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(107.1
+ ,0
+ ,96.3
+ ,87.0
+ ,96.8
+ ,115.2
+ ,0
+ ,107.1
+ ,96.3
+ ,87.0
+ ,106.1
+ ,0
+ ,115.2
+ ,107.1
+ ,96.3
+ ,89.5
+ ,0
+ ,106.1
+ ,115.2
+ ,107.1
+ ,91.3
+ ,0
+ ,89.5
+ ,106.1
+ ,115.2
+ ,97.6
+ ,0
+ ,91.3
+ ,89.5
+ ,106.1
+ ,100.7
+ ,0
+ ,97.6
+ ,91.3
+ ,89.5
+ ,104.6
+ ,0
+ ,100.7
+ ,97.6
+ ,91.3
+ ,94.7
+ ,0
+ ,104.6
+ ,100.7
+ ,97.6
+ ,101.8
+ ,0
+ ,94.7
+ ,104.6
+ ,100.7
+ ,102.5
+ ,0
+ ,101.8
+ ,94.7
+ ,104.6
+ ,105.3
+ ,0
+ ,102.5
+ ,101.8
+ ,94.7
+ ,110.3
+ ,0
+ ,105.3
+ ,102.5
+ ,101.8
+ ,109.8
+ ,0
+ ,110.3
+ ,105.3
+ ,102.5
+ ,117.3
+ ,0
+ ,109.8
+ ,110.3
+ ,105.3
+ ,118.8
+ ,0
+ ,117.3
+ ,109.8
+ ,110.3
+ ,131.3
+ ,0
+ ,118.8
+ ,117.3
+ ,109.8
+ ,125.9
+ ,0
+ ,131.3
+ ,118.8
+ ,117.3
+ ,133.1
+ ,0
+ ,125.9
+ ,131.3
+ ,118.8
+ ,147.0
+ ,0
+ ,133.1
+ ,125.9
+ ,131.3
+ ,145.8
+ ,0
+ ,147.0
+ ,133.1
+ ,125.9
+ ,164.4
+ ,0
+ ,145.8
+ ,147.0
+ ,133.1
+ ,149.8
+ ,0
+ ,164.4
+ ,145.8
+ ,147.0
+ ,137.7
+ ,0
+ ,149.8
+ ,164.4
+ ,145.8
+ ,151.7
+ ,0
+ ,137.7
+ ,149.8
+ ,164.4
+ ,156.8
+ ,0
+ ,151.7
+ ,137.7
+ ,149.8
+ ,180.0
+ ,0
+ ,156.8
+ ,151.7
+ ,137.7
+ ,180.4
+ ,0
+ ,180.0
+ ,156.8
+ ,151.7
+ ,170.4
+ ,0
+ ,180.4
+ ,180.0
+ ,156.8
+ ,191.6
+ ,0
+ ,170.4
+ ,180.4
+ ,180.0
+ ,199.5
+ ,0
+ ,191.6
+ ,170.4
+ ,180.4
+ ,218.2
+ ,0
+ ,199.5
+ ,191.6
+ ,170.4
+ ,217.5
+ ,0
+ ,218.2
+ ,199.5
+ ,191.6
+ ,205.0
+ ,0
+ ,217.5
+ ,218.2
+ ,199.5
+ ,194.0
+ ,0
+ ,205.0
+ ,217.5
+ ,218.2
+ ,199.3
+ ,0
+ ,194.0
+ ,205.0
+ ,217.5
+ ,219.3
+ ,0
+ ,199.3
+ ,194.0
+ ,205.0
+ ,211.1
+ ,0
+ ,219.3
+ ,199.3
+ ,194.0
+ ,215.2
+ ,0
+ ,211.1
+ ,219.3
+ ,199.3
+ ,240.2
+ ,0
+ ,215.2
+ ,211.1
+ ,219.3
+ ,242.2
+ ,0
+ ,240.2
+ ,215.2
+ ,211.1
+ ,240.7
+ ,0
+ ,242.2
+ ,240.2
+ ,215.2
+ ,255.4
+ ,0
+ ,240.7
+ ,242.2
+ ,240.2
+ ,253.0
+ ,0
+ ,255.4
+ ,240.7
+ ,242.2
+ ,218.2
+ ,0
+ ,253.0
+ ,255.4
+ ,240.7
+ ,203.7
+ ,0
+ ,218.2
+ ,253.0
+ ,255.4
+ ,205.6
+ ,0
+ ,203.7
+ ,218.2
+ ,253.0
+ ,215.6
+ ,0
+ ,205.6
+ ,203.7
+ ,218.2
+ ,188.5
+ ,0
+ ,215.6
+ ,205.6
+ ,203.7
+ ,202.9
+ ,0
+ ,188.5
+ ,215.6
+ ,205.6
+ ,214.0
+ ,0
+ ,202.9
+ ,188.5
+ ,215.6
+ ,230.3
+ ,0
+ ,214.0
+ ,202.9
+ ,188.5
+ ,230.0
+ ,0
+ ,230.3
+ ,214.0
+ ,202.9
+ ,241.0
+ ,0
+ ,230.0
+ ,230.3
+ ,214.0
+ ,259.6
+ ,1
+ ,241.0
+ ,230.0
+ ,230.3
+ ,247.8
+ ,1
+ ,259.6
+ ,241.0
+ ,230.0
+ ,270.3
+ ,1
+ ,247.8
+ ,259.6
+ ,241.0
+ ,289.7
+ ,1
+ ,270.3
+ ,247.8
+ ,259.6
+ ,322.7
+ ,1
+ ,289.7
+ ,270.3
+ ,247.8
+ ,315.0
+ ,1
+ ,322.7
+ ,289.7
+ ,270.3
+ ,320.2
+ ,1
+ ,315.0
+ ,322.7
+ ,289.7
+ ,329.5
+ ,1
+ ,320.2
+ ,315.0
+ ,322.7
+ ,360.6
+ ,1
+ ,329.5
