R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(1418
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+ ,42)
+ ,dim=c(5
+ ,237)
+ ,dimnames=list(c('pageviews'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr
')
+ ,1:237))
> y <- array(NA,dim=c(5,237),dimnames=list(c('pageviews','time_in_rfc','logins','compendium_views_info','compendium_views_pr
'),1:237))
> 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
> 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
pageviews time_in_rfc logins compendium_views_info compendium_views_pr\r
1 1418 210907 56 396 81
2 869 120982 56 297 55
3 1530 176508 54 559 50
4 2172 179321 89 967 125
5 901 123185 40 270 40
6 463 52746 25 143 37
7 3201 385534 92 1562 63
8 371 33170 18 109 44
9 1192 101645 63 371 88
10 1583 149061 44 656 66
11 1439 165446 33 511 57
12 1764 237213 84 655 74
13 1495 173326 88 465 49
14 1373 133131 55 525 52
15 2187 258873 60 885 88
16 1491 180083 66 497 36
17 4041 324799 154 1436 108
18 1706 230964 53 612 43
19 2152 236785 119 865 75
20 1036 135473 41 385 32
21 1882 202925 61 567 44
22 1929 215147 58 639 85
23 2242 344297 75 963 86
24 1220 153935 33 398 56
25 1289 132943 40 410 50
26 2515 174724 92 966 135
27 2147 174415 100 801 63
28 2352 225548 112 892 81
29 1638 223632 73 513 52
30 1222 124817 40 469 44
31 1812 221698 45 683 113
32 1677 210767 60 643 39
33 1579 170266 62 535 73
34 1731 260561 75 625 48
35 807 84853 31 264 33
36 2452 294424 77 992 59
37 829 101011 34 238 41
38 1940 215641 46 818 69
39 2662 325107 99 937 64
40 186 7176 17 70 1
41 1499 167542 66 507 59
42 865 106408 30 260 32
43 1793 96560 76 503 129
44 2527 265769 146 927 37
45 2747 269651 67 1269 31
46 1324 149112 56 537 65
47 2702 175824 107 910 107
48 1383 152871 58 532 74
49 1179 111665 34 345 54
50 2099 116408 61 918 76
51 4308 362301 119 1635 715
52 918 78800 42 330 57
53 1831 183167 66 557 66
54 3373 277965 89 1178 106
55 1713 150629 44 740 54
56 1438 168809 66 452 32
57 496 24188 24 218 20
58 2253 329267 259 764 71
59 744 65029 17 255 21
60 1161 101097 64 454 70
61 2352 218946 41 866 112
62 2144 244052 68 574 66
63 4691 341570 168 1276 190
64 1112 103597 43 379 66
65 2694 233328 132 825 165
66 1973 256462 105 798 56
67 1769 206161 71 663 61
68 3148 311473 112 1069 53
69 2474 235800 94 921 127
70 2084 177939 82 858 63
71 1954 207176 70 711 38
72 1226 196553 57 503 50
73 1389 174184 53 382 52
74 1496 143246 103 464 42
75 2269 187559 121 717 76
76 1833 187681 62 690 67
77 1268 119016 52 462 50
78 1943 182192 52 657 53
79 893 73566 32 385 39
80 1762 194979 62 577 50
81 1403 167488 45 619 77
82 1425 143756 46 479 57
83 1857 275541 63 817 73
84 1840 243199 75 752 34
85 1502 182999 88 430 39
86 1441 135649 46 451 46
87 1420 152299 53 537 63
88 1416 120221 37 519 35
89 2970 346485 90 1000 106
90 1317 145790 63 637 43
91 1644 193339 78 465 47
