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(100.21
+ ,0
+ ,100.36
+ ,0
+ ,100.62
+ ,0
+ ,100.78
+ ,0
+ ,100.93
+ ,0
+ ,100.70
+ ,0
+ ,100.00
+ ,0
+ ,100.20
+ ,0
+ ,99.68
+ ,0
+ ,99.56
+ ,0
+ ,100.06
+ ,0
+ ,100.50
+ ,0
+ ,99.30
+ ,0
+ ,99.37
+ ,0
+ ,99.20
+ ,0
+ ,98.11
+ ,0
+ ,97.60
+ ,0
+ ,97.76
+ ,0
+ ,98.06
+ ,0
+ ,98.25
+ ,0
+ ,98.50
+ ,0
+ ,97.39
+ ,0
+ ,98.09
+ ,0
+ ,97.78
+ ,0
+ ,98.12
+ ,0
+ ,97.50
+ ,0
+ ,97.30
+ ,0
+ ,97.64
+ ,0
+ ,96.88
+ ,0
+ ,97.40
+ ,0
+ ,98.27
+ ,0
+ ,97.94
+ ,0
+ ,98.61
+ ,0
+ ,98.72
+ ,0
+ ,98.62
+ ,0
+ ,98.56
+ ,0
+ ,98.06
+ ,0
+ ,97.40
+ ,0
+ ,97.76
+ ,0
+ ,97.05
+ ,0
+ ,97.85
+ ,0
+ ,97.40
+ ,0
+ ,97.27
+ ,0
+ ,97.93
+ ,0
+ ,98.60
+ ,0
+ ,98.70
+ ,0
+ ,98.88
+ ,0
+ ,98.27
+ ,0
+ ,97.85
+ ,0
+ ,97.70
+ ,0
+ ,96.97
+ ,0
+ ,97.72
+ ,0
+ ,97.66
+ ,0
+ ,99.00
+ ,0
+ ,98.86
+ ,0
+ ,99.56
+ ,0
+ ,100.19
+ ,0
+ ,100.37
+ ,0
+ ,100.01
+ ,0
+ ,99.68
+ ,0
+ ,99.78
+ ,0
+ ,99.36
+ ,0
+ ,99.21
+ ,0
+ ,99.26
+ ,0
+ ,99.26
+ ,0
+ ,100.43
+ ,0
+ ,101.50
+ ,0
+ ,102.27
+ ,0
+ ,102.69
+ ,0
+ ,103.47
+ ,0
+ ,104.02
+ ,0
+ ,103.55
+ ,0
+ ,103.77
+ ,0
+ ,104.19
+ ,0
+ ,103.64
+ ,0
+ ,103.68
+ ,0
+ ,105.39
+ ,0
+ ,106.61
+ ,0
+ ,108.12
+ ,0
+ ,109.22
+ ,0
+ ,110.17
+ ,0
+ ,110.31
+ ,0
+ ,111.06
+ ,0
+ ,111.14
+ ,0
+ ,111.39
+ ,0
+ ,112.51
+ ,0
+ ,111.28
+ ,0
+ ,112.22
+ ,0
+ ,113.19
+ ,0
+ ,114.32
+ ,0
+ ,115.34
+ ,0
+ ,116.61
+ ,0
+ ,117.83
+ ,0
+ ,117.70
+ ,0
+ ,118.51
+ ,0
+ ,118.82
+ ,0
+ ,119.49
+ ,0
+ ,119.57
+ ,0
+ ,120.00
+ ,0
+ ,121.96
+ ,0
+ ,121.45
+ ,0
+ ,123.41
+ ,0
+ ,124.44
+ ,0
+ ,126.25
+ ,0
+ ,127.41
+ ,0
+ ,127.63
+ ,0
+ ,129.19
+ ,0
+ ,129.82
+ ,0
+ ,130.45
+ ,0
+ ,132.02
+ ,0
+ ,132.72
+ ,0
+ ,132.96
+ ,0
+ ,135.06
+ ,0
+ ,137.04
+ ,0
+ ,137.83
+ ,0
+ ,139.17
+ ,0
+ ,140.35
+ ,0
+ ,141.01
+ ,0
+ ,141.89
+ ,0
+ ,143.28
+ ,0
+ ,142.90
+ ,0
+ ,143.37
+ ,0
+ ,145.03
+ ,0
+ ,146.05
+ ,0
+ ,147.39
+ ,0
+ ,149.58
+ ,0
+ ,151.02
+ ,0
+ ,153.57
+ ,0
+ ,155.60
+ ,0
+ ,157.18
+ ,0
+ ,158.77
+ ,0
+ ,159.95
+ ,0
+ ,161.34
+ ,0
+ ,161.95
+ ,0
+ ,163.36
+ ,0
+ ,165.00
+ ,0
+ ,166.65
+ ,0
+ ,168.65
+ ,0
+ ,170.29
+ ,0
+ ,172.70
+ ,0
+ ,173.79
+ ,0
+ ,176.45
+ ,0
+ ,177.58
+ ,0
+ ,179.19
+ ,0
+ ,181.01
+ ,0
+ ,184.08
+ ,0
+ ,185.63
+ ,0
+ ,188.51
+ ,0
+ ,190.18
+ ,0
+ ,192.19
+ ,0
+ ,193.47
+ ,0
+ ,196.73
+ ,0
+ ,200.39
+ ,0
+ ,203.24
+ ,0
+ ,205.53
+ ,0
+ ,208.21
+ ,0
+ ,208.88
+ ,0
+ ,212.85
+ ,0
+ ,216.41
+ ,0
+ ,216.23
+ ,0
+ ,219.27
+ ,0
+ ,222.02
+ ,0
+ ,224.89
+ ,0
+ ,230.37
+ ,0
+ ,232.29
+ ,0
+ ,235.53
+ ,0
+ ,236.92
+ ,0
+ ,242.37
+ ,0
+ ,242.75
+ ,0
+ ,244.19
+ ,0
+ ,247.94
+ ,0
+ ,248.80
+ ,0
+ ,250.18
+ ,0
+ ,251.55
+ ,0
+ ,254.40
+ ,0
+ ,255.72
+ ,0
+ ,257.69
+ ,0
+ ,258.37
+ ,0
+ ,258.22
+ ,0
+ ,258.59
+ ,0
+ ,257.45
+ ,0
+ ,257.45
+ ,0
+ ,256.73
+ ,0
+ ,258.82
+ ,0
+ ,257.99
+ ,0
+ ,262.85
+ ,0
+ ,262.58
+ ,0
+ ,261.55
+ ,0
+ ,261.25
+ ,0
+ ,259.78
+ ,1
+ ,256.26
+ ,1
+ ,254.29
+ ,1
+ ,248.50
+ ,1
+ ,241.88
+ ,1
+ ,238.53
+ ,1
+ ,232.24
+ ,1
+ ,232.46
+ ,1
+ ,225.79
+ ,1
+ ,221.63
+ ,1
+ ,219.62
+ ,1
+ ,215.94
+ ,1
+ ,211.81
+ ,1
+ ,205.57
+ ,1
+ ,201.25
+ ,1
+ ,194.70
+ ,1
+ ,187.94
+ ,1
+ ,185.61
+ ,1
+ ,181.15
+ ,1
+ ,186.50
+ ,1
+ ,183.21
+ ,1
+ ,182.61
+ ,1
+ ,187.09
+ ,1
+ ,189.10
+ ,1
+ ,191.25
+ ,1
+ ,190.74
+ ,1
+ ,190.79
+ ,1)
+ ,dim=c(2
+ ,216)
+ ,dimnames=list(c('Huizenprijs_Pacific'
+ ,'Dummy_Crisis')
+ ,1:216))
> y <- array(NA,dim=c(2,216),dimnames=list(c('Huizenprijs_Pacific','Dummy_Crisis'),1:216))
> 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
Huizenprijs_Pacific Dummy_Crisis
1 100.21 0
2 100.36 0
3 100.62 0
4 100.78 0
5 100.93 0
6 100.70 0
7 100.00 0
8 100.20 0
9 99.68 0
10 99.56 0
11 100.06 0
12 100.50 0
13 99.30 0
14 99.37 0
15 99.20 0
16 98.11 0
17 97.60 0
18 97.76 0
19 98.06 0
20 98.25 0
21 98.50 0
22 97.39 0
23 98.09 0
24 97.78 0
25 98.12 0
26 97.50 0
27 97.30 0
28 97.64 0
29 96.88 0
30 97.40 0
31 98.27 0
32 97.94 0
33 98.61 0
34 98.72 0
35 98.62 0
36 98.56 0
37 98.06 0
38 97.40 0
39 97.76 0
40 97.05 0
41 97.85 0
42 97.40 0
43 97.27 0
44 97.93 0
45 98.60 0
46 98.70 0
47 98.88 0
48 98.27 0
49 97.85 0
50 97.70 0
51 96.97 0
52 97.72 0
53 97.66 0
54 99.00 0
55 98.86 0
56 99.56 0
57 100.19 0
58 100.37 0
59 100.01 0
60 99.68 0
61 99.78 0
62 99.36 0
63 99.21 0
64 99.26 0
65 99.26 0
66 100.43 0
67 101.50 0
68 102.27 0
69 102.69 0
70 103.47 0
71 104.02 0
72 103.55 0
73 103.77 0
74 104.19 0
75 103.64 0
76 103.68 0
77 105.39 0
78 106.61 0
79 108.12 0
80 109.22 0
81 110.17 0
82 110.31 0
83 111.06 0
84 111.14 0
85 111.39 0
86 112.51 0
87 111.28 0
88 112.22 0
89 113.19 0
90 114.32 0
91 115.34 0
92 116.61 0
93 117.83 0
94 117.70 0
95 118.51 0
96 118.82 0
97 119.49 0
98 119.57 0
99 120.00 0
100 121.96 0
101 121.45 0
102 123.41 0
103 124.44 0
104 126.25 0
105 127.41 0
106 127.63 0
107 129.19 0
108 129.82 0
109 130.45 0
110 132.02 0
111 132.72 0
112 132.96 0
113 135.06 0
114 137.04 0
115 137.83 0
116 139.17 0
117 140.35 0
118 141.01 0
119 141.89 0
120 143.28 0
121 142.90 0
122 143.37 0
123 145.03 0
