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(1280
+ ,1024
+ ,1024
+ ,768
+ ,1120
+ ,700
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1688
+ ,949
+ ,1440
+ ,900
+ ,1600
+ ,1200
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,768
+ ,1176
+ ,735
+ ,1280
+ ,800
+ ,1503
+ ,845
+ ,1440
+ ,900
+ ,1366
+ ,768
+ ,1280
+ ,768
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,2560
+ ,1440
+ ,1280
+ ,768
+ ,1024
+ ,768
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1024
+ ,768
+ ,1440
+ ,900
+ ,1143
+ ,857
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1366
+ ,768
+ ,1024
+ ,768
+ ,1408
+ ,880
+ ,1366
+ ,768
+ ,1176
+ ,735
+ ,1920
+ ,1200
+ ,1257
+ ,785
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1680
+ ,1050
+ ,1440
+ ,900
+ ,1024
+ ,768
+ ,1140
+ ,641
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1152
+ ,864
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1600
+ ,900
+ ,1024
+ ,768
+ ,1366
+ ,768
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1366
+ ,768
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1408
+ ,880
+ ,1280
+ ,800
+ ,1600
+ ,900
+ ,1600
+ ,900
+ ,1680
+ ,1050
+ ,1440
+ ,900
+ ,1440
+ ,900
+ ,917
+ ,550
+ ,1280
+ ,800
+ ,1760
+ ,990
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1366
+ ,768
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1920
+ ,1080
+ ,1024
+ ,768
+ ,1024
+ ,768
+ ,1600
+ ,900
+ ,1117
+ ,698
+ ,1440
+ ,900
+ ,983
+ ,737
+ ,1024
+ ,768
+ ,1024
+ ,640
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1024
+ ,768
+ ,1152
+ ,864
+ ,1280
+ ,768
+ ,1024
+ ,768
+ ,1366
+ ,768
+ ,1680
+ ,1050
+ ,1680
+ ,1050
+ ,1280
+ ,800
+ ,1366
+ ,768
+ ,1024
+ ,768
+ ,1440
+ ,900
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1280
+ ,800)
+ ,dim=c(2
+ ,139)
+ ,dimnames=list(c('br'
+ ,'gr')
+ ,1:139))
> y <- array(NA,dim=c(2,139),dimnames=list(c('br','gr'),1:139))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '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
br gr
1 1280 1024
2 1024 768
3 1120 700
4 1024 768
5 1280 800
6 1280 1024
7 1280 800
8 1024 768
9 1280 800
10 1280 1024
11 1280 800
12 1280 800
13 1280 1024
14 1688 949
15 1440 900
16 1600 1200
17 1280 800
18 1280 800
19 1280 768
20 1176 735
21 1280 800
22 1503 845
23 1440 900
24 1366 768
25 1280 768
26 1024 768
27 1280 800
28 2560 1440
29 1280 768
30 1024 768
31 1280 1024
32 1280 800
33 1440 900
34 1280 800
35 1440 900
36 1024 768
37 1440 900
38 1143 857
39 1280 800
40 1440 900
41 1280 800
42 1366 768
43 1024 768
44 1408 880
45 1366 768
46 1176 735
47 1920 1200
48 1257 785
49 1280 800
50 1280 800
51 1440 900
52 1680 1050
53 1440 900
54 1024 768
55 1140 641
56 1280 1024
57 1280 800
58 1280 800
59 1280 800
60 1280 800
61 1440 900
62 1280 800
63 1152 864
64 1280 1024
65 1280 800
66 1440 900
67 1280 800
68 1280 1024
69 1440 900
70 1280 800
71 1280 800
72 1440 900
73 1280 800
74 1280 1024
75 1600 900
76 1024 768
77 1366 768
78 1280 800
79 1280 800
80 1440 900
81 1366 768
82 1280 800
83 1024 768
84 1280 800
85 1440 900
86 1280 800
87 1280 800
88 1408 880
