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(33024
+ ,31086
+ ,19828
+ ,18932
+ ,32526
+ ,30839
+ ,19967
+ ,18927
+ ,31455
+ ,30051
+ ,19814
+ ,19124
+ ,31524
+ ,29976
+ ,20053
+ ,19066
+ ,31856
+ ,30463
+ ,20719
+ ,19971
+ ,32696
+ ,31422
+ ,21174
+ ,20165
+ ,32584
+ ,31588
+ ,20648
+ ,19705
+ ,33498
+ ,31900
+ ,20659
+ ,19718
+ ,34175
+ ,32878
+ ,20733
+ ,19938
+ ,34172
+ ,33010
+ ,21069
+ ,20039
+ ,34379
+ ,32954
+ ,20566
+ ,19721
+ ,34988
+ ,33076
+ ,20839
+ ,19777
+ ,36158
+ ,35057
+ ,21615
+ ,20505
+ ,37411
+ ,35906
+ ,22739
+ ,21763
+ ,38015
+ ,36100
+ ,23222
+ ,22404
+ ,37577
+ ,35824
+ ,23031
+ ,22038
+ ,36354
+ ,34579
+ ,23014
+ ,22038
+ ,36030
+ ,34484
+ ,22868
+ ,21874
+ ,35636
+ ,33920
+ ,22182
+ ,21269
+ ,35669
+ ,34059
+ ,22177
+ ,21127
+ ,34635
+ ,33812
+ ,21216
+ ,20609
+ ,35496
+ ,34594
+ ,21031
+ ,20565
+ ,36376
+ ,36083
+ ,20968
+ ,19791
+ ,37635
+ ,36563
+ ,21049
+ ,20672
+ ,38875
+ ,37416
+ ,21033
+ ,20938
+ ,38372
+ ,37953
+ ,21078
+ ,20675
+ ,38897
+ ,37517
+ ,20702
+ ,19992
+ ,38018
+ ,37467
+ ,20309
+ ,19801
+ ,37325
+ ,36963
+ ,20449
+ ,20050
+ ,36893
+ ,36019
+ ,20737
+ ,20427
+ ,36117
+ ,35232
+ ,20849
+ ,20815
+ ,37599
+ ,36857
+ ,21966
+ ,21666
+ ,39037
+ ,37978
+ ,23100
+ ,22720
+ ,40809
+ ,40160
+ ,23975
+ ,23650
+ ,42508
+ ,42165
+ ,24350
+ ,24244
+ ,44021
+ ,43069
+ ,24020
+ ,23669
+ ,44088
+ ,43021
+ ,24005
+ ,23881
+ ,44510
+ ,43376
+ ,23602
+ ,23857
+ ,45786
+ ,43978
+ ,24120
+ ,23999
+ ,47349
+ ,45911
+ ,24847
+ ,24780
+ ,48696
+ ,47107
+ ,25702
+ ,25426
+ ,50598
+ ,49168
+ ,26312
+ ,26229
+ ,50066
+ ,48390
+ ,25891
+ ,25973
+ ,49367
+ ,47678
+ ,25172
+ ,25375
+ ,48784
+ ,47822
+ ,25698
+ ,25966
+ ,47841
+ ,46695
+ ,25833
+ ,25391
+ ,48300
+ ,47185
+ ,25658
+ ,26046
+ ,47518
+ ,45684
+ ,25269
+ ,25572
+ ,46504
+ ,44884
+ ,24846
+ ,24900
+ ,45147
+ ,44256
+ ,24390
+ ,24744
+ ,44404
+ ,43637
+ ,23954
+ ,24526
+ ,43455
+ ,42368
+ ,23828
+ ,24274
+ ,42299
+ ,40892
+ ,23507
+ ,23774
+ ,42105
+ ,40616
+ ,23144
+ ,23414
+ ,40152
+ ,39026
+ ,22302
+ ,23002
+ ,39519
+ ,38921
+ ,23028
+ ,23137
+ ,39633
+ ,38512
+ ,22741
+ ,22947
+ ,39376
+ ,38884
+ ,23129
+ ,23733
+ ,38850
+ ,38406
+ ,22911
+ ,23234
+ ,39657
+ ,38804
+ ,22071
+ ,22969
+ ,34804
+ ,34871
+ ,16466
+ ,17708
+ ,34372
+ ,34660
+ ,16370
+ ,17377
+ ,32678
+ ,33104
+ ,15049
+ ,16273
+ ,28420
+ ,28952
+ ,13174
+ ,14342
+ ,25420
+ ,26488
+ ,12231
+ ,13522
+ ,27683
+ ,29418
+ ,13620
+ ,15210
+ ,29904
+ ,32315
+ ,14317
+ ,16493
+ ,30546
+ ,32885
+ ,14039
+ ,16701
+ ,29142
+ ,31565
+ ,13526
+ ,15662
+ ,27724
+ ,30782
+ ,12826
+ ,15526
+ ,27069
+ ,30442
+ ,12360
+ ,15413
+ ,26665
+ ,30851
+ ,12592
+ ,15805
+ ,26004
+ ,30432
+ ,12381
+ ,15802
+ ,25767
+ ,31260
+ ,12554
+ ,16753
+ ,24915
+ ,30737
+ ,12338
+ ,16906
+ ,23689
+ ,30129
+ ,11768
+ ,16891
+ ,20915
+ ,27672
+ ,10687
+ ,15703
+ ,19414
+ ,26469
+ ,9964
+ ,15429
+ ,17824
+ ,24895
+ ,9338
+ ,14762
+ ,16348
+ ,24427
+ ,8697
+ ,14426
+ ,15571
+ ,23252
+ ,8068
+ ,14250
+ ,13929
+ ,21815
+ ,7295
+ ,13267
+ ,12480
+ ,20837
+ ,6372
+ ,12397
+ ,10837
+ ,18537
+ ,5649
+ ,11586
+ ,9473
+ ,17237
+ ,4926
