R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
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(35532
+ ,37903
+ ,36763
+ ,40399
+ ,44164
+ ,35533
+ ,35532
+ ,37903
+ ,36763
+ ,40399
+ ,32110
+ ,35533
+ ,35532
+ ,37903
+ ,36763
+ ,33374
+ ,32110
+ ,35533
+ ,35532
+ ,37903
+ ,35462
+ ,33374
+ ,32110
+ ,35533
+ ,35532
+ ,33508
+ ,35462
+ ,33374
+ ,32110
+ ,35533
+ ,36080
+ ,33508
+ ,35462
+ ,33374
+ ,32110
+ ,34560
+ ,36080
+ ,33508
+ ,35462
+ ,33374
+ ,38737
+ ,34560
+ ,36080
+ ,33508
+ ,35462
+ ,38144
+ ,38737
+ ,34560
+ ,36080
+ ,33508
+ ,37594
+ ,38144
+ ,38737
+ ,34560
+ ,36080
+ ,36424
+ ,37594
+ ,38144
+ ,38737
+ ,34560
+ ,36843
+ ,36424
+ ,37594
+ ,38144
+ ,38737
+ ,37246
+ ,36843
+ ,36424
+ ,37594
+ ,38144
+ ,38661
+ ,37246
+ ,36843
+ ,36424
+ ,37594
+ ,40454
+ ,38661
+ ,37246
+ ,36843
+ ,36424
+ ,44928
+ ,40454
+ ,38661
+ ,37246
+ ,36843
+ ,48441
+ ,44928
+ ,40454
+ ,38661
+ ,37246
+ ,48140
+ ,48441
+ ,44928
+ ,40454
+ ,38661
+ ,45998
+ ,48140
+ ,48441
+ ,44928
+ ,40454
+ ,47369
+ ,45998
+ ,48140
+ ,48441
+ ,44928
+ ,49554
+ ,47369
+ ,45998
+ ,48140
+ ,48441
+ ,47510
+ ,49554
+ ,47369
+ ,45998
+ ,48140
+ ,44873
+ ,47510
+ ,49554
+ ,47369
+ ,45998
+ ,45344
+ ,44873
+ ,47510
+ ,49554
+ ,47369
+ ,42413
+ ,45344
+ ,44873
+ ,47510
+ ,49554
+ ,36912
+ ,42413
+ ,45344
+ ,44873
+ ,47510
+ ,43452
+ ,36912
+ ,42413
+ ,45344
+ ,44873
+ ,42142
+ ,43452
+ ,36912
+ ,42413
+ ,45344
+ ,44382
+ ,42142
+ ,43452
+ ,36912
+ ,42413
+ ,43636
+ ,44382
+ ,42142
+ ,43452
+ ,36912
+ ,44167
+ ,43636
+ ,44382
+ ,42142
+ ,43452
+ ,44423
+ ,44167
+ ,43636
+ ,44382
+ ,42142
+ ,42868
+ ,44423
+ ,44167
+ ,43636
+ ,44382
+ ,43908
+ ,42868
+ ,44423
+ ,44167
+ ,43636
+ ,42013
+ ,43908
+ ,42868
+ ,44423
+ ,44167
+ ,38846
+ ,42013
+ ,43908
+ ,42868
+ ,44423
+ ,35087
+ ,38846
+ ,42013
+ ,43908
+ ,42868
+ ,33026
+ ,35087
+ ,38846
+ ,42013
+ ,43908
+ ,34646
+ ,33026
+ ,35087
+ ,38846
+ ,42013
+ ,37135
+ ,34646
+ ,33026
+ ,35087
+ ,38846
+ ,37985
+ ,37135
+ ,34646
+ ,33026
+ ,35087
+ ,43121
+ ,37985
+ ,37135
+ ,34646
+ ,33026
+ ,43722
+ ,43121
+ ,37985
+ ,37135
+ ,34646
+ ,43630
+ ,43722
+ ,43121
+ ,37985
+ ,37135
+ ,42234
+ ,43630
+ ,43722
+ ,43121
+ ,37985
+ ,39351
+ ,42234
+ ,43630
+ ,43722
+ ,43121
+ ,39327
+ ,39351
+ ,42234
+ ,43630
+ ,43722
+ ,35704
+ ,39327
+ ,39351
+ ,42234
+ ,43630
+ ,30466
+ ,35704
+ ,39327
+ ,39351
+ ,42234
+ ,28155
+ ,30466
+ ,35704
+ ,39327
+ ,39351
+ ,29257
+ ,28155
+ ,30466
+ ,35704
+ ,39327
+ ,29998
+ ,29257
+ ,28155
+ ,30466
+ ,35704
+ ,32529
+ ,29998
+ ,29257
+ ,28155
+ ,30466
+ ,34787
+ ,32529
+ ,29998
+ ,29257
+ ,28155
+ ,33855
+ ,34787
+ ,32529
+ ,29998
+ ,29257
+ ,34556
+ ,33855
+ ,34787
+ ,32529
+ ,29998
+ ,31348
+ ,34556
+ ,33855
+ ,34787
+ ,32529
+ ,30805
+ ,31348
+ ,34556
+ ,33855
+ ,34787
+ ,28353
+ ,30805
+ ,31348
+ ,34556
+ ,33855
+ ,24514
+ ,28353
+ ,30805
+ ,31348
+ ,34556
+ ,21106
+ ,24514
+ ,28353
+ ,30805
+ ,31348
+ ,21346
+ ,21106
+ ,24514
+ ,28353
+ ,30805
+ ,23335
+ ,21346