89 1280 800
90 1600 900
91 1600 900
92 1680 1050
93 1440 900
94 1440 900
95 917 550
96 1280 800
97 1760 990
98 1280 800
99 1280 800
100 1280 800
101 1024 768
102 1366 768
103 1440 900
104 1280 800
105 1280 1024
106 1920 1080
107 1024 768
108 1024 768
109 1600 900
110 1117 698
111 1440 900
112 983 737
113 1024 768
114 1024 640
115 1280 800
116 1440 900
117 1280 800
118 1280 800
119 1280 800
120 1440 900
121 1280 800
122 1024 768
123 1024 768
124 1152 864
125 1280 768
126 1024 768
127 1366 768
128 1680 1050
129 1680 1050
130 1280 800
131 1366 768
132 1024 768
133 1440 900
134 1024 768
135 1280 800
136 1280 800
137 1280 800
138 1024 768
139 1280 800
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) gr
94.974 1.438
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-287.22 -81.36 34.83 51.06 394.68
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 94.9736 87.4092 1.087 0.279
gr 1.4377 0.1026 14.016 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 137.6 on 137 degrees of freedom
Multiple R-squared: 0.5891, Adjusted R-squared: 0.5861
F-statistic: 196.5 on 1 and 137 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,] 0.4557547 9.115094e-01 5.442453e-01
[2,] 0.3029019 6.058038e-01 6.970981e-01
[3,] 0.3216282 6.432563e-01 6.783718e-01
[4,] 0.2964047 5.928095e-01 7.035953e-01
[5,] 0.3017735 6.035470e-01 6.982265e-01
[6,] 0.2291586 4.583172e-01 7.708414e-01
[7,] 0.2203740 4.407480e-01 7.796260e-01
[8,] 0.1991244 3.982488e-01 8.008756e-01
[9,] 0.1577499 3.154998e-01 8.422501e-01
[10,] 0.7983901 4.032197e-01 2.016099e-01
[11,] 0.8070886 3.858227e-01 1.929114e-01
[12,] 0.7906977 4.186046e-01 2.093023e-01
[13,] 0.7454619 5.090762e-01 2.545381e-01
[14,] 0.6947468 6.105064e-01 3.052532e-01
[15,] 0.6540091 6.919818e-01 3.459909e-01
[16,] 0.5852152 8.295695e-01 4.147848e-01
[17,] 0.5252869 9.494262e-01 4.747131e-01
[18,] 0.6542358 6.915284e-01 3.457642e-01
[19,] 0.6344298 7.311403e-01 3.655702e-01
[20,] 0.6470510 7.058980e-01 3.529490e-01
[21,] 0.5966867 8.066266e-01 4.033133e-01
[22,] 0.6634263 6.731473e-01 3.365737e-01
[23,] 0.6080693 7.838613e-01 3.919307e-01
[24,] 0.9863930 2.721404e-02 1.360702e-02
[25,] 0.9828154 3.436929e-02 1.718464e-02
[26,] 0.9842470 3.150598e-02 1.575299e-02
[27,] 0.9937375 1.252495e-02 6.262475e-03
[28,] 0.9911647 1.767067e-02 8.835337e-03
[29,] 0.9881320 2.373597e-02 1.186799e-02
[30,] 0.9837010 3.259803e-02 1.629901e-02
[31,] 0.9785974 4.280527e-02 2.140263e-02
[32,] 0.9805869 3.882616e-02 1.941308e-02
[33,] 0.9748409 5.031816e-02 2.515908e-02
[34,] 0.9781546 4.369077e-02 2.184538e-02
[35,] 0.9712113 5.757735e-02 2.878868e-02
[36,] 0.9634808 7.303831e-02 3.651915e-02
[37,] 0.9529693 9.406134e-02 4.703067e-02
[38,] 0.9589187 8.216252e-02 4.108126e-02
[39,] 0.9632260 7.354809e-02 3.677405e-02
[40,] 0.9536085 9.278303e-02 4.639152e-02
[41,] 0.9592348 8.153038e-02 4.076519e-02
[42,] 0.9472460 1.055080e-01 5.275398e-02
[43,] 0.9409790 1.180420e-01 5.902100e-02
[44,] 0.9257486 1.485029e-01 7.425145e-02
[45,] 0.9078170 1.843661e-01 9.218304e-02
[46,] 0.8868885 2.262230e-01 1.131115e-01
