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(54.64
+ ,4606.07
+ ,14.36
+ ,52.39
+ ,4176.60
+ ,14.62
+ ,52.51
+ ,4331.53
+ ,13.51
+ ,52.92
+ ,3987.30
+ ,14.95
+ ,55.22
+ ,4205.86
+ ,16.72
+ ,55.41
+ ,4331.37
+ ,16.33
+ ,57.02
+ ,4106.30
+ ,15.21
+ ,58.55
+ ,4009.33
+ ,16.69
+ ,57.49
+ ,3857.64
+ ,15.81
+ ,55.52
+ ,3929.00
+ ,16.02
+ ,57.84
+ ,4210.47
+ ,16.7
+ ,58.69
+ ,4445.82
+ ,15.99
+ ,59.74
+ ,4497.07
+ ,17.68
+ ,60.7
+ ,4443.71
+ ,18.89
+ ,60.74
+ ,4529.25
+ ,18.72
+ ,64.32
+ ,4634.22
+ ,21.14
+ ,66.9
+ ,4772.67
+ ,20.97
+ ,70.93
+ ,4881.52
+ ,23.75
+ ,75.89
+ ,5153.13
+ ,23.05
+ ,80.6
+ ,5324.19
+ ,23.45
+ ,81.39
+ ,5209.36
+ ,21.74
+ ,81.33
+ ,5108.92
+ ,19.37
+ ,77.04
+ ,5130.88
+ ,21.1
+ ,79.54
+ ,5195.68
+ ,21.2
+ ,81.93
+ ,5050.42
+ ,22.67
+ ,80.79
+ ,5101.03
+ ,22.24
+ ,81.98
+ ,5139.84
+ ,23.78
+ ,85.94
+ ,5234.31
+ ,23.27
+ ,86.6
+ ,5435.73
+ ,25.74
+ ,87.42
+ ,5633.57
+ ,26.1
+ ,93.14
+ ,5498.28
+ ,27.49
+ ,95.76
+ ,5668.13
+ ,31.41
+ ,99.75
+ ,5537.64
+ ,28.79
+ ,97.71
+ ,5442.78
+ ,26.76
+ ,94.99
+ ,5491.50
+ ,26.41
+ ,96.41
+ ,5501.20
+ ,27.05
+ ,96.28
+ ,5658.08
+ ,29.43
+ ,100.14
+ ,5686.16
+ ,32.1
+ ,99.9
+ ,5801.24
+ ,36.84
+ ,102.87
+ ,5678.40
+ ,34.22
+ ,107.37
+ ,5793.68
+ ,36.53
+ ,115.68
+ ,5866.10
+ ,40.99
+ ,124.33
+ ,6087.27
+ ,45.97
+ ,128.44
+ ,6058.70
+ ,43.6
+ ,130.19
+ ,6171.63
+ ,47.84
+ ,148.4
+ ,6385.55
+ ,51.47
+ ,169.14
+ ,6180.05
+ ,51.31
+ ,153.98
+ ,6159.65
+ ,48.47
+ ,163.13
+ ,6271.59
+ ,48.28
+ ,165.4
+ ,6365.59
+ ,46.56
+ ,166.35
+ ,6420.76
+ ,43.83
+ ,173.73
+ ,6628.97
+ ,51.17
+ ,174.23
+ ,6731.85
+ ,49.59
+ ,177.04
+ ,6884.40
+ ,49.11
+ ,170.78
+ ,6927.25
+ ,49.97
+ ,174.01
+ ,6796.18
+ ,50.07
+ ,183.76
+ ,6903.69
+ ,53.3
+ ,201.95
+ ,7189.46
+ ,57.08
+ ,205.38
+ ,7435.08
+ ,68.54
+ ,197.36
+ ,7379.99
+ ,71.62
+ ,196.53
+ ,7174.80
+ ,67.64
+ ,179.94
+ ,7233.46
+ ,64.79
+ ,174.84
+ ,7597.58
+ ,80.97
+ ,179.86
+ ,7790.04
+ ,88.42
+ ,172.77
+ ,7466.77
+ ,110.22
+ ,162.56
+ ,7350.45
+ ,99
+ ,178.4
+ ,6850.64
+ ,95.95
+ ,190.83
+ ,6717.18
+ ,107.94
+ ,201.07
+ ,6600.54
+ ,97.82
+ ,198.95
+ ,6979.58
+ ,111.64
+ ,190.46
+ ,6971.45
+ ,114.73
+ ,186.27
+ ,6411.48
+ ,117.58
+ ,187.96
+ ,6276.01
+ ,99.19
+ ,174.99
+ ,6190.56
+ ,90.19
+ ,164.1
+ ,5618.64
+ ,59.74
+ ,131.48
+ ,4595.00
+ ,44.51
+ ,116.14
+ ,4287.38
+ ,23.94
+ ,103.43
+ ,4385.35
+ ,21.29
+ ,96.87
+ ,3927.01
+ ,20.77
+ ,93.68
+ ,3495.28
+ ,25.07
+ ,96.49
+ ,3757.45
+ ,32.95
+ ,105.22
+ ,4076.75
+ ,40.05
+ ,110.11
+ ,4475.36
+ ,44.59
+ ,118.47
+ ,4396.44
+ ,40.28
+ ,122.15
+ ,4766.91
+ ,41.19
+ ,137.35
+ ,4907.38
+ ,38.14
+ ,134.83
+ ,5069.67
+ ,41.85
+ ,138.34
+ ,4983.56
+ ,43.76
+ ,141.98
+ ,5245.81
+ ,50.16
+ ,149.45
+ ,5241.07
+ ,52.94
+ ,154.68
+ ,5003.74
+ ,47.69
+ ,145.98