+ ,21106
+ ,24514
+ ,28353
+ ,24379
+ ,23335
+ ,21346
+ ,21106
+ ,24514
+ ,26290
+ ,24379
+ ,23335
+ ,21346
+ ,21106
+ ,30084
+ ,26290
+ ,24379
+ ,23335
+ ,21346
+ ,29429
+ ,30084
+ ,26290
+ ,24379
+ ,23335
+ ,30632
+ ,29429
+ ,30084
+ ,26290
+ ,24379
+ ,27349
+ ,30632
+ ,29429
+ ,30084
+ ,26290
+ ,27264
+ ,27349
+ ,30632
+ ,29429
+ ,30084
+ ,27474
+ ,27264
+ ,27349
+ ,30632
+ ,29429
+ ,24482
+ ,27474
+ ,27264
+ ,27349
+ ,30632
+ ,21453
+ ,24482
+ ,27474
+ ,27264
+ ,27349
+ ,18788
+ ,21453
+ ,24482
+ ,27474
+ ,27264
+ ,19282
+ ,18788
+ ,21453
+ ,24482
+ ,27474
+ ,19713
+ ,19282
+ ,18788
+ ,21453
+ ,24482
+ ,21917
+ ,19713
+ ,19282
+ ,18788
+ ,21453
+ ,23812
+ ,21917
+ ,19713
+ ,19282
+ ,18788
+ ,23785
+ ,23812
+ ,21917
+ ,19713
+ ,19282
+ ,24696
+ ,23785
+ ,23812
+ ,21917
+ ,19713
+ ,24562
+ ,24696
+ ,23785
+ ,23812
+ ,21917
+ ,23580
+ ,24562
+ ,24696
+ ,23785
+ ,23812
+ ,24939
+ ,23580
+ ,24562
+ ,24696
+ ,23785
+ ,23899
+ ,24939
+ ,23580
+ ,24562
+ ,24696
+ ,21454
+ ,23899
+ ,24939
+ ,23580
+ ,24562
+ ,19761
+ ,21454
+ ,23899
+ ,24939
+ ,23580
+ ,19815
+ ,19761
+ ,21454
+ ,23899
+ ,24939
+ ,20780
+ ,19815
+ ,19761
+ ,21454
+ ,23899
+ ,23462
+ ,20780
+ ,19815
+ ,19761
+ ,21454
+ ,25005
+ ,23462
+ ,20780
+ ,19815
+ ,19761
+ ,24725
+ ,25005
+ ,23462
+ ,20780
+ ,19815
+ ,26198
+ ,24725
+ ,25005
+ ,23462
+ ,20780
+ ,27543
+ ,26198
+ ,24725
+ ,25005
+ ,23462
+ ,26471
+ ,27543
+ ,26198
+ ,24725
+ ,25005
+ ,26558
+ ,26471
+ ,27543
+ ,26198
+ ,24725
+ ,25317
+ ,26558
+ ,26471
+ ,27543
+ ,26198
+ ,22896
+ ,25317
+ ,26558
+ ,26471
+ ,27543)
+ ,dim=c(5
+ ,98)
+ ,dimnames=list(c('OPENVAC'
+ ,'X1'
+ ,'X2'
+ ,'X3'
+ ,'X4')
+ ,1:98))
> y <- array(NA,dim=c(5,98),dimnames=list(c('OPENVAC','X1','X2','X3','X4'),1:98))
> 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 = '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
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
OPENVAC X1 X2 X3 X4
1 35532 37903 36763 40399 44164
2 35533 35532 37903 36763 40399
3 32110 35533 35532 37903 36763
4 33374 32110 35533 35532 37903
5 35462 33374 32110 35533 35532
6 33508 35462 33374 32110 35533
7 36080 33508 35462 33374 32110
8 34560 36080 33508 35462 33374
9 38737 34560 36080 33508 35462
10 38144 38737 34560 36080 33508
11 37594 38144 38737 34560 36080
12 36424 37594 38144 38737 34560
13 36843 36424 37594 38144 38737
14 37246 36843 36424 37594 38144
15 38661 37246 36843 36424 37594
16 40454 38661 37246 36843 36424
17 44928 40454 38661 37246 36843
18 48441 44928 40454 38661 37246
19 48140 48441 44928 40454 38661
20 45998 48140 48441 44928 40454
21 47369 45998 48140 48441 44928
22 49554 47369 45998 48140 48441
23 47510 49554 47369 45998 48140
24 44873 47510 49554 47369 45998
25 45344 44873 47510 49554 47369
26 42413 45344 44873 47510 49554
27 36912 42413 45344 44873 47510
28 43452 36912 42413 45344 44873
29 42142 43452 36912 42413 45344
30 44382 42142 43452 36912 42413
31 43636 44382 42142 43452 36912
32 44167 43636 44382 42142 43452
