R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
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'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(103.7
+ ,114813
+ ,123297
+ ,116476
+ ,109375
+ ,106370
+ ,106.2
+ ,117925
+ ,114813
+ ,123297
+ ,116476
+ ,109375
+ ,107.7
+ ,126466
+ ,117925
+ ,114813
+ ,123297
+ ,116476
+ ,109.9
+ ,131235
+ ,126466
+ ,117925
+ ,114813
+ ,123297
+ ,111.7
+ ,120546
+ ,131235
+ ,126466
+ ,117925
+ ,114813
+ ,114.9
+ ,123791
+ ,120546
+ ,131235
+ ,126466
+ ,117925
+ ,116
+ ,129813
+ ,123791
+ ,120546
+ ,131235
+ ,126466
+ ,118.3
+ ,133463
+ ,129813
+ ,123791
+ ,120546
+ ,131235
+ ,120.4
+ ,122987
+ ,133463
+ ,129813
+ ,123791
+ ,120546
+ ,126
+ ,125418
+ ,122987
+ ,133463
+ ,129813
+ ,123791
+ ,128.1
+ ,130199
+ ,125418
+ ,122987
+ ,133463
+ ,129813
+ ,130.1
+ ,133016
+ ,130199
+ ,125418
+ ,122987
+ ,133463
+ ,130.8
+ ,121454
+ ,133016
+ ,130199
+ ,125418
+ ,122987
+ ,133.6
+ ,122044
+ ,121454
+ ,133016
+ ,130199
+ ,125418
+ ,134.2
+ ,128313
+ ,122044
+ ,121454
+ ,133016
+ ,130199
+ ,135.5
+ ,131556
+ ,128313
+ ,122044
+ ,121454
+ ,133016
+ ,136.2
+ ,120027
+ ,131556
+ ,128313
+ ,122044
+ ,121454
+ ,139.1
+ ,123001
+ ,120027
+ ,131556
+ ,128313
+ ,122044
+ ,139
+ ,130111
+ ,123001
+ ,120027
+ ,131556
+ ,128313
+ ,139.6
+ ,132524
+ ,130111
+ ,123001
+ ,120027
+ ,131556
+ ,138.7
+ ,123742
+ ,132524
+ ,130111
+ ,123001
+ ,120027
+ ,140.9
+ ,124931
+ ,123742
+ ,132524
+ ,130111
+ ,123001
+ ,141.3
+ ,133646
+ ,124931
+ ,123742
+ ,132524
+ ,130111
+ ,141.8
+ ,136557
+ ,133646
+ ,124931
+ ,123742
+ ,132524
+ ,142
+ ,127509
+ ,136557
+ ,133646
+ ,124931
+ ,123742
+ ,144.5
+ ,128945
+ ,127509
+ ,136557
+ ,133646
+ ,124931
+ ,144.6
+ ,137191
+ ,128945
+ ,127509
+ ,136557
+ ,133646
+ ,145.5
+ ,139716
+ ,137191
+ ,128945
+ ,127509
+ ,136557
+ ,146.8
+ ,129083
+ ,139716
+ ,137191
+ ,128945
+ ,127509
+ ,149.5
+ ,131604
+ ,129083
+ ,139716
+ ,137191
+ ,128945
+ ,149.9
+ ,139413
+ ,131604
+ ,129083
+ ,139716
+ ,137191
+ ,150.1
+ ,143125
+ ,139413
+ ,131604
+ ,129083
+ ,139716
+ ,150.9
+ ,133948
+ ,143125
+ ,139413
+ ,131604
+ ,129083
+ ,152.8
+ ,137116
+ ,133948
+ ,143125
+ ,139413
+ ,131604
+ ,153.1
+ ,144864
+ ,137116
+ ,133948
+ ,143125
+ ,139413
+ ,154
+ ,149277
+ ,144864
+ ,137116
+ ,133948
+ ,143125
+ ,154.9
+ ,138796
+ ,149277
+ ,144864
+ ,137116
+ ,133948
+ ,156.9
+ ,143258
+ ,138796
+ ,149277
+ ,144864
+ ,137116
+ ,158.4
+ ,150034
+ ,143258
+ ,138796
+ ,149277
+ ,144864
+ ,159.7
+ ,154708
+ ,150034
+ ,143258
+ ,138796
+ ,149277
+ ,160.2
+ ,144888
+ ,154708
+ ,150034
+ ,143258
+ ,138796
+ ,163.2
+ ,148762
+ ,144888
+ ,154708
+ ,150034
+ ,143258
+ ,163.7
+ ,156500
+ ,148762
+ ,144888
+ ,154708
+ ,150034
+ ,164.4
+ ,161088
+ ,156500
+ ,148762
+ ,144888
+ ,154708
+ ,163.7
+ ,152772
+ ,161088
+ ,156500
+ ,148762
+ ,144888
+ ,165.5
+ ,158011
+ ,152772
+ ,161088
+ ,156500
+ ,148762
+ ,165.6
+ ,163318
+ ,158011
+ ,152772
+ ,161088
+ ,156500
+ ,166.8
+ ,169969
+ ,163318
+ ,158011
+ ,152772
+ ,161088
+ ,167.5
+ ,162269
+ ,169969