+ ,10888
+ ,8051
+ ,15476
+ ,4199
+ ,9841
+ ,5278
+ ,10709
+ ,2568
+ ,6443
+ ,3008
+ ,6776
+ ,1461
+ ,4019
+ ,2404
+ ,5810
+ ,1173
+ ,3449
+ ,2298
+ ,5765
+ ,1084
+ ,3179
+ ,2260
+ ,5775
+ ,978
+ ,3341
+ ,1938
+ ,5589
+ ,947
+ ,3325
+ ,1371
+ ,4687
+ ,679
+ ,2478
+ ,1009
+ ,3630
+ ,457
+ ,1982
+ ,686
+ ,2552
+ ,262
+ ,1405
+ ,493
+ ,1928
+ ,218
+ ,1059
+ ,285
+ ,1323
+ ,132
+ ,740
+ ,192
+ ,1005
+ ,70
+ ,533
+ ,129
+ ,678
+ ,44
+ ,366
+ ,60
+ ,397
+ ,24
+ ,224
+ ,54
+ ,286
+ ,20
+ ,147
+ ,26
+ ,166
+ ,4
+ ,75
+ ,11
+ ,80
+ ,4
+ ,54
+ ,3
+ ,53
+ ,1
+ ,23
+ ,0
+ ,32
+ ,0
+ ,16
+ ,2
+ ,11
+ ,0
+ ,6
+ ,1
+ ,6
+ ,0
+ ,7
+ ,0
+ ,4
+ ,0
+ ,2
+ ,0
+ ,2
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,0
+ ,1
+ ,0
+ ,0)
+ ,dim=c(4
+ ,111)
+ ,dimnames=list(c('MVG'
+ ,'VVG'
+ ,'MWG'
+ ,'VWG')
+ ,1:111))
> y <- array(NA,dim=c(4,111),dimnames=list(c('MVG','VVG','MWG','VWG'),1:111))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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
MVG VVG MWG VWG t
1 33024 31086 19828 18932 1
2 32526 30839 19967 18927 2
3 31455 30051 19814 19124 3
4 31524 29976 20053 19066 4
5 31856 30463 20719 19971 5
6 32696 31422 21174 20165 6
7 32584 31588 20648 19705 7
8 33498 31900 20659 19718 8
9 34175 32878 20733 19938 9
10 34172 33010 21069 20039 10
11 34379 32954 20566 19721 11
12 34988 33076 20839 19777 12
13 36158 35057 21615 20505 13
14 37411 35906 22739 21763 14
15 38015 36100 23222 22404 15
16 37577 35824 23031 22038 16
17 36354 34579 23014 22038 17
18 36030 34484 22868 21874 18
19 35636 33920 22182 21269 19
20 35669 34059 22177 21127 20
21 34635 33812 21216 20609 21
22 35496 34594 21031 20565 22
23 36376 36083 20968 19791 23
24 37635 36563 21049 20672 24
25 38875 37416 21033 20938 25
26 38372 37953 21078 20675 26
27 38897 37517 20702 19992 27
28 38018 37467 20309 19801 28
29 37325 36963 20449 20050 29
30 36893 36019 20737 20427 30
31 36117 35232 20849 20815 31
32 37599 36857 21966 21666 32
33 39037 37978 23100 22720 33
34 40809 40160 23975 23650 34
35 42508 42165 24350 24244 35
36 44021 43069 24020 23669 36
37 44088 43021 24005 23881 37
38 44510 43376 23602 23857 38
39 45786 43978 24120 23999 39
40 47349 45911 24847 24780 40
41 48696 47107 25702 25426 41
42 50598 49168 26312 26229 42
43 50066 48390 25891 25973 43
44 49367 47678 25172 25375 44
45 48784 47822 25698 25966 45
46 47841 46695 25833 25391 46
47 48300 47185 25658 26046 47
48 47518 45684 25269 25572 48
49 46504 44884 24846 24900 49
50 45147 44256 24390 24744 50
51 44404 43637 23954 24526 51
52 43455 42368 23828 24274 52
53 42299 40892 23507 23774 53
54 42105 40616 23144 23414 54
55 40152 39026 22302 23002 55
56 39519 38921 23028 23137 56
57 39633 38512 22741 22947 57
58 39376 38884 23129 23733 58
59 38850 38406 22911 23234 59
60 39657 38804 22071 22969 60
61 34804 34871 16466 17708 61
62 34372 34660 16370 17377 62
63 32678 33104 15049 16273 63
64 28420 28952 13174 14342 64
65 25420 26488 12231 13522 65
66 27683 29418 13620 15210 66
67 29904 32315 14317 16493 67
68 30546 32885 14039 16701 68
69 29142 31565 13526 15662 69
70 27724 30782 12826 15526 70