+ ,5075.38
+ ,51.52
+ ,156.33
+ ,5358.33
+ ,58.69
+ ,176.28
+ ,5298.80
+ ,50.44
+ ,159.08
+ ,4784.64
+ ,45.72
+ ,151.18
+ ,4579.82
+ ,43.24
+ ,162.63
+ ,4982.42
+ ,51.49
+ ,174.2
+ ,4776.39
+ ,50.43
+ ,180.51
+ ,5157.48
+ ,58.73
+ ,185.31
+ ,5305.21
+ ,65.12
+ ,186.33
+ ,5187.20
+ ,64.13)
+ ,dim=c(3
+ ,101)
+ ,dimnames=list(c('Commodity'
+ ,'WorldLeaders'
+ ,'RioTinto')
+ ,1:101))
> y <- array(NA,dim=c(3,101),dimnames=list(c('Commodity','WorldLeaders','RioTinto'),1:101))
> 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 = '3'
> #'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
RioTinto Commodity WorldLeaders
1 14.36 54.64 4606.07
2 14.62 52.39 4176.60
3 13.51 52.51 4331.53
4 14.95 52.92 3987.30
5 16.72 55.22 4205.86
6 16.33 55.41 4331.37
7 15.21 57.02 4106.30
8 16.69 58.55 4009.33
9 15.81 57.49 3857.64
10 16.02 55.52 3929.00
11 16.70 57.84 4210.47
12 15.99 58.69 4445.82
13 17.68 59.74 4497.07
14 18.89 60.70 4443.71
15 18.72 60.74 4529.25
16 21.14 64.32 4634.22
17 20.97 66.90 4772.67
18 23.75 70.93 4881.52
19 23.05 75.89 5153.13
20 23.45 80.60 5324.19
21 21.74 81.39 5209.36
22 19.37 81.33 5108.92
23 21.10 77.04 5130.88
24 21.20 79.54 5195.68
25 22.67 81.93 5050.42
26 22.24 80.79 5101.03
27 23.78 81.98 5139.84
28 23.27 85.94 5234.31
29 25.74 86.60 5435.73
30 26.10 87.42 5633.57
31 27.49 93.14 5498.28
32 31.41 95.76 5668.13
33 28.79 99.75 5537.64
34 26.76 97.71 5442.78
35 26.41 94.99 5491.50
36 27.05 96.41 5501.20
37 29.43 96.28 5658.08
38 32.10 100.14 5686.16
39 36.84 99.90 5801.24
40 34.22 102.87 5678.40
41 36.53 107.37 5793.68
42 40.99 115.68 5866.10
43 45.97 124.33 6087.27
44 43.60 128.44 6058.70
45 47.84 130.19 6171.63
46 51.47 148.40 6385.55
47 51.31 169.14 6180.05
48 48.47 153.98 6159.65
49 48.28 163.13 6271.59
50 46.56 165.40 6365.59
51 43.83 166.35 6420.76
52 51.17 173.73 6628.97
53 49.59 174.23 6731.85
54 49.11 177.04 6884.40
55 49.97 170.78 6927.25
56 50.07 174.01 6796.18
57 53.30 183.76 6903.69
58 57.08 201.95 7189.46
59 68.54 205.38 7435.08
60 71.62 197.36 7379.99
61 67.64 196.53 7174.80
62 64.79 179.94 7233.46
63 80.97 174.84 7597.58
64 88.42 179.86 7790.04
65 110.22 172.77 7466.77
66 99.00 162.56 7350.45
67 95.95 178.40 6850.64
68 107.94 190.83 6717.18
69 97.82 201.07 6600.54
70 111.64 198.95 6979.58
71 114.73 190.46 6971.45
72 117.58 186.27 6411.48
73 99.19 187.96 6276.01
74 90.19 174.99 6190.56
75 59.74 164.10 5618.64
76 44.51 131.48 4595.00
77 23.94 116.14 4287.38
78 21.29 103.43 4385.35
79 20.77 96.87 3927.01
80 25.07 93.68 3495.28
81 32.95 96.49 3757.45
82 40.05 105.22 4076.75
83 44.59 110.11 4475.36
84 40.28 118.47 4396.44
85 41.19 122.15 4766.91
86 38.14 137.35 4907.38
87 41.85 134.83 5069.67
88 43.76 138.34 4983.56
89 50.16 141.98 5245.81
90 52.94 149.45 5241.07