124 146.05 0
125 147.39 0
126 149.58 0
127 151.02 0
128 153.57 0
129 155.60 0
130 157.18 0
131 158.77 0
132 159.95 0
133 161.34 0
134 161.95 0
135 163.36 0
136 165.00 0
137 166.65 0
138 168.65 0
139 170.29 0
140 172.70 0
141 173.79 0
142 176.45 0
143 177.58 0
144 179.19 0
145 181.01 0
146 184.08 0
147 185.63 0
148 188.51 0
149 190.18 0
150 192.19 0
151 193.47 0
152 196.73 0
153 200.39 0
154 203.24 0
155 205.53 0
156 208.21 0
157 208.88 0
158 212.85 0
159 216.41 0
160 216.23 0
161 219.27 0
162 222.02 0
163 224.89 0
164 230.37 0
165 232.29 0
166 235.53 0
167 236.92 0
168 242.37 0
169 242.75 0
170 244.19 0
171 247.94 0
172 248.80 0
173 250.18 0
174 251.55 0
175 254.40 0
176 255.72 0
177 257.69 0
178 258.37 0
179 258.22 0
180 258.59 0
181 257.45 0
182 257.45 0
183 256.73 0
184 258.82 0
185 257.99 0
186 262.85 0
187 262.58 0
188 261.55 0
189 261.25 0
190 259.78 1
191 256.26 1
192 254.29 1
193 248.50 1
194 241.88 1
195 238.53 1
196 232.24 1
197 232.46 1
198 225.79 1
199 221.63 1
200 219.62 1
201 215.94 1
202 211.81 1
203 205.57 1
204 201.25 1
205 194.70 1
206 187.94 1
207 185.61 1
208 181.15 1
209 186.50 1
210 183.21 1
211 182.61 1
212 187.09 1
213 189.10 1
214 191.25 1
215 190.74 1
216 190.79 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy_Crisis
143.78 67.93
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-46.90 -43.74 -22.08 29.19 119.07
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 143.784 3.776 38.07 < 2e-16 ***
Dummy_Crisis 67.929 10.681 6.36 1.21e-09 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 51.92 on 214 degrees of freedom
Multiple R-squared: 0.1589, Adjusted R-squared: 0.155
F-statistic: 40.44 on 1 and 214 DF, p-value: 1.206e-09
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 3.898640e-07 7.797280e-07 9.999996e-01
[2,] 2.231734e-09 4.463468e-09 1.000000e+00
[3,] 5.152440e-11 1.030488e-10 1.000000e+00
[4,] 4.590615e-13 9.181229e-13 1.000000e+00
[5,] 1.968296e-14 3.936592e-14 1.000000e+00
[6,] 6.941926e-16 1.388385e-15 1.000000e+00
[7,] 6.875268e-18 1.375054e-17 1.000000e+00
[8,] 6.474164e-20 1.294833e-19 1.000000e+00
[9,] 4.158994e-21 8.317987e-21 1.000000e+00
[10,] 1.357678e-22 2.715355e-22 1.000000e+00
[11,] 5.515390e-24 1.103078e-23 1.000000e+00
[12,] 4.053316e-24 8.106633e-24 1.000000e+00
[13,] 2.444983e-24 4.889966e-24 1.000000e+00
[14,] 3.579450e-25 7.158900e-25 1.000000e+00
[15,] 2.299987e-26 4.599974e-26 1.000000e+00
[16,] 1.033675e-27 2.067349e-27 1.000000e+00
[17,] 3.435506e-29 6.871011e-29 1.000000e+00
[18,] 4.021023e-30 8.042046e-30 1.000000e+00
[19,] 1.698822e-31 3.397643e-31 1.000000e+00
[20,] 9.249669e-33 1.849934e-32 1.000000e+00
[21,] 3.461422e-34 6.922843e-34 1.000000e+00
[22,] 2.267335e-35 4.534669e-35 1.000000e+00
[23,] 1.701888e-36 3.403776e-36 1.000000e+00
[24,] 8.285791e-38 1.657158e-37 1.000000e+00
[25,] 8.640047e-39 1.728009e-38 1.000000e+00
[26,] 4.642763e-40 9.285527e-40 1.000000e+00
[27,] 1.390836e-41 2.781672e-41 1.000000e+00
[28,] 4.816184e-43 9.632368e-43 1.000000e+00
[29,] 1.286301e-44 2.572603e-44 1.000000e+00
[30,] 3.350661e-46 6.701321e-46 1.000000e+00
[31,] 8.754192e-48 1.750838e-47 1.000000e+00
[32,] 2.291028e-49 4.582056e-49 1.000000e+00
[33,] 7.155578e-51 1.431116e-50 1.000000e+00
[34,] 3.631309e-52 7.262618e-52 1.000000e+00
[35,] 1.333734e-53 2.667469e-53 1.000000e+00
[36,] 9.271226e-55 1.854245e-54 1.000000e+00
[37,] 3.131890e-56 6.263780e-56 1.000000e+00
[38,] 1.456062e-57 2.912125e-57 1.000000e+00
[39,] 7.462796e-59 1.492559e-58 1.000000e+00
[40,] 2.365389e-60 4.730778e-60 1.000000e+00
[41,] 6.315948e-62 1.263190e-61 1.000000e+00
[42,] 1.683921e-63 3.367843e-63 1.000000e+00
[43,] 4.572552e-65 9.145104e-65 1.000000e+00
[44,] 1.273386e-66 2.546772e-66 1.000000e+00
[45,] 4.234884e-68 8.469767e-68 1.000000e+00
[46,] 1.545421e-69 3.090841e-69 1.000000e+00
[47,] 1.118981e-70 2.237962e-70 1.000000e+00
[48,] 4.001888e-72 8.003777e-72 1.000000e+00
[49,] 1.487365e-73 2.974730e-73 1.000000e+00
[50,] 4.499719e-75 8.999437e-75 1.000000e+00
[51,] 1.308160e-76 2.616321e-76 1.000000e+00
[52,] 5.496268e-78 1.099254e-77 1.000000e+00
[53,] 4.367853e-79 8.735705e-79 1.000000e+00
[54,] 4.222520e-80 8.445040e-80 1.000000e+00
[55,] 2.585409e-81 5.170817e-81 1.000000e+00
[56,] 1.169807e-82 2.339614e-82 1.000000e+00
[57,] 5.740355e-84 1.148071e-83 1.000000e+00
[58,] 2.135868e-85 4.271736e-85 1.000000e+00
[59,] 7.493337e-87 1.498667e-86 1.000000e+00
[60,] 2.709818e-88 5.419636e-88 1.000000e+00
[61,] 9.906100e-90 1.981220e-89 1.000000e+00
[62,] 1.016586e-90 2.033171e-90 1.000000e+00
[63,] 5.760454e-91 1.152091e-90 1.000000e+00
[64,] 1.256123e-90 2.512246e-90 1.000000e+00
[65,] 4.254655e-90 8.509309e-90 1.000000e+00
[66,] 4.417917e-89 8.835834e-89 1.000000e+00
[67,] 6.620974e-88 1.324195e-87 1.000000e+00
[68,] 1.931335e-87 3.862670e-87 1.000000e+00
[69,] 5.319076e-87 1.063815e-86 1.000000e+00
[70,] 1.893601e-86 3.787202e-86 1.000000e+00
[71,] 2.176681e-86 4.353361e-86 1.000000e+00
[72,] 2.165316e-86 4.330632e-86 1.000000e+00