+ ,320.2
+ ,315.0
+ ,382.2
+ ,1
+ ,360.6
+ ,329.5
+ ,320.2
+ ,435.4
+ ,1
+ ,382.2
+ ,360.6
+ ,329.5
+ ,464.0
+ ,1
+ ,435.4
+ ,382.2
+ ,360.6
+ ,468.8
+ ,1
+ ,464.0
+ ,435.4
+ ,382.2
+ ,403.0
+ ,1
+ ,468.8
+ ,464.0
+ ,435.4
+ ,351.6
+ ,1
+ ,403.0
+ ,468.8
+ ,464.0
+ ,252.0
+ ,1
+ ,351.6
+ ,403.0
+ ,468.8
+ ,188.0
+ ,1
+ ,252.0
+ ,351.6
+ ,403.0
+ ,146.5
+ ,1
+ ,188.0
+ ,252.0
+ ,351.6
+ ,152.9
+ ,1
+ ,146.5
+ ,188.0
+ ,252.0
+ ,148.1
+ ,1
+ ,152.9
+ ,146.5
+ ,188.0
+ ,165.1
+ ,1
+ ,148.1
+ ,152.9
+ ,146.5
+ ,177.0
+ ,1
+ ,165.1
+ ,148.1
+ ,152.9
+ ,206.1
+ ,1
+ ,177.0
+ ,165.1
+ ,148.1
+ ,244.9
+ ,1
+ ,206.1
+ ,177.0
+ ,165.1
+ ,228.6
+ ,1
+ ,244.9
+ ,206.1
+ ,177.0
+ ,253.4
+ ,1
+ ,228.6
+ ,244.9
+ ,206.1
+ ,241.1
+ ,1
+ ,253.4
+ ,228.6
+ ,244.9)
+ ,dim=c(5
+ ,81)
+ ,dimnames=list(c('Y'
+ ,'D'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3')
+ ,1:81))
> y <- array(NA,dim=c(5,81),dimnames=list(c('Y','D','Y1','Y2','Y3'),1:81))
> 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 Monthly 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 D Y1 Y2 Y3 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 107.1 0 96.3 87.0 96.8 1 0 0 0 0 0 0 0 0 0 0 1
2 115.2 0 107.1 96.3 87.0 0 1 0 0 0 0 0 0 0 0 0 2
3 106.1 0 115.2 107.1 96.3 0 0 1 0 0 0 0 0 0 0 0 3
4 89.5 0 106.1 115.2 107.1 0 0 0 1 0 0 0 0 0 0 0 4
5 91.3 0 89.5 106.1 115.2 0 0 0 0 1 0 0 0 0 0 0 5
6 97.6 0 91.3 89.5 106.1 0 0 0 0 0 1 0 0 0 0 0 6
7 100.7 0 97.6 91.3 89.5 0 0 0 0 0 0 1 0 0 0 0 7
8 104.6 0 100.7 97.6 91.3 0 0 0 0 0 0 0 1 0 0 0 8
9 94.7 0 104.6 100.7 97.6 0 0 0 0 0 0 0 0 1 0 0 9
10 101.8 0 94.7 104.6 100.7 0 0 0 0 0 0 0 0 0 1 0 10
11 102.5 0 101.8 94.7 104.6 0 0 0 0 0 0 0 0 0 0 1 11
12 105.3 0 102.5 101.8 94.7 0 0 0 0 0 0 0 0 0 0 0 12
13 110.3 0 105.3 102.5 101.8 1 0 0 0 0 0 0 0 0 0 0 13
14 109.8 0 110.3 105.3 102.5 0 1 0 0 0 0 0 0 0 0 0 14
15 117.3 0 109.8 110.3 105.3 0 0 1 0 0 0 0 0 0 0 0 15
16 118.8 0 117.3 109.8 110.3 0 0 0 1 0 0 0 0 0 0 0 16
17 131.3 0 118.8 117.3 109.8 0 0 0 0 1 0 0 0 0 0 0 17
18 125.9 0 131.3 118.8 117.3 0 0 0 0 0 1 0 0 0 0 0 18
19 133.1 0 125.9 131.3 118.8 0 0 0 0 0 0 1 0 0 0 0 19
20 147.0 0 133.1 125.9 131.3 0 0 0 0 0 0 0 1 0 0 0 20
21 145.8 0 147.0 133.1 125.9 0 0 0 0 0 0 0 0 1 0 0 21
22 164.4 0 145.8 147.0 133.1 0 0 0 0 0 0 0 0 0 1 0 22
23 149.8 0 164.4 145.8 147.0 0 0 0 0 0 0 0 0 0 0 1 23
24 137.7 0 149.8 164.4 145.8 0 0 0 0 0 0 0 0 0 0 0 24
25 151.7 0 137.7 149.8 164.4 1 0 0 0 0 0 0 0 0 0 0 25
26 156.8 0 151.7 137.7 149.8 0 1 0 0 0 0 0 0 0 0 0 26
27 180.0 0 156.8 151.7 137.7 0 0 1 0 0 0 0 0 0 0 0 27
28 180.4 0 180.0 156.8 151.7 0 0 0 1 0 0 0 0 0 0 0 28
