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.
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(423.4
+ ,0
+ ,404.1
+ ,0
+ ,500
+ ,0
+ ,472.6
+ ,0
+ ,496.1
+ ,0
+ ,562
+ ,0
+ ,434.8
+ ,0
+ ,538.2
+ ,0
+ ,577.6
+ ,0
+ ,518.1
+ ,0
+ ,625.2
+ ,0
+ ,561.2
+ ,0
+ ,523.3
+ ,0
+ ,536.1
+ ,0
+ ,607.3
+ ,0
+ ,637.3
+ ,0
+ ,606.9
+ ,0
+ ,652.9
+ ,0
+ ,617.2
+ ,0
+ ,670.4
+ ,0
+ ,729.9
+ ,0
+ ,677.2
+ ,0
+ ,710
+ ,0
+ ,844.3
+ ,0
+ ,748.2
+ ,0
+ ,653.9
+ ,0
+ ,742.6
+ ,0
+ ,854.2
+ ,0
+ ,808.4
+ ,0
+ ,1819
+ ,1
+ ,1936.5
+ ,1
+ ,1966.1
+ ,1
+ ,2083.1
+ ,1
+ ,1620.1
+ ,1
+ ,1527.6
+ ,1
+ ,1795
+ ,1
+ ,1685.1
+ ,1
+ ,1851.8
+ ,1
+ ,2164.4
+ ,1
+ ,1981.8
+ ,1
+ ,1726.5
+ ,1
+ ,2144.6
+ ,1
+ ,1758.2
+ ,1
+ ,1672.9
+ ,1
+ ,1837.3
+ ,1
+ ,1596.1
+ ,1
+ ,1446
+ ,1
+ ,1898.4
+ ,1
+ ,1964.1
+ ,1
+ ,1755.9
+ ,1
+ ,2255.3
+ ,1
+ ,1881.2
+ ,1
+ ,2117.9
+ ,1
+ ,1656.5
+ ,1
+ ,1544.1
+ ,1
+ ,2098.9
+ ,1
+ ,2133.3
+ ,1
+ ,1963.5
+ ,1
+ ,1801.2
+ ,1
+ ,2365.4
+ ,1
+ ,1936.5
+ ,1
+ ,1667.6
+ ,1
+ ,1983.5
+ ,1
+ ,2058.6
+ ,1
+ ,2448.3
+ ,1
+ ,1858.1
+ ,1
+ ,1625.4
+ ,1
+ ,2130.6
+ ,1
+ ,2515.7
+ ,1
+ ,2230.2
+ ,1
+ ,2086.9
+ ,1
+ ,2235
+ ,1
+ ,2100.2
+ ,1
+ ,2288.6
+ ,1
+ ,2490
+ ,1
+ ,2573.7
+ ,1
+ ,2543.8
+ ,1
+ ,2004.7
+ ,1
+ ,2390
+ ,1
+ ,2338.4
+ ,1
+ ,2724.5
+ ,1
+ ,2292.5
+ ,1
+ ,2386
+ ,1
+ ,2477.9
+ ,1
+ ,2337
+ ,1
+ ,2605.1
+ ,1
+ ,2560.8
+ ,1
+ ,2839.3
+ ,1
+ ,2407.2
+ ,1
+ ,2085.2
+ ,1
+ ,2735.6
+ ,1
+ ,2798.7
+ ,1
+ ,3053.2
+ ,1
+ ,2405
+ ,1
+ ,2471.9
+ ,1
+ ,2727.3
+ ,1
+ ,2790.7
+ ,1
+ ,2385.4
+ ,1
+ ,3206.6
+ ,1
+ ,2705.6
+ ,1
+ ,3518.4
+ ,1
+ ,1954.9
+ ,1
+ ,2584.3
+ ,1
+ ,2535.8
+ ,1
+ ,2685.9
+ ,1
+ ,2866
+ ,1
+ ,2236.6
+ ,1
+ ,2934.9
+ ,1
+ ,2668.6
+ ,1
+ ,2371.2
+ ,1
+ ,3165.9
+ ,1
+ ,2887.2
+ ,1
+ ,3112.2
+ ,1
+ ,2671.2
+ ,1
+ ,2432.6
+ ,1
+ ,2812.3
+ ,1
+ ,3095.7
+ ,1
+ ,2862.9
+ ,1
+ ,2607.3
+ ,1
+ ,2862.5
+ ,1)
+ ,dim=c(2
+ ,120)
+ ,dimnames=list(c('Y(Export_farma_prod)'
+ ,'X(sprong)')
+ ,1:120))
> y <- array(NA,dim=c(2,120),dimnames=list(c('Y(Export_farma_prod)','X(sprong)'),1:120))
> 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
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
Y(Export_farma_prod) X(sprong) t
1 423.4 0 1
2 404.1 0 2
3 500.0 0 3
4 472.6 0 4
5 496.1 0 5
6 562.0 0 6
7 434.8 0 7
8 538.2 0 8
9 577.6 0 9
10 518.1 0 10
11 625.2 0 11
12 561.2 0 12
13 523.3 0 13
14 536.1 0 14
15 607.3 0 15
16 637.3 0 16
17 606.9 0 17
18 652.9 0 18
19 617.2 0 19
20 670.4 0 20
21 729.9 0 21
22 677.2 0 22
23 710.0 0 23
24 844.3 0 24
25 748.2 0 25
26 653.9 0 26
27 742.6 0 27
28 854.2 0 28
29 808.4 0 29
30 1819.0 1 30
31 1936.5 1 31
32 1966.1 1 32
33 2083.1 1 33
34 1620.1 1 34
35 1527.6 1 35
36 1795.0 1 36
37 1685.1 1 37
38 1851.8 1 38
39 2164.4 1 39
40 1981.8 1 40
41 1726.5 1 41
42 2144.6 1 42
43 1758.2 1 43
44 1672.9 1 44
45 1837.3 1 45
46 1596.1 1 46
47 1446.0 1 47
48 1898.4 1 48
49 1964.1 1 49
50 1755.9 1 50
51 2255.3 1 51
52 1881.2 1 52
53 2117.9 1 53
54 1656.5 1 54
55 1544.1 1 55
56 2098.9 1 56
57 2133.3 1 57
58 1963.5 1 58