33 44423 44167 43636 44382 42142
34 42868 44423 44167 43636 44382
35 43908 42868 44423 44167 43636
36 42013 43908 42868 44423 44167
37 38846 42013 43908 42868 44423
38 35087 38846 42013 43908 42868
39 33026 35087 38846 42013 43908
40 34646 33026 35087 38846 42013
41 37135 34646 33026 35087 38846
42 37985 37135 34646 33026 35087
43 43121 37985 37135 34646 33026
44 43722 43121 37985 37135 34646
45 43630 43722 43121 37985 37135
46 42234 43630 43722 43121 37985
47 39351 42234 43630 43722 43121
48 39327 39351 42234 43630 43722
49 35704 39327 39351 42234 43630
50 30466 35704 39327 39351 42234
51 28155 30466 35704 39327 39351
52 29257 28155 30466 35704 39327
53 29998 29257 28155 30466 35704
54 32529 29998 29257 28155 30466
55 34787 32529 29998 29257 28155
56 33855 34787 32529 29998 29257
57 34556 33855 34787 32529 29998
58 31348 34556 33855 34787 32529
59 30805 31348 34556 33855 34787
60 28353 30805 31348 34556 33855
61 24514 28353 30805 31348 34556
62 21106 24514 28353 30805 31348
63 21346 21106 24514 28353 30805
64 23335 21346 21106 24514 28353
65 24379 23335 21346 21106 24514
66 26290 24379 23335 21346 21106
67 30084 26290 24379 23335 21346
68 29429 30084 26290 24379 23335
69 30632 29429 30084 26290 24379
70 27349 30632 29429 30084 26290
71 27264 27349 30632 29429 30084
72 27474 27264 27349 30632 29429
73 24482 27474 27264 27349 30632
74 21453 24482 27474 27264 27349
75 18788 21453 24482 27474 27264
76 19282 18788 21453 24482 27474
77 19713 19282 18788 21453 24482
78 21917 19713 19282 18788 21453
79 23812 21917 19713 19282 18788
80 23785 23812 21917 19713 19282
81 24696 23785 23812 21917 19713
82 24562 24696 23785 23812 21917
83 23580 24562 24696 23785 23812
84 24939 23580 24562 24696 23785
85 23899 24939 23580 24562 24696
86 21454 23899 24939 23580 24562
87 19761 21454 23899 24939 23580
88 19815 19761 21454 23899 24939
89 20780 19815 19761 21454 23899
90 23462 20780 19815 19761 21454
91 25005 23462 20780 19815 19761
92 24725 25005 23462 20780 19815
93 26198 24725 25005 23462 20780
94 27543 26198 24725 25005 23462
95 26471 27543 26198 24725 25005
96 26558 26471 27543 26198 24725
97 25317 26558 26471 27543 26198
98 22896 25317 26558 26471 27543
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X1 X2 X3 X4
1342.02139 1.14792 -0.01779 -0.20173 0.02783
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4580.0 -1684.1 127.6 1251.8 8390.9
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1342.02139 943.94558 1.422 0.158
X1 1.14792 0.10356 11.084 <2e-16 ***
X2 -0.01779 0.15446 -0.115 0.909
X3 -0.20173 0.15462 -1.305 0.195
X4 0.02783 0.10161 0.274 0.785
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 2207 on 93 degrees of freedom
Multiple R-squared: 0.936, Adjusted R-squared: 0.9333
F-statistic: 340.1 on 4 and 93 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,] 0.5557739 0.8884521527 0.4442260763
[2,] 0.7112647 0.5774705798 0.2887352899
[3,] 0.6640781 0.6718437577 0.3359218789