29 170.4 0 180.4 180.0 156.8 0 0 0 0 1 0 0 0 0 0 0 29
30 191.6 0 170.4 180.4 180.0 0 0 0 0 0 1 0 0 0 0 0 30
31 199.5 0 191.6 170.4 180.4 0 0 0 0 0 0 1 0 0 0 0 31
32 218.2 0 199.5 191.6 170.4 0 0 0 0 0 0 0 1 0 0 0 32
33 217.5 0 218.2 199.5 191.6 0 0 0 0 0 0 0 0 1 0 0 33
34 205.0 0 217.5 218.2 199.5 0 0 0 0 0 0 0 0 0 1 0 34
35 194.0 0 205.0 217.5 218.2 0 0 0 0 0 0 0 0 0 0 1 35
36 199.3 0 194.0 205.0 217.5 0 0 0 0 0 0 0 0 0 0 0 36
37 219.3 0 199.3 194.0 205.0 1 0 0 0 0 0 0 0 0 0 0 37
38 211.1 0 219.3 199.3 194.0 0 1 0 0 0 0 0 0 0 0 0 38
39 215.2 0 211.1 219.3 199.3 0 0 1 0 0 0 0 0 0 0 0 39
40 240.2 0 215.2 211.1 219.3 0 0 0 1 0 0 0 0 0 0 0 40
41 242.2 0 240.2 215.2 211.1 0 0 0 0 1 0 0 0 0 0 0 41
42 240.7 0 242.2 240.2 215.2 0 0 0 0 0 1 0 0 0 0 0 42
43 255.4 0 240.7 242.2 240.2 0 0 0 0 0 0 1 0 0 0 0 43
44 253.0 0 255.4 240.7 242.2 0 0 0 0 0 0 0 1 0 0 0 44
45 218.2 0 253.0 255.4 240.7 0 0 0 0 0 0 0 0 1 0 0 45
46 203.7 0 218.2 253.0 255.4 0 0 0 0 0 0 0 0 0 1 0 46
47 205.6 0 203.7 218.2 253.0 0 0 0 0 0 0 0 0 0 0 1 47
48 215.6 0 205.6 203.7 218.2 0 0 0 0 0 0 0 0 0 0 0 48
49 188.5 0 215.6 205.6 203.7 1 0 0 0 0 0 0 0 0 0 0 49
50 202.9 0 188.5 215.6 205.6 0 1 0 0 0 0 0 0 0 0 0 50
51 214.0 0 202.9 188.5 215.6 0 0 1 0 0 0 0 0 0 0 0 51
52 230.3 0 214.0 202.9 188.5 0 0 0 1 0 0 0 0 0 0 0 52
53 230.0 0 230.3 214.0 202.9 0 0 0 0 1 0 0 0 0 0 0 53
54 241.0 0 230.0 230.3 214.0 0 0 0 0 0 1 0 0 0 0 0 54
55 259.6 1 241.0 230.0 230.3 0 0 0 0 0 0 1 0 0 0 0 55
56 247.8 1 259.6 241.0 230.0 0 0 0 0 0 0 0 1 0 0 0 56
57 270.3 1 247.8 259.6 241.0 0 0 0 0 0 0 0 0 1 0 0 57
58 289.7 1 270.3 247.8 259.6 0 0 0 0 0 0 0 0 0 1 0 58
59 322.7 1 289.7 270.3 247.8 0 0 0 0 0 0 0 0 0 0 1 59
60 315.0 1 322.7 289.7 270.3 0 0 0 0 0 0 0 0 0 0 0 60
61 320.2 1 315.0 322.7 289.7 1 0 0 0 0 0 0 0 0 0 0 61
62 329.5 1 320.2 315.0 322.7 0 1 0 0 0 0 0 0 0 0 0 62
63 360.6 1 329.5 320.2 315.0 0 0 1 0 0 0 0 0 0 0 0 63
64 382.2 1 360.6 329.5 320.2 0 0 0 1 0 0 0 0 0 0 0 64
65 435.4 1 382.2 360.6 329.5 0 0 0 0 1 0 0 0 0 0 0 65
66 464.0 1 435.4 382.2 360.6 0 0 0 0 0 1 0 0 0 0 0 66
67 468.8 1 464.0 435.4 382.2 0 0 0 0 0 0 1 0 0 0 0 67
68 403.0 1 468.8 464.0 435.4 0 0 0 0 0 0 0 1 0 0 0 68
69 351.6 1 403.0 468.8 464.0 0 0 0 0 0 0 0 0 1 0 0 69
70 252.0 1 351.6 403.0 468.8 0 0 0 0 0 0 0 0 0 1 0 70
71 188.0 1 252.0 351.6 403.0 0 0 0 0 0 0 0 0 0 0 1 71
72 146.5 1 188.0 252.0 351.6 0 0 0 0 0 0 0 0 0 0 0 72
73 152.9 1 146.5 188.0 252.0 1 0 0 0 0 0 0 0 0 0 0 73
74 148.1 1 152.9 146.5 188.0 0 1 0 0 0 0 0 0 0 0 0 74
75 165.1 1 148.1 152.9 146.5 0 0 1 0 0 0 0 0 0 0 0 75
76 177.0 1 165.1 148.1 152.9 0 0 0 1 0 0 0 0 0 0 0 76