91 47.69 154.68 5003.74
92 51.52 145.98 5075.38
93 58.69 156.33 5358.33
94 50.44 176.28 5298.80
95 45.72 159.08 4784.64
96 43.24 151.18 4579.82
97 51.49 162.63 4982.42
98 50.43 174.20 4776.39
99 58.73 180.51 5157.48
100 65.12 185.31 5305.21
101 64.13 186.33 5187.20
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Commodity WorldLeaders
-32.524900 0.377868 0.005352
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-25.185 -6.257 -2.518 4.508 45.404
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -32.524900 7.551553 -4.307 3.93e-05 ***
Commodity 0.377868 0.041498 9.106 1.06e-14 ***
WorldLeaders 0.005352 0.001911 2.800 0.00615 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 13.19 on 98 degrees of freedom
Multiple R-squared: 0.7498, Adjusted R-squared: 0.7447
F-statistic: 146.9 on 2 and 98 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,] 3.313819e-05 6.627639e-05 9.999669e-01
[2,] 7.029529e-05 1.405906e-04 9.999297e-01
[3,] 4.767847e-06 9.535693e-06 9.999952e-01
[4,] 3.887130e-07 7.774261e-07 9.999996e-01
[5,] 2.472582e-08 4.945164e-08 1.000000e+00
[6,] 1.592963e-09 3.185926e-09 1.000000e+00
[7,] 9.422899e-11 1.884580e-10 1.000000e+00
[8,] 9.776076e-12 1.955215e-11 1.000000e+00
[9,] 1.860884e-12 3.721767e-12 1.000000e+00
[10,] 1.615346e-13 3.230693e-13 1.000000e+00
[11,] 2.160524e-14 4.321047e-14 1.000000e+00
[12,] 1.541657e-15 3.083314e-15 1.000000e+00
[13,] 9.199890e-17 1.839978e-16 1.000000e+00
[14,] 1.505909e-16 3.011819e-16 1.000000e+00
[15,] 2.290212e-16 4.580425e-16 1.000000e+00
[16,] 6.745642e-16 1.349128e-15 1.000000e+00
[17,] 4.282791e-15 8.565582e-15 1.000000e+00
[18,] 5.596170e-16 1.119234e-15 1.000000e+00
[19,] 8.435459e-17 1.687092e-16 1.000000e+00
[20,] 8.822909e-18 1.764582e-17 1.000000e+00
[21,] 9.139401e-19 1.827880e-18 1.000000e+00
[22,] 1.068056e-19 2.136111e-19 1.000000e+00
[23,] 1.120277e-20 2.240554e-20 1.000000e+00
[24,] 1.647569e-21 3.295138e-21 1.000000e+00
[25,] 2.043050e-22 4.086100e-22 1.000000e+00
[26,] 2.813608e-23 5.627216e-23 1.000000e+00
[27,] 6.502548e-23 1.300510e-22 1.000000e+00
[28,] 6.583907e-24 1.316781e-23 1.000000e+00
[29,] 8.531816e-25 1.706363e-24 1.000000e+00
[30,] 9.400363e-26 1.880073e-25 1.000000e+00
[31,] 9.372514e-27 1.874503e-26 1.000000e+00
[32,] 1.596922e-27 3.193845e-27 1.000000e+00
[33,] 1.087314e-27 2.174629e-27 1.000000e+00
[34,] 3.354834e-25 6.709669e-25 1.000000e+00
[35,] 1.784203e-25 3.568407e-25 1.000000e+00
[36,] 1.226821e-25 2.453643e-25 1.000000e+00
[37,] 1.692800e-25 3.385600e-25 1.000000e+00
[38,] 3.358679e-25 6.717359e-25 1.000000e+00
[39,] 4.781036e-26 9.562073e-26 1.000000e+00
[40,] 2.160926e-26 4.321851e-26 1.000000e+00
[41,] 3.265628e-27 6.531255e-27 1.000000e+00
[42,] 5.163398e-26 1.032680e-25 1.000000e+00