59 1801.2 1 59
60 2365.4 1 60
61 1936.5 1 61
62 1667.6 1 62
63 1983.5 1 63
64 2058.6 1 64
65 2448.3 1 65
66 1858.1 1 66
67 1625.4 1 67
68 2130.6 1 68
69 2515.7 1 69
70 2230.2 1 70
71 2086.9 1 71
72 2235.0 1 72
73 2100.2 1 73
74 2288.6 1 74
75 2490.0 1 75
76 2573.7 1 76
77 2543.8 1 77
78 2004.7 1 78
79 2390.0 1 79
80 2338.4 1 80
81 2724.5 1 81
82 2292.5 1 82
83 2386.0 1 83
84 2477.9 1 84
85 2337.0 1 85
86 2605.1 1 86
87 2560.8 1 87
88 2839.3 1 88
89 2407.2 1 89
90 2085.2 1 90
91 2735.6 1 91
92 2798.7 1 92
93 3053.2 1 93
94 2405.0 1 94
95 2471.9 1 95
96 2727.3 1 96
97 2790.7 1 97
98 2385.4 1 98
99 3206.6 1 99
100 2705.6 1 100
101 3518.4 1 101
102 1954.9 1 102
103 2584.3 1 103
104 2535.8 1 104
105 2685.9 1 105
106 2866.0 1 106
107 2236.6 1 107
108 2934.9 1 108
109 2668.6 1 109
110 2371.2 1 110
111 3165.9 1 111
112 2887.2 1 112
113 3112.2 1 113
114 2671.2 1 114
115 2432.6 1 115
116 2812.3 1 116
117 3095.7 1 117
118 2862.9 1 118
119 2607.3 1 119
120 2862.5 1 120
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `X(sprong)` t
404.66 851.45 13.79
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-707.68 -94.20 -10.92 114.27 869.61
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 404.6621 46.1890 8.761 1.77e-14 ***
`X(sprong)` 851.4460 75.3517 11.300 < 2e-16 ***
t 13.7890 0.9312 14.807 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 237.1 on 117 degrees of freedom
Multiple R-squared: 0.9187, Adjusted R-squared: 0.9173
F-statistic: 660.9 on 2 and 117 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,] 4.038937e-03 8.077874e-03 0.9959611
[2,] 6.052871e-03 1.210574e-02 0.9939471
[3,] 1.254413e-03 2.508825e-03 0.9987456
[4,] 2.747361e-04 5.494721e-04 0.9997253
[5,] 7.300373e-05 1.460075e-04 0.9999270
[6,] 2.165537e-05 4.331073e-05 0.9999783
[7,] 4.937423e-06 9.874847e-06 0.9999951
[8,] 2.388014e-06 4.776028e-06 0.9999976
[9,] 7.242556e-07 1.448511e-06 0.9999993
[10,] 1.395745e-07 2.791490e-07 0.9999999
[11,] 2.974095e-08 5.948190e-08 1.0000000
[12,] 5.361001e-09 1.072200e-08 1.0000000
[13,] 9.807393e-10 1.961479e-09 1.0000000
[14,] 1.908641e-10 3.817283e-10 1.0000000
[15,] 3.242326e-11 6.484652e-11 1.0000000
[16,] 1.242608e-11 2.485215e-11 1.0000000
[17,] 2.018662e-12 4.037325e-12 1.0000000
[18,] 3.145108e-13 6.290216e-13 1.0000000
[19,] 1.860220e-12 3.720440e-12 1.0000000
[20,] 3.201759e-13 6.403519e-13 1.0000000
[21,] 4.325539e-13 8.651078e-13 1.0000000
[22,] 8.108679e-14 1.621736e-13 1.0000000
[23,] 5.062400e-14 1.012480e-13 1.0000000
[24,] 9.498402e-15 1.899680e-14 1.0000000
[25,] 1.751829e-15 3.503657e-15 1.0000000
[26,] 1.045364e-15 2.090728e-15 1.0000000
[27,] 4.109330e-16 8.218660e-16 1.0000000
[28,] 2.088464e-15 4.176928e-15 1.0000000
[29,] 2.972021e-11 5.944043e-11 1.0000000
[30,] 1.062841e-08 2.125682e-08 1.0000000
[31,] 4.663528e-09 9.327056e-09 1.0000000
[32,] 5.573663e-09 1.114733e-08 1.0000000
[33,] 2.063832e-09 4.127664e-09 1.0000000
[34,] 1.968489e-08 3.936977e-08 1.0000000
[35,] 1.009790e-08 2.019580e-08 1.0000000