[4,] 0.5491885 0.9016230384 0.4508115192
[5,] 0.4295921 0.8591841427 0.5704079287
[6,] 0.3487004 0.6974007388 0.6512996306
[7,] 0.2920712 0.5841424665 0.7079287668
[8,] 0.2811981 0.5623961692 0.7188019154
[9,] 0.3183259 0.6366518259 0.6816740870
[10,] 0.5954163 0.8091673143 0.4045836571
[11,] 0.5974395 0.8051210809 0.4025605405
[12,] 0.6118498 0.7763003010 0.3881501505
[13,] 0.5891609 0.8216782200 0.4108391100
[14,] 0.6410869 0.7178262419 0.3589131209
[15,] 0.6835000 0.6330000835 0.3165000418
[16,] 0.6793298 0.6413403170 0.3206701585
[17,] 0.6818324 0.6363352606 0.3181676303
[18,] 0.6513779 0.6972442615 0.3486221308
[19,] 0.6262043 0.7475913614 0.3737956807
[20,] 0.7921127 0.4157746759 0.2078873380
[21,] 0.9942149 0.0115702602 0.0057851301
[22,] 0.9925726 0.0148547546 0.0074273773
[23,] 0.9926983 0.0146034182 0.0073017091
[24,] 0.9891274 0.0217451228 0.0108725614
[25,] 0.9852148 0.0295704549 0.0147852275
[26,] 0.9801670 0.0396659323 0.0198329661
[27,] 0.9730370 0.0539259516 0.0269629758
[28,] 0.9731550 0.0536899318 0.0268449659
[29,] 0.9649654 0.0700692373 0.0350346186
[30,] 0.9686774 0.0626451287 0.0313225643
[31,] 0.9760037 0.0479926146 0.0239963073
[32,] 0.9694545 0.0610910658 0.0305455329
[33,] 0.9736876 0.0526248624 0.0263124312
[34,] 0.9761288 0.0477424201 0.0238712100
[35,] 0.9664147 0.0671705273 0.0335852636
[36,] 0.9947332 0.0105336779 0.0052668389
[37,] 0.9920865 0.0158269799 0.0079134899
[38,] 0.9897578 0.0204844806 0.0102422403
[39,] 0.9872073 0.0255854898 0.0127927449
[40,] 0.9846127 0.0307746062 0.0153873031
[41,] 0.9895396 0.0209208815 0.0104604408
[42,] 0.9889648 0.0220703334 0.0110351667
[43,] 0.9954411 0.0091177988 0.0045588994
[44,] 0.9943084 0.0113832948 0.0056916474
[45,] 0.9960735 0.0078529979 0.0039264989
[46,] 0.9946360 0.0107279367 0.0053639683
[47,] 0.9962738 0.0074523757 0.0037261879
[48,] 0.9974077 0.0051846467 0.0025923233
[49,] 0.9967923 0.0064154425 0.0032077213
[50,] 0.9979261 0.0041478284 0.0020739142
[51,] 0.9979017 0.0041966378 0.0020983189
[52,] 0.9988814 0.0022371945 0.0011185972
[53,] 0.9985216 0.0029568964 0.0014784482
[54,] 0.9985433 0.0029134784 0.0014567392
[55,] 0.9984080 0.0031839222 0.0015919611
[56,] 0.9980600 0.0038799832 0.0019399916
[57,] 0.9984852 0.0030295826 0.0015147913
[58,] 0.9975220 0.0049560867 0.0024780434
[59,] 0.9963023 0.0073953330 0.0036976665
[60,] 0.9987981 0.0024037023 0.0012018511
[61,] 0.9981441 0.0037117656 0.0018558828
[62,] 0.9987854 0.0024292394 0.0012146197
[63,] 0.9991595 0.0016809858 0.0008404929
[64,] 0.9998825 0.0002350201 0.0001175100
[65,] 0.9998961 0.0002078357 0.0001039178
[66,] 0.9998186 0.0003628432 0.0001814216
[67,] 0.9997061 0.0005877641 0.0002938821
[68,] 0.9997457 0.0005086309 0.0002543155
[69,] 0.9995783 0.0008433675 0.0004216838
[70,] 0.9991215 0.0017570759 0.0008785380
[71,] 0.9988621 0.0022757382 0.0011378691
[72,] 0.9975547 0.0048906140 0.0024453070
[73,] 0.9967472 0.0065056965 0.0032528482
[74,] 0.9930796 0.0138408396 0.0069204198
