R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'q()' to quit R.
> x <- array(list(8.4
+ ,1.58
+ ,8.4
+ ,8.4
+ ,8.3
+ ,7.6
+ ,8.4
+ ,1.86
+ ,8.4
+ ,8.4
+ ,8.4
+ ,8.3
+ ,8.6
+ ,1.74
+ ,8.4
+ ,8.4
+ ,8.4
+ ,8.4
+ ,8.9
+ ,1.59
+ ,8.6
+ ,8.4
+ ,8.4
+ ,8.4
+ ,8.8
+ ,1.26
+ ,8.9
+ ,8.6
+ ,8.4
+ ,8.4
+ ,8.3
+ ,1.13
+ ,8.8
+ ,8.9
+ ,8.6
+ ,8.4
+ ,7.5
+ ,1.92
+ ,8.3
+ ,8.8
+ ,8.9
+ ,8.6
+ ,7.2
+ ,2.61
+ ,7.5
+ ,8.3
+ ,8.8
+ ,8.9
+ ,7.4
+ ,2.26
+ ,7.2
+ ,7.5
+ ,8.3
+ ,8.8
+ ,8.8
+ ,2.41
+ ,7.4
+ ,7.2
+ ,7.5
+ ,8.3
+ ,9.3
+ ,2.26
+ ,8.8
+ ,7.4
+ ,7.2
+ ,7.5
+ ,9.3
+ ,2.03
+ ,9.3
+ ,8.8
+ ,7.4
+ ,7.2
+ ,8.7
+ ,2.86
+ ,9.3
+ ,9.3
+ ,8.8
+ ,7.4
+ ,8.2
+ ,2.55
+ ,8.7
+ ,9.3
+ ,9.3
+ ,8.8
+ ,8.3
+ ,2.27
+ ,8.2
+ ,8.7
+ ,9.3
+ ,9.3
+ ,8.5
+ ,2.26
+ ,8.3
+ ,8.2
+ ,8.7
+ ,9.3
+ ,8.6
+ ,2.57
+ ,8.5
+ ,8.3
+ ,8.2
+ ,8.7
+ ,8.5
+ ,3.07
+ ,8.6
+ ,8.5
+ ,8.3
+ ,8.2
+ ,8.2
+ ,2.76
+ ,8.5
+ ,8.6
+ ,8.5
+ ,8.3
+ ,8.1
+ ,2.51
+ ,8.2
+ ,8.5
+ ,8.6
+ ,8.5
+ ,7.9
+ ,2.87
+ ,8.1
+ ,8.2
+ ,8.5
+ ,8.6
+ ,8.6
+ ,3.14
+ ,7.9
+ ,8.1
+ ,8.2
+ ,8.5
+ ,8.7
+ ,3.11
+ ,8.6
+ ,7.9
+ ,8.1
+ ,8.2
+ ,8.7
+ ,3.16
+ ,8.7
+ ,8.6
+ ,7.9
+ ,8.1
+ ,8.5
+ ,2.47
+ ,8.7
+ ,8.7
+ ,8.6
+ ,7.9
+ ,8.4
+ ,2.57
+ ,8.5
+ ,8.7
+ ,8.7
+ ,8.6
+ ,8.5
+ ,2.89
+ ,8.4
+ ,8.5
+ ,8.7
+ ,8.7
+ ,8.7
+ ,2.63
+ ,8.5
+ ,8.4
+ ,8.5
+ ,8.7
+ ,8.7
+ ,2.38
+ ,8.7
+ ,8.5
+ ,8.4
+ ,8.5
+ ,8.6
+ ,1.69
+ ,8.7
+ ,8.7
+ ,8.5
+ ,8.4
+ ,8.5
+ ,1.96
+ ,8.6
+ ,8.7
+ ,8.7
+ ,8.5
+ ,8.3
+ ,2.19
+ ,8.5
+ ,8.6
+ ,8.7
+ ,8.7
+ ,8
+ ,1.87
+ ,8.3
+ ,8.5
+ ,8.6
+ ,8.7
+ ,8.2
+ ,1.6
+ ,8
+ ,8.3
+ ,8.5
+ ,8.6
+ ,8.1
+ ,1.63
+ ,8.2
+ ,8
+ ,8.3
+ ,8.5
+ ,8.1
+ ,1.22
+ ,8.1
+ ,8.2
+ ,8
+ ,8.3
+ ,8
+ ,1.21
+ ,8.1
+ ,8.1
+ ,8.2
+ ,8
+ ,7.9
+ ,1.49
+ ,8
+ ,8.1
+ ,8.1
+ ,8.2
+ ,7.9
+ ,1.64
+ ,7.9
+ ,8
+ ,8.1
+ ,8.1
+ ,8
+ ,1.66
+ ,7.9
+ ,7.9
+ ,8
+ ,8.1
+ ,8
+ ,1.77
+ ,8
+ ,7.9
+ ,7.9
+ ,8
+ ,7.9
+ ,1.82
+ ,8
+ ,8
+ ,7.9
+ ,7.9
+ ,8
+ ,1.78
+ ,7.9
+ ,8
+ ,8