[43,] 1.333113e-26 2.666225e-26 1.000000e+00
[44,] 1.441593e-26 2.883186e-26 1.000000e+00
[45,] 4.680573e-26 9.361147e-26 1.000000e+00
[46,] 7.445330e-25 1.489066e-24 1.000000e+00
[47,] 3.685284e-25 7.370568e-25 1.000000e+00
[48,] 4.374518e-25 8.749036e-25 1.000000e+00
[49,] 1.402874e-24 2.805748e-24 1.000000e+00
[50,] 1.684258e-24 3.368516e-24 1.000000e+00
[51,] 2.619817e-24 5.239634e-24 1.000000e+00
[52,] 5.497247e-24 1.099449e-23 1.000000e+00
[53,] 6.665158e-23 1.333032e-22 1.000000e+00
[54,] 2.638359e-21 5.276718e-21 1.000000e+00
[55,] 1.295298e-18 2.590595e-18 1.000000e+00
[56,] 1.006219e-16 2.012437e-16 1.000000e+00
[57,] 3.254948e-14 6.509895e-14 1.000000e+00
[58,] 7.380214e-09 1.476043e-08 1.000000e+00
[59,] 8.430267e-05 1.686053e-04 9.999157e-01
[60,] 9.810429e-02 1.962086e-01 9.018957e-01
[61,] 3.447498e-01 6.894996e-01 6.552502e-01
[62,] 6.211660e-01 7.576679e-01 3.788340e-01
[63,] 8.686567e-01 2.626865e-01 1.313433e-01
[64,] 9.023770e-01 1.952461e-01 9.762305e-02
[65,] 9.406714e-01 1.186573e-01 5.932865e-02
[66,] 9.693417e-01 6.131655e-02 3.065828e-02
[67,] 9.993565e-01 1.287079e-03 6.435393e-04
[68,] 9.999262e-01 1.475364e-04 7.376822e-05
[69,] 9.999980e-01 4.029549e-06 2.014774e-06
[70,] 9.999953e-01 9.371532e-06 4.685766e-06
[71,] 9.999898e-01 2.048481e-05 1.024240e-05
[72,] 9.999951e-01 9.745862e-06 4.872931e-06
[73,] 9.999988e-01 2.344644e-06 1.172322e-06
[74,] 9.999994e-01 1.104959e-06 5.524795e-07
[75,] 9.999987e-01 2.660552e-06 1.330276e-06
[76,] 9.999960e-01 8.028711e-06 4.014356e-06
[77,] 9.999947e-01 1.059607e-05 5.298035e-06
[78,] 9.999981e-01 3.798737e-06 1.899368e-06
[79,] 9.999988e-01 2.375789e-06 1.187894e-06
[80,] 9.999979e-01 4.181655e-06 2.090827e-06
[81,] 9.999960e-01 7.980048e-06 3.990024e-06
[82,] 9.999896e-01 2.080733e-05 1.040367e-05
[83,] 9.999620e-01 7.591210e-05 3.795605e-05
[84,] 9.998542e-01 2.916547e-04 1.458274e-04
[85,] 9.994569e-01 1.086121e-03 5.430603e-04
[86,] 9.983855e-01 3.228904e-03 1.614452e-03
[87,] 9.951310e-01 9.737951e-03 4.868976e-03
[88,] 9.934229e-01 1.315422e-02 6.577111e-03
[89,] 9.993507e-01 1.298599e-03 6.492994e-04
[90,] 9.966024e-01 6.795201e-03 3.397600e-03
> postscript(file="/var/www/html/freestat/rcomp/tmp/1ik2i1292693115.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2ik2i1292693115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ik2i1292693115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4tt1l1292693115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5tt1l1292693115.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 = 101
Frequency = 1
1 2 3 4 5 6
1.5857390 4.9945360 3.0099813 6.1374302 5.8685644 4.7350195
7 8 9 10 11 12
4.2112627 5.6321234 5.9645334 6.5370037 4.8338759 2.5430564
