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(1579,0,2146,0,2462,0,3695,0,4831,0,5134,0,6250,0,5760,0,6249,0,2917,0,1741,0,2359,0,1511,1,2059,0,2635,0,2867,0,4403,0,5720,0,4502,0,5749,0,5627,0,2846,0,1762,0,2429,0,1169,0,2154,1,2249,0,2687,0,4359,0,5382,0,4459,0,6398,0,4596,0,3024,0,1887,0,2070,0,1351,0,2218,0,2461,1,3028,0,4784,0,4975,0,4607,0,6249,0,4809,0,3157,0,1910,0,2228,0,1594,0,2467,0,2222,0,3607,1,4685,0,4962,0,5770,0,5480,0,5000,0,3228,0,1993,0,2288,0,1580,0,2111,0,2192,0,3601,0,4665,1,4876,0,5813,0,5589,0,5331,0,3075,0,2002,0,2306,0,1507,0,1992,0,2487,0,3490,0,4647,0,5594,1,5611,0,5788,0,6204,0,3013,0,1931,0,2549,0,1504,0,2090,0,2702,0,2939,0,4500,0,6208,0,6415,1,5657,0,5964,0,3163,0,1997,0,2422,0,1376,0,2202,0,2683,0,3303,0,5202,0,5231,0,4880,0,7998,1,4977,0,3531,0,2025,0,2205,0,1442,0,2238,0,2179,0,3218,0,5139,0,4990,0,4914,0,6084,0,5672,1,3548,0,1793,0,2086,0),dim=c(2,120),dimnames=list(c('Y','X'),1:120))
> y <- array(NA,dim=c(2,120),dimnames=list(c('Y','X'),1:120))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = '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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 1579 0 1 0 0 0 0 0 0 0 0 0 0 1
2 2146 0 0 1 0 0 0 0 0 0 0 0 0 2
3 2462 0 0 0 1 0 0 0 0 0 0 0 0 3
4 3695 0 0 0 0 1 0 0 0 0 0 0 0 4
5 4831 0 0 0 0 0 1 0 0 0 0 0 0 5
6 5134 0 0 0 0 0 0 1 0 0 0 0 0 6
7 6250 0 0 0 0 0 0 0 1 0 0 0 0 7
8 5760 0 0 0 0 0 0 0 0 1 0 0 0 8
9 6249 0 0 0 0 0 0 0 0 0 1 0 0 9
10 2917 0 0 0 0 0 0 0 0 0 0 1 0 10
11 1741 0 0 0 0 0 0 0 0 0 0 0 1 11
12 2359 0 0 0 0 0 0 0 0 0 0 0 0 12
13 1511 1 1 0 0 0 0 0 0 0 0 0 0 13
14 2059 0 0 1 0 0 0 0 0 0 0 0 0 14
15 2635 0 0 0 1 0 0 0 0 0 0 0 0 15
16 2867 0 0 0 0 1 0 0 0 0 0 0 0 16
17 4403 0 0 0 0 0 1 0 0 0 0 0 0 17
18 5720 0 0 0 0 0 0 1 0 0 0 0 0 18
19 4502 0 0 0 0 0 0 0 1 0 0 0 0 19
20 5749 0 0 0 0 0 0 0 0 1 0 0 0 20
21 5627 0 0 0 0 0 0 0 0 0 1 0 0 21
22 2846 0 0 0 0 0 0 0 0 0 0 1 0 22
23 1762 0 0 0 0 0 0 0 0 0 0 0 1 23
24 2429 0 0 0 0 0 0 0 0 0 0 0 0 24
25 1169 0 1 0 0 0 0 0 0 0 0 0 0 25
26 2154 1 0 1 0 0 0 0 0 0 0 0 0 26
27 2249 0 0 0 1 0 0 0 0 0 0 0 0 27
28 2687 0 0 0 0 1 0 0 0 0 0 0 0 28
29 4359 0 0 0 0 0 1 0 0 0 0 0 0 29
30 5382 0 0 0 0 0 0 1 0 0 0 0 0 30
31 4459 0 0 0 0 0 0 0 1 0 0 0 0 31
32 6398 0 0 0 0 0 0 0 0 1 0 0 0 32
33 4596 0 0 0 0 0 0 0 0 0 1 0 0 33
34 3024 0 0 0 0 0 0 0 0 0 0 1 0 34
35 1887 0 0 0 0 0 0 0 0 0 0 0 1 35
36 2070 0 0 0 0 0 0 0 0 0 0 0 0 36
37 1351 0 1 0 0 0 0 0 0 0 0 0 0 37
38 2218 0 0 1 0 0 0 0 0 0 0 0 0 38
39 2461 1 0 0 1 0 0 0 0 0 0 0 0 39
40 3028 0 0 0 0 1 0 0 0 0 0 0 0 40
41 4784 0 0 0 0 0 1 0 0 0 0 0 0 41
42 4975 0 0 0 0 0 0 1 0 0 0 0 0 42
43 4607 0 0 0 0 0 0 0 1 0 0 0 0 43
44 6249 0 0 0 0 0 0 0 0 1 0 0 0 44
45 4809 0 0 0 0 0 0 0 0 0 1 0 0 45
46 3157 0 0 0 0 0 0 0 0 0 0 1 0 46
47 1910 0 0 0 0 0 0 0 0 0 0 0 1 47
48 2228 0 0 0 0 0 0 0 0 0 0 0 0 48
49 1594 0 1 0 0 0 0 0 0 0 0 0 0 49
50 2467 0 0 1 0 0 0 0 0 0 0 0 0 50
51 2222 0 0 0 1 0 0 0 0 0 0 0 0 51