+ ,7.9
+ ,7.7
+ ,1.28
+ ,8
+ ,7.9
+ ,8
+ ,8
+ ,7.2
+ ,1.29
+ ,7.7
+ ,8
+ ,7.9
+ ,8
+ ,7.5
+ ,1.37
+ ,7.2
+ ,7.7
+ ,8
+ ,7.9
+ ,7.3
+ ,1.12
+ ,7.5
+ ,7.2
+ ,7.7
+ ,8
+ ,7
+ ,1.51
+ ,7.3
+ ,7.5
+ ,7.2
+ ,7.7
+ ,7
+ ,2.24
+ ,7
+ ,7.3
+ ,7.5
+ ,7.2
+ ,7
+ ,2.94
+ ,7
+ ,7
+ ,7.3
+ ,7.5
+ ,7.2
+ ,3.09
+ ,7
+ ,7
+ ,7
+ ,7.3
+ ,7.3
+ ,3.46
+ ,7.2
+ ,7
+ ,7
+ ,7
+ ,7.1
+ ,3.64
+ ,7.3
+ ,7.2
+ ,7
+ ,7
+ ,6.8
+ ,4.39
+ ,7.1
+ ,7.3
+ ,7.2
+ ,7
+ ,6.4
+ ,4.15
+ ,6.8
+ ,7.1
+ ,7.3
+ ,7.2
+ ,6.1
+ ,5.21
+ ,6.4
+ ,6.8
+ ,7.1
+ ,7.3
+ ,6.5
+ ,5.8
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.1
+ ,7.7
+ ,5.91
+ ,6.5
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.9
+ ,5.39
+ ,7.7
+ ,6.5
+ ,6.1
+ ,6.4
+ ,7.5
+ ,5.46
+ ,7.9
+ ,7.7
+ ,6.5
+ ,6.1
+ ,6.9
+ ,4.72
+ ,7.5
+ ,7.9
+ ,7.7
+ ,6.5
+ ,6.6
+ ,3.14
+ ,6.9
+ ,7.5
+ ,7.9
+ ,7.7
+ ,6.9
+ ,2.63
+ ,6.6
+ ,6.9
+ ,7.5
+ ,7.9
+ ,7.7
+ ,2.32
+ ,6.9
+ ,6.6
+ ,6.9
+ ,7.5
+ ,8
+ ,1.93
+ ,7.7
+ ,6.9
+ ,6.6
+ ,6.9
+ ,8
+ ,0.62
+ ,8
+ ,7.7
+ ,6.9
+ ,6.6
+ ,7.7
+ ,0.6
+ ,8
+ ,8
+ ,7.7
+ ,6.9
+ ,7.3
+ ,-0.37
+ ,7.7
+ ,8
+ ,8
+ ,7.7
+ ,7.4
+ ,-1.1
+ ,7.3
+ ,7.7
+ ,8
+ ,8)
+ ,dim=c(6
+ ,69)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:69))
> y <- array(NA,dim=c(6,69),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:69))
> 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 X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 8.4 1.58 8.4 8.4 8.3 7.6 1 0 0 0 0 0 0 0 0 0 0 1
2 8.4 1.86 8.4 8.4 8.4 8.3 0 1 0 0 0 0 0 0 0 0 0 2
3 8.6 1.74 8.4 8.4 8.4 8.4 0 0 1 0 0 0 0 0 0 0 0 3
4 8.9 1.59 8.6 8.4 8.4 8.4 0 0 0 1 0 0 0 0 0 0 0 4
5 8.8 1.26 8.9 8.6 8.4 8.4 0 0 0 0 1 0 0 0 0 0 0 5
6 8.3 1.13 8.8 8.9 8.6 8.4 0 0 0 0 0 1 0 0 0 0 0 6
7 7.5 1.92 8.3 8.8 8.9 8.6 0 0 0 0 0 0 1 0 0 0 0 7
8 7.2 2.61 7.5 8.3 8.8 8.9 0 0 0 0 0 0 0 1 0 0 0 8
9 7.4 2.26 7.2 7.5 8.3 8.8 0 0 0 0 0 0 0 0 1 0 0 9
10 8.8 2.41 7.4 7.2 7.5 8.3 0 0 0 0 0 0 0 0 0 1 0 10