[36,] 1.376667e-08 2.753335e-08 1.0000000
[37,] 2.977645e-08 5.955290e-08 1.0000000
[38,] 3.412517e-08 6.825035e-08 1.0000000
[39,] 9.242099e-08 1.848420e-07 0.9999999
[40,] 5.039495e-08 1.007899e-07 0.9999999
[41,] 2.861881e-07 5.723762e-07 0.9999997
[42,] 7.512935e-06 1.502587e-05 0.9999925
[43,] 3.818793e-06 7.637586e-06 0.9999962
[44,] 2.051784e-06 4.103569e-06 0.9999979
[45,] 1.531908e-06 3.063815e-06 0.9999985
[46,] 5.254565e-06 1.050913e-05 0.9999947
[47,] 2.848165e-06 5.696331e-06 0.9999972
[48,] 2.284541e-06 4.569082e-06 0.9999977
[49,] 5.050028e-06 1.010006e-05 0.9999949
[50,] 2.816433e-05 5.632867e-05 0.9999718
[51,] 2.096610e-05 4.193220e-05 0.9999790
[52,] 1.645410e-05 3.290820e-05 0.9999835
[53,] 9.043849e-06 1.808770e-05 0.9999910
[54,] 8.172253e-06 1.634451e-05 0.9999918
[55,] 2.399069e-05 4.798137e-05 0.9999760
[56,] 1.489964e-05 2.979929e-05 0.9999851
[57,] 4.337577e-05 8.675153e-05 0.9999566
[58,] 2.674881e-05 5.349762e-05 0.9999733
[59,] 1.592202e-05 3.184403e-05 0.9999841
[60,] 4.933849e-05 9.867698e-05 0.9999507
[61,] 5.492163e-05 1.098433e-04 0.9999451
[62,] 3.751155e-04 7.502309e-04 0.9996249
[63,] 2.642930e-04 5.285861e-04 0.9997357
[64,] 6.765278e-04 1.353056e-03 0.9993235
[65,] 4.767695e-04 9.535389e-04 0.9995232
[66,] 3.540181e-04 7.080363e-04 0.9996460
[67,] 2.435975e-04 4.871950e-04 0.9997564
[68,] 1.928126e-04 3.856253e-04 0.9998072
[69,] 1.362958e-04 2.725916e-04 0.9998637
[70,] 1.516082e-04 3.032164e-04 0.9998484
[71,] 2.129603e-04 4.259205e-04 0.9997870
[72,] 2.220855e-04 4.441711e-04 0.9997779
[73,] 3.648760e-04 7.297521e-04 0.9996351
[74,] 2.438499e-04 4.876998e-04 0.9997562
[75,] 1.602524e-04 3.205048e-04 0.9998397
[76,] 2.786877e-04 5.573754e-04 0.9997213
[77,] 1.973397e-04 3.946794e-04 0.9998027
[78,] 1.258402e-04 2.516804e-04 0.9998742
[79,] 7.860270e-05 1.572054e-04 0.9999214
[80,] 5.656173e-05 1.131235e-04 0.9999434
[81,] 3.951755e-05 7.903510e-05 0.9999605
[82,] 2.412468e-05 4.824936e-05 0.9999759
[83,] 3.806728e-05 7.613456e-05 0.9999619
[84,] 2.476695e-05 4.953390e-05 0.9999752
[85,] 1.221023e-04 2.442047e-04 0.9998779
[86,] 9.103360e-05 1.820672e-04 0.9999090
[87,] 7.674945e-05 1.534989e-04 0.9999233
[88,] 2.611503e-04 5.223007e-04 0.9997388
[89,] 2.105750e-04 4.211501e-04 0.9997894
[90,] 1.494853e-04 2.989706e-04 0.9998505
[91,] 8.727561e-05 1.745512e-04 0.9999127
[92,] 5.496534e-05 1.099307e-04 0.9999450
[93,] 6.291573e-05 1.258315e-04 0.9999371
[94,] 3.769718e-04 7.539437e-04 0.9996230
[95,] 2.080301e-04 4.160602e-04 0.9997920
[96,] 5.140430e-02 1.028086e-01 0.9485957
[97,] 2.474730e-01 4.949461e-01 0.7525270
[98,] 1.935945e-01 3.871890e-01 0.8064055
[99,] 1.563009e-01 3.126018e-01 0.8436991
[100,] 1.123882e-01 2.247765e-01 0.8876118
[101,] 9.367145e-02 1.873429e-01 0.9063286
[102,] 2.235219e-01 4.470439e-01 0.7764781
[103,] 1.819467e-01 3.638934e-01 0.8180533
[104,] 1.325373e-01 2.650746e-01 0.8674627
[105,] 3.535719e-01 7.071439e-01 0.6464281
[106,] 3.564153e-01 7.128306e-01 0.6435847