[73,] 1.651623e-85 3.303246e-85 1.000000e+00
[74,] 4.243274e-84 8.486548e-84 1.000000e+00
[75,] 4.340152e-82 8.680304e-82 1.000000e+00
[76,] 6.555182e-80 1.311036e-79 1.000000e+00
[77,] 9.983266e-78 1.996653e-77 1.000000e+00
[78,] 5.747343e-76 1.149469e-75 1.000000e+00
[79,] 3.039470e-74 6.078941e-74 1.000000e+00
[80,] 7.979599e-73 1.595920e-72 1.000000e+00
[81,] 1.432090e-71 2.864179e-71 1.000000e+00
[82,] 3.703141e-70 7.406281e-70 1.000000e+00
[83,] 2.475920e-69 4.951840e-69 1.000000e+00
[84,] 2.260271e-68 4.520542e-68 1.000000e+00
[85,] 2.739227e-67 5.478453e-67 1.000000e+00
[86,] 4.628514e-66 9.257028e-66 1.000000e+00
[87,] 9.620831e-65 1.924166e-64 1.000000e+00
[88,] 2.711950e-63 5.423899e-63 1.000000e+00
[89,] 9.441695e-62 1.888339e-61 1.000000e+00
[90,] 1.940499e-60 3.880998e-60 1.000000e+00
[91,] 4.081493e-59 8.162987e-59 1.000000e+00
[92,] 7.009877e-58 1.401975e-57 1.000000e+00
[93,] 1.183693e-56 2.367386e-56 1.000000e+00
[94,] 1.574850e-55 3.149700e-55 1.000000e+00
[95,] 1.961084e-54 3.922168e-54 1.000000e+00
[96,] 3.938624e-53 7.877248e-53 1.000000e+00
[97,] 5.181364e-52 1.036273e-51 1.000000e+00
[98,] 1.050134e-50 2.100268e-50 1.000000e+00
[99,] 2.306798e-49 4.613595e-49 1.000000e+00
[100,] 6.858863e-48 1.371773e-47 1.000000e+00
[101,] 2.156701e-46 4.313402e-46 1.000000e+00
[102,] 5.448576e-45 1.089715e-44 1.000000e+00
[103,] 1.627854e-43 3.255708e-43 1.000000e+00
[104,] 4.411562e-42 8.823123e-42 1.000000e+00
[105,] 1.102162e-40 2.204324e-40 1.000000e+00
[106,] 3.153796e-39 6.307593e-39 1.000000e+00
[107,] 8.373302e-38 1.674660e-37 1.000000e+00
[108,] 1.912222e-36 3.824443e-36 1.000000e+00
[109,] 5.401142e-35 1.080228e-34 1.000000e+00
[110,] 1.770879e-33 3.541758e-33 1.000000e+00
[111,] 5.301338e-32 1.060268e-31 1.000000e+00
[112,] 1.594224e-30 3.188448e-30 1.000000e+00
[113,] 4.645592e-29 9.291184e-29 1.000000e+00
[114,] 1.216471e-27 2.432942e-27 1.000000e+00
[115,] 2.982424e-26 5.964848e-26 1.000000e+00
[116,] 7.283847e-25 1.456769e-24 1.000000e+00
[117,] 1.459451e-23 2.918903e-23 1.000000e+00
[118,] 2.714046e-22 5.428092e-22 1.000000e+00
[119,] 5.226979e-21 1.045396e-20 1.000000e+00
[120,] 9.734211e-20 1.946842e-19 1.000000e+00
[121,] 1.786452e-18 3.572904e-18 1.000000e+00
[122,] 3.373530e-17 6.747060e-17 1.000000e+00
[123,] 6.086155e-16 1.217231e-15 1.000000e+00
[124,] 1.100695e-14 2.201390e-14 1.000000e+00
[125,] 1.877958e-13 3.755916e-13 1.000000e+00
[126,] 2.898965e-12 5.797931e-12 1.000000e+00
[127,] 4.009818e-11 8.019635e-11 1.000000e+00
[128,] 4.860220e-10 9.720441e-10 1.000000e+00
[129,] 5.190763e-09 1.038153e-08 1.000000e+00
[130,] 4.789612e-08 9.579223e-08 1.000000e+00
[131,] 3.900959e-07 7.801918e-07 9.999996e-01
[132,] 2.797345e-06 5.594691e-06 9.999972e-01
[133,] 1.753117e-05 3.506234e-05 9.999825e-01
[134,] 9.557282e-05 1.911456e-04 9.999044e-01
[135,] 4.490933e-04 8.981866e-04 9.995509e-01
[136,] 1.814329e-03 3.628658e-03 9.981857e-01
[137,] 6.270856e-03 1.254171e-02 9.937291e-01
[138,] 1.855053e-02 3.710107e-02 9.814495e-01
[139,] 4.712214e-02 9.424428e-02 9.528779e-01
[140,] 1.033098e-01 2.066197e-01 8.966902e-01
[141,] 1.965918e-01 3.931837e-01 8.034082e-01
[142,] 3.259870e-01 6.519740e-01 6.740130e-01
[143,] 4.793281e-01 9.586562e-01 5.206719e-01
[144,] 6.324056e-01 7.351888e-01 3.675944e-01
[145,] 7.649377e-01 4.701247e-01 2.350623e-01
[146,] 8.640417e-01 2.719166e-01 1.359583e-01
[147,] 9.293709e-01 1.412581e-01 7.062907e-02
[148,] 9.662514e-01 6.749715e-02 3.374858e-02
[149,] 9.848272e-01 3.034557e-02 1.517278e-02
[150,] 9.935226e-01 1.295476e-02 6.477379e-03
[151,] 9.973546e-01 5.290804e-03 2.645402e-03
[152,] 9.989437e-01 2.112659e-03 1.056330e-03
[153,] 9.996000e-01 8.000864e-04 4.000432e-04
[154,] 9.998438e-01 3.124772e-04 1.562386e-04
[155,] 9.999363e-01 1.274926e-04 6.374628e-05
[156,] 9.999749e-01 5.017202e-05 2.508601e-05
[157,] 9.999896e-01 2.075608e-05 1.037804e-05
[158,] 9.999955e-01 9.079796e-06 4.539898e-06
[159,] 9.999979e-01 4.261340e-06 2.130670e-06
[160,] 9.999988e-01 2.308704e-06 1.154352e-06
[161,] 9.999993e-01 1.341446e-06 6.707229e-07
[162,] 9.999996e-01 8.590677e-07 4.295339e-07
[163,] 9.999997e-01 5.872757e-07 2.936379e-07
[164,] 9.999998e-01 4.524133e-07 2.262066e-07
[165,] 9.999998e-01 3.696022e-07 1.848011e-07
[166,] 9.999998e-01 3.221496e-07 1.610748e-07
[167,] 9.999998e-01 3.032331e-07 1.516166e-07
[168,] 9.999998e-01 3.021814e-07 1.510907e-07
[169,] 9.999998e-01 3.181131e-07 1.590566e-07
[170,] 9.999998e-01 3.523953e-07 1.761976e-07
[171,] 9.999998e-01 4.086570e-07 2.043285e-07
[172,] 9.999998e-01 4.946316e-07 2.473158e-07
[173,] 9.999997e-01 6.199419e-07 3.099709e-07
[174,] 9.999996e-01 8.073505e-07 4.036753e-07
[175,] 9.999995e-01 1.094395e-06 5.471974e-07
[176,] 9.999992e-01 1.533279e-06 7.666397e-07
[177,] 9.999989e-01 2.228343e-06 1.114171e-06
[178,] 9.999983e-01 3.326440e-06 1.663220e-06
[179,] 9.999975e-01 5.086415e-06 2.543208e-06
[180,] 9.999960e-01 7.907379e-06 3.953690e-06