52 3607 1 0 0 0 1 0 0 0 0 0 0 0 52
53 4685 0 0 0 0 0 1 0 0 0 0 0 0 53
54 4962 0 0 0 0 0 0 1 0 0 0 0 0 54
55 5770 0 0 0 0 0 0 0 1 0 0 0 0 55
56 5480 0 0 0 0 0 0 0 0 1 0 0 0 56
57 5000 0 0 0 0 0 0 0 0 0 1 0 0 57
58 3228 0 0 0 0 0 0 0 0 0 0 1 0 58
59 1993 0 0 0 0 0 0 0 0 0 0 0 1 59
60 2288 0 0 0 0 0 0 0 0 0 0 0 0 60
61 1580 0 1 0 0 0 0 0 0 0 0 0 0 61
62 2111 0 0 1 0 0 0 0 0 0 0 0 0 62
63 2192 0 0 0 1 0 0 0 0 0 0 0 0 63
64 3601 0 0 0 0 1 0 0 0 0 0 0 0 64
65 4665 1 0 0 0 0 1 0 0 0 0 0 0 65
66 4876 0 0 0 0 0 0 1 0 0 0 0 0 66
67 5813 0 0 0 0 0 0 0 1 0 0 0 0 67
68 5589 0 0 0 0 0 0 0 0 1 0 0 0 68
69 5331 0 0 0 0 0 0 0 0 0 1 0 0 69
70 3075 0 0 0 0 0 0 0 0 0 0 1 0 70
71 2002 0 0 0 0 0 0 0 0 0 0 0 1 71
72 2306 0 0 0 0 0 0 0 0 0 0 0 0 72
73 1507 0 1 0 0 0 0 0 0 0 0 0 0 73
74 1992 0 0 1 0 0 0 0 0 0 0 0 0 74
75 2487 0 0 0 1 0 0 0 0 0 0 0 0 75
76 3490 0 0 0 0 1 0 0 0 0 0 0 0 76
77 4647 0 0 0 0 0 1 0 0 0 0 0 0 77
78 5594 1 0 0 0 0 0 1 0 0 0 0 0 78
79 5611 0 0 0 0 0 0 0 1 0 0 0 0 79
80 5788 0 0 0 0 0 0 0 0 1 0 0 0 80
81 6204 0 0 0 0 0 0 0 0 0 1 0 0 81
82 3013 0 0 0 0 0 0 0 0 0 0 1 0 82
83 1931 0 0 0 0 0 0 0 0 0 0 0 1 83
84 2549 0 0 0 0 0 0 0 0 0 0 0 0 84
85 1504 0 1 0 0 0 0 0 0 0 0 0 0 85
86 2090 0 0 1 0 0 0 0 0 0 0 0 0 86
87 2702 0 0 0 1 0 0 0 0 0 0 0 0 87
88 2939 0 0 0 0 1 0 0 0 0 0 0 0 88
89 4500 0 0 0 0 0 1 0 0 0 0 0 0 89
90 6208 0 0 0 0 0 0 1 0 0 0 0 0 90
91 6415 1 0 0 0 0 0 0 1 0 0 0 0 91
92 5657 0 0 0 0 0 0 0 0 1 0 0 0 92
93 5964 0 0 0 0 0 0 0 0 0 1 0 0 93
94 3163 0 0 0 0 0 0 0 0 0 0 1 0 94
95 1997 0 0 0 0 0 0 0 0 0 0 0 1 95
96 2422 0 0 0 0 0 0 0 0 0 0 0 0 96
97 1376 0 1 0 0 0 0 0 0 0 0 0 0 97
98 2202 0 0 1 0 0 0 0 0 0 0 0 0 98
99 2683 0 0 0 1 0 0 0 0 0 0 0 0 99
100 3303 0 0 0 0 1 0 0 0 0 0 0 0 100
101 5202 0 0 0 0 0 1 0 0 0 0 0 0 101
102 5231 0 0 0 0 0 0 1 0 0 0 0 0 102
103 4880 0 0 0 0 0 0 0 1 0 0 0 0 103
104 7998 1 0 0 0 0 0 0 0 1 0 0 0 104
105 4977 0 0 0 0 0 0 0 0 0 1 0 0 105
106 3531 0 0 0 0 0 0 0 0 0 0 1 0 106
107 2025 0 0 0 0 0 0 0 0 0 0 0 1 107
108 2205 0 0 0 0 0 0 0 0 0 0 0 0 108
109 1442 0 1 0 0 0 0 0 0 0 0 0 0 109
110 2238 0 0 1 0 0 0 0 0 0 0 0 0 110
111 2179 0 0 0 1 0 0 0 0 0 0 0 0 111
112 3218 0 0 0 0 1 0 0 0 0 0 0 0 112
113 5139 0 0 0 0 0 1 0 0 0 0 0 0 113
114 4990 0 0 0 0 0 0 1 0 0 0 0 0 114
115 4914 0 0 0 0 0 0 0 1 0 0 0 0 115
116 6084 0 0 0 0 0 0 0 0 1 0 0 0 116
117 5672 1 0 0 0 0 0 0 0 0 1 0 0 117
118 3548 0 0 0 0 0 0 0 0 0 0 1 0 118
119 1793 0 0 0 0 0 0 0 0 0 0 0 1 119
120 2086 0 0 0 0 0 0 0 0 0 0 0 0 120
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
2187.301 471.721 -862.256 -157.475 100.405 915.085
M5 M6 M7 M8 M9 M10
2391.466 2975.546 2988.826 3740.307 3106.387 859.239
M11 t
-388.480 1.620
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-767.34 -213.98 -34.88 175.32 1430.22
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2187.301 138.566 15.785 < 2e-16 ***
X 471.721 134.877 3.497 0.000688 ***
M1 -862.256 172.390 -5.002 2.26e-06 ***
M2 -157.475 172.323 -0.914 0.362877