[75,] 0.9896995 0.0206010234 0.0103005117
[76,] 0.9803608 0.0392783526 0.0196391763
[77,] 0.9798396 0.0403208520 0.0201604260
[78,] 0.9747753 0.0504494925 0.0252247463
[79,] 0.9629985 0.0740029204 0.0370014602
[80,] 0.9733620 0.0532759849 0.0266379924
[81,] 0.9564088 0.0871823148 0.0435911574
[82,] 0.9099634 0.1800731074 0.0900365537
[83,] 0.8899502 0.2200995024 0.1100497512
> postscript(file="/var/www/html/freestat/rcomp/tmp/1wrb01293201825.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2o0al1293201825.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/freestat/rcomp/tmp/3o0al1293201825.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4o0al1293201825.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5zsro1293201825.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 = 98
Frequency = 1
1 2 3 4 5 6
-1745.01031 369.28116 -2765.89491 1917.44059 2559.74570 -2459.18311
7 8 9 10 11 12
2743.25286 -1377.93459 4137.38383 -704.31215 -877.48173 -541.74659
13 14 15 16 17 18
974.67526 781.42904 1520.55095 1813.49207 4324.07639 3007.39747
19 20 21 22 23 24
-924.33475 -1805.66088 2603.01419 3017.61932 -1933.93353 -1849.52121
25 26 27 28 29 30
2014.81801 -1976.91247 -4580.04933 8390.93277 -1128.74312 1703.23933
31 32 33 34 35 36
-165.01797 815.92401 937.43490 -1114.81230 1842.64332 -1236.99762
37 38 39 40 41 42
-2530.99279 -2435.15920 -648.67845 2684.16842 2606.68898 317.16700
43 44 45 46 47 48
4905.87189 83.28140 -505.03651 -772.30049 -2076.12006 1149.22469
49 50 51 52 53 54
-2776.57403 -4398.81245 -686.05716 2245.40147 724.42905 2103.98779
55 56 57 58 59 60
1756.39279 -1603.77391 697.22442 -2946.97765 -45.81329 -1764.21702
61 62 63 64 65 66
-3464.82659 -2529.83742 1074.45390 2021.10914 205.49207 1096.70013
67 68 69 70 71 72
3110.15456 -1710.81382 668.03255 -3295.38769 171.93779 682.01071
73 74 75 76 77 78
-3248.32427 -2764.78599 -1961.22702 928.67871 217.40927 1482.12236
79 80 81 82 83 84
1028.58217 -1061.32285 347.00644 -512.28670 -1382.43765 1285.96782
85 86 87 88 89 90
-1383.91596 -2805.26631 -1408.61569 297.70148 706.30238 2008.02606
91 92 93 94 95 96
547.46843 -1262.89436 1073.16413 958.92526 -1730.24917 -83.80363
97 98
-1213.40886 -2461.97088
> postscript(file="/var/www/html/freestat/rcomp/tmp/6zsro1293201825.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 = 98
Frequency = 1
lag(myerror, k = 1) myerror
0 -1745.01031 NA
1 369.28116 -1745.01031
2 -2765.89491 369.28116
3 1917.44059 -2765.89491
4 2559.74570 1917.44059
5 -2459.18311 2559.74570
6 2743.25286 -2459.18311
7 -1377.93459 2743.25286
8 4137.38383 -1377.93459
9 -704.31215 4137.38383
10 -877.48173 -704.31215
11 -541.74659 -877.48173
12 974.67526 -541.74659
13 781.42904 974.67526
14 1520.55095 781.42904
15 1813.49207 1520.55095
16 4324.07639 1813.49207
17 3007.39747 4324.07639
18 -924.33475 3007.39747
19 -1805.66088 -924.33475
20 2603.01419 -1805.66088
21 3017.61932 2603.01419
22 -1933.93353 3017.61932
23 -1849.52121 -1933.93353