92 870 80953 25 437 31
93 1654 122774 45 711 162
94 1054 130585 46 299 57
95 937 112611 41 248 36
96 3004 286468 144 1162 263
97 2008 241066 82 714 78
98 2547 148446 91 905 63
99 1885 204713 71 649 54
100 1626 182079 63 512 63
101 1468 140344 53 472 77
102 2445 220516 62 905 79
103 1964 243060 63 786 110
104 1381 162765 32 489 56
105 1369 182613 39 479 56
106 1659 232138 62 617 43
107 2888 265318 117 925 111
108 1290 85574 34 351 71
109 2845 310839 92 1144 62
110 1982 225060 93 669 56
111 1904 232317 54 707 74
112 1391 144966 144 458 60
113 602 43287 14 214 43
114 1743 155754 61 599 68
115 1559 164709 109 572 53
116 2014 201940 38 897 87
117 2143 235454 73 819 46
118 2146 220801 75 720 105
119 874 99466 50 273 32
120 1590 92661 61 508 133
121 1590 133328 55 506 79
122 1210 61361 77 451 51
123 2072 125930 75 699 207
124 1281 100750 72 407 67
125 1401 224549 50 465 47
126 834 82316 32 245 34
127 1105 102010 53 370 66
128 1272 101523 42 316 76
129 1944 243511 71 603 65
130 391 22938 10 154 9
131 761 41566 35 229 42
132 1605 152474 65 577 45
133 530 61857 25 192 25
134 1988 99923 66 617 115
135 1386 132487 41 411 97
136 2395 317394 86 975 53
137 387 21054 16 146 2
138 1742 209641 42 705 52
139 620 22648 19 184 44
140 449 31414 19 200 22
141 800 46698 45 274 35
142 1684 131698 65 502 74
143 1050 91735 35 382 103
144 2699 244749 95 964 144
145 1606 184510 49 537 60
146 1502 79863 37 438 134
147 1204 128423 64 369 89
148 1138 97839 38 417 42
149 568 38214 34 276 52
150 1459 151101 32 514 98
151 2158 272458 65 822 99
152 1111 172494 52 389 52
153 1421 108043 62 466 29
154 2833 328107 65 1255 125
155 1955 250579 83 694 106
156 2922 351067 95 1024 95
157 1002 158015 29 400 40
158 1060 98866 18 397 140
159 956 85439 33 350 43
160 2186 229242 247 719 128
161 3604 351619 139 1277 142
162 1035 84207 29 356 73
163 1417 120445 118 457 72
164 3261 324598 110 1402 128
165 1587 131069 67 600 61
166 1424 204271 42 480 73
167 1701 165543 65 595 148
168 1249 141722 94 436 64
169 946 116048 64 230 45
170 1926 250047 81 651 58
171 3352 299775 95 1367 97
172 1641 195838 67 564 50
173 2035 173260 63 716 37
174 2312 254488 83 747 50
175 1369 104389 45 467 105
176 1577 136084 30 671 69
177 2201 199476 70 861 46
178 961 92499 32 319 57
179 1900 224330 83 612 52
180 1254 135781 31 433 98
181 1335 74408 67 434 61
182 1597 81240 66 503 89
183 207 14688 10 85 0
184 1645 181633 70 564 48
185 2429 271856 103 824 91
186 151 7199 5 74 0
187 474 46660 20 259 7
188 141 17547 5 69 3
189 1639 133368 36 535 54
190 872 95227 34 239 70
191 1318 152601 48 438 36
192 1018 98146 40 459 37
193 1383 79619 43 426 123
194 1314 59194 31 288 247
195 1335 139942 42 498 46
196 1403 118612 46 454 72
197 910 72880 33 376 41
198 616 65475 18 225 24
199 1407 99643 55 555 45
200 771 71965 35 252 33
201 766 77272 59 208 27
202 473 49289 19 130 36