[181,] 9.999937e-01 1.253439e-05 6.267193e-06
[182,] 9.999901e-01 1.989134e-05 9.945671e-06
[183,] 9.999839e-01 3.217676e-05 1.608838e-05
[184,] 9.999734e-01 5.311033e-05 2.655516e-05
[185,] 9.999556e-01 8.883748e-05 4.441874e-05
[186,] 9.999758e-01 4.834100e-05 2.417050e-05
[187,] 9.999875e-01 2.504462e-05 1.252231e-05
[188,] 9.999946e-01 1.073622e-05 5.368110e-06
[189,] 9.999975e-01 4.929895e-06 2.464948e-06
[190,] 9.999986e-01 2.739787e-06 1.369894e-06
[191,] 9.999993e-01 1.437410e-06 7.187052e-07
[192,] 9.999995e-01 9.669727e-07 4.834863e-07
[193,] 9.999998e-01 4.103718e-07 2.051859e-07
[194,] 9.999999e-01 2.360777e-07 1.180389e-07
[195,] 9.999999e-01 1.444237e-07 7.221186e-08
[196,] 1.000000e+00 6.284771e-08 3.142386e-08
[197,] 1.000000e+00 2.144815e-08 1.072408e-08
[198,] 1.000000e+00 5.109167e-09 2.554583e-09
[199,] 1.000000e+00 1.773766e-09 8.868829e-10
[200,] 1.000000e+00 5.767242e-10 2.883621e-10
[201,] 1.000000e+00 1.362914e-09 6.814568e-10
[202,] 1.000000e+00 1.917028e-08 9.585139e-09
[203,] 9.999999e-01 2.544894e-07 1.272447e-07
[204,] 9.999995e-01 1.071559e-06 5.357795e-07
[205,] 9.999924e-01 1.517552e-05 7.587762e-06
[206,] 9.999503e-01 9.935896e-05 4.967948e-05
[207,] 9.999249e-01 1.502003e-04 7.510017e-05
> postscript(file="/var/www/html/rcomp/tmp/1paie1261239931.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2r44r1261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/37m941261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4lbsj1261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/51pq91261239931.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 = 216
Frequency = 1
1 2 3 4 5 6
-43.5739153 -43.4239153 -43.1639153 -43.0039153 -42.8539153 -43.0839153
7 8 9 10 11 12
-43.7839153 -43.5839153 -44.1039153 -44.2239153 -43.7239153 -43.2839153
13 14 15 16 17 18
-44.4839153 -44.4139153 -44.5839153 -45.6739153 -46.1839153 -46.0239153
19 20 21 22 23 24
-45.7239153 -45.5339153 -45.2839153 -46.3939153 -45.6939153 -46.0039153
25 26 27 28 29 30
-45.6639153 -46.2839153 -46.4839153 -46.1439153 -46.9039153 -46.3839153
31 32 33 34 35 36
-45.5139153 -45.8439153 -45.1739153 -45.0639153 -45.1639153 -45.2239153
37 38 39 40 41 42
-45.7239153 -46.3839153 -46.0239153 -46.7339153 -45.9339153 -46.3839153
43 44 45 46 47 48
-46.5139153 -45.8539153 -45.1839153 -45.0839153 -44.9039153 -45.5139153
49 50 51 52 53 54
-45.9339153 -46.0839153 -46.8139153 -46.0639153 -46.1239153 -44.7839153
55 56 57 58 59 60
-44.9239153 -44.2239153 -43.5939153 -43.4139153 -43.7739153 -44.1039153
61 62 63 64 65 66
-44.0039153 -44.4239153 -44.5739153 -44.5239153 -44.5239153 -43.3539153
67 68 69 70 71 72
-42.2839153 -41.5139153 -41.0939153 -40.3139153 -39.7639153 -40.2339153
73 74 75 76 77 78
-40.0139153 -39.5939153 -40.1439153 -40.1039153 -38.3939153 -37.1739153
79 80 81 82 83 84
-35.6639153 -34.5639153 -33.6139153 -33.4739153 -32.7239153 -32.6439153
85 86 87 88 89 90
-32.3939153 -31.2739153 -32.5039153 -31.5639153 -30.5939153 -29.4639153
91 92 93 94 95 96
-28.4439153 -27.1739153 -25.9539153 -26.0839153 -25.2739153 -24.9639153
97 98 99 100 101 102
-24.2939153 -24.2139153 -23.7839153 -21.8239153 -22.3339153 -20.3739153
103 104 105 106 107 108
-19.3439153 -17.5339153 -16.3739153 -16.1539153 -14.5939153 -13.9639153
109 110 111 112 113 114
-13.3339153 -11.7639153 -11.0639153 -10.8239153 -8.7239153 -6.7439153
115 116 117 118 119 120
-5.9539153 -4.6139153 -3.4339153 -2.7739153 -1.8939153 -0.5039153
121 122 123 124 125 126
-0.8839153 -0.4139153 1.2460847 2.2660847 3.6060847 5.7960847
127 128 129 130 131 132
7.2360847 9.7860847 11.8160847 13.3960847 14.9860847 16.1660847
133 134 135 136 137 138
17.5560847 18.1660847 19.5760847 21.2160847 22.8660847 24.8660847
139 140 141 142 143 144
26.5060847 28.9160847 30.0060847 32.6660847 33.7960847 35.4060847
145 146 147 148 149 150
37.2260847 40.2960847 41.8460847 44.7260847 46.3960847 48.4060847
151 152 153 154 155 156
49.6860847 52.9460847 56.6060847 59.4560847 61.7460847 64.4260847
157 158 159 160 161 162
65.0960847 69.0660847 72.6260847 72.4460847 75.4860847 78.2360847
163 164 165 166 167 168
81.1060847 86.5860847 88.5060847 91.7460847 93.1360847 98.5860847
169 170 171 172 173 174
98.9660847 100.4060847 104.1560847 105.0160847 106.3960847 107.7660847
175 176 177 178 179 180
110.6160847 111.9360847 113.9060847 114.5860847 114.4360847 114.8060847
181 182 183 184 185 186
113.6660847 113.6660847 112.9460847 115.0360847 114.2060847 119.0660847
187 188 189 190 191 192
118.7960847 117.7660847 117.4660847 48.0674074 44.5474074 42.5774074
193 194 195 196 197 198
36.7874074 30.1674074 26.8174074 20.5274074 20.7474074 14.0774074
199 200 201 202 203 204
9.9174074 7.9074074 4.2274074 0.0974074 -6.1425926 -10.4625926
205 206 207 208 209 210
-17.0125926 -23.7725926 -26.1025926 -30.5625926 -25.2125926 -28.5025926
211 212 213 214 215 216
-29.1025926 -24.6225926 -22.6125926 -20.4625926 -20.9725926 -20.9225926
> postscript(file="/var/www/html/rcomp/tmp/6w0oh1261239931.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 = 216