77 206.1 1 177.0 165.1 148.1 0 0 0 0 1 0 0 0 0 0 0 77
78 244.9 1 206.1 177.0 165.1 0 0 0 0 0 1 0 0 0 0 0 78
79 228.6 1 244.9 206.1 177.0 0 0 0 0 0 0 1 0 0 0 0 79
80 253.4 1 228.6 244.9 206.1 0 0 0 0 0 0 0 1 0 0 0 80
81 241.1 1 253.4 228.6 244.9 0 0 0 0 0 0 0 0 1 0 0 81
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D Y1 Y2 Y3 M1
12.06300 4.10249 1.26715 -0.08184 -0.30610 8.12828
M2 M3 M4 M5 M6 M7
1.82766 8.39072 3.13299 6.63553 8.96124 -0.41942
M8 M9 M10 M11 t
-5.56120 -10.17032 -3.70759 1.00729 0.24820
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-47.271 -10.564 1.054 14.138 42.533
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.06300 9.99800 1.207 0.2321
D 4.10249 7.90593 0.519 0.6056
Y1 1.26715 0.12015 10.547 1.24e-15 ***
Y2 -0.08184 0.20153 -0.406 0.6860
Y3 -0.30610 0.12411 -2.466 0.0163 *
M1 8.12828 10.63704 0.764 0.4476
M2 1.82766 10.71927 0.171 0.8652
M3 8.39072 10.82373 0.775 0.4411
M4 3.13299 10.86559 0.288 0.7740
M5 6.63553 10.97206 0.605 0.5475
M6 8.96124 10.93353 0.820 0.4155
M7 -0.41942 11.02992 -0.038 0.9698
M8 -5.56120 11.00080 -0.506 0.6149
M9 -10.17032 10.81095 -0.941 0.3504
M10 -3.70759 11.08029 -0.335 0.7390
M11 1.00729 11.02754 0.091 0.9275
t 0.24820 0.18239 1.361 0.1784
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 19.06 on 64 degrees of freedom
Multiple R-squared: 0.9621, Adjusted R-squared: 0.9526
F-statistic: 101.5 on 16 and 64 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,] 1.255494e-01 2.510988e-01 0.8744506
[2,] 4.962979e-02 9.925958e-02 0.9503702
[3,] 2.166906e-02 4.333811e-02 0.9783309
[4,] 2.053025e-02 4.106050e-02 0.9794697
[5,] 8.521634e-03 1.704327e-02 0.9914784
[6,] 3.234566e-03 6.469132e-03 0.9967654
[7,] 1.835594e-03 3.671189e-03 0.9981644
[8,] 3.201580e-03 6.403160e-03 0.9967984
[9,] 1.535532e-03 3.071064e-03 0.9984645
[10,] 1.544244e-03 3.088488e-03 0.9984558
[11,] 3.348590e-03 6.697179e-03 0.9966514
[12,] 1.512819e-03 3.025637e-03 0.9984872
[13,] 1.018165e-03 2.036331e-03 0.9989818
[14,] 4.442311e-04 8.884622e-04 0.9995558
[15,] 6.721527e-04 1.344305e-03 0.9993278
[16,] 3.348096e-04 6.696192e-04 0.9996652
[17,] 1.450170e-04 2.900340e-04 0.9998550
[18,] 6.738141e-05 1.347628e-04 0.9999326
[19,] 6.811581e-05 1.362316e-04 0.9999319
[20,] 3.690293e-05 7.380586e-05 0.9999631
[21,] 6.178587e-05 1.235717e-04 0.9999382
[22,] 3.790298e-05 7.580595e-05 0.9999621
[23,] 3.500385e-05 7.000770e-05 0.9999650
[24,] 2.194252e-05 4.388503e-05 0.9999781
[25,] 2.465947e-05 4.931893e-05 0.9999753
[26,] 1.268840e-04 2.537680e-04 0.9998731
[27,] 1.750714e-04 3.501428e-04 0.9998249