203 1376 135131 66 481 87
204 1232 108446 60 389 90
205 1521 89746 36 565 114
206 572 44296 25 173 31
207 1059 77648 47 278 45
208 1544 181528 54 609 69
209 1230 134019 53 422 51
210 1206 124064 40 445 34
211 1205 92630 40 387 60
212 1255 121848 39 339 45
213 613 52915 14 181 54
214 721 81872 45 245 25
215 1109 58981 36 384 38
216 740 53515 28 212 52
217 1126 60812 44 399 67
218 728 56375 30 229 74
219 689 65490 22 224 38
220 592 80949 17 203 30
221 995 76302 31 333 26
222 1613 104011 55 384 67
223 2048 98104 54 636 132
224 705 67989 21 185 42
225 301 30989 14 93 35
226 1803 135458 81 581 118
227 799 73504 35 248 68
228 861 63123 43 304 43
229 1186 61254 46 344 76
230 1451 74914 30 407 64
231 628 31774 23 170 48
232 1161 81437 38 312 64
233 1463 87186 54 507 56
234 742 50090 20 224 71
235 979 65745 53 340 75
236 675 56653 45 168 39
237 1241 158399 39 443 42
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc logins
1.150e+02 1.144e-03 3.133e+00
compendium_views_info `compendium_views_pr\r`
1.793e+00 1.302e+00
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-525.17 -91.21 -9.45 84.85 1124.39
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.150e+02 2.597e+01 4.428 1.47e-05 ***
time_in_rfc 1.144e-03 3.085e-04 3.709 0.000261 ***
logins 3.133e+00 4.720e-01 6.637 2.23e-10 ***
compendium_views_info 1.793e+00 9.140e-02 19.611 < 2e-16 ***
`compendium_views_pr\r` 1.302e+00 2.407e-01 5.407 1.59e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 176.2 on 232 degrees of freedom
Multiple R-squared: 0.9446, Adjusted R-squared: 0.9436
F-statistic: 988 on 4 and 232 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,] 0.19235181 3.847036e-01 8.076482e-01
[2,] 0.11723026 2.344605e-01 8.827697e-01
[3,] 0.08202480 1.640496e-01 9.179752e-01
[4,] 0.04652360 9.304721e-02 9.534764e-01
[5,] 0.02097882 4.195764e-02 9.790212e-01
[6,] 0.04605508 9.211015e-02 9.539449e-01
[7,] 0.03021474 6.042948e-02 9.697853e-01
[8,] 0.01621157 3.242314e-02 9.837884e-01
[9,] 0.01342223 2.684446e-02 9.865778e-01
[10,] 0.50824605 9.835079e-01 4.917540e-01
[11,] 0.45241755 9.048351e-01 5.475824e-01
[12,] 0.61177090 7.764582e-01 3.882291e-01
[13,] 0.53710609 9.257878e-01 4.628939e-01
[14,] 0.68303757 6.339249e-01 3.169624e-01
[15,] 0.67637101 6.472580e-01 3.236290e-01
[16,] 0.75750146 4.849971e-01 2.424985e-01
[17,] 0.72337134 5.532573e-01 2.766287e-01
[18,] 0.70555544 5.888891e-01 2.944446e-01
[19,] 0.66491102 6.701780e-01 3.350890e-01
[20,] 0.60532852 7.893430e-01 3.946715e-01
[21,] 0.55306735 8.938653e-01 4.469327e-01
[22,] 0.49402843 9.880569e-01 5.059716e-01
[23,] 0.43432716 8.686543e-01 5.656728e-01
[24,] 0.37820178 7.564036e-01 6.217982e-01
[25,] 0.32403867 6.480773e-01 6.759613e-01
[26,] 0.27536101 5.507220e-01 7.246390e-01
[27,] 0.23986645 4.797329e-01 7.601336e-01
[28,] 0.19740277 3.948055e-01 8.025972e-01