13 14 15 16 17 18
3.5619963 4.6948341 4.0518954 4.5573103 2.6714031 3.3460109
19 20 21 22 23 24
-0.6819169 -2.9772176 -4.3711448 -6.1809015 -2.9473799 -4.1388708
25 26 27 28 29 30
-2.7945209 -3.0646240 -2.1820047 -4.6939821 -3.5514078 -4.5601317
31 32 33 34 35 36
-4.6074444 -2.5865242 -6.0158151 -6.7672576 -6.3502131 -6.2987021
37 38 39 40 41 42
-4.7092265 -3.6480869 0.5666746 -2.5181347 -2.5255394 -1.5932288
43 44 45 46 47 48
-1.0655276 -4.8356551 -1.8613444 -6.2572611 -13.1543807 -10.1567128
49 50 51 52 53 54
-14.4033290 -17.4841934 -20.8684471 -17.4314891 -19.7510538 -22.1093362
55 56 57 58 59 60
-19.1132206 -19.5322274 -20.5618545 -25.1847668 -16.3354533 -9.9300987
61 62 63 64 65 66
-12.4982578 -9.3933802 6.7649188 11.2879426 37.4972226 30.7578217
67 68 69 70 71 72
24.3974519 32.4048484 19.0397530 31.6321501 37.9737652 45.4040840
73 74 75 76 77 78
27.1005440 23.4588384 0.1848333 2.7595857 -10.3674820 -8.7391270
79 80 81 82 83 84
-4.3272006 3.4888885 8.9039021 10.9961661 11.5549645 4.5083780
85 86 87 88 89 90
2.0450069 -7.5004099 -3.7067842 -2.6622273 0.9587274 0.9414203
91 92 93 94 95 96
-5.0146023 1.7194232 3.4640916 -12.0057671 -7.4745640 -5.8731744
97 98 99 100 101
-4.1045473 -8.4337777 -4.5577825 -0.7722254 -1.5160424
> postscript(file="/var/www/html/freestat/rcomp/tmp/6tt1l1292693115.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 = 101
Frequency = 1
lag(myerror, k = 1) myerror
0 1.5857390 NA
1 4.9945360 1.5857390
2 3.0099813 4.9945360
3 6.1374302 3.0099813
4 5.8685644 6.1374302
5 4.7350195 5.8685644
6 4.2112627 4.7350195
7 5.6321234 4.2112627
8 5.9645334 5.6321234
9 6.5370037 5.9645334
10 4.8338759 6.5370037
11 2.5430564 4.8338759
12 3.5619963 2.5430564
13 4.6948341 3.5619963
14 4.0518954 4.6948341
15 4.5573103 4.0518954
16 2.6714031 4.5573103
17 3.3460109 2.6714031
18 -0.6819169 3.3460109
19 -2.9772176 -0.6819169
20 -4.3711448 -2.9772176
21 -6.1809015 -4.3711448
22 -2.9473799 -6.1809015
23 -4.1388708 -2.9473799
24 -2.7945209 -4.1388708
25 -3.0646240 -2.7945209
26 -2.1820047 -3.0646240
27 -4.6939821 -2.1820047
28 -3.5514078 -4.6939821
29 -4.5601317 -3.5514078
30 -4.6074444 -4.5601317
31 -2.5865242 -4.6074444
32 -6.0158151 -2.5865242
33 -6.7672576 -6.0158151
34 -6.3502131 -6.7672576
35 -6.2987021 -6.3502131
36 -4.7092265 -6.2987021
37 -3.6480869 -4.7092265
38 0.5666746 -3.6480869
39 -2.5181347 0.5666746
40 -2.5255394 -2.5181347
41 -1.5932288 -2.5255394
42 -1.0655276 -1.5932288
43 -4.8356551 -1.0655276
44 -1.8613444 -4.8356551
45 -6.2572611 -1.8613444
46 -13.1543807 -6.2572611
47 -10.1567128 -13.1543807
48 -14.4033290 -10.1567128
49 -17.4841934 -14.4033290
50 -20.8684471 -17.4841934
51 -17.4314891 -20.8684471
52 -19.7510538 -17.4314891
53 -22.1093362 -19.7510538