+ ,163318
+ ,158011
+ ,152772
+ ,170.6
+ ,165765
+ ,162269
+ ,169969
+ ,163318
+ ,158011
+ ,170.9
+ ,170600
+ ,165765
+ ,162269
+ ,169969
+ ,163318
+ ,172
+ ,174681
+ ,170600
+ ,165765
+ ,162269
+ ,169969
+ ,171.8
+ ,166364
+ ,174681
+ ,170600
+ ,165765
+ ,162269
+ ,173.9
+ ,170240
+ ,166364
+ ,174681
+ ,170600
+ ,165765
+ ,174
+ ,176150
+ ,170240
+ ,166364
+ ,174681
+ ,170600
+ ,173.8
+ ,182056
+ ,176150
+ ,170240
+ ,166364
+ ,174681
+ ,173.9
+ ,172218
+ ,182056
+ ,176150
+ ,170240
+ ,166364
+ ,176
+ ,177856
+ ,172218
+ ,182056
+ ,176150
+ ,170240
+ ,176.6
+ ,182253
+ ,177856
+ ,172218
+ ,182056
+ ,176150
+ ,178.2
+ ,188090
+ ,182253
+ ,177856
+ ,172218
+ ,182056
+ ,179.2
+ ,176863
+ ,188090
+ ,182253
+ ,177856
+ ,172218
+ ,181.3
+ ,183273
+ ,176863
+ ,188090
+ ,182253
+ ,177856
+ ,181.8
+ ,187969
+ ,183273
+ ,176863
+ ,188090
+ ,182253
+ ,182.9
+ ,194650
+ ,187969
+ ,183273
+ ,176863
+ ,188090
+ ,183.8
+ ,183036
+ ,194650
+ ,187969
+ ,183273
+ ,176863
+ ,186.3
+ ,189516
+ ,183036
+ ,194650
+ ,187969
+ ,183273
+ ,187.4
+ ,193805
+ ,189516
+ ,183036
+ ,194650
+ ,187969
+ ,189.2
+ ,200499
+ ,193805
+ ,189516
+ ,183036
+ ,194650
+ ,189.7
+ ,188142
+ ,200499
+ ,193805
+ ,189516
+ ,183036
+ ,191.9
+ ,193732
+ ,188142
+ ,200499
+ ,193805
+ ,189516
+ ,192.6
+ ,197126
+ ,193732
+ ,188142
+ ,200499
+ ,193805
+ ,193.7
+ ,205140
+ ,197126
+ ,193732
+ ,188142
+ ,200499
+ ,194.2
+ ,191751
+ ,205140
+ ,197126
+ ,193732
+ ,188142
+ ,197.6
+ ,196700
+ ,191751
+ ,205140
+ ,197126
+ ,193732
+ ,199.3
+ ,199784
+ ,196700
+ ,191751
+ ,205140
+ ,197126
+ ,201.4
+ ,207360
+ ,199784
+ ,196700
+ ,191751
+ ,205140
+ ,203
+ ,196101
+ ,207360
+ ,199784
+ ,196700
+ ,191751
+ ,206.3
+ ,200824
+ ,196101
+ ,207360
+ ,199784
+ ,196700
+ ,207.1
+ ,205743
+ ,200824
+ ,196101
+ ,207360
+ ,199784
+ ,209.8
+ ,212489
+ ,205743
+ ,200824
+ ,196101
+ ,207360
+ ,211.1
+ ,200810
+ ,212489
+ ,205743
+ ,200824
+ ,196101
+ ,215.3
+ ,203683
+ ,200810
+ ,212489
+ ,205743
+ ,200824
+ ,217.4
+ ,207286
+ ,203683
+ ,200810
+ ,212489
+ ,205743
+ ,215.5
+ ,210910
+ ,207286
+ ,203683
+ ,200810
+ ,212489
+ ,210.9
+ ,194915
+ ,210910
+ ,207286
+ ,203683
+ ,200810
+ ,212.6
+ ,217920
+ ,194915
+ ,210910
+ ,207286
+ ,203683)
+ ,dim=c(6
+ ,86)
+ ,dimnames=list(c('RPI'
+ ,'HFCE'
+ ,'HFCE-1'
+ ,'HFCE-2'
+ ,'HFCE-3'
+ ,'HFCE-4')
+ ,1:86))
> y <- array(NA,dim=c(6,86),dimnames=list(c('RPI','HFCE','HFCE-1','HFCE-2','HFCE-3','HFCE-4'),1:86))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Quarterly Dummies'
> par1 = '2'
> #'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
HFCE RPI HFCE-1 HFCE-2 HFCE-3 HFCE-4 Q1 Q2 Q3 t
1 114813 103.7 123297 116476 109375 106370 1 0 0 1
2 117925 106.2 114813 123297 116476 109375 0 1 0 2
3 126466 107.7 117925 114813 123297 116476 0 0 1 3
4 131235 109.9 126466 117925 114813 123297 0 0 0 4
5 120546 111.7 131235 126466 117925 114813 1 0 0 5
6 123791 114.9 120546 131235 126466 117925 0 1 0 6
7 129813 116.0 123791 120546 131235 126466 0 0 1 7
8 133463 118.3 129813 123791 120546 131235 0 0 0 8