Frequency = 1
lag(myerror, k = 1) myerror
0 -43.5739153 NA
1 -43.4239153 -43.5739153
2 -43.1639153 -43.4239153
3 -43.0039153 -43.1639153
4 -42.8539153 -43.0039153
5 -43.0839153 -42.8539153
6 -43.7839153 -43.0839153
7 -43.5839153 -43.7839153
8 -44.1039153 -43.5839153
9 -44.2239153 -44.1039153
10 -43.7239153 -44.2239153
11 -43.2839153 -43.7239153
12 -44.4839153 -43.2839153
13 -44.4139153 -44.4839153
14 -44.5839153 -44.4139153
15 -45.6739153 -44.5839153
16 -46.1839153 -45.6739153
17 -46.0239153 -46.1839153
18 -45.7239153 -46.0239153
19 -45.5339153 -45.7239153
20 -45.2839153 -45.5339153
21 -46.3939153 -45.2839153
22 -45.6939153 -46.3939153
23 -46.0039153 -45.6939153
24 -45.6639153 -46.0039153
25 -46.2839153 -45.6639153
26 -46.4839153 -46.2839153
27 -46.1439153 -46.4839153
28 -46.9039153 -46.1439153
29 -46.3839153 -46.9039153
30 -45.5139153 -46.3839153
31 -45.8439153 -45.5139153
32 -45.1739153 -45.8439153
33 -45.0639153 -45.1739153
34 -45.1639153 -45.0639153
35 -45.2239153 -45.1639153
36 -45.7239153 -45.2239153
37 -46.3839153 -45.7239153
38 -46.0239153 -46.3839153
39 -46.7339153 -46.0239153
40 -45.9339153 -46.7339153
41 -46.3839153 -45.9339153
42 -46.5139153 -46.3839153
43 -45.8539153 -46.5139153
44 -45.1839153 -45.8539153
45 -45.0839153 -45.1839153
46 -44.9039153 -45.0839153
47 -45.5139153 -44.9039153
48 -45.9339153 -45.5139153
49 -46.0839153 -45.9339153
50 -46.8139153 -46.0839153
51 -46.0639153 -46.8139153
52 -46.1239153 -46.0639153
53 -44.7839153 -46.1239153
54 -44.9239153 -44.7839153
55 -44.2239153 -44.9239153
56 -43.5939153 -44.2239153
57 -43.4139153 -43.5939153
58 -43.7739153 -43.4139153
59 -44.1039153 -43.7739153
60 -44.0039153 -44.1039153
61 -44.4239153 -44.0039153
62 -44.5739153 -44.4239153
63 -44.5239153 -44.5739153
64 -44.5239153 -44.5239153
65 -43.3539153 -44.5239153
66 -42.2839153 -43.3539153
67 -41.5139153 -42.2839153
68 -41.0939153 -41.5139153
69 -40.3139153 -41.0939153
70 -39.7639153 -40.3139153
71 -40.2339153 -39.7639153
72 -40.0139153 -40.2339153
73 -39.5939153 -40.0139153
74 -40.1439153 -39.5939153
75 -40.1039153 -40.1439153
76 -38.3939153 -40.1039153
77 -37.1739153 -38.3939153
78 -35.6639153 -37.1739153
79 -34.5639153 -35.6639153
80 -33.6139153 -34.5639153
81 -33.4739153 -33.6139153
82 -32.7239153 -33.4739153
83 -32.6439153 -32.7239153
84 -32.3939153 -32.6439153
85 -31.2739153 -32.3939153
86 -32.5039153 -31.2739153
87 -31.5639153 -32.5039153
88 -30.5939153 -31.5639153
89 -29.4639153 -30.5939153
90 -28.4439153 -29.4639153
91 -27.1739153 -28.4439153
92 -25.9539153 -27.1739153
93 -26.0839153 -25.9539153
94 -25.2739153 -26.0839153
95 -24.9639153 -25.2739153
96 -24.2939153 -24.9639153
97 -24.2139153 -24.2939153
98 -23.7839153 -24.2139153
99 -21.8239153 -23.7839153
100 -22.3339153 -21.8239153
101 -20.3739153 -22.3339153
102 -19.3439153 -20.3739153
103 -17.5339153 -19.3439153
104 -16.3739153 -17.5339153
105 -16.1539153 -16.3739153
106 -14.5939153 -16.1539153
107 -13.9639153 -14.5939153
108 -13.3339153 -13.9639153
109 -11.7639153 -13.3339153
110 -11.0639153 -11.7639153
111 -10.8239153 -11.0639153
112 -8.7239153 -10.8239153
113 -6.7439153 -8.7239153
114 -5.9539153 -6.7439153
115 -4.6139153 -5.9539153
116 -3.4339153 -4.6139153
117 -2.7739153 -3.4339153
118 -1.8939153 -2.7739153
119 -0.5039153 -1.8939153
120 -0.8839153 -0.5039153
121 -0.4139153 -0.8839153
122 1.2460847 -0.4139153
123 2.2660847 1.2460847
124 3.6060847 2.2660847
125 5.7960847 3.6060847
126 7.2360847 5.7960847
127 9.7860847 7.2360847
128 11.8160847 9.7860847
129 13.3960847 11.8160847
130 14.9860847 13.3960847
131 16.1660847 14.9860847
132 17.5560847 16.1660847
133 18.1660847 17.5560847
134 19.5760847 18.1660847
135 21.2160847 19.5760847
136 22.8660847 21.2160847
137 24.8660847 22.8660847
138 26.5060847 24.8660847
139 28.9160847 26.5060847
140 30.0060847 28.9160847
141 32.6660847 30.0060847
142 33.7960847 32.6660847
143 35.4060847 33.7960847
144 37.2260847 35.4060847
145 40.2960847 37.2260847
146 41.8460847 40.2960847
147 44.7260847 41.8460847
148 46.3960847 44.7260847
149 48.4060847 46.3960847
150 49.6860847 48.4060847
151 52.9460847 49.6860847
152 56.6060847 52.9460847
153 59.4560847 56.6060847
154 61.7460847 59.4560847
155 64.4260847 61.7460847
156 65.0960847 64.4260847
157 69.0660847 65.0960847
158 72.6260847 69.0660847
159 72.4460847 72.6260847
160 75.4860847 72.4460847
161 78.2360847 75.4860847
162 81.1060847 78.2360847
163 86.5860847 81.1060847
164 88.5060847 86.5860847
165 91.7460847 88.5060847
166 93.1360847 91.7460847
167 98.5860847 93.1360847
168 98.9660847 98.5860847
169 100.4060847 98.9660847
170 104.1560847 100.4060847
171 105.0160847 104.1560847
172 106.3960847 105.0160847
173 107.7660847 106.3960847
174 110.6160847 107.7660847
175 111.9360847 110.6160847
176 113.9060847 111.9360847
177 114.5860847 113.9060847
178 114.4360847 114.5860847
179 114.8060847 114.4360847
180 113.6660847 114.8060847
181 113.6660847 113.6660847