M3 100.405 172.262 0.583 0.561225
M4 915.085 172.207 5.314 5.98e-07 ***
M5 2391.466 172.158 13.891 < 2e-16 ***
M6 2975.546 172.115 17.288 < 2e-16 ***
M7 2988.826 172.078 17.369 < 2e-16 ***
M8 3740.307 172.047 21.740 < 2e-16 ***
M9 3106.387 172.022 18.058 < 2e-16 ***
M10 859.239 171.466 5.011 2.18e-06 ***
M11 -388.480 171.457 -2.266 0.025498 *
t 1.620 1.017 1.593 0.114112
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 383.4 on 106 degrees of freedom
Multiple R-squared: 0.9503, Adjusted R-squared: 0.9442
F-statistic: 155.9 on 13 and 106 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,] 0.4430246 0.886049153 0.556975424
[2,] 0.6489999 0.702000298 0.351000149
[3,] 0.9700142 0.059971587 0.029985794
[4,] 0.9525852 0.094829662 0.047414831
[5,] 0.9331170 0.133765978 0.066882989
[6,] 0.9025211 0.194957743 0.097478871
[7,] 0.8685980 0.262803991 0.131401996
[8,] 0.8372525 0.325494975 0.162747488
[9,] 0.7778063 0.444387459 0.222193730
[10,] 0.7299192 0.540161681 0.270080840
[11,] 0.6555706 0.688858808 0.344429404
[12,] 0.6031227 0.793754517 0.396877258
[13,] 0.5293024 0.941395154 0.470697577
[14,] 0.4896208 0.979241526 0.510379237
[15,] 0.5556421 0.888715887 0.444357944
[16,] 0.7529634 0.494073268 0.247036634
[17,] 0.8810162 0.237967508 0.118983754
[18,] 0.8725819 0.254836235 0.127418117
[19,] 0.8587881 0.282423800 0.141211900
[20,] 0.8173269 0.365346171 0.182673085
[21,] 0.7937867 0.412426578 0.206213289
[22,] 0.7830900 0.433819996 0.216909998
[23,] 0.7584545 0.483090932 0.241545466
[24,] 0.7153910 0.569218051 0.284609026
[25,] 0.7105549 0.578890287 0.289445144
[26,] 0.6619424 0.676115277 0.338057639
[27,] 0.6756364 0.648727288 0.324363644
[28,] 0.6835403 0.632919400 0.316459700
[29,] 0.6944498 0.611100379 0.305550189
[30,] 0.6775314 0.644937150 0.322468575
[31,] 0.6401266 0.719746756 0.359873378
[32,] 0.5851095 0.829781069 0.414890534
[33,] 0.5684748 0.863050407 0.431525203
[34,] 0.5842718 0.831456349 0.415728174
[35,] 0.5277215 0.944556903 0.472278451
[36,] 0.5439740 0.912051945 0.456025973
[37,] 0.4938233 0.987646641 0.506176679
[38,] 0.4481248 0.896249561 0.551875220
[39,] 0.5657745 0.868451062 0.434225531
[40,] 0.5817728 0.836454454 0.418227227
[41,] 0.5598882 0.880223523 0.440111761
[42,] 0.5208872 0.958225526 0.479112763
[43,] 0.4735649 0.947129874 0.526435063
[44,] 0.4166517 0.833303366 0.583348317
[45,] 0.3741026 0.748205241 0.625897379
[46,] 0.3193449 0.638689799 0.680655100
[47,] 0.2800552 0.560110405 0.719944797
[48,] 0.2870117 0.574023333 0.712988333
[49,] 0.3749946 0.749989180 0.625005410
[50,] 0.3608570 0.721714089 0.639142956
[51,] 0.4375488 0.875097667 0.562451166
[52,] 0.4536674 0.907334896 0.546332552
[53,] 0.4046509 0.809301897 0.595349052
[54,] 0.3653599 0.730719886 0.634640057
[55,] 0.3143176 0.628635261 0.685682369
[56,] 0.2643447 0.528689316 0.735655342
[57,] 0.2179283 0.435856645 0.782071677
[58,] 0.1853379 0.370675792 0.814662104
[59,] 0.1512382 0.302476440 0.848761780