[28,] 1.141319e-04 2.282638e-04 0.9998859
[29,] 9.971797e-05 1.994359e-04 0.9999003
[30,] 1.603178e-03 3.206357e-03 0.9983968
[31,] 1.249825e-03 2.499651e-03 0.9987502
[32,] 8.355854e-04 1.671171e-03 0.9991644
[33,] 6.045635e-04 1.209127e-03 0.9993954
[34,] 3.221877e-04 6.443754e-04 0.9996778
[35,] 1.396249e-04 2.792498e-04 0.9998604
[36,] 5.532833e-05 1.106567e-04 0.9999447
[37,] 2.593172e-04 5.186344e-04 0.9997407
[38,] 1.943270e-03 3.886540e-03 0.9980567
[39,] 9.591264e-04 1.918253e-03 0.9990409
[40,] 9.734355e-04 1.946871e-03 0.9990266
[41,] 4.983528e-04 9.967055e-04 0.9995016
[42,] 1.086304e-02 2.172609e-02 0.9891370
> postscript(file="/var/www/html/rcomp/tmp/1ij9i1260834280.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2vm5f1260834280.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wfjo1260834280.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4vg9b1260834280.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5nvyf1260834280.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 = 81
Frequency = 1
1 2 3 4 5 6
1.3847238 -0.3867996 -22.8313560 -18.9219554 1.8967224 -0.8021058
7 8 9 10 11 12
-1.4867110 4.4452712 -3.8535361 10.3484113 -2.5278185 -2.3051181
13 14 15 16 17 18
-6.9989942 -7.3388991 -4.7503000 -6.2547998 1.0544721 -20.3402714
19 20 21 22 23 24
4.3169278 17.3714067 1.8552150 18.6063606 -20.3690664 -12.0547295
25 26 27 28 29 30
13.4000110 1.3529799 8.7211270 -10.5644015 -21.3622291 17.0697180
31 32 33 34 35 36
6.5426602 18.7996758 5.9008189 -8.4745166 -2.9313562 15.8291386
37 38 39 40 41 42
16.0102454 -14.4137350 -3.4752536 26.7899679 -8.8140379 -12.1212722
43 44 45 46 47 48
21.4281915 5.7841187 -20.8699370 6.3192783 18.0472756 14.5597087
49 50 51 52 53 54
-37.8712914 18.3208792 5.2058995 5.3331002 -14.0558829 -0.5179315
55 56 57 58 59 60
14.1383326 -15.5286933 31.1739305 20.0799749 21.7635071 -18.5183647
61 62 63 64 65 66
-3.2987251 14.9358059 25.5086084 15.0625964 42.5333415 12.4345832
67 68 69 70 71 72
1.0921665 -47.2712744 -1.7844726 -46.8795085 -13.9825417 2.4893649
73 74 75 76 77 78
17.3740306 -12.4702314 -8.3787253 -11.4445078 -1.2523862 4.2772796
79 80 81
-46.0315676 16.3994953 -12.4220187
> postscript(file="/var/www/html/rcomp/tmp/6rpwm1260834280.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 = 81
Frequency = 1
lag(myerror, k = 1) myerror
0 1.3847238 NA
1 -0.3867996 1.3847238
2 -22.8313560 -0.3867996
3 -18.9219554 -22.8313560
4 1.8967224 -18.9219554
5 -0.8021058 1.8967224
6 -1.4867110 -0.8021058
7 4.4452712 -1.4867110
8 -3.8535361 4.4452712
9 10.3484113 -3.8535361
10 -2.5278185 10.3484113
11 -2.3051181 -2.5278185