[107,] 2.499960e-01 4.999920e-01 0.7500040
[108,] 3.769735e-01 7.539471e-01 0.6230265
[109,] 2.395201e-01 4.790401e-01 0.7604799
> postscript(file="/var/www/html/rcomp/tmp/1w49c1258767904.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/22v6k1258767904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3mahc1258767904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4jjxz1258767904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5meol1258767904.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 = 120
Frequency = 1
1 2 3 4 5
4.94891264 -28.14004910 53.97098916 12.78202742 22.49306568
6 7 8 9 10
74.60410394 -66.38485780 23.22618046 48.83721872 -24.45174302
11 12 13 14 15
68.85929524 -8.92966650 -60.61862824 -61.60758998 -4.19655172
16 17 18 19 20
12.01448654 -32.17447520 0.03656306 -49.45239868 -10.04136043
21 22 23 24 25
35.66967783 -30.81928391 -11.80824565 108.70279261 -1.18616913
26 27 28 29 30
-109.27513087 -34.36409261 63.44694565 3.85798391 149.22305853
31 32 33 34 35
252.93409679 268.74513505 371.95617331 -104.83278843 -211.12175017
36 37 38 39 40
42.48928809 -81.19967365 71.71136461 370.52240287 174.13344113
41 42 43 44 45
-94.95552061 309.35551765 -90.83344409 -189.92240583 -39.31136757
46 47 48 49 50
-294.30032931 -458.18929105 -19.57825279 32.33278547 -189.65617628
51 52 53 54 55
295.95486198 -91.93409976 130.97693850 -344.21202324 -470.40098498
56 57 58 59 60
70.61005328 91.22109154 -92.36787020 -268.45683194 281.95420632
61 62 63 64 65
-160.73475542 -443.42371716 -141.31267890 -80.00164064 295.90939762
66 67 68 69 70
-308.07956412 -554.56852586 -63.15748760 308.15355066 8.86458892
71 72 73 74 75
-148.22437282 -13.91333456 -162.50229630 12.10874196 199.71978022
76 77 78 79 80
269.63081848 225.94185674 -326.94710500 44.56393326 -20.82502848
81 82 83 84 85
351.48600978 -94.30295196 -14.59191370 63.51912456 -91.16983718
86 87 88 89 90
163.14120108 105.05223934 369.76327760 -76.12568414 -411.91464588
91 92 93 94 95
224.69639238 274.00743064 514.71846890 -147.27049284 -94.15945458
96 97 98 99 100
147.45158368 197.06262194 -222.02633980 585.38469845 70.59573671
101 102 103 104 105
869.60677497 -707.68218677 -92.07114851 -154.36011025 -18.04907199
106 107 108 109 110
148.26196627 -494.92699547 189.58404279 -90.50491895 -401.69388069
111 112 113 114 115
379.21715757 86.72819583 297.93923409 -156.84972765 -409.23868939
116 117 118 119 120
-43.32765113 226.28338713 -20.30557461 -289.69453635 -48.28349809
> postscript(file="/var/www/html/rcomp/tmp/6ml2h1258767904.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 = 120
Frequency = 1
lag(myerror, k = 1) myerror
0 4.94891264 NA
1 -28.14004910 4.94891264
2 53.97098916 -28.14004910
3 12.78202742 53.97098916
4 22.49306568 12.78202742
5 74.60410394 22.49306568
6 -66.38485780 74.60410394
7 23.22618046 -66.38485780
8 48.83721872 23.22618046
9 -24.45174302 48.83721872
10 68.85929524 -24.45174302
11 -8.92966650 68.85929524
12 -60.61862824 -8.92966650