[60,] 0.1294742 0.258948435 0.870525782
[61,] 0.1124702 0.224940381 0.887529810
[62,] 0.2116069 0.423213833 0.788393084
[63,] 0.2087915 0.417583056 0.791208472
[64,] 0.2152460 0.430491997 0.784754002
[65,] 0.4226030 0.845205902 0.577397049
[66,] 0.4368593 0.873718600 0.563140700
[67,] 0.3811553 0.762310596 0.618844702
[68,] 0.3263957 0.652791474 0.673604263
[69,] 0.2667710 0.533542065 0.733228968
[70,] 0.2272814 0.454562882 0.772718559
[71,] 0.1853599 0.370719714 0.814640143
[72,] 0.1869523 0.373904605 0.813047698
[73,] 0.3016789 0.603357873 0.698321063
[74,] 0.5336512 0.932697691 0.466348846
[75,] 0.5140028 0.971994319 0.485997159
[76,] 0.8174063 0.365187409 0.182593704
[77,] 0.9847695 0.030460951 0.015230476
[78,] 0.9966254 0.006749238 0.003374619
[79,] 0.9942922 0.011415629 0.005707814
[80,] 0.9876674 0.024665294 0.012332647
[81,] 0.9827501 0.034499710 0.017249855
[82,] 0.9752652 0.049469599 0.024734800
[83,] 0.9661598 0.067680455 0.033840228
[84,] 0.9354732 0.129053512 0.064526756
[85,] 0.8922769 0.215446236 0.107723118
[86,] 0.7950499 0.409900117 0.204950059
[87,] 0.7386031 0.522793753 0.261396876
> postscript(file="/var/www/html/freestat/rcomp/tmp/19lii1290867543.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/29lii1290867543.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/39lii1290867543.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4jvz31290867543.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5jvz31290867543.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 120
Frequency = 1
1 2 3 4 5 6
252.334599 112.934599 169.434599 586.134599 244.134599 -38.565401
7 8 9 10 11 12
1062.534599 -180.565401 940.734599 -145.737468 -75.637468 152.262532
13 14 15 16 17 18
-306.822194 6.498481 322.998481 -261.301519 -203.301519 527.998481
19 20 21 22 23 24
-704.901519 -211.001519 299.298481 -236.173586 -74.073586 202.826414
25 26 27 28 29 30
-196.537637 -389.658312 -82.437637 -460.737637 -266.737637 170.562363
31 32 33 34 35 36
-767.337637 418.562363 -751.137637 -77.609705 31.490295 -175.609705
37 38 39 40 41 42
-33.973755 126.626245 -361.594430 -139.173755 138.826245 -255.873755
43 44 45 46 47 48
-638.773755 250.126245 -557.573755 35.954177 35.054177 -37.045823
49 50 51 52 53 54
189.590127 356.190127 -148.309873 -51.330549 20.390127 -288.309873
55 56 57 58 59 60
504.790127 -538.309873 -386.009873 87.518059 98.618059 3.518059
61 62 63 64 65 66
156.154008 -19.245992 -197.745992 394.954008 -490.766667 -393.745992
67 68 69 70 71 72
528.354008 -448.745992 -74.445992 -84.918059 88.181941 2.081941
73 74 75 76 77 78
63.717890 -157.682110 77.817890 264.517890 -56.482110 -166.902785
79 80 81 82 83 84
306.917890 -269.182110 779.117890 -166.354177 -2.254177 225.645823
85 86 87 88 89 90
41.281772 -79.118228 273.381772 -305.918228 -222.918228 899.381772
91 92 93 94 95 96
619.761097 -419.618228 519.681772 -35.790295 44.309705 79.209705
97 98 99 100 101 102
-106.154346 13.445654 234.945654 38.645654 459.645654 -97.054346