12 -6.9989942 -2.3051181
13 -7.3388991 -6.9989942
14 -4.7503000 -7.3388991
15 -6.2547998 -4.7503000
16 1.0544721 -6.2547998
17 -20.3402714 1.0544721
18 4.3169278 -20.3402714
19 17.3714067 4.3169278
20 1.8552150 17.3714067
21 18.6063606 1.8552150
22 -20.3690664 18.6063606
23 -12.0547295 -20.3690664
24 13.4000110 -12.0547295
25 1.3529799 13.4000110
26 8.7211270 1.3529799
27 -10.5644015 8.7211270
28 -21.3622291 -10.5644015
29 17.0697180 -21.3622291
30 6.5426602 17.0697180
31 18.7996758 6.5426602
32 5.9008189 18.7996758
33 -8.4745166 5.9008189
34 -2.9313562 -8.4745166
35 15.8291386 -2.9313562
36 16.0102454 15.8291386
37 -14.4137350 16.0102454
38 -3.4752536 -14.4137350
39 26.7899679 -3.4752536
40 -8.8140379 26.7899679
41 -12.1212722 -8.8140379
42 21.4281915 -12.1212722
43 5.7841187 21.4281915
44 -20.8699370 5.7841187
45 6.3192783 -20.8699370
46 18.0472756 6.3192783
47 14.5597087 18.0472756
48 -37.8712914 14.5597087
49 18.3208792 -37.8712914
50 5.2058995 18.3208792
51 5.3331002 5.2058995
52 -14.0558829 5.3331002
53 -0.5179315 -14.0558829
54 14.1383326 -0.5179315
55 -15.5286933 14.1383326
56 31.1739305 -15.5286933
57 20.0799749 31.1739305
58 21.7635071 20.0799749
59 -18.5183647 21.7635071
60 -3.2987251 -18.5183647
61 14.9358059 -3.2987251
62 25.5086084 14.9358059
63 15.0625964 25.5086084
64 42.5333415 15.0625964
65 12.4345832 42.5333415
66 1.0921665 12.4345832
67 -47.2712744 1.0921665
68 -1.7844726 -47.2712744
69 -46.8795085 -1.7844726
70 -13.9825417 -46.8795085
71 2.4893649 -13.9825417
72 17.3740306 2.4893649
73 -12.4702314 17.3740306
74 -8.3787253 -12.4702314
75 -11.4445078 -8.3787253
76 -1.2523862 -11.4445078
77 4.2772796 -1.2523862
78 -46.0315676 4.2772796
79 16.3994953 -46.0315676
80 -12.4220187 16.3994953
81 NA -12.4220187
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.3867996 1.3847238
[2,] -22.8313560 -0.3867996
[3,] -18.9219554 -22.8313560
[4,] 1.8967224 -18.9219554
[5,] -0.8021058 1.8967224
[6,] -1.4867110 -0.8021058
[7,] 4.4452712 -1.4867110
[8,] -3.8535361 4.4452712
[9,] 10.3484113 -3.8535361
[10,] -2.5278185 10.3484113
[11,] -2.3051181 -2.5278185
[12,] -6.9989942 -2.3051181
[13,] -7.3388991 -6.9989942
[14,] -4.7503000 -7.3388991
[15,] -6.2547998 -4.7503000
[16,] 1.0544721 -6.2547998
[17,] -20.3402714 1.0544721
[18,] 4.3169278 -20.3402714
[19,] 17.3714067 4.3169278
[20,] 1.8552150 17.3714067
[21,] 18.6063606 1.8552150
[22,] -20.3690664 18.6063606
[23,] -12.0547295 -20.3690664
[24,] 13.4000110 -12.0547295
[25,] 1.3529799 13.4000110
[26,] 8.7211270 1.3529799
[27,] -10.5644015 8.7211270
[28,] -21.3622291 -10.5644015
[29,] 17.0697180 -21.3622291