182 112.9460847 113.6660847
183 115.0360847 112.9460847
184 114.2060847 115.0360847
185 119.0660847 114.2060847
186 118.7960847 119.0660847
187 117.7660847 118.7960847
188 117.4660847 117.7660847
189 48.0674074 117.4660847
190 44.5474074 48.0674074
191 42.5774074 44.5474074
192 36.7874074 42.5774074
193 30.1674074 36.7874074
194 26.8174074 30.1674074
195 20.5274074 26.8174074
196 20.7474074 20.5274074
197 14.0774074 20.7474074
198 9.9174074 14.0774074
199 7.9074074 9.9174074
200 4.2274074 7.9074074
201 0.0974074 4.2274074
202 -6.1425926 0.0974074
203 -10.4625926 -6.1425926
204 -17.0125926 -10.4625926
205 -23.7725926 -17.0125926
206 -26.1025926 -23.7725926
207 -30.5625926 -26.1025926
208 -25.2125926 -30.5625926
209 -28.5025926 -25.2125926
210 -29.1025926 -28.5025926
211 -24.6225926 -29.1025926
212 -22.6125926 -24.6225926
213 -20.4625926 -22.6125926
214 -20.9725926 -20.4625926
215 -20.9225926 -20.9725926
216 NA -20.9225926
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -43.4239153 -43.5739153
[2,] -43.1639153 -43.4239153
[3,] -43.0039153 -43.1639153
[4,] -42.8539153 -43.0039153
[5,] -43.0839153 -42.8539153
[6,] -43.7839153 -43.0839153
[7,] -43.5839153 -43.7839153
[8,] -44.1039153 -43.5839153
[9,] -44.2239153 -44.1039153
[10,] -43.7239153 -44.2239153
[11,] -43.2839153 -43.7239153
[12,] -44.4839153 -43.2839153
[13,] -44.4139153 -44.4839153
[14,] -44.5839153 -44.4139153
[15,] -45.6739153 -44.5839153
[16,] -46.1839153 -45.6739153
[17,] -46.0239153 -46.1839153
[18,] -45.7239153 -46.0239153
[19,] -45.5339153 -45.7239153
[20,] -45.2839153 -45.5339153
[21,] -46.3939153 -45.2839153
[22,] -45.6939153 -46.3939153
[23,] -46.0039153 -45.6939153
[24,] -45.6639153 -46.0039153
[25,] -46.2839153 -45.6639153
[26,] -46.4839153 -46.2839153
[27,] -46.1439153 -46.4839153
[28,] -46.9039153 -46.1439153
[29,] -46.3839153 -46.9039153
[30,] -45.5139153 -46.3839153
[31,] -45.8439153 -45.5139153
[32,] -45.1739153 -45.8439153
[33,] -45.0639153 -45.1739153
[34,] -45.1639153 -45.0639153
[35,] -45.2239153 -45.1639153
[36,] -45.7239153 -45.2239153
[37,] -46.3839153 -45.7239153
[38,] -46.0239153 -46.3839153
[39,] -46.7339153 -46.0239153
[40,] -45.9339153 -46.7339153
[41,] -46.3839153 -45.9339153
[42,] -46.5139153 -46.3839153
[43,] -45.8539153 -46.5139153
[44,] -45.1839153 -45.8539153
[45,] -45.0839153 -45.1839153
[46,] -44.9039153 -45.0839153
[47,] -45.5139153 -44.9039153
[48,] -45.9339153 -45.5139153
[49,] -46.0839153 -45.9339153
[50,] -46.8139153 -46.0839153
[51,] -46.0639153 -46.8139153
[52,] -46.1239153 -46.0639153
[53,] -44.7839153 -46.1239153
[54,] -44.9239153 -44.7839153
[55,] -44.2239153 -44.9239153
[56,] -43.5939153 -44.2239153
[57,] -43.4139153 -43.5939153
[58,] -43.7739153 -43.4139153
[59,] -44.1039153 -43.7739153
[60,] -44.0039153 -44.1039153
[61,] -44.4239153 -44.0039153
[62,] -44.5739153 -44.4239153
[63,] -44.5239153 -44.5739153
[64,] -44.5239153 -44.5239153
[65,] -43.3539153 -44.5239153
[66,] -42.2839153 -43.3539153
[67,] -41.5139153 -42.2839153
[68,] -41.0939153 -41.5139153
[69,] -40.3139153 -41.0939153
[70,] -39.7639153 -40.3139153
[71,] -40.2339153 -39.7639153
[72,] -40.0139153 -40.2339153
[73,] -39.5939153 -40.0139153
[74,] -40.1439153 -39.5939153
[75,] -40.1039153 -40.1439153
[76,] -38.3939153 -40.1039153
[77,] -37.1739153 -38.3939153
[78,] -35.6639153 -37.1739153
[79,] -34.5639153 -35.6639153
[80,] -33.6139153 -34.5639153
[81,] -33.4739153 -33.6139153
[82,] -32.7239153 -33.4739153
[83,] -32.6439153 -32.7239153
[84,] -32.3939153 -32.6439153
[85,] -31.2739153 -32.3939153
[86,] -32.5039153 -31.2739153
[87,] -31.5639153 -32.5039153
[88,] -30.5939153 -31.5639153
[89,] -29.4639153 -30.5939153
[90,] -28.4439153 -29.4639153
[91,] -27.1739153 -28.4439153
[92,] -25.9539153 -27.1739153
[93,] -26.0839153 -25.9539153
[94,] -25.2739153 -26.0839153
[95,] -24.9639153 -25.2739153
[96,] -24.2939153 -24.9639153
[97,] -24.2139153 -24.2939153
[98,] -23.7839153 -24.2139153
[99,] -21.8239153 -23.7839153
[100,] -22.3339153 -21.8239153
[101,] -20.3739153 -22.3339153
[102,] -19.3439153 -20.3739153
[103,] -17.5339153 -19.3439153
[104,] -16.3739153 -17.5339153
[105,] -16.1539153 -16.3739153
[106,] -14.5939153 -16.1539153
[107,] -13.9639153 -14.5939153
[108,] -13.3339153 -13.9639153
[109,] -11.7639153 -13.3339153
[110,] -11.0639153 -11.7639153
[111,] -10.8239153 -11.0639153
[112,] -8.7239153 -10.8239153
[113,] -6.7439153 -8.7239153
[114,] -5.9539153 -6.7439153
[115,] -4.6139153 -5.9539153
[116,] -3.4339153 -4.6139153
[117,] -2.7739153 -3.4339153
[118,] -1.8939153 -2.7739153
[119,] -0.5039153 -1.8939153
[120,] -0.8839153 -0.5039153
[121,] -0.4139153 -0.8839153
[122,] 1.2460847 -0.4139153
[123,] 2.2660847 1.2460847
[124,] 3.6060847 2.2660847
[125,] 5.7960847 3.6060847
[126,] 7.2360847 5.7960847
[127,] 9.7860847 7.2360847
[128,] 11.8160847 9.7860847
[129,] 13.3960847 11.8160847
[130,] 14.9860847 13.3960847
[131,] 16.1660847 14.9860847
[132,] 17.5560847 16.1660847
[133,] 18.1660847 17.5560847
[134,] 19.5760847 18.1660847