103 104 105 106 107 108
-462.954346 1430.224979 -486.754346 312.773586 52.873586 -157.226414
109 110 111 112 113 114
-59.590464 30.009536 -288.490464 -65.790464 377.209536 -357.490464
115 116 117 118 119 120
-448.390464 -31.490464 -282.911139 310.337468 -198.562532 -295.662532
> postscript(file="/var/www/html/freestat/rcomp/tmp/6c4y51290867543.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 120
Frequency = 1
lag(myerror, k = 1) myerror
0 252.334599 NA
1 112.934599 252.334599
2 169.434599 112.934599
3 586.134599 169.434599
4 244.134599 586.134599
5 -38.565401 244.134599
6 1062.534599 -38.565401
7 -180.565401 1062.534599
8 940.734599 -180.565401
9 -145.737468 940.734599
10 -75.637468 -145.737468
11 152.262532 -75.637468
12 -306.822194 152.262532
13 6.498481 -306.822194
14 322.998481 6.498481
15 -261.301519 322.998481
16 -203.301519 -261.301519
17 527.998481 -203.301519
18 -704.901519 527.998481
19 -211.001519 -704.901519
20 299.298481 -211.001519
21 -236.173586 299.298481
22 -74.073586 -236.173586
23 202.826414 -74.073586
24 -196.537637 202.826414
25 -389.658312 -196.537637
26 -82.437637 -389.658312
27 -460.737637 -82.437637
28 -266.737637 -460.737637
29 170.562363 -266.737637
30 -767.337637 170.562363
31 418.562363 -767.337637
32 -751.137637 418.562363
33 -77.609705 -751.137637
34 31.490295 -77.609705
35 -175.609705 31.490295
36 -33.973755 -175.609705
37 126.626245 -33.973755
38 -361.594430 126.626245
39 -139.173755 -361.594430
40 138.826245 -139.173755
41 -255.873755 138.826245
42 -638.773755 -255.873755
43 250.126245 -638.773755
44 -557.573755 250.126245
45 35.954177 -557.573755
46 35.054177 35.954177
47 -37.045823 35.054177
48 189.590127 -37.045823
49 356.190127 189.590127
50 -148.309873 356.190127
51 -51.330549 -148.309873
52 20.390127 -51.330549
53 -288.309873 20.390127
54 504.790127 -288.309873
55 -538.309873 504.790127
56 -386.009873 -538.309873
57 87.518059 -386.009873
58 98.618059 87.518059
59 3.518059 98.618059
60 156.154008 3.518059
61 -19.245992 156.154008
62 -197.745992 -19.245992
63 394.954008 -197.745992
64 -490.766667 394.954008
65 -393.745992 -490.766667
66 528.354008 -393.745992
67 -448.745992 528.354008
68 -74.445992 -448.745992
69 -84.918059 -74.445992
70 88.181941 -84.918059
71 2.081941 88.181941
72 63.717890 2.081941
73 -157.682110 63.717890
74 77.817890 -157.682110
75 264.517890 77.817890
76 -56.482110 264.517890
77 -166.902785 -56.482110
78 306.917890 -166.902785
79 -269.182110 306.917890
80 779.117890 -269.182110
81 -166.354177 779.117890
82 -2.254177 -166.354177
83 225.645823 -2.254177
84 41.281772 225.645823
85 -79.118228 41.281772
86 273.381772 -79.118228
87 -305.918228 273.381772
88 -222.918228 -305.918228
89 899.381772 -222.918228
90 619.761097 899.381772
91 -419.618228 619.761097
92 519.681772 -419.618228
93 -35.790295 519.681772
94 44.309705 -35.790295
95 79.209705 44.309705
96 -106.154346 79.209705
97 13.445654 -106.154346