24 2014.81801 -1849.52121
25 -1976.91247 2014.81801
26 -4580.04933 -1976.91247
27 8390.93277 -4580.04933
28 -1128.74312 8390.93277
29 1703.23933 -1128.74312
30 -165.01797 1703.23933
31 815.92401 -165.01797
32 937.43490 815.92401
33 -1114.81230 937.43490
34 1842.64332 -1114.81230
35 -1236.99762 1842.64332
36 -2530.99279 -1236.99762
37 -2435.15920 -2530.99279
38 -648.67845 -2435.15920
39 2684.16842 -648.67845
40 2606.68898 2684.16842
41 317.16700 2606.68898
42 4905.87189 317.16700
43 83.28140 4905.87189
44 -505.03651 83.28140
45 -772.30049 -505.03651
46 -2076.12006 -772.30049
47 1149.22469 -2076.12006
48 -2776.57403 1149.22469
49 -4398.81245 -2776.57403
50 -686.05716 -4398.81245
51 2245.40147 -686.05716
52 724.42905 2245.40147
53 2103.98779 724.42905
54 1756.39279 2103.98779
55 -1603.77391 1756.39279
56 697.22442 -1603.77391
57 -2946.97765 697.22442
58 -45.81329 -2946.97765
59 -1764.21702 -45.81329
60 -3464.82659 -1764.21702
61 -2529.83742 -3464.82659
62 1074.45390 -2529.83742
63 2021.10914 1074.45390
64 205.49207 2021.10914
65 1096.70013 205.49207
66 3110.15456 1096.70013
67 -1710.81382 3110.15456
68 668.03255 -1710.81382
69 -3295.38769 668.03255
70 171.93779 -3295.38769
71 682.01071 171.93779
72 -3248.32427 682.01071
73 -2764.78599 -3248.32427
74 -1961.22702 -2764.78599
75 928.67871 -1961.22702
76 217.40927 928.67871
77 1482.12236 217.40927
78 1028.58217 1482.12236
79 -1061.32285 1028.58217
80 347.00644 -1061.32285
81 -512.28670 347.00644
82 -1382.43765 -512.28670
83 1285.96782 -1382.43765
84 -1383.91596 1285.96782
85 -2805.26631 -1383.91596
86 -1408.61569 -2805.26631
87 297.70148 -1408.61569
88 706.30238 297.70148
89 2008.02606 706.30238
90 547.46843 2008.02606
91 -1262.89436 547.46843
92 1073.16413 -1262.89436
93 958.92526 1073.16413
94 -1730.24917 958.92526
95 -83.80363 -1730.24917
96 -1213.40886 -83.80363
97 -2461.97088 -1213.40886
98 NA -2461.97088
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 369.28116 -1745.01031
[2,] -2765.89491 369.28116
[3,] 1917.44059 -2765.89491
[4,] 2559.74570 1917.44059
[5,] -2459.18311 2559.74570
[6,] 2743.25286 -2459.18311
[7,] -1377.93459 2743.25286
[8,] 4137.38383 -1377.93459
[9,] -704.31215 4137.38383
[10,] -877.48173 -704.31215
[11,] -541.74659 -877.48173
[12,] 974.67526 -541.74659
[13,] 781.42904 974.67526
[14,] 1520.55095 781.42904
[15,] 1813.49207 1520.55095
[16,] 4324.07639 1813.49207
[17,] 3007.39747 4324.07639
[18,] -924.33475 3007.39747
[19,] -1805.66088 -924.33475
[20,] 2603.01419 -1805.66088
[21,] 3017.61932 2603.01419
[22,] -1933.93353 3017.61932
[23,] -1849.52121 -1933.93353
[24,] 2014.81801 -1849.52121
[25,] -1976.91247 2014.81801
[26,] -4580.04933 -1976.91247
[27,] 8390.93277 -4580.04933
[28,] -1128.74312 8390.93277
[29,] 1703.23933 -1128.74312
[30,] -165.01797 1703.23933
[31,] 815.92401 -165.01797
[32,] 937.43490 815.92401
[33,] -1114.81230 937.43490
[34,] 1842.64332 -1114.81230
[35,] -1236.99762 1842.64332
[36,] -2530.99279 -1236.99762