[30,] 6.5426602 17.0697180
[31,] 18.7996758 6.5426602
[32,] 5.9008189 18.7996758
[33,] -8.4745166 5.9008189
[34,] -2.9313562 -8.4745166
[35,] 15.8291386 -2.9313562
[36,] 16.0102454 15.8291386
[37,] -14.4137350 16.0102454
[38,] -3.4752536 -14.4137350
[39,] 26.7899679 -3.4752536
[40,] -8.8140379 26.7899679
[41,] -12.1212722 -8.8140379
[42,] 21.4281915 -12.1212722
[43,] 5.7841187 21.4281915
[44,] -20.8699370 5.7841187
[45,] 6.3192783 -20.8699370
[46,] 18.0472756 6.3192783
[47,] 14.5597087 18.0472756
[48,] -37.8712914 14.5597087
[49,] 18.3208792 -37.8712914
[50,] 5.2058995 18.3208792
[51,] 5.3331002 5.2058995
[52,] -14.0558829 5.3331002
[53,] -0.5179315 -14.0558829
[54,] 14.1383326 -0.5179315
[55,] -15.5286933 14.1383326
[56,] 31.1739305 -15.5286933
[57,] 20.0799749 31.1739305
[58,] 21.7635071 20.0799749
[59,] -18.5183647 21.7635071
[60,] -3.2987251 -18.5183647
[61,] 14.9358059 -3.2987251
[62,] 25.5086084 14.9358059
[63,] 15.0625964 25.5086084
[64,] 42.5333415 15.0625964
[65,] 12.4345832 42.5333415
[66,] 1.0921665 12.4345832
[67,] -47.2712744 1.0921665
[68,] -1.7844726 -47.2712744
[69,] -46.8795085 -1.7844726
[70,] -13.9825417 -46.8795085
[71,] 2.4893649 -13.9825417
[72,] 17.3740306 2.4893649
[73,] -12.4702314 17.3740306
[74,] -8.3787253 -12.4702314
[75,] -11.4445078 -8.3787253
[76,] -1.2523862 -11.4445078
[77,] 4.2772796 -1.2523862
[78,] -46.0315676 4.2772796
[79,] 16.3994953 -46.0315676
[80,] -12.4220187 16.3994953
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.3867996 1.3847238
2 -22.8313560 -0.3867996
3 -18.9219554 -22.8313560
4 1.8967224 -18.9219554
5 -0.8021058 1.8967224
6 -1.4867110 -0.8021058
7 4.4452712 -1.4867110
8 -3.8535361 4.4452712
9 10.3484113 -3.8535361
10 -2.5278185 10.3484113
11 -2.3051181 -2.5278185
12 -6.9989942 -2.3051181
13 -7.3388991 -6.9989942
14 -4.7503000 -7.3388991
15 -6.2547998 -4.7503000
16 1.0544721 -6.2547998
17 -20.3402714 1.0544721
18 4.3169278 -20.3402714
19 17.3714067 4.3169278
20 1.8552150 17.3714067
21 18.6063606 1.8552150
22 -20.3690664 18.6063606
23 -12.0547295 -20.3690664
24 13.4000110 -12.0547295
25 1.3529799 13.4000110
26 8.7211270 1.3529799
27 -10.5644015 8.7211270
28 -21.3622291 -10.5644015
29 17.0697180 -21.3622291
30 6.5426602 17.0697180
31 18.7996758 6.5426602
32 5.9008189 18.7996758
33 -8.4745166 5.9008189
34 -2.9313562 -8.4745166
35 15.8291386 -2.9313562
36 16.0102454 15.8291386
37 -14.4137350 16.0102454
38 -3.4752536 -14.4137350
39 26.7899679 -3.4752536
40 -8.8140379 26.7899679
41 -12.1212722 -8.8140379
42 21.4281915 -12.1212722
43 5.7841187 21.4281915
44 -20.8699370 5.7841187
45 6.3192783 -20.8699370