98 234.945654 13.445654
99 38.645654 234.945654
100 459.645654 38.645654
101 -97.054346 459.645654
102 -462.954346 -97.054346
103 1430.224979 -462.954346
104 -486.754346 1430.224979
105 312.773586 -486.754346
106 52.873586 312.773586
107 -157.226414 52.873586
108 -59.590464 -157.226414
109 30.009536 -59.590464
110 -288.490464 30.009536
111 -65.790464 -288.490464
112 377.209536 -65.790464
113 -357.490464 377.209536
114 -448.390464 -357.490464
115 -31.490464 -448.390464
116 -282.911139 -31.490464
117 310.337468 -282.911139
118 -198.562532 310.337468
119 -295.662532 -198.562532
120 NA -295.662532
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 112.934599 252.334599
[2,] 169.434599 112.934599
[3,] 586.134599 169.434599
[4,] 244.134599 586.134599
[5,] -38.565401 244.134599
[6,] 1062.534599 -38.565401
[7,] -180.565401 1062.534599
[8,] 940.734599 -180.565401
[9,] -145.737468 940.734599
[10,] -75.637468 -145.737468
[11,] 152.262532 -75.637468
[12,] -306.822194 152.262532
[13,] 6.498481 -306.822194
[14,] 322.998481 6.498481
[15,] -261.301519 322.998481
[16,] -203.301519 -261.301519
[17,] 527.998481 -203.301519
[18,] -704.901519 527.998481
[19,] -211.001519 -704.901519
[20,] 299.298481 -211.001519
[21,] -236.173586 299.298481
[22,] -74.073586 -236.173586
[23,] 202.826414 -74.073586
[24,] -196.537637 202.826414
[25,] -389.658312 -196.537637
[26,] -82.437637 -389.658312
[27,] -460.737637 -82.437637
[28,] -266.737637 -460.737637
[29,] 170.562363 -266.737637
[30,] -767.337637 170.562363
[31,] 418.562363 -767.337637
[32,] -751.137637 418.562363
[33,] -77.609705 -751.137637
[34,] 31.490295 -77.609705
[35,] -175.609705 31.490295
[36,] -33.973755 -175.609705
[37,] 126.626245 -33.973755
[38,] -361.594430 126.626245
[39,] -139.173755 -361.594430
[40,] 138.826245 -139.173755
[41,] -255.873755 138.826245
[42,] -638.773755 -255.873755
[43,] 250.126245 -638.773755
[44,] -557.573755 250.126245
[45,] 35.954177 -557.573755
[46,] 35.054177 35.954177
[47,] -37.045823 35.054177
[48,] 189.590127 -37.045823
[49,] 356.190127 189.590127
[50,] -148.309873 356.190127
[51,] -51.330549 -148.309873
[52,] 20.390127 -51.330549
[53,] -288.309873 20.390127
[54,] 504.790127 -288.309873
[55,] -538.309873 504.790127
[56,] -386.009873 -538.309873
[57,] 87.518059 -386.009873
[58,] 98.618059 87.518059
[59,] 3.518059 98.618059
[60,] 156.154008 3.518059
[61,] -19.245992 156.154008
[62,] -197.745992 -19.245992
[63,] 394.954008 -197.745992
[64,] -490.766667 394.954008
[65,] -393.745992 -490.766667
[66,] 528.354008 -393.745992
[67,] -448.745992 528.354008
[68,] -74.445992 -448.745992
[69,] -84.918059 -74.445992
[70,] 88.181941 -84.918059
[71,] 2.081941 88.181941
[72,] 63.717890 2.081941
[73,] -157.682110 63.717890
[74,] 77.817890 -157.682110
[75,] 264.517890 77.817890
[76,] -56.482110 264.517890
[77,] -166.902785 -56.482110
[78,] 306.917890 -166.902785
[79,] -269.182110 306.917890
[80,] 779.117890 -269.182110
[81,] -166.354177 779.117890