[47,] 0.8648432 2.703137e-01 1.351568e-01
[48,] 0.8447342 3.105315e-01 1.552658e-01
[49,] 0.8175778 3.648445e-01 1.824222e-01
[50,] 0.8341112 3.317777e-01 1.658888e-01
[51,] 0.8281619 3.436763e-01 1.718381e-01
[52,] 0.9112456 1.775088e-01 8.875440e-02
[53,] 0.8912879 2.174242e-01 1.087121e-01
[54,] 0.8683008 2.633984e-01 1.316992e-01
[55,] 0.8421739 3.156523e-01 1.578261e-01
[56,] 0.8128695 3.742609e-01 1.871305e-01
[57,] 0.7829360 4.341280e-01 2.170640e-01
[58,] 0.7477031 5.045938e-01 2.522969e-01
[59,] 0.7774954 4.450092e-01 2.225046e-01
[60,] 0.8863036 2.273928e-01 1.136964e-01
[61,] 0.8628055 2.743890e-01 1.371945e-01
[62,] 0.8380973 3.238054e-01 1.619027e-01
[63,] 0.8085009 3.829983e-01 1.914991e-01
[64,] 0.9164121 1.671758e-01 8.358789e-02
[65,] 0.8986737 2.026525e-01 1.013263e-01
[66,] 0.8768692 2.462617e-01 1.231308e-01
[67,] 0.8519474 2.961052e-01 1.480526e-01
[68,] 0.8255060 3.489880e-01 1.744940e-01
[69,] 0.7943368 4.113264e-01 2.056632e-01
[70,] 0.9253010 1.493979e-01 7.469896e-02
[71,] 0.9427944 1.144112e-01 5.720559e-02
[72,] 0.9516867 9.662665e-02 4.831333e-02
[73,] 0.9597911 8.041777e-02 4.020889e-02
[74,] 0.9486184 1.027632e-01 5.138160e-02
[75,] 0.9350854 1.298292e-01 6.491462e-02
[76,] 0.9194097 1.611806e-01 8.059031e-02
[77,] 0.9324723 1.350553e-01 6.752766e-02
[78,] 0.9158201 1.683598e-01 8.417989e-02
[79,] 0.9274635 1.450729e-01 7.253645e-02
[80,] 0.9096751 1.806498e-01 9.032491e-02
[81,] 0.8891414 2.217171e-01 1.108586e-01
[82,] 0.8649681 2.700638e-01 1.350319e-01
[83,] 0.8373541 3.252917e-01 1.626459e-01
[84,] 0.8062267 3.875467e-01 1.937733e-01
[85,] 0.7716026 4.567949e-01 2.283974e-01
[86,] 0.8103842 3.792316e-01 1.896158e-01
[87,] 0.8464621 3.070758e-01 1.535379e-01
[88,] 0.8193651 3.612698e-01 1.806349e-01
[89,] 0.7852102 4.295797e-01 2.147898e-01
[90,] 0.7473816 5.052368e-01 2.526184e-01
[91,] 0.7420761 5.158479e-01 2.579239e-01
[92,] 0.7020790 5.958419e-01 2.979210e-01
[93,] 0.7569671 4.860658e-01 2.430329e-01
[94,] 0.7181309 5.637382e-01 2.818691e-01
[95,] 0.6765437 6.469125e-01 3.234563e-01
[96,] 0.6326527 7.346945e-01 3.673473e-01
[97,] 0.6487613 7.024774e-01 3.512387e-01
[98,] 0.6993522 6.012955e-01 3.006478e-01
[99,] 0.6525449 6.949103e-01 3.474551e-01
[100,] 0.6072453 7.855095e-01 3.927547e-01
[101,] 0.8907818 2.184365e-01 1.092182e-01
[102,] 0.9103769 1.792462e-01 8.962310e-02
[103,] 0.9180747 1.638507e-01 8.192535e-02
[104,] 0.9269586 1.460827e-01 7.304137e-02
[105,] 0.9501573 9.968535e-02 4.984268e-02
[106,] 0.9386057 1.227886e-01 6.139431e-02
[107,] 0.9179885 1.640231e-01 8.201155e-02
[108,] 0.9210765 1.578471e-01 7.892355e-02
[109,] 0.9322063 1.355874e-01 6.779369e-02
[110,] 0.9172014 1.655972e-01 8.279859e-02
[111,] 0.8924507 2.150985e-01 1.075493e-01
[112,] 0.8584041 2.831917e-01 1.415959e-01
[113,] 0.8223557 3.552887e-01 1.776443e-01
[114,] 0.7810157 4.379686e-01 2.189843e-01
[115,] 0.7347335 5.305330e-01 2.652665e-01
[116,] 0.6749479 6.501042e-01 3.250521e-01
[117,] 0.6194089 7.611822e-01 3.805911e-01
[118,] 0.6231858 7.536285e-01 3.768142e-01