54 -19.1132206 -22.1093362
55 -19.5322274 -19.1132206
56 -20.5618545 -19.5322274
57 -25.1847668 -20.5618545
58 -16.3354533 -25.1847668
59 -9.9300987 -16.3354533
60 -12.4982578 -9.9300987
61 -9.3933802 -12.4982578
62 6.7649188 -9.3933802
63 11.2879426 6.7649188
64 37.4972226 11.2879426
65 30.7578217 37.4972226
66 24.3974519 30.7578217
67 32.4048484 24.3974519
68 19.0397530 32.4048484
69 31.6321501 19.0397530
70 37.9737652 31.6321501
71 45.4040840 37.9737652
72 27.1005440 45.4040840
73 23.4588384 27.1005440
74 0.1848333 23.4588384
75 2.7595857 0.1848333
76 -10.3674820 2.7595857
77 -8.7391270 -10.3674820
78 -4.3272006 -8.7391270
79 3.4888885 -4.3272006
80 8.9039021 3.4888885
81 10.9961661 8.9039021
82 11.5549645 10.9961661
83 4.5083780 11.5549645
84 2.0450069 4.5083780
85 -7.5004099 2.0450069
86 -3.7067842 -7.5004099
87 -2.6622273 -3.7067842
88 0.9587274 -2.6622273
89 0.9414203 0.9587274
90 -5.0146023 0.9414203
91 1.7194232 -5.0146023
92 3.4640916 1.7194232
93 -12.0057671 3.4640916
94 -7.4745640 -12.0057671
95 -5.8731744 -7.4745640
96 -4.1045473 -5.8731744
97 -8.4337777 -4.1045473
98 -4.5577825 -8.4337777
99 -0.7722254 -4.5577825
100 -1.5160424 -0.7722254
101 NA -1.5160424
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 4.9945360 1.5857390
[2,] 3.0099813 4.9945360
[3,] 6.1374302 3.0099813
[4,] 5.8685644 6.1374302
[5,] 4.7350195 5.8685644
[6,] 4.2112627 4.7350195
[7,] 5.6321234 4.2112627
[8,] 5.9645334 5.6321234
[9,] 6.5370037 5.9645334
[10,] 4.8338759 6.5370037
[11,] 2.5430564 4.8338759
[12,] 3.5619963 2.5430564
[13,] 4.6948341 3.5619963
[14,] 4.0518954 4.6948341
[15,] 4.5573103 4.0518954
[16,] 2.6714031 4.5573103
[17,] 3.3460109 2.6714031
[18,] -0.6819169 3.3460109
[19,] -2.9772176 -0.6819169
[20,] -4.3711448 -2.9772176
[21,] -6.1809015 -4.3711448
[22,] -2.9473799 -6.1809015
[23,] -4.1388708 -2.9473799
[24,] -2.7945209 -4.1388708
[25,] -3.0646240 -2.7945209
[26,] -2.1820047 -3.0646240
[27,] -4.6939821 -2.1820047
[28,] -3.5514078 -4.6939821
[29,] -4.5601317 -3.5514078
[30,] -4.6074444 -4.5601317
[31,] -2.5865242 -4.6074444
[32,] -6.0158151 -2.5865242
[33,] -6.7672576 -6.0158151
[34,] -6.3502131 -6.7672576
[35,] -6.2987021 -6.3502131
[36,] -4.7092265 -6.2987021
[37,] -3.6480869 -4.7092265
[38,] 0.5666746 -3.6480869
[39,] -2.5181347 0.5666746
[40,] -2.5255394 -2.5181347
[41,] -1.5932288 -2.5255394
[42,] -1.0655276 -1.5932288
[43,] -4.8356551 -1.0655276
[44,] -1.8613444 -4.8356551
[45,] -6.2572611 -1.8613444
[46,] -13.1543807 -6.2572611
[47,] -10.1567128 -13.1543807
[48,] -14.4033290 -10.1567128
[49,] -17.4841934 -14.4033290
[50,] -20.8684471 -17.4841934
[51,] -17.4314891 -20.8684471
[52,] -19.7510538 -17.4314891
[53,] -22.1093362 -19.7510538
[54,] -19.1132206 -22.1093362
[55,] -19.5322274 -19.1132206
