] 1.832512149 -1.444634969
[54,] 2.295264251 1.832512149
[55,] -0.661672768 2.295264251
[56,] -3.878122208 -0.661672768
[57,] -3.247029716 -3.878122208
[58,] 1.430562311 -3.247029716
[59,] 2.780876570 1.430562311
[60,] -0.921882353 2.780876570
[61,] -1.326225348 -0.921882353
[62,] -2.362656582 -1.326225348
[63,] 1.334701219 -2.362656582
[64,] -0.905332462 1.334701219
[65,] -1.579970595 -0.905332462
[66,] -2.768480547 -1.579970595
[67,] -0.460284782 -2.768480547
[68,] -1.982509954 -0.460284782
[69,] -1.346334440 -1.982509954
[70,] 0.631564724 -1.346334440
[71,] 4.674400939 0.631564724
[72,] 1.134264036 4.674400939
[73,] -0.010288595 1.134264036
[74,] -6.682615525 -0.010288595
[75,] -1.158758442 -6.682615525
[76,] -0.234637690 -1.158758442
[77,] -0.376859906 -0.234637690
[78,] 0.157426995 -0.376859906
[79,] -2.190803731 0.157426995
[80,] -1.427498649 -2.190803731
[81,] -0.184257846 -1.427498649
[82,] 2.157469600 -0.184257846
[83,] 0.438799487 2.157469600
[84,] 1.312499765 0.438799487
[85,] 1.741380004 1.312499765
[86,] 2.046844555 1.741380004
[87,] 8.144438154 2.046844555
[88,] 2.413768603 8.144438154
[89,] 8.033686010 2.413768603
[90,] 3.129661670 8.033686010
[91,] -1.430923256 3.129661670
[92,] 4.093240657 -1.430923256
[93,] -1.594125589 4.093240657
[94,] -1.719813753 -1.594125589
[95,] -5.965677741 -1.719813753
[96,] -1.661418380 -5.965677741
[97,] -7.535410201 -1.661418380
[98,] -8.448906898 -7.535410201
[99,] -6.664215519 -8.448906898
[100,] -9.662171862 -6.664215519
[101,] -4.223222195 -9.662171862
[102,] -5.700093638 -4.223222195
[103,] -7.302848146 -5.700093638
[104,] -8.274252283 -7.302848146
[105,] 1.204786055 -8.274252283
[106,] 0.715719567 1.204786055
[107,] 0.919894562 0.715719567
[108,] -6.026080096 0.919894562
[109,] -4.367467469 -6.026080096
[110,] -5.538923089 -4.367467469
[111,] -2.844911912 -5.538923089
[112,] -2.374863570 -2.844911912
[113,] -5.750529137 -2.374863570
[114,] -0.373009788 -5.750529137
[115,] -0.410613910 -0.373009788
[116,] -2.480749493 -0.410613910
[117,] 4.260182568 -2.480749493
[118,] 5.135082268 4.260182568
[119,] 4.404579595 5.135082268
[120,] -0.006193083 4.404579595
[121,] 3.566813982 -0.006193083
[122,] 4.851535419 3.566813982
[123,] 6.737428091 4.851535419
[124,] 2.003816231 6.737428091
[125,] 9.987873534 2.003816231
[126,] 4.985360326 9.987873534
[127,] 4.466279259 4.985360326
[128,] 3.553922654 4.466279259
[129,] 6.707956713 3.553922654
[130,] 2.001288166 6.707956713
[131,] -0.409342978 2.001288166
[132,] -4.144778595 -0.409342978
[133,] -4.879586576 -4.144778595
[134,] 4.476133646 -4.879586576
[135,] 4.753983688 4.476133646
[136,] -0.066130259 4.753983688
[137,] 3.563352354 -0.066130259
[138,] 0.432913217 3.563352354
[139,] 0.899848131 0.432913217
[140,] -3.404592107 0.899848131
[141,] -0.384191267 -3.404592107
[142,] -1.171278003 -0.384191267
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.859918310 2.955230897
2 3.569037523 2.859918310
3 5.183048216 3.569037523
4 -2.094352140 5.183048216
5 0.537871167 -2.094352140
6 -1.114239840 0.537871167
7 2.120104681 -1.114239840
8 0.635953435 2.120104681
9 -1.958448387 0.635953435
10 0.067668496 -1.958448387
11 -0.648640863 0.067668496
12 -2.104932375 -0.648640863
13 -8.752624861 -2.104932375
14 0.481368272 -8.752624861
15 0.469257770 0.481368272
16 -1.901583519 0.469257770
17 0.910007056 -1.901583519
18 -0.386133612 0.910007056
19 0.974987732 -0.386133612
20 1.147418946 0.974987732
21 -4.195154342 1.147418946
22 1.839338053 -4.195154342
23 1.870868606 1.839338053
24 1.022472501 1.870868606
25 2.857842704 1.022472501
26 -0.893855607 2.857842704
27 -0.890853111 -0.893855607
28 1.186088561 -0.890853111
29 1.763771937 1.186088561
30 -0.315223925 1.763771937
31 0.434542670 -0.315223925
32 0.276560144 0.434542670
33 0.303442402 0.276560144
34 5.970208189 0.303442402
35 4.278664438 5.970208189
36 -2.316598607 4.278664438
37 1.015238541 -2.316598607
38 -0.823692459 1.015238541
39 4.511189173 -0.823692459
40 3.768776002 4.511189173
41 2.441994085 3.768776002
42 -1.115018255 2.441994085
43 -1.568891881 -1.115018255
44 1.475154083 -1.568891881
45 -0.051956348 1.475154083
46 1.239457046 -0.051956348
47 2.892148140 1.239457046
48 -6.119449353 2.892148140
49 -0.027592000 -6.119449353
50 -2.214102474 -0.027592000
51 -1.011219650 -2.214102474
52 -1.444634969 -1.011219650
53 1.832512149 -1.444634969