11 9.3 2.26 8.8 7.4 7.2 7.5 0 0 0 0 0 0 0 0 0 0 1 11
12 9.3 2.03 9.3 8.8 7.4 7.2 0 0 0 0 0 0 0 0 0 0 0 12
13 8.7 2.86 9.3 9.3 8.8 7.4 1 0 0 0 0 0 0 0 0 0 0 13
14 8.2 2.55 8.7 9.3 9.3 8.8 0 1 0 0 0 0 0 0 0 0 0 14
15 8.3 2.27 8.2 8.7 9.3 9.3 0 0 1 0 0 0 0 0 0 0 0 15
16 8.5 2.26 8.3 8.2 8.7 9.3 0 0 0 1 0 0 0 0 0 0 0 16
17 8.6 2.57 8.5 8.3 8.2 8.7 0 0 0 0 1 0 0 0 0 0 0 17
18 8.5 3.07 8.6 8.5 8.3 8.2 0 0 0 0 0 1 0 0 0 0 0 18
19 8.2 2.76 8.5 8.6 8.5 8.3 0 0 0 0 0 0 1 0 0 0 0 19
20 8.1 2.51 8.2 8.5 8.6 8.5 0 0 0 0 0 0 0 1 0 0 0 20
21 7.9 2.87 8.1 8.2 8.5 8.6 0 0 0 0 0 0 0 0 1 0 0 21
22 8.6 3.14 7.9 8.1 8.2 8.5 0 0 0 0 0 0 0 0 0 1 0 22
23 8.7 3.11 8.6 7.9 8.1 8.2 0 0 0 0 0 0 0 0 0 0 1 23
24 8.7 3.16 8.7 8.6 7.9 8.1 0 0 0 0 0 0 0 0 0 0 0 24
25 8.5 2.47 8.7 8.7 8.6 7.9 1 0 0 0 0 0 0 0 0 0 0 25
26 8.4 2.57 8.5 8.7 8.7 8.6 0 1 0 0 0 0 0 0 0 0 0 26
27 8.5 2.89 8.4 8.5 8.7 8.7 0 0 1 0 0 0 0 0 0 0 0 27
28 8.7 2.63 8.5 8.4 8.5 8.7 0 0 0 1 0 0 0 0 0 0 0 28
29 8.7 2.38 8.7 8.5 8.4 8.5 0 0 0 0 1 0 0 0 0 0 0 29
30 8.6 1.69 8.7 8.7 8.5 8.4 0 0 0 0 0 1 0 0 0 0 0 30
31 8.5 1.96 8.6 8.7 8.7 8.5 0 0 0 0 0 0 1 0 0 0 0 31
32 8.3 2.19 8.5 8.6 8.7 8.7 0 0 0 0 0 0 0 1 0 0 0 32
33 8.0 1.87 8.3 8.5 8.6 8.7 0 0 0 0 0 0 0 0 1 0 0 33
34 8.2 1.60 8.0 8.3 8.5 8.6 0 0 0 0 0 0 0 0 0 1 0 34
35 8.1 1.63 8.2 8.0 8.3 8.5 0 0 0 0 0 0 0 0 0 0 1 35
36 8.1 1.22 8.1 8.2 8.0 8.3 0 0 0 0 0 0 0 0 0 0 0 36
37 8.0 1.21 8.1 8.1 8.2 8.0 1 0 0 0 0 0 0 0 0 0 0 37
38 7.9 1.49 8.0 8.1 8.1 8.2 0 1 0 0 0 0 0 0 0 0 0 38
39 7.9 1.64 7.9 8.0 8.1 8.1 0 0 1 0 0 0 0 0 0 0 0 39
40 8.0 1.66 7.9 7.9 8.0 8.1 0 0 0 1 0 0 0 0 0 0 0 40
41 8.0 1.77 8.0 7.9 7.9 8.0 0 0 0 0 1 0 0 0 0 0 0 41
42 7.9 1.82 8.0 8.0 7.9 7.9 0 0 0 0 0 1 0 0 0 0 0 42
43 8.0 1.78 7.9 8.0 8.0 7.9 0 0 0 0 0 0 1 0 0 0 0 43
44 7.7 1.28 8.0 7.9 8.0 8.0 0 0 0 0 0 0 0 1 0 0 0 44
45 7.2 1.29 7.7 8.0 7.9 8.0 0 0 0 0 0 0 0 0 1 0 0 45