9 122987 120.4 133463 129813 123791 120546 1 0 0 9
10 125418 126.0 122987 133463 129813 123791 0 1 0 10
11 130199 128.1 125418 122987 133463 129813 0 0 1 11
12 133016 130.1 130199 125418 122987 133463 0 0 0 12
13 121454 130.8 133016 130199 125418 122987 1 0 0 13
14 122044 133.6 121454 133016 130199 125418 0 1 0 14
15 128313 134.2 122044 121454 133016 130199 0 0 1 15
16 131556 135.5 128313 122044 121454 133016 0 0 0 16
17 120027 136.2 131556 128313 122044 121454 1 0 0 17
18 123001 139.1 120027 131556 128313 122044 0 1 0 18
19 130111 139.0 123001 120027 131556 128313 0 0 1 19
20 132524 139.6 130111 123001 120027 131556 0 0 0 20
21 123742 138.7 132524 130111 123001 120027 1 0 0 21
22 124931 140.9 123742 132524 130111 123001 0 1 0 22
23 133646 141.3 124931 123742 132524 130111 0 0 1 23
24 136557 141.8 133646 124931 123742 132524 0 0 0 24
25 127509 142.0 136557 133646 124931 123742 1 0 0 25
26 128945 144.5 127509 136557 133646 124931 0 1 0 26
27 137191 144.6 128945 127509 136557 133646 0 0 1 27
28 139716 145.5 137191 128945 127509 136557 0 0 0 28
29 129083 146.8 139716 137191 128945 127509 1 0 0 29
30 131604 149.5 129083 139716 137191 128945 0 1 0 30
31 139413 149.9 131604 129083 139716 137191 0 0 1 31
32 143125 150.1 139413 131604 129083 139716 0 0 0 32
33 133948 150.9 143125 139413 131604 129083 1 0 0 33
34 137116 152.8 133948 143125 139413 131604 0 1 0 34
35 144864 153.1 137116 133948 143125 139413 0 0 1 35
36 149277 154.0 144864 137116 133948 143125 0 0 0 36
37 138796 154.9 149277 144864 137116 133948 1 0 0 37
38 143258 156.9 138796 149277 144864 137116 0 1 0 38
39 150034 158.4 143258 138796 149277 144864 0 0 1 39
40 154708 159.7 150034 143258 138796 149277 0 0 0 40
41 144888 160.2 154708 150034 143258 138796 1 0 0 41
42 148762 163.2 144888 154708 150034 143258 0 1 0 42
43 156500 163.7 148762 144888 154708 150034 0 0 1 43
44 161088 164.4 156500 148762 144888 154708 0 0 0 44
45 152772 163.7 161088 156500 148762 144888 1 0 0 45
46 158011 165.5 152772 161088 156500 148762 0 1 0 46
47 163318 165.6 158011 152772 161088 156500 0 0 1 47
48 169969 166.8 163318 158011 152772 161088 0 0 0 48
49 162269 167.5 169969 163318 158011 152772 1 0 0 49
50 165765 170.6 162269 169969 163318 158011 0 1 0 50
51 170600 170.9 165765 162269 169969 163318 0 0 1 51
52 174681 172.0 170600 165765 162269 169969 0 0 0 52
53 166364 171.8 174681 170600 165765 162269 1 0 0 53
54 170240 173.9 166364 174681 170600 165765 0 1 0 54
55 176150 174.0 170240 166364 174681 170600 0 0 1 55
56 182056 173.8 176150 170240 166364 174681 0 0 0 56
57 172218 173.9 182056 176150 170240 166364 1 0 0 57
58 177856 176.0 172218 182056 176150 170240 0 1 0 58
59 182253 176.6 177856 172218 182056 176150 0 0 1 59
60 188090 178.2 182253 177856 172218 182056 0 0 0 60
61 176863 179.2 188090 182253 177856 172218 1 0 0 61
62 183273 181.3 176863 188090 182253 177856 0 1 0 62
63 187969 181.8 183273 176863 188090 182253 0 0 1 63
64 194650 182.9 187969 183273 176863 188090 0 0 0 64
65 183036 183.8 194650 187969 183273 176863 1 0 0 65