71 27069 30442 12360 15413 71
72 26665 30851 12592 15805 72
73 26004 30432 12381 15802 73
74 25767 31260 12554 16753 74
75 24915 30737 12338 16906 75
76 23689 30129 11768 16891 76
77 20915 27672 10687 15703 77
78 19414 26469 9964 15429 78
79 17824 24895 9338 14762 79
80 16348 24427 8697 14426 80
81 15571 23252 8068 14250 81
82 13929 21815 7295 13267 82
83 12480 20837 6372 12397 83
84 10837 18537 5649 11586 84
85 9473 17237 4926 10888 85
86 8051 15476 4199 9841 86
87 5278 10709 2568 6443 87
88 3008 6776 1461 4019 88
89 2404 5810 1173 3449 89
90 2298 5765 1084 3179 90
91 2260 5775 978 3341 91
92 1938 5589 947 3325 92
93 1371 4687 679 2478 93
94 1009 3630 457 1982 94
95 686 2552 262 1405 95
96 493 1928 218 1059 96
97 285 1323 132 740 97
98 192 1005 70 533 98
99 129 678 44 366 99
100 60 397 24 224 100
101 54 286 20 147 101
102 26 166 4 75 102
103 11 80 4 54 103
104 3 53 1 23 104
105 0 32 0 16 105
106 2 11 0 6 106
107 1 6 0 7 107
108 0 4 0 2 108
109 0 2 0 0 109
110 0 0 0 0 110
111 0 1 0 0 111
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) VVG MWG VWG t
-2483.046 1.001 1.467 -1.357 22.824
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1707.86 -233.16 -2.61 271.79 953.21
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -2.483e+03 2.984e+02 -8.322 3.24e-13 ***
VVG 1.001e+00 2.258e-02 44.349 < 2e-16 ***
MWG 1.467e+00 2.652e-02 55.343 < 2e-16 ***
VWG -1.357e+00 4.617e-02 -29.393 < 2e-16 ***
t 2.282e+01 3.032e+00 7.529 1.78e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 429.3 on 106 degrees of freedom
Multiple R-squared: 0.9994, Adjusted R-squared: 0.9993
F-statistic: 4.105e+04 on 4 and 106 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,] 0.31010882 6.202176e-01 6.898912e-01
[2,] 0.16995195 3.399039e-01 8.300480e-01
[3,] 0.08716824 1.743365e-01 9.128318e-01
[4,] 0.05281347 1.056269e-01 9.471865e-01
[5,] 0.13467074 2.693415e-01 8.653293e-01
[6,] 0.09262753 1.852551e-01 9.073725e-01
[7,] 0.14938577 2.987715e-01 8.506142e-01
[8,] 0.23628227 4.725645e-01 7.637177e-01
[9,] 0.19758992 3.951798e-01 8.024101e-01
[10,] 0.17545175 3.509035e-01 8.245483e-01
[11,] 0.12210417 2.442083e-01 8.778958e-01
[12,] 0.09978977 1.995795e-01 9.002102e-01
[13,] 0.06790887 1.358177e-01 9.320911e-01
[14,] 0.07800702 1.560140e-01 9.219930e-01
[15,] 0.05344551 1.068910e-01 9.465545e-01
[16,] 0.15825672 3.165134e-01 8.417433e-01
[17,] 0.14557760 2.911552e-01 8.544224e-01
[18,] 0.23304775 4.660955e-01 7.669523e-01
[19,] 0.26859159 5.371832e-01 7.314084e-01
[20,] 0.42162527 8.432505e-01 5.783747e-01
[21,] 0.37458800 7.491760e-01 6.254120e-01
[22,] 0.36800934 7.360187e-01 6.319907e-01
[23,] 0.31718470 6.343694e-01 6.828153e-01
[24,] 0.29068557 5.813711e-01 7.093144e-01
[25,] 0.25295040 5.059008e-01 7.470496e-01
[26,] 0.20614886 4.122977e-01 7.938511e-01
[27,] 0.29093474 5.818695e-01 7.090653e-01
[28,] 0.47065565 9.413113e-01 5.293443e-01
[29,] 0.51191473 9.761705e-01 4.880853e-01
[30,] 0.50932543 9.813491e-01 4.906746e-01
[31,] 0.49370112 9.874022e-01 5.062989e-01
[32,] 0.67904237 6.419153e-01 3.209576e-01
[33,] 0.64903541 7.019292e-01 3.509646e-01