[135,] 21.2160847 19.5760847
[136,] 22.8660847 21.2160847
[137,] 24.8660847 22.8660847
[138,] 26.5060847 24.8660847
[139,] 28.9160847 26.5060847
[140,] 30.0060847 28.9160847
[141,] 32.6660847 30.0060847
[142,] 33.7960847 32.6660847
[143,] 35.4060847 33.7960847
[144,] 37.2260847 35.4060847
[145,] 40.2960847 37.2260847
[146,] 41.8460847 40.2960847
[147,] 44.7260847 41.8460847
[148,] 46.3960847 44.7260847
[149,] 48.4060847 46.3960847
[150,] 49.6860847 48.4060847
[151,] 52.9460847 49.6860847
[152,] 56.6060847 52.9460847
[153,] 59.4560847 56.6060847
[154,] 61.7460847 59.4560847
[155,] 64.4260847 61.7460847
[156,] 65.0960847 64.4260847
[157,] 69.0660847 65.0960847
[158,] 72.6260847 69.0660847
[159,] 72.4460847 72.6260847
[160,] 75.4860847 72.4460847
[161,] 78.2360847 75.4860847
[162,] 81.1060847 78.2360847
[163,] 86.5860847 81.1060847
[164,] 88.5060847 86.5860847
[165,] 91.7460847 88.5060847
[166,] 93.1360847 91.7460847
[167,] 98.5860847 93.1360847
[168,] 98.9660847 98.5860847
[169,] 100.4060847 98.9660847
[170,] 104.1560847 100.4060847
[171,] 105.0160847 104.1560847
[172,] 106.3960847 105.0160847
[173,] 107.7660847 106.3960847
[174,] 110.6160847 107.7660847
[175,] 111.9360847 110.6160847
[176,] 113.9060847 111.9360847
[177,] 114.5860847 113.9060847
[178,] 114.4360847 114.5860847
[179,] 114.8060847 114.4360847
[180,] 113.6660847 114.8060847
[181,] 113.6660847 113.6660847
[182,] 112.9460847 113.6660847
[183,] 115.0360847 112.9460847
[184,] 114.2060847 115.0360847
[185,] 119.0660847 114.2060847
[186,] 118.7960847 119.0660847
[187,] 117.7660847 118.7960847
[188,] 117.4660847 117.7660847
[189,] 48.0674074 117.4660847
[190,] 44.5474074 48.0674074
[191,] 42.5774074 44.5474074
[192,] 36.7874074 42.5774074
[193,] 30.1674074 36.7874074
[194,] 26.8174074 30.1674074
[195,] 20.5274074 26.8174074
[196,] 20.7474074 20.5274074
[197,] 14.0774074 20.7474074
[198,] 9.9174074 14.0774074
[199,] 7.9074074 9.9174074
[200,] 4.2274074 7.9074074
[201,] 0.0974074 4.2274074
[202,] -6.1425926 0.0974074
[203,] -10.4625926 -6.1425926
[204,] -17.0125926 -10.4625926
[205,] -23.7725926 -17.0125926
[206,] -26.1025926 -23.7725926
[207,] -30.5625926 -26.1025926
[208,] -25.2125926 -30.5625926
[209,] -28.5025926 -25.2125926
[210,] -29.1025926 -28.5025926
[211,] -24.6225926 -29.1025926
[212,] -22.6125926 -24.6225926
[213,] -20.4625926 -22.6125926
[214,] -20.9725926 -20.4625926
[215,] -20.9225926 -20.9725926
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -43.4239153 -43.5739153
2 -43.1639153 -43.4239153
3 -43.0039153 -43.1639153
4 -42.8539153 -43.0039153
5 -43.0839153 -42.8539153
6 -43.7839153 -43.0839153
7 -43.5839153 -43.7839153
8 -44.1039153 -43.5839153
9 -44.2239153 -44.1039153
10 -43.7239153 -44.2239153
11 -43.2839153 -43.7239153
12 -44.4839153 -43.2839153
13 -44.4139153 -44.4839153
14 -44.5839153 -44.4139153
15 -45.6739153 -44.5839153
16 -46.1839153 -45.6739153
17 -46.0239153 -46.1839153
18 -45.7239153 -46.0239153
19 -45.5339153 -45.7239153
20 -45.2839153 -45.5339153
21 -46.3939153 -45.2839153
22 -45.6939153 -46.3939153
23 -46.0039153 -45.6939153
24 -45.6639153 -46.0039153
25 -46.2839153 -45.6639153
26 -46.4839153 -46.2839153
27 -46.1439153 -46.4839153
28 -46.9039153 -46.1439153
29 -46.3839153 -46.9039153
30 -45.5139153 -46.3839153
31 -45.8439153 -45.5139153
32 -45.1739153 -45.8439153
33 -45.0639153 -45.1739153
34 -45.1639153 -45.0639153
35 -45.2239153 -45.1639153
36 -45.7239153 -45.2239153
37 -46.3839153 -45.7239153
38 -46.0239153 -46.3839153
39 -46.7339153 -46.0239153
40 -45.9339153 -46.7339153
41 -46.3839153 -45.9339153
42 -46.5139153 -46.3839153
43 -45.8539153 -46.5139153
44 -45.1839153 -45.8539153
45 -45.0839153 -45.1839153
46 -44.9039153 -45.0839153
47 -45.5139153 -44.9039153
48 -45.9339153 -45.5139153
49 -46.0839153 -45.9339153
50 -46.8139153 -46.0839153
51 -46.0639153 -46.8139153
52 -46.1239153 -46.0639153
53 -44.7839153 -46.1239153
54 -44.9239153 -44.7839153
55 -44.2239153 -44.9239153
56 -43.5939153 -44.2239153
57 -43.4139153 -43.5939153
58 -43.7739153 -43.4139153
59 -44.1039153 -43.7739153
60 -44.0039153 -44.1039153
61 -44.4239153 -44.0039153
62 -44.5739153 -44.4239153
63 -44.5239153 -44.5739153
64 -44.5239153 -44.5239153
65 -43.3539153 -44.5239153
66 -42.2839153 -43.3539153
67 -41.5139153 -42.2839153
68 -41.0939153 -41.5139153
69 -40.3139153 -41.0939153
70 -39.7639153 -40.3139153
71 -40.2339153 -39.7639153
72 -40.0139153 -40.2339153
73 -39.5939153 -40.0139153
74 -40.1439153 -39.5939153
75 -40.1039153 -40.1439153
76 -38.3939153 -40.1039153
77 -37.1739153 -38.3939153
78 -35.6639153 -37.1739153
79 -34.5639153 -35.6639153
80 -33.6139153 -34.5639153
81 -33.4739153 -33.6139153
82 -32.7239153 -33.4739153
83 -32.6439153 -32.7239153
84 -32.3939153 -32.6439153
85 -31.2739153 -32.3939153
86 -32.5039153 -31.2739153
87 -31.5639153 -32.5039153
88 -30.5939153 -31.5639153
89 -29.4639153 -30.5939153
90 -28.4439153 -29.4639153
91 -27.1739153 -28.4439153
92 -25.9539153 -27.1739153