[119,] 0.6384881 7.230239e-01 3.615119e-01
[120,] 0.7297615 5.404770e-01 2.702385e-01
[121,] 0.6974422 6.051157e-01 3.025578e-01
[122,] 0.7360958 5.278084e-01 2.639042e-01
[123,] 0.8180103 3.639794e-01 1.819897e-01
[124,] 0.7459597 5.080805e-01 2.540403e-01
[125,] 0.6943094 6.113811e-01 3.056906e-01
[126,] 0.6011058 7.977883e-01 3.988942e-01
[127,] 0.8676800 2.646401e-01 1.323200e-01
[128,] 0.8366493 3.267014e-01 1.633507e-01
[129,] 1.0000000 2.026662e-59 1.013331e-59
[130,] 1.0000000 8.674904e-42 4.337452e-42
> postscript(file="/var/www/html/rcomp/tmp/1daka1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2daka1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/36kjv1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/46kjv1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56kjv1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 139
Frequency = 1
1 2 3 4 5 6
-287.220415 -175.158722 18.607665 -175.158722 34.833567 -287.220415
7 8 9 10 11 12
34.833567 -175.158722 34.833567 -287.220415 34.833567 34.833567
13 14 15 16 17 18
-287.220415 228.610159 51.059468 -220.262828 34.833567 34.833567
19 20 21 22 23 24
80.841278 24.286731 34.833567 193.135222 51.059468 166.841278
25 26 27 28 29 30
80.841278 -175.158722 34.833567 394.679335 80.841278 -175.158722
31 32 33 34 35 36
-287.220415 34.833567 51.059468 34.833567 51.059468 -175.158722
37 38 39 40 41 42
51.059468 -184.117670 34.833567 51.059468 34.833567 166.841278
43 44 45 46 47 48
-175.158722 47.814288 166.841278 24.286731 99.737172 33.399681
49 50 51 52 53 54
34.833567 34.833567 51.059468 75.398320 51.059468 -175.158722
55 56 57 58 59 60
123.434383 -287.220415 34.833567 34.833567 34.833567 34.833567
61 62 63 64 65 66
51.059468 34.833567 -185.181857 -287.220415 34.833567 51.059468
67 68 69 70 71 72
34.833567 -287.220415 51.059468 34.833567 34.833567 51.059468
73 74 75 76 77 78
34.833567 -287.220415 211.059468 -175.158722 166.841278 34.833567
79 80 81 82 83 84
34.833567 51.059468 166.841278 34.833567 -175.158722 34.833567
85 86 87 88 89 90
51.059468 34.833567 34.833567 47.814288 34.833567 211.059468
91 92 93 94 95 96
211.059468 75.398320 51.059468 51.059468 31.268813 34.833567
97 98 99 100 101 102
241.662779 34.833567 34.833567 34.833567 -175.158722 166.841278
103 104 105 106 107 108
51.059468 34.833567 -287.220415 272.266090 -175.158722 -175.158722
109 110 111 112 113 114
211.059468 18.483147 51.059468 -171.588751 -175.158722 8.872124
115 116 117 118 119 120
34.833567 51.059468 34.833567 34.833567 34.833567 51.059468
121 122 123 124 125 126
34.833567 -175.158722 -175.158722 -185.181857 80.841278 -175.158722
127 128 129 130 131 132
166.841278 75.398320 75.398320 34.833567 166.841278 -175.158722
133 134 135 136 137 138
51.059468 -175.158722 34.833567 34.833567 34.833567 -175.158722
139
34.833567
> postscript(file="/var/www/html/rcomp/tmp/6hbig1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 139
Frequency = 1
lag(myerror, k = 1) myerror
0 -287.220415 NA
1 -175.158722 -287.220415
2 18.607665 -175.158722
3 -175.158722 18.607665
4 34.833567 -175.158722
5 -287.220415 34.833567