46 7.5 1.37 7.2 7.7 8.0 7.9 0 0 0 0 0 0 0 0 0 1 0 46
47 7.3 1.12 7.5 7.2 7.7 8.0 0 0 0 0 0 0 0 0 0 0 1 47
48 7.0 1.51 7.3 7.5 7.2 7.7 0 0 0 0 0 0 0 0 0 0 0 48
49 7.0 2.24 7.0 7.3 7.5 7.2 1 0 0 0 0 0 0 0 0 0 0 49
50 7.0 2.94 7.0 7.0 7.3 7.5 0 1 0 0 0 0 0 0 0 0 0 50
51 7.2 3.09 7.0 7.0 7.0 7.3 0 0 1 0 0 0 0 0 0 0 0 51
52 7.3 3.46 7.2 7.0 7.0 7.0 0 0 0 1 0 0 0 0 0 0 0 52
53 7.1 3.64 7.3 7.2 7.0 7.0 0 0 0 0 1 0 0 0 0 0 0 53
54 6.8 4.39 7.1 7.3 7.2 7.0 0 0 0 0 0 1 0 0 0 0 0 54
55 6.4 4.15 6.8 7.1 7.3 7.2 0 0 0 0 0 0 1 0 0 0 0 55
56 6.1 5.21 6.4 6.8 7.1 7.3 0 0 0 0 0 0 0 1 0 0 0 56
57 6.5 5.80 6.1 6.4 6.8 7.1 0 0 0 0 0 0 0 0 1 0 0 57
58 7.7 5.91 6.5 6.1 6.4 6.8 0 0 0 0 0 0 0 0 0 1 0 58
59 7.9 5.39 7.7 6.5 6.1 6.4 0 0 0 0 0 0 0 0 0 0 1 59
60 7.5 5.46 7.9 7.7 6.5 6.1 0 0 0 0 0 0 0 0 0 0 0 60
61 6.9 4.72 7.5 7.9 7.7 6.5 1 0 0 0 0 0 0 0 0 0 0 61
62 6.6 3.14 6.9 7.5 7.9 7.7 0 1 0 0 0 0 0 0 0 0 0 62
63 6.9 2.63 6.6 6.9 7.5 7.9 0 0 1 0 0 0 0 0 0 0 0 63
64 7.7 2.32 6.9 6.6 6.9 7.5 0 0 0 1 0 0 0 0 0 0 0 64
65 8.0 1.93 7.7 6.9 6.6 6.9 0 0 0 0 1 0 0 0 0 0 0 65
66 8.0 0.62 8.0 7.7 6.9 6.6 0 0 0 0 0 1 0 0 0 0 0 66
67 7.7 0.60 8.0 8.0 7.7 6.9 0 0 0 0 0 0 1 0 0 0 0 67
68 7.3 -0.37 7.7 8.0 8.0 7.7 0 0 0 0 0 0 0 1 0 0 0 68
69 7.4 -1.10 7.3 7.7 8.0 8.0 0 0 0 0 0 0 0 0 1 0 0 69
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
0.881778 -0.011323 1.638065 -1.002869 0.014560 0.251295
M1 M2 M3 M4 M5 M6
0.062567 -0.000682 0.149464 0.054089 -0.176549 -0.063074
M7 M8 M9 M10 M11 t
-0.085187 -0.113416 -0.027978 0.625143 -0.521386 -0.001831
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.323439 -0.085626 0.003209 0.102130 0.359194
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.881778 0.698477 1.262 0.212537
X -0.011323 0.019941 -0.568 0.572649
Y1 1.638065 0.142074 11.530 8.08e-16 ***
Y2 -1.002869 0.277449 -3.615 0.000688 ***
Y3 0.014560 0.277990 0.052 0.958435
Y4 0.251295 0.144383 1.740 0.087807 .