13 -61.60758998 -60.61862824
14 -4.19655172 -61.60758998
15 12.01448654 -4.19655172
16 -32.17447520 12.01448654
17 0.03656306 -32.17447520
18 -49.45239868 0.03656306
19 -10.04136043 -49.45239868
20 35.66967783 -10.04136043
21 -30.81928391 35.66967783
22 -11.80824565 -30.81928391
23 108.70279261 -11.80824565
24 -1.18616913 108.70279261
25 -109.27513087 -1.18616913
26 -34.36409261 -109.27513087
27 63.44694565 -34.36409261
28 3.85798391 63.44694565
29 149.22305853 3.85798391
30 252.93409679 149.22305853
31 268.74513505 252.93409679
32 371.95617331 268.74513505
33 -104.83278843 371.95617331
34 -211.12175017 -104.83278843
35 42.48928809 -211.12175017
36 -81.19967365 42.48928809
37 71.71136461 -81.19967365
38 370.52240287 71.71136461
39 174.13344113 370.52240287
40 -94.95552061 174.13344113
41 309.35551765 -94.95552061
42 -90.83344409 309.35551765
43 -189.92240583 -90.83344409
44 -39.31136757 -189.92240583
45 -294.30032931 -39.31136757
46 -458.18929105 -294.30032931
47 -19.57825279 -458.18929105
48 32.33278547 -19.57825279
49 -189.65617628 32.33278547
50 295.95486198 -189.65617628
51 -91.93409976 295.95486198
52 130.97693850 -91.93409976
53 -344.21202324 130.97693850
54 -470.40098498 -344.21202324
55 70.61005328 -470.40098498
56 91.22109154 70.61005328
57 -92.36787020 91.22109154
58 -268.45683194 -92.36787020
59 281.95420632 -268.45683194
60 -160.73475542 281.95420632
61 -443.42371716 -160.73475542
62 -141.31267890 -443.42371716
63 -80.00164064 -141.31267890
64 295.90939762 -80.00164064
65 -308.07956412 295.90939762
66 -554.56852586 -308.07956412
67 -63.15748760 -554.56852586
68 308.15355066 -63.15748760
69 8.86458892 308.15355066
70 -148.22437282 8.86458892
71 -13.91333456 -148.22437282
72 -162.50229630 -13.91333456
73 12.10874196 -162.50229630
74 199.71978022 12.10874196
75 269.63081848 199.71978022
76 225.94185674 269.63081848
77 -326.94710500 225.94185674
78 44.56393326 -326.94710500
79 -20.82502848 44.56393326
80 351.48600978 -20.82502848
81 -94.30295196 351.48600978
82 -14.59191370 -94.30295196
83 63.51912456 -14.59191370
84 -91.16983718 63.51912456
85 163.14120108 -91.16983718
86 105.05223934 163.14120108
87 369.76327760 105.05223934
88 -76.12568414 369.76327760
89 -411.91464588 -76.12568414
90 224.69639238 -411.91464588
91 274.00743064 224.69639238
92 514.71846890 274.00743064
93 -147.27049284 514.71846890
94 -94.15945458 -147.27049284
95 147.45158368 -94.15945458
96 197.06262194 147.45158368
97 -222.02633980 197.06262194
98 585.38469845 -222.02633980
99 70.59573671 585.38469845
100 869.60677497 70.59573671
101 -707.68218677 869.60677497
102 -92.07114851 -707.68218677
103 -154.36011025 -92.07114851
104 -18.04907199 -154.36011025
105 148.26196627 -18.04907199
106 -494.92699547 148.26196627
107 189.58404279 -494.92699547
108 -90.50491895 189.58404279
109 -401.69388069 -90.50491895
110 379.21715757 -401.69388069
111 86.72819583 379.21715757
112 297.93923409 86.72819583
113 -156.84972765 297.93923409
114 -409.23868939 -156.84972765
115 -43.32765113 -409.23868939