54 2.295264251 1.832512149
55 -0.661672768 2.295264251
56 -3.878122208 -0.661672768
57 -3.247029716 -3.878122208
58 1.430562311 -3.247029716
59 2.780876570 1.430562311
60 -0.921882353 2.780876570
61 -1.326225348 -0.921882353
62 -2.362656582 -1.326225348
63 1.334701219 -2.362656582
64 -0.905332462 1.334701219
65 -1.579970595 -0.905332462
66 -2.768480547 -1.579970595
67 -0.460284782 -2.768480547
68 -1.982509954 -0.460284782
69 -1.346334440 -1.982509954
70 0.631564724 -1.346334440
71 4.674400939 0.631564724
72 1.134264036 4.674400939
73 -0.010288595 1.134264036
74 -6.682615525 -0.010288595
75 -1.158758442 -6.682615525
76 -0.234637690 -1.158758442
77 -0.376859906 -0.234637690
78 0.157426995 -0.376859906
79 -2.190803731 0.157426995
80 -1.427498649 -2.190803731
81 -0.184257846 -1.427498649
82 2.157469600 -0.184257846
83 0.438799487 2.157469600
84 1.312499765 0.438799487
85 1.741380004 1.312499765
86 2.046844555 1.741380004
87 8.144438154 2.046844555
88 2.413768603 8.144438154
89 8.033686010 2.413768603
90 3.129661670 8.033686010
91 -1.430923256 3.129661670
92 4.093240657 -1.430923256
93 -1.594125589 4.093240657
94 -1.719813753 -1.594125589
95 -5.965677741 -1.719813753
96 -1.661418380 -5.965677741
97 -7.535410201 -1.661418380
98 -8.448906898 -7.535410201
99 -6.664215519 -8.448906898
100 -9.662171862 -6.664215519
101 -4.223222195 -9.662171862
102 -5.700093638 -4.223222195
103 -7.302848146 -5.700093638
104 -8.274252283 -7.302848146
105 1.204786055 -8.274252283
106 0.715719567 1.204786055
107 0.919894562 0.715719567
108 -6.026080096 0.919894562
109 -4.367467469 -6.026080096
110 -5.538923089 -4.367467469
111 -2.844911912 -5.538923089
112 -2.374863570 -2.844911912
113 -5.750529137 -2.374863570
114 -0.373009788 -5.750529137
115 -0.410613910 -0.373009788
116 -2.480749493 -0.410613910
117 4.260182568 -2.480749493
118 5.135082268 4.260182568
119 4.404579595 5.135082268
120 -0.006193083 4.404579595
121 3.566813982 -0.006193083
122 4.851535419 3.566813982
123 6.737428091 4.851535419
124 2.003816231 6.737428091
125 9.987873534 2.003816231
126 4.985360326 9.987873534
127 4.466279259 4.985360326
128 3.553922654 4.466279259
129 6.707956713 3.553922654
130 2.001288166 6.707956713
131 -0.409342978 2.001288166
132 -4.144778595 -0.409342978
133 -4.879586576 -4.144778595
134 4.476133646 -4.879586576
135 4.753983688 4.476133646
136 -0.066130259 4.753983688
137 3.563352354 -0.066130259
138 0.432913217 3.563352354
139 0.899848131 0.432913217
140 -3.404592107 0.899848131
141 -0.384191267 -3.404592107
142 -1.171278003 -0.384191267
> 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/wessaorg/rcomp/tmp/757fe1355497170.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/wessaorg/rcomp/tmp/82sa91355497170.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/wessaorg/rcomp/tmp/994mz1355497170.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/wessaorg/rcomp/tmp/10mb341355497170.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/119sxg1355497170.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12xb1l1355497170.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13ooh21355497170.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/146lzh1355497170.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/wessaorg/rcomp/tmp/15pv0l1355497170.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/wessaorg/rcomp/tmp/168rtb1355497170.tab")
+ }
>
> try(system("convert tmp/13noz1355497170.ps tmp/13noz1355497170.png",intern=TRUE))
character(0)
> try(system("convert tmp/2v0fr1355497170.ps tmp/2v0fr1355497170.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wbsg1355497170.ps tmp/3wbsg1355497170.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ttdo1355497170.ps tmp/4ttdo1355497170.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ivuh1355497170.ps tmp/5ivuh1355497170.png",intern=TRUE))
character(0)
> try(system("convert tmp/6dbp21355497170.ps tmp/6dbp21355497170.png",intern=TRUE))
character(0)
> try(system("convert tmp/757fe1355497170.ps tmp/757fe1355497170.png",intern=TRUE))
character(0)
> try(system("convert tmp/82sa91355497170.ps tmp/82sa91355497170.png",intern=TRUE))
character(0)
> try(system("convert tmp/994mz1355497170.ps tmp/994mz1355497170.png",intern=TRUE))
character(0)
> try(system("convert tmp/10mb341355497170.ps tmp/10mb341355497170.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.699 1.822 12.593