M1 0.062567 0.214197 0.292 0.771396
M2 -0.000682 0.165888 -0.004 0.996736
M3 0.149464 0.170434 0.877 0.384619
M4 0.054089 0.173733 0.311 0.756814
M5 -0.176549 0.152101 -1.161 0.251153
M6 -0.063074 0.141031 -0.447 0.656598
M7 -0.085187 0.170104 -0.501 0.618669
M8 -0.113416 0.164323 -0.690 0.493199
M9 -0.027978 0.165786 -0.169 0.866654
M10 0.625143 0.165394 3.780 0.000413 ***
M11 -0.521386 0.224014 -2.327 0.023946 *
t -0.001831 0.002001 -0.915 0.364429
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1724 on 51 degrees of freedom
Multiple R-squared: 0.9558, Adjusted R-squared: 0.9411
F-statistic: 64.89 on 17 and 51 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.04566636 0.09133272 0.9543336
[2,] 0.10574223 0.21148446 0.8942578
[3,] 0.07862593 0.15725185 0.9213741
[4,] 0.04337198 0.08674395 0.9566280
[5,] 0.08647062 0.17294124 0.9135294
[6,] 0.08088709 0.16177418 0.9191129
[7,] 0.12286921 0.24573842 0.8771308
[8,] 0.07501586 0.15003172 0.9249841
[9,] 0.04635121 0.09270243 0.9536488
[10,] 0.03288252 0.06576504 0.9671175
[11,] 0.05142497 0.10284995 0.9485750
[12,] 0.04625002 0.09250005 0.9537500
[13,] 0.03146919 0.06293838 0.9685308
[14,] 0.20426838 0.40853676 0.7957316
[15,] 0.19026557 0.38053114 0.8097344
[16,] 0.18564479 0.37128958 0.8143552
[17,] 0.19632338 0.39264676 0.8036766
[18,] 0.19422686 0.38845373 0.8057731
[19,] 0.16600972 0.33201944 0.8339903
[20,] 0.11085413 0.22170825 0.8891459
[21,] 0.11037725 0.22075450 0.8896227
[22,] 0.06933027 0.13866054 0.9306697
[23,] 0.65947880 0.68104240 0.3405212
[24,] 0.88072833 0.23854335 0.1192717
[25,] 0.81174030 0.37651941 0.1882597
[26,] 0.73345358 0.53309284 0.2665464
[27,] 0.61873221 0.76253558 0.3812678
[28,] 0.54012697 0.91974605 0.4598730
> postscript(file="/var/www/html/rcomp/tmp/17lko1261069256.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2e8as1261069256.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/32m1c1261069256.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4lod01261069256.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5fkbv1261069256.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 = 69
Frequency = 1
1 2 3 4 5
1.090493e-01 -6.339116e-05 2.513304e-02 9.302689e-02 -6.908611e-02
6 7 8 9 10
-2.204469e-01 -3.234392e-01 1.495172e-01 -1.651975e-02 2.427105e-01
11 12 13 14 15
2.058555e-03 1.373601e-01 -8.318537e-02 1.021298e-01 1.423073e-01
16 17 18 19 20
-2.171060e-01 4.960408e-02 4.580483e-03 -3.893381e-02 2.277118e-01
21 22 23 24 25
-2.125468e-01 9.604407e-02 7.368906e-02 1.209433e-01 -7.251320e-03
26 27 28 29 30
1.092108e-01 2.622012e-03 3.570177e-02 8.972912e-02 9.451949e-02
31 32 33 34 35
1.572857e-01 3.209399e-03 -1.552391e-01 -2.921551e-01 1.561116e-01
36 37 38 39 40
5.092102e-02 -1.377385e-01 -5.448523e-02 -1.124530e-01 -1.385228e-02
41 42 43 44 45
8.264142e-02 -3.020076e-03 2.828214e-01 -2.820042e-01 -2.723358e-01
46 47 48 49 50