116 226.28338713 -43.32765113
117 -20.30557461 226.28338713
118 -289.69453635 -20.30557461
119 -48.28349809 -289.69453635
120 NA -48.28349809
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -28.14004910 4.94891264
[2,] 53.97098916 -28.14004910
[3,] 12.78202742 53.97098916
[4,] 22.49306568 12.78202742
[5,] 74.60410394 22.49306568
[6,] -66.38485780 74.60410394
[7,] 23.22618046 -66.38485780
[8,] 48.83721872 23.22618046
[9,] -24.45174302 48.83721872
[10,] 68.85929524 -24.45174302
[11,] -8.92966650 68.85929524
[12,] -60.61862824 -8.92966650
[13,] -61.60758998 -60.61862824
[14,] -4.19655172 -61.60758998
[15,] 12.01448654 -4.19655172
[16,] -32.17447520 12.01448654
[17,] 0.03656306 -32.17447520
[18,] -49.45239868 0.03656306
[19,] -10.04136043 -49.45239868
[20,] 35.66967783 -10.04136043
[21,] -30.81928391 35.66967783
[22,] -11.80824565 -30.81928391
[23,] 108.70279261 -11.80824565
[24,] -1.18616913 108.70279261
[25,] -109.27513087 -1.18616913
[26,] -34.36409261 -109.27513087
[27,] 63.44694565 -34.36409261
[28,] 3.85798391 63.44694565
[29,] 149.22305853 3.85798391
[30,] 252.93409679 149.22305853
[31,] 268.74513505 252.93409679
[32,] 371.95617331 268.74513505
[33,] -104.83278843 371.95617331
[34,] -211.12175017 -104.83278843
[35,] 42.48928809 -211.12175017
[36,] -81.19967365 42.48928809
[37,] 71.71136461 -81.19967365
[38,] 370.52240287 71.71136461
[39,] 174.13344113 370.52240287
[40,] -94.95552061 174.13344113
[41,] 309.35551765 -94.95552061
[42,] -90.83344409 309.35551765
[43,] -189.92240583 -90.83344409
[44,] -39.31136757 -189.92240583
[45,] -294.30032931 -39.31136757
[46,] -458.18929105 -294.30032931
[47,] -19.57825279 -458.18929105
[48,] 32.33278547 -19.57825279
[49,] -189.65617628 32.33278547
[50,] 295.95486198 -189.65617628
[51,] -91.93409976 295.95486198
[52,] 130.97693850 -91.93409976
[53,] -344.21202324 130.97693850
[54,] -470.40098498 -344.21202324
[55,] 70.61005328 -470.40098498
[56,] 91.22109154 70.61005328
[57,] -92.36787020 91.22109154
[58,] -268.45683194 -92.36787020
[59,] 281.95420632 -268.45683194
[60,] -160.73475542 281.95420632
[61,] -443.42371716 -160.73475542
[62,] -141.31267890 -443.42371716
[63,] -80.00164064 -141.31267890
[64,] 295.90939762 -80.00164064
[65,] -308.07956412 295.90939762
[66,] -554.56852586 -308.07956412
[67,] -63.15748760 -554.56852586
[68,] 308.15355066 -63.15748760
[69,] 8.86458892 308.15355066
[70,] -148.22437282 8.86458892
[71,] -13.91333456 -148.22437282
[72,] -162.50229630 -13.91333456
[73,] 12.10874196 -162.50229630
[74,] 199.71978022 12.10874196
[75,] 269.63081848 199.71978022
[76,] 225.94185674 269.63081848
[77,] -326.94710500 225.94185674
[78,] 44.56393326 -326.94710500
[79,] -20.82502848 44.56393326
[80,] 351.48600978 -20.82502848
[81,] -94.30295196 351.48600978
[82,] -14.59191370 -94.30295196
[83,] 63.51912456 -14.59191370
[84,] -91.16983718 63.51912456
[85,] 163.14120108 -91.16983718
[86,] 105.05223934 163.14120108
[87,] 369.76327760 105.05223934
[88,] -76.12568414 369.76327760