6 34.833567 -287.220415
7 -175.158722 34.833567
8 34.833567 -175.158722
9 -287.220415 34.833567
10 34.833567 -287.220415
11 34.833567 34.833567
12 -287.220415 34.833567
13 228.610159 -287.220415
14 51.059468 228.610159
15 -220.262828 51.059468
16 34.833567 -220.262828
17 34.833567 34.833567
18 80.841278 34.833567
19 24.286731 80.841278
20 34.833567 24.286731
21 193.135222 34.833567
22 51.059468 193.135222
23 166.841278 51.059468
24 80.841278 166.841278
25 -175.158722 80.841278
26 34.833567 -175.158722
27 394.679335 34.833567
28 80.841278 394.679335
29 -175.158722 80.841278
30 -287.220415 -175.158722
31 34.833567 -287.220415
32 51.059468 34.833567
33 34.833567 51.059468
34 51.059468 34.833567
35 -175.158722 51.059468
36 51.059468 -175.158722
37 -184.117670 51.059468
38 34.833567 -184.117670
39 51.059468 34.833567
40 34.833567 51.059468
41 166.841278 34.833567
42 -175.158722 166.841278
43 47.814288 -175.158722
44 166.841278 47.814288
45 24.286731 166.841278
46 99.737172 24.286731
47 33.399681 99.737172
48 34.833567 33.399681
49 34.833567 34.833567
50 51.059468 34.833567
51 75.398320 51.059468
52 51.059468 75.398320
53 -175.158722 51.059468
54 123.434383 -175.158722
55 -287.220415 123.434383
56 34.833567 -287.220415
57 34.833567 34.833567
58 34.833567 34.833567
59 34.833567 34.833567
60 51.059468 34.833567
61 34.833567 51.059468
62 -185.181857 34.833567
63 -287.220415 -185.181857
64 34.833567 -287.220415
65 51.059468 34.833567
66 34.833567 51.059468
67 -287.220415 34.833567
68 51.059468 -287.220415
69 34.833567 51.059468
70 34.833567 34.833567
71 51.059468 34.833567
72 34.833567 51.059468
73 -287.220415 34.833567
74 211.059468 -287.220415
75 -175.158722 211.059468
76 166.841278 -175.158722
77 34.833567 166.841278
78 34.833567 34.833567
79 51.059468 34.833567
80 166.841278 51.059468
81 34.833567 166.841278
82 -175.158722 34.833567
83 34.833567 -175.158722
84 51.059468 34.833567
85 34.833567 51.059468
86 34.833567 34.833567
87 47.814288 34.833567
88 34.833567 47.814288
89 211.059468 34.833567
90 211.059468 211.059468
91 75.398320 211.059468
92 51.059468 75.398320
93 51.059468 51.059468
94 31.268813 51.059468
95 34.833567 31.268813
96 241.662779 34.833567
97 34.833567 241.662779
98 34.833567 34.833567
99 34.833567 34.833567
100 -175.158722 34.833567
101 166.841278 -175.158722
102 51.059468 166.841278
103 34.833567 51.059468
104 -287.220415 34.833567
105 272.266090 -287.220415
106 -175.158722 272.266090
107 -175.158722 -175.158722
108 211.059468 -175.158722
109 18.483147 211.059468
110 51.059468 18.483147
111 -171.588751 51.059468
112 -175.158722 -171.588751
113 8.872124 -175.158722
114 34.833567 8.872124
115 51.059468 34.833567
116 34.833567 51.059468
117 34.833567 34.833567
118 34.833567 34.833567
119 51.059468 34.833567
120 34.833567 51.059468
121 -175.158722 34.833567
122 -175.158722 -175.158722
123 -185.181857 -175.158722
124 80.841278 -185.181857
125 -175.158722 80.841278
126 166.841278 -175.158722
127 75.398320 166.841278
128 75.398320 75.398320
129 34.833567 75.398320
130 166.841278 34.833567