66 189516 186.3 183036 194650 187969 183273 0 1 0 66
67 193805 187.4 189516 183036 194650 187969 0 0 1 67
68 200499 189.2 193805 189516 183036 194650 0 0 0 68
69 188142 189.7 200499 193805 189516 183036 1 0 0 69
70 193732 191.9 188142 200499 193805 189516 0 1 0 70
71 197126 192.6 193732 188142 200499 193805 0 0 1 71
72 205140 193.7 197126 193732 188142 200499 0 0 0 72
73 191751 194.2 205140 197126 193732 188142 1 0 0 73
74 196700 197.6 191751 205140 197126 193732 0 1 0 74
75 199784 199.3 196700 191751 205140 197126 0 0 1 75
76 207360 201.4 199784 196700 191751 205140 0 0 0 76
77 196101 203.0 207360 199784 196700 191751 1 0 0 77
78 200824 206.3 196101 207360 199784 196700 0 1 0 78
79 205743 207.1 200824 196101 207360 199784 0 0 1 79
80 212489 209.8 205743 200824 196101 207360 0 0 0 80
81 200810 211.1 212489 205743 200824 196101 1 0 0 81
82 203683 215.3 200810 212489 205743 200824 0 1 0 82
83 207286 217.4 203683 200810 212489 205743 0 0 1 83
84 210910 215.5 207286 203683 200810 212489 0 0 0 84
85 194915 210.9 210910 207286 203683 200810 1 0 0 85
86 217920 212.6 194915 210910 207286 203683 0 1 0 86
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) RPI `HFCE-1` `HFCE-2` `HFCE-3` `HFCE-4`
7.377e+04 -4.416e+02 1.345e-02 6.703e-01 -1.126e-01 2.694e-01
Q1 Q2 Q3 t
-1.193e+04 -1.033e+04 4.731e+02 7.201e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7945.6 -664.3 -138.3 484.0 10906.1
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.377e+04 1.260e+04 5.854 1.15e-07 ***
RPI -4.416e+02 8.487e+01 -5.203 1.61e-06 ***
`HFCE-1` 1.345e-02 1.771e-01 0.076 0.939630
`HFCE-2` 6.703e-01 2.131e-01 3.145 0.002371 **
`HFCE-3` -1.126e-01 2.044e-01 -0.551 0.583344
`HFCE-4` 2.694e-01 1.903e-01 1.416 0.160989
Q1 -1.193e+04 2.951e+03 -4.041 0.000126 ***
Q2 -1.033e+04 5.126e+03 -2.014 0.047511 *
Q3 4.731e+02 3.356e+03 0.141 0.888260
t 7.201e+02 1.293e+02 5.570 3.69e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2001 on 76 degrees of freedom
Multiple R-squared: 0.9961, Adjusted R-squared: 0.9957
F-statistic: 2164 on 9 and 76 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,] 3.051715e-02 6.103430e-02 0.9694828
[2,] 7.325169e-03 1.465034e-02 0.9926748
[3,] 1.035306e-02 2.070613e-02 0.9896469
[4,] 3.931719e-03 7.863438e-03 0.9960683
[5,] 1.267193e-03 2.534386e-03 0.9987328
[6,] 4.673885e-04 9.347770e-04 0.9995326
[7,] 2.212454e-04 4.424908e-04 0.9997788
[8,] 1.394245e-04 2.788490e-04 0.9998606
[9,] 7.120401e-05 1.424080e-04 0.9999288
[10,] 1.273028e-04 2.546056e-04 0.9998727
[11,] 2.041945e-04 4.083889e-04 0.9997958
[12,] 8.977375e-05 1.795475e-04 0.9999102
[13,] 3.589123e-05 7.178245e-05 0.9999641
[14,] 1.727351e-05 3.454702e-05 0.9999827
[15,] 6.404079e-06 1.280816e-05 0.9999936
[16,] 2.762128e-06 5.524256e-06 0.9999972
[17,] 1.999967e-06 3.999935e-06 0.9999980
[18,] 6.843491e-07 1.368698e-06 0.9999993
[19,] 3.880860e-07 7.761721e-07 0.9999996
[20,] 1.395390e-07 2.790781e-07 0.9999999
[21,] 8.148898e-08 1.629780e-07 0.9999999