[89,] -411.91464588 -76.12568414
[90,] 224.69639238 -411.91464588
[91,] 274.00743064 224.69639238
[92,] 514.71846890 274.00743064
[93,] -147.27049284 514.71846890
[94,] -94.15945458 -147.27049284
[95,] 147.45158368 -94.15945458
[96,] 197.06262194 147.45158368
[97,] -222.02633980 197.06262194
[98,] 585.38469845 -222.02633980
[99,] 70.59573671 585.38469845
[100,] 869.60677497 70.59573671
[101,] -707.68218677 869.60677497
[102,] -92.07114851 -707.68218677
[103,] -154.36011025 -92.07114851
[104,] -18.04907199 -154.36011025
[105,] 148.26196627 -18.04907199
[106,] -494.92699547 148.26196627
[107,] 189.58404279 -494.92699547
[108,] -90.50491895 189.58404279
[109,] -401.69388069 -90.50491895
[110,] 379.21715757 -401.69388069
[111,] 86.72819583 379.21715757
[112,] 297.93923409 86.72819583
[113,] -156.84972765 297.93923409
[114,] -409.23868939 -156.84972765
[115,] -43.32765113 -409.23868939
[116,] 226.28338713 -43.32765113
[117,] -20.30557461 226.28338713
[118,] -289.69453635 -20.30557461
[119,] -48.28349809 -289.69453635
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -28.14004910 4.94891264
2 53.97098916 -28.14004910
3 12.78202742 53.97098916
4 22.49306568 12.78202742
5 74.60410394 22.49306568
6 -66.38485780 74.60410394
7 23.22618046 -66.38485780
8 48.83721872 23.22618046
9 -24.45174302 48.83721872
10 68.85929524 -24.45174302
11 -8.92966650 68.85929524
12 -60.61862824 -8.92966650
13 -61.60758998 -60.61862824
14 -4.19655172 -61.60758998
15 12.01448654 -4.19655172
16 -32.17447520 12.01448654
17 0.03656306 -32.17447520
18 -49.45239868 0.03656306
19 -10.04136043 -49.45239868
20 35.66967783 -10.04136043
21 -30.81928391 35.66967783
22 -11.80824565 -30.81928391
23 108.70279261 -11.80824565
24 -1.18616913 108.70279261
25 -109.27513087 -1.18616913
26 -34.36409261 -109.27513087
27 63.44694565 -34.36409261
28 3.85798391 63.44694565
29 149.22305853 3.85798391
30 252.93409679 149.22305853
31 268.74513505 252.93409679
32 371.95617331 268.74513505
33 -104.83278843 371.95617331
34 -211.12175017 -104.83278843
35 42.48928809 -211.12175017
36 -81.19967365 42.48928809
37 71.71136461 -81.19967365
38 370.52240287 71.71136461
39 174.13344113 370.52240287
40 -94.95552061 174.13344113
41 309.35551765 -94.95552061
42 -90.83344409 309.35551765
43 -189.92240583 -90.83344409
44 -39.31136757 -189.92240583
45 -294.30032931 -39.31136757
46 -458.18929105 -294.30032931
47 -19.57825279 -458.18929105
48 32.33278547 -19.57825279
49 -189.65617628 32.33278547
50 295.95486198 -189.65617628
51 -91.93409976 295.95486198
52 130.97693850 -91.93409976
53 -344.21202324 130.97693850
54 -470.40098498 -344.21202324
55 70.61005328 -470.40098498
56 91.22109154 70.61005328
57 -92.36787020 91.22109154
58 -268.45683194 -92.36787020
59 281.95420632 -268.45683194
60 -160.73475542 281.95420632
61 -443.42371716 -160.73475542
62 -141.31267890 -443.42371716
63 -80.00164064 -141.31267890
64 295.90939762 -80.00164064
65 -308.07956412 295.90939762
66 -554.56852586 -308.07956412
67 -63.15748760 -554.56852586