131 -175.158722 166.841278
132 51.059468 -175.158722
133 -175.158722 51.059468
134 34.833567 -175.158722
135 34.833567 34.833567
136 34.833567 34.833567
137 -175.158722 34.833567
138 34.833567 -175.158722
139 NA 34.833567
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -175.158722 -287.220415
[2,] 18.607665 -175.158722
[3,] -175.158722 18.607665
[4,] 34.833567 -175.158722
[5,] -287.220415 34.833567
[6,] 34.833567 -287.220415
[7,] -175.158722 34.833567
[8,] 34.833567 -175.158722
[9,] -287.220415 34.833567
[10,] 34.833567 -287.220415
[11,] 34.833567 34.833567
[12,] -287.220415 34.833567
[13,] 228.610159 -287.220415
[14,] 51.059468 228.610159
[15,] -220.262828 51.059468
[16,] 34.833567 -220.262828
[17,] 34.833567 34.833567
[18,] 80.841278 34.833567
[19,] 24.286731 80.841278
[20,] 34.833567 24.286731
[21,] 193.135222 34.833567
[22,] 51.059468 193.135222
[23,] 166.841278 51.059468
[24,] 80.841278 166.841278
[25,] -175.158722 80.841278
[26,] 34.833567 -175.158722
[27,] 394.679335 34.833567
[28,] 80.841278 394.679335
[29,] -175.158722 80.841278
[30,] -287.220415 -175.158722
[31,] 34.833567 -287.220415
[32,] 51.059468 34.833567
[33,] 34.833567 51.059468
[34,] 51.059468 34.833567
[35,] -175.158722 51.059468
[36,] 51.059468 -175.158722
[37,] -184.117670 51.059468
[38,] 34.833567 -184.117670
[39,] 51.059468 34.833567
[40,] 34.833567 51.059468
[41,] 166.841278 34.833567
[42,] -175.158722 166.841278
[43,] 47.814288 -175.158722
[44,] 166.841278 47.814288
[45,] 24.286731 166.841278
[46,] 99.737172 24.286731
[47,] 33.399681 99.737172
[48,] 34.833567 33.399681
[49,] 34.833567 34.833567
[50,] 51.059468 34.833567
[51,] 75.398320 51.059468
[52,] 51.059468 75.398320
[53,] -175.158722 51.059468
[54,] 123.434383 -175.158722
[55,] -287.220415 123.434383
[56,] 34.833567 -287.220415
[57,] 34.833567 34.833567
[58,] 34.833567 34.833567
[59,] 34.833567 34.833567
[60,] 51.059468 34.833567
[61,] 34.833567 51.059468
[62,] -185.181857 34.833567
[63,] -287.220415 -185.181857
[64,] 34.833567 -287.220415
[65,] 51.059468 34.833567
[66,] 34.833567 51.059468
[67,] -287.220415 34.833567
[68,] 51.059468 -287.220415
[69,] 34.833567 51.059468
[70,] 34.833567 34.833567
[71,] 51.059468 34.833567
[72,] 34.833567 51.059468
[73,] -287.220415 34.833567
[74,] 211.059468 -287.220415
[75,] -175.158722 211.059468
[76,] 166.841278 -175.158722
[77,] 34.833567 166.841278
[78,] 34.833567 34.833567
[79,] 51.059468 34.833567
[80,] 166.841278 51.059468
[81,] 34.833567 166.841278
[82,] -175.158722 34.833567
[83,] 34.833567 -175.158722
[84,] 51.059468 34.833567
[85,] 34.833567 51.059468
[86,] 34.833567 34.833567
[87,] 47.814288 34.833567
[88,] 34.833567 47.814288
[89,] 211.059468 34.833567
[90,] 211.059468 211.059468
[91,] 75.398320 211.059468
[92,] 51.059468 75.398320
[93,] 51.059468 51.059468
[94,] 31.268813 51.059468
[95,] 34.833567 31.268813
[96,] 241.662779 34.833567
[97,] 34.833567 241.662779
[98,] 34.833567 34.833567
[99,] 34.833567 34.833567
[100,] -175.158722 34.833567
[101,] 166.841278 -175.158722
[102,] 51.059468 166.841278
[103,] 34.833567 51.059468