[22,] 6.739284e-08 1.347857e-07 0.9999999
[23,] 2.547846e-08 5.095693e-08 1.0000000
[24,] 1.225148e-08 2.450297e-08 1.0000000
[25,] 4.337328e-09 8.674655e-09 1.0000000
[26,] 8.063319e-09 1.612664e-08 1.0000000
[27,] 2.839368e-09 5.678735e-09 1.0000000
[28,] 1.318095e-09 2.636190e-09 1.0000000
[29,] 5.604469e-10 1.120894e-09 1.0000000
[30,] 9.104685e-10 1.820937e-09 1.0000000
[31,] 4.260057e-10 8.520115e-10 1.0000000
[32,] 1.787727e-10 3.575453e-10 1.0000000
[33,] 1.321816e-10 2.643632e-10 1.0000000
[34,] 3.929129e-10 7.858258e-10 1.0000000
[35,] 1.941044e-09 3.882088e-09 1.0000000
[36,] 8.222463e-10 1.644493e-09 1.0000000
[37,] 3.808722e-09 7.617444e-09 1.0000000
[38,] 1.398892e-09 2.797783e-09 1.0000000
[39,] 7.632743e-09 1.526549e-08 1.0000000
[40,] 1.093706e-08 2.187412e-08 1.0000000
[41,] 5.295129e-09 1.059026e-08 1.0000000
[42,] 1.986585e-09 3.973171e-09 1.0000000
[43,] 2.134805e-09 4.269610e-09 1.0000000
[44,] 1.264669e-09 2.529337e-09 1.0000000
[45,] 9.130360e-10 1.826072e-09 1.0000000
[46,] 8.305673e-10 1.661135e-09 1.0000000
[47,] 2.133629e-09 4.267257e-09 1.0000000
[48,] 3.397869e-09 6.795739e-09 1.0000000
[49,] 1.959482e-09 3.918963e-09 1.0000000
[50,] 1.781577e-09 3.563155e-09 1.0000000
[51,] 8.218215e-10 1.643643e-09 1.0000000
[52,] 8.545568e-10 1.709114e-09 1.0000000
[53,] 9.336454e-10 1.867291e-09 1.0000000
[54,] 8.340689e-09 1.668138e-08 1.0000000
[55,] 7.597497e-09 1.519499e-08 1.0000000
[56,] 4.759788e-08 9.519576e-08 1.0000000
[57,] 1.327899e-05 2.655798e-05 0.9999867
[58,] 1.984146e-04 3.968292e-04 0.9998016
[59,] 2.538900e-03 5.077799e-03 0.9974611
[60,] 1.997965e-03 3.995929e-03 0.9980020
[61,] 1.583167e-03 3.166334e-03 0.9984168
> postscript(file="/var/www/html/rcomp/tmp/13h3v1258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2xdp81258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3efnk1258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4v21p1258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5px7k1258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 86
Frequency = 1
1 2 3 4 5 6
1973.945784 -599.632622 1584.626448 2084.351628 244.442573 -348.620853
7 8 9 10 11 12
-2.807372 -328.671277 489.389862 569.802837 536.981263 133.393557
13 14 15 16 17 18
-58.764046 -2403.255974 -617.220116 412.180771 -664.829196 -203.628619
19 20 21 22 23 24
1707.216522 -122.801781 547.689296 -1113.380219 485.973611 817.587298
25 26 27 28 29 30
-315.732296 -1265.943515 -469.396912 -670.516908 -2484.075103 -2100.271077
31 32 33 34 35 36
-477.569083 -596.660705 -348.888815 -828.065129 -43.767388 258.568374
37 38 39 40 41 42
-1041.434684 -815.947655 478.248719 28.259522 357.637316 -205.192264
43 44 45 46 47 48
1465.528903 1049.897897 1465.446763 2041.870164 -190.354054 988.099512
49 50 51 52 53 54
3988.086102 1363.002118 -755.138395 -1502.592923 471.706043 -67.612446
55 56 57 58 59 60
-952.855840 -95.651230 -45.978616 -7.420475 -1273.180519 -1513.749692
61 62 63 64 65 66
-832.427695 -601.984694 -292.435551 -569.093658 -69.572932 -327.318825