68 308.15355066 -63.15748760
69 8.86458892 308.15355066
70 -148.22437282 8.86458892
71 -13.91333456 -148.22437282
72 -162.50229630 -13.91333456
73 12.10874196 -162.50229630
74 199.71978022 12.10874196
75 269.63081848 199.71978022
76 225.94185674 269.63081848
77 -326.94710500 225.94185674
78 44.56393326 -326.94710500
79 -20.82502848 44.56393326
80 351.48600978 -20.82502848
81 -94.30295196 351.48600978
82 -14.59191370 -94.30295196
83 63.51912456 -14.59191370
84 -91.16983718 63.51912456
85 163.14120108 -91.16983718
86 105.05223934 163.14120108
87 369.76327760 105.05223934
88 -76.12568414 369.76327760
89 -411.91464588 -76.12568414
90 224.69639238 -411.91464588
91 274.00743064 224.69639238
92 514.71846890 274.00743064
93 -147.27049284 514.71846890
94 -94.15945458 -147.27049284
95 147.45158368 -94.15945458
96 197.06262194 147.45158368
97 -222.02633980 197.06262194
98 585.38469845 -222.02633980
99 70.59573671 585.38469845
100 869.60677497 70.59573671
101 -707.68218677 869.60677497
102 -92.07114851 -707.68218677
103 -154.36011025 -92.07114851
104 -18.04907199 -154.36011025
105 148.26196627 -18.04907199
106 -494.92699547 148.26196627
107 189.58404279 -494.92699547
108 -90.50491895 189.58404279
109 -401.69388069 -90.50491895
110 379.21715757 -401.69388069
111 86.72819583 379.21715757
112 297.93923409 86.72819583
113 -156.84972765 297.93923409
114 -409.23868939 -156.84972765
115 -43.32765113 -409.23868939
116 226.28338713 -43.32765113
117 -20.30557461 226.28338713
118 -289.69453635 -20.30557461
119 -48.28349809 -289.69453635
> 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/7qp9x1258767904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/81cgm1258767904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/90ztl1258767904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10d18q1258767904.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11f5js1258767904.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/1281601258767904.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/13ujii1258767904.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/14e9861258767904.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/15xl1u1258767904.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/16jcq81258767904.tab")
+ }
> system("convert tmp/1w49c1258767904.ps tmp/1w49c1258767904.png")
> system("convert tmp/22v6k1258767904.ps tmp/22v6k1258767904.png")
> system("convert tmp/3mahc1258767904.ps tmp/3mahc1258767904.png")
> system("convert tmp/4jjxz1258767904.ps tmp/4jjxz1258767904.png")
> system("convert tmp/5meol1258767904.ps tmp/5meol1258767904.png")
> system("convert tmp/6ml2h1258767904.ps tmp/6ml2h1258767904.png")
> system("convert tmp/7qp9x1258767904.ps tmp/7qp9x1258767904.png")
> system("convert tmp/81cgm1258767904.ps tmp/81cgm1258767904.png")
> system("convert tmp/90ztl1258767904.ps tmp/90ztl1258767904.png")
> system("convert tmp/10d18q1258767904.ps tmp/10d18q1258767904.png")
>
>
> proc.time()
user system elapsed
3.216 1.611 5.738