-8.087453e-02 -1.489616e-01 -2.529590e-01 1.066962e-01 -1.936357e-01
51 52 53 54 55
-8.562563e-02 -1.364553e-01 -6.518055e-02 -4.334437e-02 -1.829874e-01
56 57 58 59 60
-1.087786e-01 3.591935e-01 3.427506e-02 -8.289762e-02 -5.626549e-02
61 62 63 64 65
1.242972e-02 3.684371e-02 2.801630e-02 2.386849e-01 -8.770796e-02
66 67 68 69
1.677113e-01 1.052534e-01 1.034437e-02 2.974480e-01
> postscript(file="/var/www/html/rcomp/tmp/6xe6h1261069256.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 = 69
Frequency = 1
lag(myerror, k = 1) myerror
0 1.090493e-01 NA
1 -6.339116e-05 1.090493e-01
2 2.513304e-02 -6.339116e-05
3 9.302689e-02 2.513304e-02
4 -6.908611e-02 9.302689e-02
5 -2.204469e-01 -6.908611e-02
6 -3.234392e-01 -2.204469e-01
7 1.495172e-01 -3.234392e-01
8 -1.651975e-02 1.495172e-01
9 2.427105e-01 -1.651975e-02
10 2.058555e-03 2.427105e-01
11 1.373601e-01 2.058555e-03
12 -8.318537e-02 1.373601e-01
13 1.021298e-01 -8.318537e-02
14 1.423073e-01 1.021298e-01
15 -2.171060e-01 1.423073e-01
16 4.960408e-02 -2.171060e-01
17 4.580483e-03 4.960408e-02
18 -3.893381e-02 4.580483e-03
19 2.277118e-01 -3.893381e-02
20 -2.125468e-01 2.277118e-01
21 9.604407e-02 -2.125468e-01
22 7.368906e-02 9.604407e-02
23 1.209433e-01 7.368906e-02
24 -7.251320e-03 1.209433e-01
25 1.092108e-01 -7.251320e-03
26 2.622012e-03 1.092108e-01
27 3.570177e-02 2.622012e-03
28 8.972912e-02 3.570177e-02
29 9.451949e-02 8.972912e-02
30 1.572857e-01 9.451949e-02
31 3.209399e-03 1.572857e-01
32 -1.552391e-01 3.209399e-03
33 -2.921551e-01 -1.552391e-01
34 1.561116e-01 -2.921551e-01
35 5.092102e-02 1.561116e-01
36 -1.377385e-01 5.092102e-02
37 -5.448523e-02 -1.377385e-01
38 -1.124530e-01 -5.448523e-02
39 -1.385228e-02 -1.124530e-01
40 8.264142e-02 -1.385228e-02
41 -3.020076e-03 8.264142e-02
42 2.828214e-01 -3.020076e-03
43 -2.820042e-01 2.828214e-01
44 -2.723358e-01 -2.820042e-01
45 -8.087453e-02 -2.723358e-01
46 -1.489616e-01 -8.087453e-02
47 -2.529590e-01 -1.489616e-01
48 1.066962e-01 -2.529590e-01
49 -1.936357e-01 1.066962e-01
50 -8.562563e-02 -1.936357e-01
51 -1.364553e-01 -8.562563e-02
52 -6.518055e-02 -1.364553e-01
53 -4.334437e-02 -6.518055e-02
54 -1.829874e-01 -4.334437e-02
55 -1.087786e-01 -1.829874e-01
56 3.591935e-01 -1.087786e-01
57 3.427506e-02 3.591935e-01
58 -8.289762e-02 3.427506e-02
59 -5.626549e-02 -8.289762e-02
60 1.242972e-02 -5.626549e-02
61 3.684371e-02 1.242972e-02
62 2.801630e-02 3.684371e-02
63 2.386849e-01 2.801630e-02
64 -8.770796e-02 2.386849e-01
65 1.677113e-01 -8.770796e-02
66 1.052534e-01 1.677113e-01
67 1.034437e-02 1.052534e-01
68 2.974480e-01 1.034437e-02
69 NA 2.974480e-01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -6.339116e-05 1.090493e-01
[2,] 2.513304e-02 -6.339116e-05
[3,] 9.302689e-02 2.513304e-02
[4,] -6.908611e-02 9.302689e-02
[5,] -2.204469e-01 -6.908611e-02
[6,] -3.234392e-01 -2.204469e-01
[7,] 1.495172e-01 -3.234392e-01
[8,] -1.651975e-02 1.495172e-01