46 18.0472756 6.3192783
47 14.5597087 18.0472756
48 -37.8712914 14.5597087
49 18.3208792 -37.8712914
50 5.2058995 18.3208792
51 5.3331002 5.2058995
52 -14.0558829 5.3331002
53 -0.5179315 -14.0558829
54 14.1383326 -0.5179315
55 -15.5286933 14.1383326
56 31.1739305 -15.5286933
57 20.0799749 31.1739305
58 21.7635071 20.0799749
59 -18.5183647 21.7635071
60 -3.2987251 -18.5183647
61 14.9358059 -3.2987251
62 25.5086084 14.9358059
63 15.0625964 25.5086084
64 42.5333415 15.0625964
65 12.4345832 42.5333415
66 1.0921665 12.4345832
67 -47.2712744 1.0921665
68 -1.7844726 -47.2712744
69 -46.8795085 -1.7844726
70 -13.9825417 -46.8795085
71 2.4893649 -13.9825417
72 17.3740306 2.4893649
73 -12.4702314 17.3740306
74 -8.3787253 -12.4702314
75 -11.4445078 -8.3787253
76 -1.2523862 -11.4445078
77 4.2772796 -1.2523862
78 -46.0315676 4.2772796
79 16.3994953 -46.0315676
80 -12.4220187 16.3994953
> 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/7363e1260834281.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8mnh01260834281.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9egev1260834281.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/102kwe1260834281.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ih8q1260834281.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/12op3z1260834281.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/13pzku1260834281.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/14hbs91260834281.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/15skxu1260834281.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/16fi3r1260834281.tab")
+ }
>
> try(system("convert tmp/1ij9i1260834280.ps tmp/1ij9i1260834280.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vm5f1260834280.ps tmp/2vm5f1260834280.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wfjo1260834280.ps tmp/3wfjo1260834280.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vg9b1260834280.ps tmp/4vg9b1260834280.png",intern=TRUE))
character(0)
> try(system("convert tmp/5nvyf1260834280.ps tmp/5nvyf1260834280.png",intern=TRUE))
character(0)
> try(system("convert tmp/6rpwm1260834280.ps tmp/6rpwm1260834280.png",intern=TRUE))
character(0)
> try(system("convert tmp/7363e1260834281.ps tmp/7363e1260834281.png",intern=TRUE))
character(0)
> try(system("convert tmp/8mnh01260834281.ps tmp/8mnh01260834281.png",intern=TRUE))
character(0)
> try(system("convert tmp/9egev1260834281.ps tmp/9egev1260834281.png",intern=TRUE))
character(0)
> try(system("convert tmp/102kwe1260834281.ps tmp/102kwe1260834281.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.687 1.571 3.487