[34,] 0.63449640 7.310072e-01 3.655036e-01
[35,] 0.60117589 7.976482e-01 3.988241e-01
[36,] 0.56844193 8.631161e-01 4.315581e-01
[37,] 0.58184138 8.363172e-01 4.181586e-01
[38,] 0.57807946 8.438411e-01 4.219205e-01
[39,] 0.77755627 4.448875e-01 2.224437e-01
[40,] 0.73614069 5.277186e-01 2.638593e-01
[41,] 0.84591114 3.081777e-01 1.540889e-01
[42,] 0.86809251 2.638150e-01 1.319075e-01
[43,] 0.84461936 3.107613e-01 1.553806e-01
[44,] 0.80935026 3.812995e-01 1.906497e-01
[45,] 0.78714915 4.257017e-01 2.128508e-01
[46,] 0.81909460 3.618108e-01 1.809054e-01
[47,] 0.86010420 2.797916e-01 1.398958e-01
[48,] 0.91149729 1.770054e-01 8.850271e-02
[49,] 0.93972664 1.205467e-01 6.027336e-02
[50,] 0.92688153 1.462369e-01 7.311847e-02
[51,] 0.92663667 1.467267e-01 7.336333e-02
[52,] 0.99069106 1.861787e-02 9.308935e-03
[53,] 0.99238083 1.523835e-02 7.619174e-03
[54,] 0.99418243 1.163513e-02 5.817566e-03
[55,] 0.99127189 1.745623e-02 8.728113e-03
[56,] 0.99347976 1.304048e-02 6.520238e-03
[57,] 0.99582374 8.352510e-03 4.176255e-03
[58,] 0.99472866 1.054268e-02 5.271338e-03
[59,] 0.99792466 4.150673e-03 2.075337e-03
[60,] 0.99966231 6.753775e-04 3.376888e-04
[61,] 0.99998445 3.110044e-05 1.555022e-05
[62,] 0.99998565 2.870931e-05 1.435466e-05
[63,] 0.99999471 1.057765e-05 5.288824e-06
[64,] 0.99999997 6.146915e-08 3.073457e-08
[65,] 0.99999999 1.804807e-08 9.024034e-09
[66,] 1.00000000 4.178076e-09 2.089038e-09
[67,] 1.00000000 1.827618e-09 9.138088e-10
[68,] 1.00000000 7.577714e-10 3.788857e-10
[69,] 1.00000000 5.890736e-13 2.945368e-13
[70,] 1.00000000 3.184961e-13 1.592481e-13
[71,] 1.00000000 5.811889e-15 2.905944e-15
[72,] 1.00000000 1.521837e-14 7.609186e-15
[73,] 1.00000000 7.747537e-17 3.873768e-17
[74,] 1.00000000 6.403197e-17 3.201599e-17
[75,] 1.00000000 2.329335e-16 1.164667e-16
[76,] 1.00000000 1.212167e-15 6.060837e-16
[77,] 1.00000000 8.427372e-15 4.213686e-15
[78,] 1.00000000 5.131418e-14 2.565709e-14
[79,] 1.00000000 1.220723e-15 6.103614e-16
[80,] 1.00000000 9.610191e-15 4.805096e-15
[81,] 1.00000000 8.438963e-14 4.219482e-14
[82,] 1.00000000 3.443906e-13 1.721953e-13
[83,] 1.00000000 2.562385e-12 1.281193e-12
[84,] 1.00000000 1.095196e-19 5.475978e-20
[85,] 1.00000000 1.673886e-18 8.369432e-19
[86,] 1.00000000 3.753924e-17 1.876962e-17
[87,] 1.00000000 7.059218e-16 3.529609e-16
[88,] 1.00000000 7.365261e-20 3.682631e-20
[89,] 1.00000000 2.355858e-20 1.177929e-20
[90,] 1.00000000 3.250307e-18 1.625154e-18
[91,] 1.00000000 3.212197e-16 1.606098e-16
[92,] 1.00000000 3.717776e-15 1.858888e-15
[93,] 1.00000000 7.370835e-14 3.685418e-14
[94,] 1.00000000 1.726442e-11 8.632211e-12
[95,] 1.00000000 1.817930e-11 9.089650e-12
[96,] 0.99999999 1.232968e-08 6.164841e-09
> postscript(file="/var/www/rcomp/tmp/1btov1292262484.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2btov1292262484.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/34kny1292262484.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/44kny1292262484.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/54kny1292262484.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 = 111