[9,] 2.427105e-01 -1.651975e-02
[10,] 2.058555e-03 2.427105e-01
[11,] 1.373601e-01 2.058555e-03
[12,] -8.318537e-02 1.373601e-01
[13,] 1.021298e-01 -8.318537e-02
[14,] 1.423073e-01 1.021298e-01
[15,] -2.171060e-01 1.423073e-01
[16,] 4.960408e-02 -2.171060e-01
[17,] 4.580483e-03 4.960408e-02
[18,] -3.893381e-02 4.580483e-03
[19,] 2.277118e-01 -3.893381e-02
[20,] -2.125468e-01 2.277118e-01
[21,] 9.604407e-02 -2.125468e-01
[22,] 7.368906e-02 9.604407e-02
[23,] 1.209433e-01 7.368906e-02
[24,] -7.251320e-03 1.209433e-01
[25,] 1.092108e-01 -7.251320e-03
[26,] 2.622012e-03 1.092108e-01
[27,] 3.570177e-02 2.622012e-03
[28,] 8.972912e-02 3.570177e-02
[29,] 9.451949e-02 8.972912e-02
[30,] 1.572857e-01 9.451949e-02
[31,] 3.209399e-03 1.572857e-01
[32,] -1.552391e-01 3.209399e-03
[33,] -2.921551e-01 -1.552391e-01
[34,] 1.561116e-01 -2.921551e-01
[35,] 5.092102e-02 1.561116e-01
[36,] -1.377385e-01 5.092102e-02
[37,] -5.448523e-02 -1.377385e-01
[38,] -1.124530e-01 -5.448523e-02
[39,] -1.385228e-02 -1.124530e-01
[40,] 8.264142e-02 -1.385228e-02
[41,] -3.020076e-03 8.264142e-02
[42,] 2.828214e-01 -3.020076e-03
[43,] -2.820042e-01 2.828214e-01
[44,] -2.723358e-01 -2.820042e-01
[45,] -8.087453e-02 -2.723358e-01
[46,] -1.489616e-01 -8.087453e-02
[47,] -2.529590e-01 -1.489616e-01
[48,] 1.066962e-01 -2.529590e-01
[49,] -1.936357e-01 1.066962e-01
[50,] -8.562563e-02 -1.936357e-01
[51,] -1.364553e-01 -8.562563e-02
[52,] -6.518055e-02 -1.364553e-01
[53,] -4.334437e-02 -6.518055e-02
[54,] -1.829874e-01 -4.334437e-02
[55,] -1.087786e-01 -1.829874e-01
[56,] 3.591935e-01 -1.087786e-01
[57,] 3.427506e-02 3.591935e-01
[58,] -8.289762e-02 3.427506e-02
[59,] -5.626549e-02 -8.289762e-02
[60,] 1.242972e-02 -5.626549e-02
[61,] 3.684371e-02 1.242972e-02
[62,] 2.801630e-02 3.684371e-02
[63,] 2.386849e-01 2.801630e-02
[64,] -8.770796e-02 2.386849e-01
[65,] 1.677113e-01 -8.770796e-02
[66,] 1.052534e-01 1.677113e-01
[67,] 1.034437e-02 1.052534e-01
[68,] 2.974480e-01 1.034437e-02
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -6.339116e-05 1.090493e-01
2 2.513304e-02 -6.339116e-05
3 9.302689e-02 2.513304e-02
4 -6.908611e-02 9.302689e-02
5 -2.204469e-01 -6.908611e-02
6 -3.234392e-01 -2.204469e-01
7 1.495172e-01 -3.234392e-01
8 -1.651975e-02 1.495172e-01
9 2.427105e-01 -1.651975e-02
10 2.058555e-03 2.427105e-01
11 1.373601e-01 2.058555e-03
12 -8.318537e-02 1.373601e-01
13 1.021298e-01 -8.318537e-02
14 1.423073e-01 1.021298e-01
15 -2.171060e-01 1.423073e-01
16 4.960408e-02 -2.171060e-01
17 4.580483e-03 4.960408e-02
18 -3.893381e-02 4.580483e-03
19 2.277118e-01 -3.893381e-02
20 -2.125468e-01 2.277118e-01
21 9.604407e-02 -2.125468e-01
22 7.368906e-02 9.604407e-02
23 1.209433e-01 7.368906e-02
24 -7.251320e-03 1.209433e-01
25 1.092108e-01 -7.251320e-03
26 2.622012e-03 1.092108e-01
27 3.570177e-02 2.622012e-03
28 8.972912e-02 3.570177e-02
29 9.451949e-02 8.972912e-02