[37,] -2435.15920 -2530.99279
[38,] -648.67845 -2435.15920
[39,] 2684.16842 -648.67845
[40,] 2606.68898 2684.16842
[41,] 317.16700 2606.68898
[42,] 4905.87189 317.16700
[43,] 83.28140 4905.87189
[44,] -505.03651 83.28140
[45,] -772.30049 -505.03651
[46,] -2076.12006 -772.30049
[47,] 1149.22469 -2076.12006
[48,] -2776.57403 1149.22469
[49,] -4398.81245 -2776.57403
[50,] -686.05716 -4398.81245
[51,] 2245.40147 -686.05716
[52,] 724.42905 2245.40147
[53,] 2103.98779 724.42905
[54,] 1756.39279 2103.98779
[55,] -1603.77391 1756.39279
[56,] 697.22442 -1603.77391
[57,] -2946.97765 697.22442
[58,] -45.81329 -2946.97765
[59,] -1764.21702 -45.81329
[60,] -3464.82659 -1764.21702
[61,] -2529.83742 -3464.82659
[62,] 1074.45390 -2529.83742
[63,] 2021.10914 1074.45390
[64,] 205.49207 2021.10914
[65,] 1096.70013 205.49207
[66,] 3110.15456 1096.70013
[67,] -1710.81382 3110.15456
[68,] 668.03255 -1710.81382
[69,] -3295.38769 668.03255
[70,] 171.93779 -3295.38769
[71,] 682.01071 171.93779
[72,] -3248.32427 682.01071
[73,] -2764.78599 -3248.32427
[74,] -1961.22702 -2764.78599
[75,] 928.67871 -1961.22702
[76,] 217.40927 928.67871
[77,] 1482.12236 217.40927
[78,] 1028.58217 1482.12236
[79,] -1061.32285 1028.58217
[80,] 347.00644 -1061.32285
[81,] -512.28670 347.00644
[82,] -1382.43765 -512.28670
[83,] 1285.96782 -1382.43765
[84,] -1383.91596 1285.96782
[85,] -2805.26631 -1383.91596
[86,] -1408.61569 -2805.26631
[87,] 297.70148 -1408.61569
[88,] 706.30238 297.70148
[89,] 2008.02606 706.30238
[90,] 547.46843 2008.02606
[91,] -1262.89436 547.46843
[92,] 1073.16413 -1262.89436
[93,] 958.92526 1073.16413
[94,] -1730.24917 958.92526
[95,] -83.80363 -1730.24917
[96,] -1213.40886 -83.80363
[97,] -2461.97088 -1213.40886
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 369.28116 -1745.01031
2 -2765.89491 369.28116
3 1917.44059 -2765.89491
4 2559.74570 1917.44059
5 -2459.18311 2559.74570
6 2743.25286 -2459.18311
7 -1377.93459 2743.25286
8 4137.38383 -1377.93459
9 -704.31215 4137.38383
10 -877.48173 -704.31215
11 -541.74659 -877.48173
12 974.67526 -541.74659
13 781.42904 974.67526
14 1520.55095 781.42904
15 1813.49207 1520.55095
16 4324.07639 1813.49207
17 3007.39747 4324.07639
18 -924.33475 3007.39747
19 -1805.66088 -924.33475
20 2603.01419 -1805.66088
21 3017.61932 2603.01419
22 -1933.93353 3017.61932
23 -1849.52121 -1933.93353
24 2014.81801 -1849.52121
25 -1976.91247 2014.81801
26 -4580.04933 -1976.91247
27 8390.93277 -4580.04933
28 -1128.74312 8390.93277
29 1703.23933 -1128.74312
30 -165.01797 1703.23933
31 815.92401 -165.01797
32 937.43490 815.92401
33 -1114.81230 937.43490
34 1842.64332 -1114.81230
35 -1236.99762 1842.64332
36 -2530.99279 -1236.99762
37 -2435.15920 -2530.99279
38 -648.67845 -2435.15920
39 2684.16842 -648.67845
40 2606.68898 2684.16842
41 317.16700 2606.68898
42 4905.87189 317.16700
43 83.28140 4905.87189
44 -505.03651 83.28140
45 -772.30049 -505.03651
46 -2076.12006 -772.30049
47 1149.22469 -2076.12006
48 -2776.57403 1149.22469