Frequency = 1
1 2 3 4 5 6
953.210126 468.960298 656.113342 347.947474 420.394976 -127.148049
7 8 9 10 11 12
-280.627471 299.621161 164.447135 -349.551116 197.246941 336.638664
13 14 15 16 17 18
-650.615501 -212.671939 335.421412 -65.476371 -39.642991 -299.668599
19 20 21 22 23 24
33.854792 -280.547436 -382.826676 -115.960113 -1707.862821 124.493385
25 26 27 28 29 30
871.995587 -614.550040 -50.982094 -585.248255 -663.880146 -84.370261
31 32 33 34 35 36
267.128665 -385.107663 -326.084172 -783.737230 -859.433994 -570.631865
37 38 39 40 41 42
-168.648742 433.858084 516.779591 114.429928 -136.967643 -126.940027
43 44 45 46 47 48
367.664427 602.318299 -117.481718 -933.264424 158.021037 783.787096
49 50 51 52 53 54
256.755789 -36.762886 161.209341 303.012473 394.668401 498.319408
55 56 57 58 59 60
791.120669 -641.721494 22.310579 -132.634617 -560.142499 698.502806
61 62 63 64 65 66
845.971655 294.077030 575.559620 583.173736 298.647476 -142.546825
67 68 69 70 71 72
-126.875448 611.775340 -150.566319 35.335871 228.456427 -416.355915
73 74 75 76 77 78
-375.039137 -427.163702 -253.641311 -77.528299 -440.007458 -70.071807
79 80 81 82 83 84
-93.356402 -638.910727 422.050860 -3.582866 -322.361001 275.258080
85 86 87 88 89 90
303.868357 268.314314 27.677161 7.864046 -2.612350 -322.217329
91 92 93 94 95 96
-17.634462 -152.426895 -595.288922 -269.059742 -32.357821 -28.351849
97 98 99 100 101 102
39.906694 52.559481 105.684125 131.871069 115.563754 110.664560
103 104 105 106 107 108
130.456973 88.998605 76.170177 62.802634 45.342459 16.734880
109 110 111
-6.801058 -27.622569 -51.448202
> postscript(file="/var/www/rcomp/tmp/64kny1292262484.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 = 111
Frequency = 1
lag(myerror, k = 1) myerror
0 953.210126 NA
1 468.960298 953.210126
2 656.113342 468.960298
3 347.947474 656.113342
4 420.394976 347.947474
5 -127.148049 420.394976
6 -280.627471 -127.148049
7 299.621161 -280.627471
8 164.447135 299.621161
9 -349.551116 164.447135
10 197.246941 -349.551116
11 336.638664 197.246941
12 -650.615501 336.638664
13 -212.671939 -650.615501
14 335.421412 -212.671939
15 -65.476371 335.421412
16 -39.642991 -65.476371
17 -299.668599 -39.642991
18 33.854792 -299.668599
19 -280.547436 33.854792
20 -382.826676 -280.547436
21 -115.960113 -382.826676
22 -1707.862821 -115.960113
23 124.493385 -1707.862821
24 871.995587 124.493385
25 -614.550040 871.995587
26 -50.982094 -614.550040
27 -585.248255 -50.982094
28 -663.880146 -585.248255
29 -84.370261 -663.880146
30 267.128665 -84.370261
31 -385.107663 267.128665
32 -326.084172 -385.107663
33 -783.737230 -326.084172
34 -859.433994 -783.737230
35 -570.631865 -859.433994
36 -168.648742 -570.631865
37 433.858084 -168.648742
38 516.779591 433.858084
39 114.429928 516.779591
40 -136.967643 114.429928
41 -126.940027 -136.967643
42 367.664427 -126.940027
43 602.318299 367.664427
44 -117.481718 602.318299
45 -933.264424 -117.481718
46 158.021037 -933.264424
47 783.787096 158.021037
48 256.755789 783.787096
49 -36.762886 256.755789
50 161.209341 -36.762886
51 303.012473 161.209341