67 68 69 70 71 72
113.121613 -153.829039 -189.168258 -1532.792203 -1542.878257 -277.505997
73 74 75 76 77 78
-662.757059 -2849.397881 -1637.802596 -406.848630 2243.151877 189.057295
79 80 81 82 83 84
1447.765831 2598.306629 2877.764824 200.587906 435.943172 -2132.723349
85 86
-7945.631740 10906.144131
> postscript(file="/var/www/html/rcomp/tmp/64emw1258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 86
Frequency = 1
lag(myerror, k = 1) myerror
0 1973.945784 NA
1 -599.632622 1973.945784
2 1584.626448 -599.632622
3 2084.351628 1584.626448
4 244.442573 2084.351628
5 -348.620853 244.442573
6 -2.807372 -348.620853
7 -328.671277 -2.807372
8 489.389862 -328.671277
9 569.802837 489.389862
10 536.981263 569.802837
11 133.393557 536.981263
12 -58.764046 133.393557
13 -2403.255974 -58.764046
14 -617.220116 -2403.255974
15 412.180771 -617.220116
16 -664.829196 412.180771
17 -203.628619 -664.829196
18 1707.216522 -203.628619
19 -122.801781 1707.216522
20 547.689296 -122.801781
21 -1113.380219 547.689296
22 485.973611 -1113.380219
23 817.587298 485.973611
24 -315.732296 817.587298
25 -1265.943515 -315.732296
26 -469.396912 -1265.943515
27 -670.516908 -469.396912
28 -2484.075103 -670.516908
29 -2100.271077 -2484.075103
30 -477.569083 -2100.271077
31 -596.660705 -477.569083
32 -348.888815 -596.660705
33 -828.065129 -348.888815
34 -43.767388 -828.065129
35 258.568374 -43.767388
36 -1041.434684 258.568374
37 -815.947655 -1041.434684
38 478.248719 -815.947655
39 28.259522 478.248719
40 357.637316 28.259522
41 -205.192264 357.637316
42 1465.528903 -205.192264
43 1049.897897 1465.528903
44 1465.446763 1049.897897
45 2041.870164 1465.446763
46 -190.354054 2041.870164
47 988.099512 -190.354054
48 3988.086102 988.099512
49 1363.002118 3988.086102
50 -755.138395 1363.002118
51 -1502.592923 -755.138395
52 471.706043 -1502.592923
53 -67.612446 471.706043
54 -952.855840 -67.612446
55 -95.651230 -952.855840
56 -45.978616 -95.651230
57 -7.420475 -45.978616
58 -1273.180519 -7.420475
59 -1513.749692 -1273.180519
60 -832.427695 -1513.749692
61 -601.984694 -832.427695
62 -292.435551 -601.984694
63 -569.093658 -292.435551
64 -69.572932 -569.093658
65 -327.318825 -69.572932
66 113.121613 -327.318825
67 -153.829039 113.121613
68 -189.168258 -153.829039
69 -1532.792203 -189.168258
70 -1542.878257 -1532.792203
71 -277.505997 -1542.878257
72 -662.757059 -277.505997
73 -2849.397881 -662.757059
74 -1637.802596 -2849.397881
75 -406.848630 -1637.802596
76 2243.151877 -406.848630
77 189.057295 2243.151877
78 1447.765831 189.057295
79 2598.306629 1447.765831
80 2877.764824 2598.306629
81 200.587906 2877.764824
82 435.943172 200.587906
83 -2132.723349 435.943172
84 -7945.631740 -2132.723349
85 10906.144131 -7945.631740
86 NA 10906.144131
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -599.632622 1973.945784
[2,] 1584.626448 -599.632622
[3,] 2084.351628 1584.626448
[4,] 244.442573 2084.351628
[5,] -348.620853 244.442573
[6,] -2.807372 -348.620853
[7,] -328.671277 -2.807372
[8,] 489.389862 -328.671277