[104,] -287.220415 34.833567
[105,] 272.266090 -287.220415
[106,] -175.158722 272.266090
[107,] -175.158722 -175.158722
[108,] 211.059468 -175.158722
[109,] 18.483147 211.059468
[110,] 51.059468 18.483147
[111,] -171.588751 51.059468
[112,] -175.158722 -171.588751
[113,] 8.872124 -175.158722
[114,] 34.833567 8.872124
[115,] 51.059468 34.833567
[116,] 34.833567 51.059468
[117,] 34.833567 34.833567
[118,] 34.833567 34.833567
[119,] 51.059468 34.833567
[120,] 34.833567 51.059468
[121,] -175.158722 34.833567
[122,] -175.158722 -175.158722
[123,] -185.181857 -175.158722
[124,] 80.841278 -185.181857
[125,] -175.158722 80.841278
[126,] 166.841278 -175.158722
[127,] 75.398320 166.841278
[128,] 75.398320 75.398320
[129,] 34.833567 75.398320
[130,] 166.841278 34.833567
[131,] -175.158722 166.841278
[132,] 51.059468 -175.158722
[133,] -175.158722 51.059468
[134,] 34.833567 -175.158722
[135,] 34.833567 34.833567
[136,] 34.833567 34.833567
[137,] -175.158722 34.833567
[138,] 34.833567 -175.158722
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -175.158722 -287.220415
2 18.607665 -175.158722
3 -175.158722 18.607665
4 34.833567 -175.158722
5 -287.220415 34.833567
6 34.833567 -287.220415
7 -175.158722 34.833567
8 34.833567 -175.158722
9 -287.220415 34.833567
10 34.833567 -287.220415
11 34.833567 34.833567
12 -287.220415 34.833567
13 228.610159 -287.220415
14 51.059468 228.610159
15 -220.262828 51.059468
16 34.833567 -220.262828
17 34.833567 34.833567
18 80.841278 34.833567
19 24.286731 80.841278
20 34.833567 24.286731
21 193.135222 34.833567
22 51.059468 193.135222
23 166.841278 51.059468
24 80.841278 166.841278
25 -175.158722 80.841278
26 34.833567 -175.158722
27 394.679335 34.833567
28 80.841278 394.679335
29 -175.158722 80.841278
30 -287.220415 -175.158722
31 34.833567 -287.220415
32 51.059468 34.833567
33 34.833567 51.059468
34 51.059468 34.833567
35 -175.158722 51.059468
36 51.059468 -175.158722
37 -184.117670 51.059468
38 34.833567 -184.117670
39 51.059468 34.833567
40 34.833567 51.059468
41 166.841278 34.833567
42 -175.158722 166.841278
43 47.814288 -175.158722
44 166.841278 47.814288
45 24.286731 166.841278
46 99.737172 24.286731
47 33.399681 99.737172
48 34.833567 33.399681
49 34.833567 34.833567
50 51.059468 34.833567
51 75.398320 51.059468
52 51.059468 75.398320
53 -175.158722 51.059468
54 123.434383 -175.158722
55 -287.220415 123.434383
56 34.833567 -287.220415
57 34.833567 34.833567
58 34.833567 34.833567
59 34.833567 34.833567
60 51.059468 34.833567
61 34.833567 51.059468
62 -185.181857 34.833567
63 -287.220415 -185.181857
64 34.833567 -287.220415
65 51.059468 34.833567
66 34.833567 51.059468
67 -287.220415 34.833567
68 51.059468 -287.220415
69 34.833567 51.059468
70 34.833567 34.833567
71 51.059468 34.833567
72 34.833567 51.059468
73 -287.220415 34.833567
74 211.059468 -287.220415
75 -175.158722 211.059468
76 166.841278 -175.158722
77 34.833567 166.841278
78 34.833567 34.833567
79 51.059468 34.833567
80 166.841278 51.059468
81 34.833567 166.841278
82 -175.158722 34.833567
83 34.833567 -175.158722