52 394.668401 303.012473
53 498.319408 394.668401
54 791.120669 498.319408
55 -641.721494 791.120669
56 22.310579 -641.721494
57 -132.634617 22.310579
58 -560.142499 -132.634617
59 698.502806 -560.142499
60 845.971655 698.502806
61 294.077030 845.971655
62 575.559620 294.077030
63 583.173736 575.559620
64 298.647476 583.173736
65 -142.546825 298.647476
66 -126.875448 -142.546825
67 611.775340 -126.875448
68 -150.566319 611.775340
69 35.335871 -150.566319
70 228.456427 35.335871
71 -416.355915 228.456427
72 -375.039137 -416.355915
73 -427.163702 -375.039137
74 -253.641311 -427.163702
75 -77.528299 -253.641311
76 -440.007458 -77.528299
77 -70.071807 -440.007458
78 -93.356402 -70.071807
79 -638.910727 -93.356402
80 422.050860 -638.910727
81 -3.582866 422.050860
82 -322.361001 -3.582866
83 275.258080 -322.361001
84 303.868357 275.258080
85 268.314314 303.868357
86 27.677161 268.314314
87 7.864046 27.677161
88 -2.612350 7.864046
89 -322.217329 -2.612350
90 -17.634462 -322.217329
91 -152.426895 -17.634462
92 -595.288922 -152.426895
93 -269.059742 -595.288922
94 -32.357821 -269.059742
95 -28.351849 -32.357821
96 39.906694 -28.351849
97 52.559481 39.906694
98 105.684125 52.559481
99 131.871069 105.684125
100 115.563754 131.871069
101 110.664560 115.563754
102 130.456973 110.664560
103 88.998605 130.456973
104 76.170177 88.998605
105 62.802634 76.170177
106 45.342459 62.802634
107 16.734880 45.342459
108 -6.801058 16.734880
109 -27.622569 -6.801058
110 -51.448202 -27.622569
111 NA -51.448202
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 468.960298 953.210126
[2,] 656.113342 468.960298
[3,] 347.947474 656.113342
[4,] 420.394976 347.947474
[5,] -127.148049 420.394976
[6,] -280.627471 -127.148049
[7,] 299.621161 -280.627471
[8,] 164.447135 299.621161
[9,] -349.551116 164.447135
[10,] 197.246941 -349.551116
[11,] 336.638664 197.246941
[12,] -650.615501 336.638664
[13,] -212.671939 -650.615501
[14,] 335.421412 -212.671939
[15,] -65.476371 335.421412
[16,] -39.642991 -65.476371
[17,] -299.668599 -39.642991
[18,] 33.854792 -299.668599
[19,] -280.547436 33.854792
[20,] -382.826676 -280.547436
[21,] -115.960113 -382.826676
[22,] -1707.862821 -115.960113
[23,] 124.493385 -1707.862821
[24,] 871.995587 124.493385
[25,] -614.550040 871.995587
[26,] -50.982094 -614.550040
[27,] -585.248255 -50.982094
[28,] -663.880146 -585.248255
[29,] -84.370261 -663.880146
[30,] 267.128665 -84.370261
[31,] -385.107663 267.128665
[32,] -326.084172 -385.107663
[33,] -783.737230 -326.084172
[34,] -859.433994 -783.737230
[35,] -570.631865 -859.433994
[36,] -168.648742 -570.631865
[37,] 433.858084 -168.648742
[38,] 516.779591 433.858084
[39,] 114.429928 516.779591
[40,] -136.967643 114.429928
[41,] -126.940027 -136.967643
[42,] 367.664427 -126.940027
[43,] 602.318299 367.664427
[44,] -117.481718 602.318299
[45,] -933.264424 -117.481718
[46,] 158.021037 -933.264424
[47,] 783.787096 158.021037
[48,] 256.755789 783.787096
[49,] -36.762886 256.755789
[50,] 161.209341 -36.762886
[51,] 303.012473 161.209341
[52,] 394.668401 303.012473
[53,] 498.319408 394.668401