[9,] 569.802837 489.389862
[10,] 536.981263 569.802837
[11,] 133.393557 536.981263
[12,] -58.764046 133.393557
[13,] -2403.255974 -58.764046
[14,] -617.220116 -2403.255974
[15,] 412.180771 -617.220116
[16,] -664.829196 412.180771
[17,] -203.628619 -664.829196
[18,] 1707.216522 -203.628619
[19,] -122.801781 1707.216522
[20,] 547.689296 -122.801781
[21,] -1113.380219 547.689296
[22,] 485.973611 -1113.380219
[23,] 817.587298 485.973611
[24,] -315.732296 817.587298
[25,] -1265.943515 -315.732296
[26,] -469.396912 -1265.943515
[27,] -670.516908 -469.396912
[28,] -2484.075103 -670.516908
[29,] -2100.271077 -2484.075103
[30,] -477.569083 -2100.271077
[31,] -596.660705 -477.569083
[32,] -348.888815 -596.660705
[33,] -828.065129 -348.888815
[34,] -43.767388 -828.065129
[35,] 258.568374 -43.767388
[36,] -1041.434684 258.568374
[37,] -815.947655 -1041.434684
[38,] 478.248719 -815.947655
[39,] 28.259522 478.248719
[40,] 357.637316 28.259522
[41,] -205.192264 357.637316
[42,] 1465.528903 -205.192264
[43,] 1049.897897 1465.528903
[44,] 1465.446763 1049.897897
[45,] 2041.870164 1465.446763
[46,] -190.354054 2041.870164
[47,] 988.099512 -190.354054
[48,] 3988.086102 988.099512
[49,] 1363.002118 3988.086102
[50,] -755.138395 1363.002118
[51,] -1502.592923 -755.138395
[52,] 471.706043 -1502.592923
[53,] -67.612446 471.706043
[54,] -952.855840 -67.612446
[55,] -95.651230 -952.855840
[56,] -45.978616 -95.651230
[57,] -7.420475 -45.978616
[58,] -1273.180519 -7.420475
[59,] -1513.749692 -1273.180519
[60,] -832.427695 -1513.749692
[61,] -601.984694 -832.427695
[62,] -292.435551 -601.984694
[63,] -569.093658 -292.435551
[64,] -69.572932 -569.093658
[65,] -327.318825 -69.572932
[66,] 113.121613 -327.318825
[67,] -153.829039 113.121613
[68,] -189.168258 -153.829039
[69,] -1532.792203 -189.168258
[70,] -1542.878257 -1532.792203
[71,] -277.505997 -1542.878257
[72,] -662.757059 -277.505997
[73,] -2849.397881 -662.757059
[74,] -1637.802596 -2849.397881
[75,] -406.848630 -1637.802596
[76,] 2243.151877 -406.848630
[77,] 189.057295 2243.151877
[78,] 1447.765831 189.057295
[79,] 2598.306629 1447.765831
[80,] 2877.764824 2598.306629
[81,] 200.587906 2877.764824
[82,] 435.943172 200.587906
[83,] -2132.723349 435.943172
[84,] -7945.631740 -2132.723349
[85,] 10906.144131 -7945.631740
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -599.632622 1973.945784
2 1584.626448 -599.632622
3 2084.351628 1584.626448
4 244.442573 2084.351628
5 -348.620853 244.442573
6 -2.807372 -348.620853
7 -328.671277 -2.807372
8 489.389862 -328.671277
9 569.802837 489.389862
10 536.981263 569.802837
11 133.393557 536.981263
12 -58.764046 133.393557
13 -2403.255974 -58.764046
14 -617.220116 -2403.255974
15 412.180771 -617.220116
16 -664.829196 412.180771
17 -203.628619 -664.829196
18 1707.216522 -203.628619
19 -122.801781 1707.216522
20 547.689296 -122.801781
21 -1113.380219 547.689296
22 485.973611 -1113.380219
23 817.587298 485.973611
24 -315.732296 817.587298
25 -1265.943515 -315.732296
26 -469.396912 -1265.943515