84 51.059468 34.833567
85 34.833567 51.059468
86 34.833567 34.833567
87 47.814288 34.833567
88 34.833567 47.814288
89 211.059468 34.833567
90 211.059468 211.059468
91 75.398320 211.059468
92 51.059468 75.398320
93 51.059468 51.059468
94 31.268813 51.059468
95 34.833567 31.268813
96 241.662779 34.833567
97 34.833567 241.662779
98 34.833567 34.833567
99 34.833567 34.833567
100 -175.158722 34.833567
101 166.841278 -175.158722
102 51.059468 166.841278
103 34.833567 51.059468
104 -287.220415 34.833567
105 272.266090 -287.220415
106 -175.158722 272.266090
107 -175.158722 -175.158722
108 211.059468 -175.158722
109 18.483147 211.059468
110 51.059468 18.483147
111 -171.588751 51.059468
112 -175.158722 -171.588751
113 8.872124 -175.158722
114 34.833567 8.872124
115 51.059468 34.833567
116 34.833567 51.059468
117 34.833567 34.833567
118 34.833567 34.833567
119 51.059468 34.833567
120 34.833567 51.059468
121 -175.158722 34.833567
122 -175.158722 -175.158722
123 -185.181857 -175.158722
124 80.841278 -185.181857
125 -175.158722 80.841278
126 166.841278 -175.158722
127 75.398320 166.841278
128 75.398320 75.398320
129 34.833567 75.398320
130 166.841278 34.833567
131 -175.158722 166.841278
132 51.059468 -175.158722
133 -175.158722 51.059468
134 34.833567 -175.158722
135 34.833567 34.833567
136 34.833567 34.833567
137 -175.158722 34.833567
138 34.833567 -175.158722
> 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/792hj1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/892hj1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/992hj1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10kchm1292348177.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/115ufr1292348177.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/129uwx1292348177.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/1354t61292348177.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/14q5su1292348177.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/15un901292348177.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/16fo761292348177.tab")
+ }
>
> try(system("convert tmp/1daka1292348177.ps tmp/1daka1292348177.png",intern=TRUE))
character(0)
> try(system("convert tmp/2daka1292348177.ps tmp/2daka1292348177.png",intern=TRUE))
character(0)
> try(system("convert tmp/36kjv1292348177.ps tmp/36kjv1292348177.png",intern=TRUE))
character(0)
> try(system("convert tmp/46kjv1292348177.ps tmp/46kjv1292348177.png",intern=TRUE))
character(0)
> try(system("convert tmp/56kjv1292348177.ps tmp/56kjv1292348177.png",intern=TRUE))
character(0)
> try(system("convert tmp/6hbig1292348177.ps tmp/6hbig1292348177.png",intern=TRUE))
character(0)
> try(system("convert tmp/792hj1292348177.ps tmp/792hj1292348177.png",intern=TRUE))
character(0)
> try(system("convert tmp/892hj1292348177.ps tmp/892hj1292348177.png",intern=TRUE))
character(0)
> try(system("convert tmp/992hj1292348177.ps tmp/992hj1292348177.png",intern=TRUE))
character(0)
> try(system("convert tmp/10kchm1292348177.ps tmp/10kchm1292348177.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.518 1.790 8.170