[82,] -2.254177 -166.354177
[83,] 225.645823 -2.254177
[84,] 41.281772 225.645823
[85,] -79.118228 41.281772
[86,] 273.381772 -79.118228
[87,] -305.918228 273.381772
[88,] -222.918228 -305.918228
[89,] 899.381772 -222.918228
[90,] 619.761097 899.381772
[91,] -419.618228 619.761097
[92,] 519.681772 -419.618228
[93,] -35.790295 519.681772
[94,] 44.309705 -35.790295
[95,] 79.209705 44.309705
[96,] -106.154346 79.209705
[97,] 13.445654 -106.154346
[98,] 234.945654 13.445654
[99,] 38.645654 234.945654
[100,] 459.645654 38.645654
[101,] -97.054346 459.645654
[102,] -462.954346 -97.054346
[103,] 1430.224979 -462.954346
[104,] -486.754346 1430.224979
[105,] 312.773586 -486.754346
[106,] 52.873586 312.773586
[107,] -157.226414 52.873586
[108,] -59.590464 -157.226414
[109,] 30.009536 -59.590464
[110,] -288.490464 30.009536
[111,] -65.790464 -288.490464
[112,] 377.209536 -65.790464
[113,] -357.490464 377.209536
[114,] -448.390464 -357.490464
[115,] -31.490464 -448.390464
[116,] -282.911139 -31.490464
[117,] 310.337468 -282.911139
[118,] -198.562532 310.337468
[119,] -295.662532 -198.562532
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 112.934599 252.334599
2 169.434599 112.934599
3 586.134599 169.434599
4 244.134599 586.134599
5 -38.565401 244.134599
6 1062.534599 -38.565401
7 -180.565401 1062.534599
8 940.734599 -180.565401
9 -145.737468 940.734599
10 -75.637468 -145.737468
11 152.262532 -75.637468
12 -306.822194 152.262532
13 6.498481 -306.822194
14 322.998481 6.498481
15 -261.301519 322.998481
16 -203.301519 -261.301519
17 527.998481 -203.301519
18 -704.901519 527.998481
19 -211.001519 -704.901519
20 299.298481 -211.001519
21 -236.173586 299.298481
22 -74.073586 -236.173586
23 202.826414 -74.073586
24 -196.537637 202.826414
25 -389.658312 -196.537637
26 -82.437637 -389.658312
27 -460.737637 -82.437637
28 -266.737637 -460.737637
29 170.562363 -266.737637
30 -767.337637 170.562363
31 418.562363 -767.337637
32 -751.137637 418.562363
33 -77.609705 -751.137637
34 31.490295 -77.609705
35 -175.609705 31.490295
36 -33.973755 -175.609705
37 126.626245 -33.973755
38 -361.594430 126.626245
39 -139.173755 -361.594430
40 138.826245 -139.173755
41 -255.873755 138.826245
42 -638.773755 -255.873755
43 250.126245 -638.773755
44 -557.573755 250.126245
45 35.954177 -557.573755
46 35.054177 35.954177
47 -37.045823 35.054177
48 189.590127 -37.045823
49 356.190127 189.590127
50 -148.309873 356.190127
51 -51.330549 -148.309873
52 20.390127 -51.330549
53 -288.309873 20.390127
54 504.790127 -288.309873
55 -538.309873 504.790127
56 -386.009873 -538.309873
57 87.518059 -386.009873
58 98.618059 87.518059
59 3.518059 98.618059
60 156.154008 3.518059
61 -19.245992 156.154008
62 -197.745992 -19.245992
63 394.954008 -197.745992
64 -490.766667 394.954008
65 -393.745992 -490.766667
66 528.354008 -393.745992
67 -448.745992 528.354008
68 -74.445992 -448.745992
69 -84.918059 -74.445992
70 88.181941 -84.918059
71 2.081941 88.181941