[56,] -20.5618545 -19.5322274
[57,] -25.1847668 -20.5618545
[58,] -16.3354533 -25.1847668
[59,] -9.9300987 -16.3354533
[60,] -12.4982578 -9.9300987
[61,] -9.3933802 -12.4982578
[62,] 6.7649188 -9.3933802
[63,] 11.2879426 6.7649188
[64,] 37.4972226 11.2879426
[65,] 30.7578217 37.4972226
[66,] 24.3974519 30.7578217
[67,] 32.4048484 24.3974519
[68,] 19.0397530 32.4048484
[69,] 31.6321501 19.0397530
[70,] 37.9737652 31.6321501
[71,] 45.4040840 37.9737652
[72,] 27.1005440 45.4040840
[73,] 23.4588384 27.1005440
[74,] 0.1848333 23.4588384
[75,] 2.7595857 0.1848333
[76,] -10.3674820 2.7595857
[77,] -8.7391270 -10.3674820
[78,] -4.3272006 -8.7391270
[79,] 3.4888885 -4.3272006
[80,] 8.9039021 3.4888885
[81,] 10.9961661 8.9039021
[82,] 11.5549645 10.9961661
[83,] 4.5083780 11.5549645
[84,] 2.0450069 4.5083780
[85,] -7.5004099 2.0450069
[86,] -3.7067842 -7.5004099
[87,] -2.6622273 -3.7067842
[88,] 0.9587274 -2.6622273
[89,] 0.9414203 0.9587274
[90,] -5.0146023 0.9414203
[91,] 1.7194232 -5.0146023
[92,] 3.4640916 1.7194232
[93,] -12.0057671 3.4640916
[94,] -7.4745640 -12.0057671
[95,] -5.8731744 -7.4745640
[96,] -4.1045473 -5.8731744
[97,] -8.4337777 -4.1045473
[98,] -4.5577825 -8.4337777
[99,] -0.7722254 -4.5577825
[100,] -1.5160424 -0.7722254
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 4.9945360 1.5857390
2 3.0099813 4.9945360
3 6.1374302 3.0099813
4 5.8685644 6.1374302
5 4.7350195 5.8685644
6 4.2112627 4.7350195
7 5.6321234 4.2112627
8 5.9645334 5.6321234
9 6.5370037 5.9645334
10 4.8338759 6.5370037
11 2.5430564 4.8338759
12 3.5619963 2.5430564
13 4.6948341 3.5619963
14 4.0518954 4.6948341
15 4.5573103 4.0518954
16 2.6714031 4.5573103
17 3.3460109 2.6714031
18 -0.6819169 3.3460109
19 -2.9772176 -0.6819169
20 -4.3711448 -2.9772176
21 -6.1809015 -4.3711448
22 -2.9473799 -6.1809015
23 -4.1388708 -2.9473799
24 -2.7945209 -4.1388708
25 -3.0646240 -2.7945209
26 -2.1820047 -3.0646240
27 -4.6939821 -2.1820047
28 -3.5514078 -4.6939821
29 -4.5601317 -3.5514078
30 -4.6074444 -4.5601317
31 -2.5865242 -4.6074444
32 -6.0158151 -2.5865242
33 -6.7672576 -6.0158151
34 -6.3502131 -6.7672576
35 -6.2987021 -6.3502131
36 -4.7092265 -6.2987021
37 -3.6480869 -4.7092265
38 0.5666746 -3.6480869
39 -2.5181347 0.5666746
40 -2.5255394 -2.5181347
41 -1.5932288 -2.5255394
42 -1.0655276 -1.5932288
43 -4.8356551 -1.0655276
44 -1.8613444 -4.8356551
45 -6.2572611 -1.8613444
46 -13.1543807 -6.2572611
47 -10.1567128 -13.1543807
48 -14.4033290 -10.1567128
49 -17.4841934 -14.4033290
50 -20.8684471 -17.4841934
51 -17.4314891 -20.8684471
52 -19.7510538 -17.4314891
53 -22.1093362 -19.7510538
54 -19.1132206 -22.1093362
55 -19.5322274 -19.1132206
56 -20.5618545 -19.5322274
57 -25.1847668 -20.5618545
58 -16.3354533 -25.1847668