49 -4398.81245 -2776.57403
50 -686.05716 -4398.81245
51 2245.40147 -686.05716
52 724.42905 2245.40147
53 2103.98779 724.42905
54 1756.39279 2103.98779
55 -1603.77391 1756.39279
56 697.22442 -1603.77391
57 -2946.97765 697.22442
58 -45.81329 -2946.97765
59 -1764.21702 -45.81329
60 -3464.82659 -1764.21702
61 -2529.83742 -3464.82659
62 1074.45390 -2529.83742
63 2021.10914 1074.45390
64 205.49207 2021.10914
65 1096.70013 205.49207
66 3110.15456 1096.70013
67 -1710.81382 3110.15456
68 668.03255 -1710.81382
69 -3295.38769 668.03255
70 171.93779 -3295.38769
71 682.01071 171.93779
72 -3248.32427 682.01071
73 -2764.78599 -3248.32427
74 -1961.22702 -2764.78599
75 928.67871 -1961.22702
76 217.40927 928.67871
77 1482.12236 217.40927
78 1028.58217 1482.12236
79 -1061.32285 1028.58217
80 347.00644 -1061.32285
81 -512.28670 347.00644
82 -1382.43765 -512.28670
83 1285.96782 -1382.43765
84 -1383.91596 1285.96782
85 -2805.26631 -1383.91596
86 -1408.61569 -2805.26631
87 297.70148 -1408.61569
88 706.30238 297.70148
89 2008.02606 706.30238
90 547.46843 2008.02606
91 -1262.89436 547.46843
92 1073.16413 -1262.89436
93 958.92526 1073.16413
94 -1730.24917 958.92526
95 -83.80363 -1730.24917
96 -1213.40886 -83.80363
97 -2461.97088 -1213.40886
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/7sjrr1293201825.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8sjrr1293201825.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9ksqc1293201825.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10ksqc1293201825.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/11tev61293201825.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/129tno1293201825.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/1353ke1293201825.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/14ql121293201825.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/15cmi81293201825.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/16xngw1293201825.tab")
+ }
>
> try(system("convert tmp/1wrb01293201825.ps tmp/1wrb01293201825.png",intern=TRUE))
character(0)
> try(system("convert tmp/2o0al1293201825.ps tmp/2o0al1293201825.png",intern=TRUE))
character(0)
> try(system("convert tmp/3o0al1293201825.ps tmp/3o0al1293201825.png",intern=TRUE))
character(0)
> try(system("convert tmp/4o0al1293201825.ps tmp/4o0al1293201825.png",intern=TRUE))
character(0)
> try(system("convert tmp/5zsro1293201825.ps tmp/5zsro1293201825.png",intern=TRUE))
character(0)
> try(system("convert tmp/6zsro1293201825.ps tmp/6zsro1293201825.png",intern=TRUE))
character(0)
> try(system("convert tmp/7sjrr1293201825.ps tmp/7sjrr1293201825.png",intern=TRUE))
character(0)
> try(system("convert tmp/8sjrr1293201825.ps tmp/8sjrr1293201825.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ksqc1293201825.ps tmp/9ksqc1293201825.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ksqc1293201825.ps tmp/10ksqc1293201825.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.490 2.582 4.838