27 -670.516908 -469.396912
28 -2484.075103 -670.516908
29 -2100.271077 -2484.075103
30 -477.569083 -2100.271077
31 -596.660705 -477.569083
32 -348.888815 -596.660705
33 -828.065129 -348.888815
34 -43.767388 -828.065129
35 258.568374 -43.767388
36 -1041.434684 258.568374
37 -815.947655 -1041.434684
38 478.248719 -815.947655
39 28.259522 478.248719
40 357.637316 28.259522
41 -205.192264 357.637316
42 1465.528903 -205.192264
43 1049.897897 1465.528903
44 1465.446763 1049.897897
45 2041.870164 1465.446763
46 -190.354054 2041.870164
47 988.099512 -190.354054
48 3988.086102 988.099512
49 1363.002118 3988.086102
50 -755.138395 1363.002118
51 -1502.592923 -755.138395
52 471.706043 -1502.592923
53 -67.612446 471.706043
54 -952.855840 -67.612446
55 -95.651230 -952.855840
56 -45.978616 -95.651230
57 -7.420475 -45.978616
58 -1273.180519 -7.420475
59 -1513.749692 -1273.180519
60 -832.427695 -1513.749692
61 -601.984694 -832.427695
62 -292.435551 -601.984694
63 -569.093658 -292.435551
64 -69.572932 -569.093658
65 -327.318825 -69.572932
66 113.121613 -327.318825
67 -153.829039 113.121613
68 -189.168258 -153.829039
69 -1532.792203 -189.168258
70 -1542.878257 -1532.792203
71 -277.505997 -1542.878257
72 -662.757059 -277.505997
73 -2849.397881 -662.757059
74 -1637.802596 -2849.397881
75 -406.848630 -1637.802596
76 2243.151877 -406.848630
77 189.057295 2243.151877
78 1447.765831 189.057295
79 2598.306629 1447.765831
80 2877.764824 2598.306629
81 200.587906 2877.764824
82 435.943172 200.587906
83 -2132.723349 435.943172
84 -7945.631740 -2132.723349
85 10906.144131 -7945.631740
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7novu1258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8udbc1258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9k2rs1258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10of4p1258726692.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11yzw51258726692.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12iyf91258726692.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13wv1u1258726692.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/14qume1258726692.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15y9wn1258726692.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16gijd1258726693.tab")
+ }
>
> system("convert tmp/13h3v1258726692.ps tmp/13h3v1258726692.png")
> system("convert tmp/2xdp81258726692.ps tmp/2xdp81258726692.png")
> system("convert tmp/3efnk1258726692.ps tmp/3efnk1258726692.png")
> system("convert tmp/4v21p1258726692.ps tmp/4v21p1258726692.png")
> system("convert tmp/5px7k1258726692.ps tmp/5px7k1258726692.png")
> system("convert tmp/64emw1258726692.ps tmp/64emw1258726692.png")
> system("convert tmp/7novu1258726692.ps tmp/7novu1258726692.png")
> system("convert tmp/8udbc1258726692.ps tmp/8udbc1258726692.png")
> system("convert tmp/9k2rs1258726692.ps tmp/9k2rs1258726692.png")
> system("convert tmp/10of4p1258726692.ps tmp/10of4p1258726692.png")
>
>
> proc.time()
user system elapsed
2.838 1.618 5.128