[54,] 791.120669 498.319408
[55,] -641.721494 791.120669
[56,] 22.310579 -641.721494
[57,] -132.634617 22.310579
[58,] -560.142499 -132.634617
[59,] 698.502806 -560.142499
[60,] 845.971655 698.502806
[61,] 294.077030 845.971655
[62,] 575.559620 294.077030
[63,] 583.173736 575.559620
[64,] 298.647476 583.173736
[65,] -142.546825 298.647476
[66,] -126.875448 -142.546825
[67,] 611.775340 -126.875448
[68,] -150.566319 611.775340
[69,] 35.335871 -150.566319
[70,] 228.456427 35.335871
[71,] -416.355915 228.456427
[72,] -375.039137 -416.355915
[73,] -427.163702 -375.039137
[74,] -253.641311 -427.163702
[75,] -77.528299 -253.641311
[76,] -440.007458 -77.528299
[77,] -70.071807 -440.007458
[78,] -93.356402 -70.071807
[79,] -638.910727 -93.356402
[80,] 422.050860 -638.910727
[81,] -3.582866 422.050860
[82,] -322.361001 -3.582866
[83,] 275.258080 -322.361001
[84,] 303.868357 275.258080
[85,] 268.314314 303.868357
[86,] 27.677161 268.314314
[87,] 7.864046 27.677161
[88,] -2.612350 7.864046
[89,] -322.217329 -2.612350
[90,] -17.634462 -322.217329
[91,] -152.426895 -17.634462
[92,] -595.288922 -152.426895
[93,] -269.059742 -595.288922
[94,] -32.357821 -269.059742
[95,] -28.351849 -32.357821
[96,] 39.906694 -28.351849
[97,] 52.559481 39.906694
[98,] 105.684125 52.559481
[99,] 131.871069 105.684125
[100,] 115.563754 131.871069
[101,] 110.664560 115.563754
[102,] 130.456973 110.664560
[103,] 88.998605 130.456973
[104,] 76.170177 88.998605
[105,] 62.802634 76.170177
[106,] 45.342459 62.802634
[107,] 16.734880 45.342459
[108,] -6.801058 16.734880
[109,] -27.622569 -6.801058
[110,] -51.448202 -27.622569
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 468.960298 953.210126
2 656.113342 468.960298
3 347.947474 656.113342
4 420.394976 347.947474
5 -127.148049 420.394976
6 -280.627471 -127.148049
7 299.621161 -280.627471
8 164.447135 299.621161
9 -349.551116 164.447135
10 197.246941 -349.551116
11 336.638664 197.246941
12 -650.615501 336.638664
13 -212.671939 -650.615501
14 335.421412 -212.671939
15 -65.476371 335.421412
16 -39.642991 -65.476371
17 -299.668599 -39.642991
18 33.854792 -299.668599
19 -280.547436 33.854792
20 -382.826676 -280.547436
21 -115.960113 -382.826676
22 -1707.862821 -115.960113
23 124.493385 -1707.862821
24 871.995587 124.493385
25 -614.550040 871.995587
26 -50.982094 -614.550040
27 -585.248255 -50.982094
28 -663.880146 -585.248255
29 -84.370261 -663.880146
30 267.128665 -84.370261
31 -385.107663 267.128665
32 -326.084172 -385.107663
33 -783.737230 -326.084172
34 -859.433994 -783.737230
35 -570.631865 -859.433994
36 -168.648742 -570.631865
37 433.858084 -168.648742
38 516.779591 433.858084
39 114.429928 516.779591
40 -136.967643 114.429928
41 -126.940027 -136.967643
42 367.664427 -126.940027
43 602.318299 367.664427
44 -117.481718 602.318299
45 -933.264424 -117.481718
46 158.021037 -933.264424
47 783.787096 158.021037
48 256.755789 783.787096
49 -36.762886 256.755789
50 161.209341 -36.762886
51 303.012473 161.209341
52 394.668401 303.012473
53 498.319408 394.668401
54 791.120669 498.319408
55 -641.721494 791.120669
56 22.310579 -641.721494