59 -9.9300987 -16.3354533
60 -12.4982578 -9.9300987
61 -9.3933802 -12.4982578
62 6.7649188 -9.3933802
63 11.2879426 6.7649188
64 37.4972226 11.2879426
65 30.7578217 37.4972226
66 24.3974519 30.7578217
67 32.4048484 24.3974519
68 19.0397530 32.4048484
69 31.6321501 19.0397530
70 37.9737652 31.6321501
71 45.4040840 37.9737652
72 27.1005440 45.4040840
73 23.4588384 27.1005440
74 0.1848333 23.4588384
75 2.7595857 0.1848333
76 -10.3674820 2.7595857
77 -8.7391270 -10.3674820
78 -4.3272006 -8.7391270
79 3.4888885 -4.3272006
80 8.9039021 3.4888885
81 10.9961661 8.9039021
82 11.5549645 10.9961661
83 4.5083780 11.5549645
84 2.0450069 4.5083780
85 -7.5004099 2.0450069
86 -3.7067842 -7.5004099
87 -2.6622273 -3.7067842
88 0.9587274 -2.6622273
89 0.9414203 0.9587274
90 -5.0146023 0.9414203
91 1.7194232 -5.0146023
92 3.4640916 1.7194232
93 -12.0057671 3.4640916
94 -7.4745640 -12.0057671
95 -5.8731744 -7.4745640
96 -4.1045473 -5.8731744
97 -8.4337777 -4.1045473
98 -4.5577825 -8.4337777
99 -0.7722254 -4.5577825
100 -1.5160424 -0.7722254
> 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/7ml161292693115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8ml161292693115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9fc091292693115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10fc091292693115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/110vhx1292693115.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/12mvxl1292693115.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/13awuw1292693115.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/14l5bz1292693115.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/15o6sn1292693115.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/16ky7w1292693115.tab")
+ }
>
> try(system("convert tmp/1ik2i1292693115.ps tmp/1ik2i1292693115.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ik2i1292693115.ps tmp/2ik2i1292693115.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ik2i1292693115.ps tmp/3ik2i1292693115.png",intern=TRUE))
character(0)
> try(system("convert tmp/4tt1l1292693115.ps tmp/4tt1l1292693115.png",intern=TRUE))
character(0)
> try(system("convert tmp/5tt1l1292693115.ps tmp/5tt1l1292693115.png",intern=TRUE))
character(0)
> try(system("convert tmp/6tt1l1292693115.ps tmp/6tt1l1292693115.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ml161292693115.ps tmp/7ml161292693115.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ml161292693115.ps tmp/8ml161292693115.png",intern=TRUE))
character(0)
> try(system("convert tmp/9fc091292693115.ps tmp/9fc091292693115.png",intern=TRUE))
character(0)
> try(system("convert tmp/10fc091292693115.ps tmp/10fc091292693115.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.422 2.538 4.828