72 63.717890 2.081941
73 -157.682110 63.717890
74 77.817890 -157.682110
75 264.517890 77.817890
76 -56.482110 264.517890
77 -166.902785 -56.482110
78 306.917890 -166.902785
79 -269.182110 306.917890
80 779.117890 -269.182110
81 -166.354177 779.117890
82 -2.254177 -166.354177
83 225.645823 -2.254177
84 41.281772 225.645823
85 -79.118228 41.281772
86 273.381772 -79.118228
87 -305.918228 273.381772
88 -222.918228 -305.918228
89 899.381772 -222.918228
90 619.761097 899.381772
91 -419.618228 619.761097
92 519.681772 -419.618228
93 -35.790295 519.681772
94 44.309705 -35.790295
95 79.209705 44.309705
96 -106.154346 79.209705
97 13.445654 -106.154346
98 234.945654 13.445654
99 38.645654 234.945654
100 459.645654 38.645654
101 -97.054346 459.645654
102 -462.954346 -97.054346
103 1430.224979 -462.954346
104 -486.754346 1430.224979
105 312.773586 -486.754346
106 52.873586 312.773586
107 -157.226414 52.873586
108 -59.590464 -157.226414
109 30.009536 -59.590464
110 -288.490464 30.009536
111 -65.790464 -288.490464
112 377.209536 -65.790464
113 -357.490464 377.209536
114 -448.390464 -357.490464
115 -31.490464 -448.390464
116 -282.911139 -31.490464
117 310.337468 -282.911139
118 -198.562532 310.337468
119 -295.662532 -198.562532
> 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/7c4y51290867543.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/85dfq1290867543.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/95dfq1290867543.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10xmxt1290867543.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1115vz1290867543.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/12m5un1290867543.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/13if9w1290867543.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/14myqk1290867543.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/15pgo81290867543.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/16bz5v1290867543.tab")
+ }
>
> try(system("convert tmp/19lii1290867543.ps tmp/19lii1290867543.png",intern=TRUE))
character(0)
> try(system("convert tmp/29lii1290867543.ps tmp/29lii1290867543.png",intern=TRUE))
character(0)
> try(system("convert tmp/39lii1290867543.ps tmp/39lii1290867543.png",intern=TRUE))
character(0)
> try(system("convert tmp/4jvz31290867543.ps tmp/4jvz31290867543.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jvz31290867543.ps tmp/5jvz31290867543.png",intern=TRUE))
character(0)
> try(system("convert tmp/6c4y51290867543.ps tmp/6c4y51290867543.png",intern=TRUE))
character(0)
> try(system("convert tmp/7c4y51290867543.ps tmp/7c4y51290867543.png",intern=TRUE))
character(0)
> try(system("convert tmp/85dfq1290867543.ps tmp/85dfq1290867543.png",intern=TRUE))
character(0)
> try(system("convert tmp/95dfq1290867543.ps tmp/95dfq1290867543.png",intern=TRUE))
character(0)
> try(system("convert tmp/10xmxt1290867543.ps tmp/10xmxt1290867543.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.022 2.711 5.534