93 -26.0839153 -25.9539153
94 -25.2739153 -26.0839153
95 -24.9639153 -25.2739153
96 -24.2939153 -24.9639153
97 -24.2139153 -24.2939153
98 -23.7839153 -24.2139153
99 -21.8239153 -23.7839153
100 -22.3339153 -21.8239153
101 -20.3739153 -22.3339153
102 -19.3439153 -20.3739153
103 -17.5339153 -19.3439153
104 -16.3739153 -17.5339153
105 -16.1539153 -16.3739153
106 -14.5939153 -16.1539153
107 -13.9639153 -14.5939153
108 -13.3339153 -13.9639153
109 -11.7639153 -13.3339153
110 -11.0639153 -11.7639153
111 -10.8239153 -11.0639153
112 -8.7239153 -10.8239153
113 -6.7439153 -8.7239153
114 -5.9539153 -6.7439153
115 -4.6139153 -5.9539153
116 -3.4339153 -4.6139153
117 -2.7739153 -3.4339153
118 -1.8939153 -2.7739153
119 -0.5039153 -1.8939153
120 -0.8839153 -0.5039153
121 -0.4139153 -0.8839153
122 1.2460847 -0.4139153
123 2.2660847 1.2460847
124 3.6060847 2.2660847
125 5.7960847 3.6060847
126 7.2360847 5.7960847
127 9.7860847 7.2360847
128 11.8160847 9.7860847
129 13.3960847 11.8160847
130 14.9860847 13.3960847
131 16.1660847 14.9860847
132 17.5560847 16.1660847
133 18.1660847 17.5560847
134 19.5760847 18.1660847
135 21.2160847 19.5760847
136 22.8660847 21.2160847
137 24.8660847 22.8660847
138 26.5060847 24.8660847
139 28.9160847 26.5060847
140 30.0060847 28.9160847
141 32.6660847 30.0060847
142 33.7960847 32.6660847
143 35.4060847 33.7960847
144 37.2260847 35.4060847
145 40.2960847 37.2260847
146 41.8460847 40.2960847
147 44.7260847 41.8460847
148 46.3960847 44.7260847
149 48.4060847 46.3960847
150 49.6860847 48.4060847
151 52.9460847 49.6860847
152 56.6060847 52.9460847
153 59.4560847 56.6060847
154 61.7460847 59.4560847
155 64.4260847 61.7460847
156 65.0960847 64.4260847
157 69.0660847 65.0960847
158 72.6260847 69.0660847
159 72.4460847 72.6260847
160 75.4860847 72.4460847
161 78.2360847 75.4860847
162 81.1060847 78.2360847
163 86.5860847 81.1060847
164 88.5060847 86.5860847
165 91.7460847 88.5060847
166 93.1360847 91.7460847
167 98.5860847 93.1360847
168 98.9660847 98.5860847
169 100.4060847 98.9660847
170 104.1560847 100.4060847
171 105.0160847 104.1560847
172 106.3960847 105.0160847
173 107.7660847 106.3960847
174 110.6160847 107.7660847
175 111.9360847 110.6160847
176 113.9060847 111.9360847
177 114.5860847 113.9060847
178 114.4360847 114.5860847
179 114.8060847 114.4360847
180 113.6660847 114.8060847
181 113.6660847 113.6660847
182 112.9460847 113.6660847
183 115.0360847 112.9460847
184 114.2060847 115.0360847
185 119.0660847 114.2060847
186 118.7960847 119.0660847
187 117.7660847 118.7960847
188 117.4660847 117.7660847
189 48.0674074 117.4660847
190 44.5474074 48.0674074
191 42.5774074 44.5474074
192 36.7874074 42.5774074
193 30.1674074 36.7874074
194 26.8174074 30.1674074
195 20.5274074 26.8174074
196 20.7474074 20.5274074
197 14.0774074 20.7474074
198 9.9174074 14.0774074
199 7.9074074 9.9174074
200 4.2274074 7.9074074
201 0.0974074 4.2274074
202 -6.1425926 0.0974074
203 -10.4625926 -6.1425926
204 -17.0125926 -10.4625926
205 -23.7725926 -17.0125926
206 -26.1025926 -23.7725926
207 -30.5625926 -26.1025926
208 -25.2125926 -30.5625926
209 -28.5025926 -25.2125926
210 -29.1025926 -28.5025926
211 -24.6225926 -29.1025926
212 -22.6125926 -24.6225926
213 -20.4625926 -22.6125926
214 -20.9725926 -20.4625926
215 -20.9225926 -20.9725926
> 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/7fbqb1261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/84tuj1261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rjw71261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ka681261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/111lt71261239931.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/12zp4w1261239931.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/13t3cm1261239931.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/14w9u41261239931.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/153hm01261239931.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/16ceh21261239932.tab")
+ }
>
> try(system("convert tmp/1paie1261239931.ps tmp/1paie1261239931.png",intern=TRUE))
character(0)
> try(system("convert tmp/2r44r1261239931.ps tmp/2r44r1261239931.png",intern=TRUE))
character(0)
> try(system("convert tmp/37m941261239931.ps tmp/37m941261239931.png",intern=TRUE))
character(0)
> try(system("convert tmp/4lbsj1261239931.ps tmp/4lbsj1261239931.png",intern=TRUE))
character(0)
> try(system("convert tmp/51pq91261239931.ps tmp/51pq91261239931.png",intern=TRUE))
character(0)
> try(system("convert tmp/6w0oh1261239931.ps tmp/6w0oh1261239931.png",intern=TRUE))
character(0)
> try(system("convert tmp/7fbqb1261239931.ps tmp/7fbqb1261239931.png",intern=TRUE))
character(0)
> try(system("convert tmp/84tuj1261239931.ps tmp/84tuj1261239931.png",intern=TRUE))
character(0)
> try(system("convert tmp/9rjw71261239931.ps tmp/9rjw71261239931.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ka681261239931.ps tmp/10ka681261239931.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.774 1.730 5.565