30 1.572857e-01 9.451949e-02
31 3.209399e-03 1.572857e-01
32 -1.552391e-01 3.209399e-03
33 -2.921551e-01 -1.552391e-01
34 1.561116e-01 -2.921551e-01
35 5.092102e-02 1.561116e-01
36 -1.377385e-01 5.092102e-02
37 -5.448523e-02 -1.377385e-01
38 -1.124530e-01 -5.448523e-02
39 -1.385228e-02 -1.124530e-01
40 8.264142e-02 -1.385228e-02
41 -3.020076e-03 8.264142e-02
42 2.828214e-01 -3.020076e-03
43 -2.820042e-01 2.828214e-01
44 -2.723358e-01 -2.820042e-01
45 -8.087453e-02 -2.723358e-01
46 -1.489616e-01 -8.087453e-02
47 -2.529590e-01 -1.489616e-01
48 1.066962e-01 -2.529590e-01
49 -1.936357e-01 1.066962e-01
50 -8.562563e-02 -1.936357e-01
51 -1.364553e-01 -8.562563e-02
52 -6.518055e-02 -1.364553e-01
53 -4.334437e-02 -6.518055e-02
54 -1.829874e-01 -4.334437e-02
55 -1.087786e-01 -1.829874e-01
56 3.591935e-01 -1.087786e-01
57 3.427506e-02 3.591935e-01
58 -8.289762e-02 3.427506e-02
59 -5.626549e-02 -8.289762e-02
60 1.242972e-02 -5.626549e-02
61 3.684371e-02 1.242972e-02
62 2.801630e-02 3.684371e-02
63 2.386849e-01 2.801630e-02
64 -8.770796e-02 2.386849e-01
65 1.677113e-01 -8.770796e-02
66 1.052534e-01 1.677113e-01
67 1.034437e-02 1.052534e-01
68 2.974480e-01 1.034437e-02
> 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/7phk51261069256.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8zbln1261069256.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9p1p71261069256.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ftk81261069256.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/113vb71261069256.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/12zm821261069256.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/13megc1261069256.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/141qwp1261069256.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/15dsbk1261069256.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/16wmkd1261069257.tab")
+ }
>
> try(system("convert tmp/17lko1261069256.ps tmp/17lko1261069256.png",intern=TRUE))
character(0)
> try(system("convert tmp/2e8as1261069256.ps tmp/2e8as1261069256.png",intern=TRUE))
character(0)
> try(system("convert tmp/32m1c1261069256.ps tmp/32m1c1261069256.png",intern=TRUE))
character(0)
> try(system("convert tmp/4lod01261069256.ps tmp/4lod01261069256.png",intern=TRUE))
character(0)
> try(system("convert tmp/5fkbv1261069256.ps tmp/5fkbv1261069256.png",intern=TRUE))
character(0)
> try(system("convert tmp/6xe6h1261069256.ps tmp/6xe6h1261069256.png",intern=TRUE))
character(0)
> try(system("convert tmp/7phk51261069256.ps tmp/7phk51261069256.png",intern=TRUE))
character(0)
> try(system("convert tmp/8zbln1261069256.ps tmp/8zbln1261069256.png",intern=TRUE))
character(0)
> try(system("convert tmp/9p1p71261069256.ps tmp/9p1p71261069256.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ftk81261069256.ps tmp/10ftk81261069256.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.516 1.575 3.174