57 -132.634617 22.310579
58 -560.142499 -132.634617
59 698.502806 -560.142499
60 845.971655 698.502806
61 294.077030 845.971655
62 575.559620 294.077030
63 583.173736 575.559620
64 298.647476 583.173736
65 -142.546825 298.647476
66 -126.875448 -142.546825
67 611.775340 -126.875448
68 -150.566319 611.775340
69 35.335871 -150.566319
70 228.456427 35.335871
71 -416.355915 228.456427
72 -375.039137 -416.355915
73 -427.163702 -375.039137
74 -253.641311 -427.163702
75 -77.528299 -253.641311
76 -440.007458 -77.528299
77 -70.071807 -440.007458
78 -93.356402 -70.071807
79 -638.910727 -93.356402
80 422.050860 -638.910727
81 -3.582866 422.050860
82 -322.361001 -3.582866
83 275.258080 -322.361001
84 303.868357 275.258080
85 268.314314 303.868357
86 27.677161 268.314314
87 7.864046 27.677161
88 -2.612350 7.864046
89 -322.217329 -2.612350
90 -17.634462 -322.217329
91 -152.426895 -17.634462
92 -595.288922 -152.426895
93 -269.059742 -595.288922
94 -32.357821 -269.059742
95 -28.351849 -32.357821
96 39.906694 -28.351849
97 52.559481 39.906694
98 105.684125 52.559481
99 131.871069 105.684125
100 115.563754 131.871069
101 110.664560 115.563754
102 130.456973 110.664560
103 88.998605 130.456973
104 76.170177 88.998605
105 62.802634 76.170177
106 45.342459 62.802634
107 16.734880 45.342459
108 -6.801058 16.734880
109 -27.622569 -6.801058
110 -51.448202 -27.622569
> 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/7xb4j1292262484.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8q3mm1292262484.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9q3mm1292262484.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10q3mm1292262484.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11wm4q1292262485.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/127wlb1292262485.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/13exi41292262485.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/1466h71292262485.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/15soyv1292262485.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/16ogem1292262485.tab")
+ }
>
> try(system("convert tmp/1btov1292262484.ps tmp/1btov1292262484.png",intern=TRUE))
character(0)
> try(system("convert tmp/2btov1292262484.ps tmp/2btov1292262484.png",intern=TRUE))
character(0)
> try(system("convert tmp/34kny1292262484.ps tmp/34kny1292262484.png",intern=TRUE))
character(0)
> try(system("convert tmp/44kny1292262484.ps tmp/44kny1292262484.png",intern=TRUE))
character(0)
> try(system("convert tmp/54kny1292262484.ps tmp/54kny1292262484.png",intern=TRUE))
character(0)
> try(system("convert tmp/64kny1292262484.ps tmp/64kny1292262484.png",intern=TRUE))
character(0)
> try(system("convert tmp/7xb4j1292262484.ps tmp/7xb4j1292262484.png",intern=TRUE))
character(0)
> try(system("convert tmp/8q3mm1292262484.ps tmp/8q3mm1292262484.png",intern=TRUE))
character(0)
> try(system("convert tmp/9q3mm1292262484.ps tmp/9q3mm1292262484.png",intern=TRUE))
character(0)
> try(system("convert tmp/10q3mm1292262484.ps tmp/10q3mm1292262484.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.730 1.750 5.443