[29,] 0.16430393 3.286079e-01 8.356961e-01
[30,] 0.13197197 2.639439e-01 8.680280e-01
[31,] 0.10745252 2.149050e-01 8.925475e-01
[32,] 0.10123605 2.024721e-01 8.987640e-01
[33,] 0.08388348 1.677670e-01 9.161165e-01
[34,] 0.06478906 1.295781e-01 9.352109e-01
[35,] 0.05131278 1.026256e-01 9.486872e-01
[36,] 0.06064528 1.212906e-01 9.393547e-01
[37,] 0.04965964 9.931929e-02 9.503404e-01
[38,] 0.04561918 9.123835e-02 9.543808e-01
[39,] 0.04507348 9.014696e-02 9.549265e-01
[40,] 0.07072199 1.414440e-01 9.292780e-01
[41,] 0.06474915 1.294983e-01 9.352508e-01
[42,] 0.06620589 1.324118e-01 9.337941e-01
[43,] 0.05329389 1.065878e-01 9.467061e-01
[44,] 0.12366034 2.473207e-01 8.763397e-01
[45,] 0.10659950 2.131990e-01 8.934005e-01
[46,] 0.13021279 2.604256e-01 8.697872e-01
[47,] 0.43296428 8.659286e-01 5.670357e-01
[48,] 0.39386938 7.877388e-01 6.061306e-01
[49,] 0.35609614 7.121923e-01 6.439039e-01
[50,] 0.33828113 6.765623e-01 6.617189e-01
[51,] 0.73463784 5.307243e-01 2.653622e-01
[52,] 0.69815481 6.036904e-01 3.018452e-01
[53,] 0.69293261 6.141348e-01 3.070674e-01
[54,] 0.69720981 6.055804e-01 3.027902e-01
[55,] 0.86407016 2.718597e-01 1.359298e-01
[56,] 0.99999974 5.165134e-07 2.582567e-07
[57,] 0.99999957 8.640791e-07 4.320395e-07
[58,] 0.99999960 8.099257e-07 4.049628e-07
[59,] 0.99999977 4.682921e-07 2.341460e-07
[60,] 0.99999963 7.335867e-07 3.667933e-07
[61,] 0.99999990 1.971463e-07 9.857316e-08
[62,] 0.99999983 3.310578e-07 1.655289e-07
[63,] 0.99999976 4.718318e-07 2.359159e-07
[64,] 0.99999963 7.340247e-07 3.670123e-07
[65,] 0.99999977 4.534446e-07 2.267223e-07
[66,] 0.99999975 5.039429e-07 2.519714e-07
[67,] 0.99999959 8.262766e-07 4.131383e-07
[68,] 0.99999959 8.117019e-07 4.058509e-07
[69,] 0.99999934 1.328725e-06 6.643624e-07
[70,] 0.99999894 2.128695e-06 1.064348e-06
[71,] 0.99999915 1.707705e-06 8.538526e-07
[72,] 0.99999895 2.098716e-06 1.049358e-06
[73,] 0.99999872 2.563604e-06 1.281802e-06
[74,] 0.99999920 1.591835e-06 7.959174e-07
[75,] 0.99999882 2.351677e-06 1.175839e-06
[76,] 0.99999965 7.013271e-07 3.506636e-07
[77,] 0.99999964 7.181001e-07 3.590500e-07
[78,] 0.99999949 1.028238e-06 5.141188e-07
[79,] 0.99999946 1.089202e-06 5.446008e-07
[80,] 0.99999920 1.604336e-06 8.021682e-07
[81,] 0.99999884 2.329268e-06 1.164634e-06
[82,] 0.99999922 1.555408e-06 7.777038e-07
[83,] 0.99999982 3.556528e-07 1.778264e-07
[84,] 0.99999983 3.447512e-07 1.723756e-07
[85,] 0.99999989 2.252070e-07 1.126035e-07
[86,] 0.99999994 1.163513e-07 5.817563e-08
[87,] 0.99999991 1.879205e-07 9.396026e-08
[88,] 0.99999986 2.728458e-07 1.364229e-07
[89,] 0.99999998 3.568403e-08 1.784202e-08
[90,] 0.99999997 6.045469e-08 3.022734e-08
[91,] 0.99999999 2.340533e-08 1.170266e-08
[92,] 0.99999998 3.433231e-08 1.716616e-08
[93,] 0.99999998 4.620509e-08 2.310254e-08
[94,] 0.99999997 6.983144e-08 3.491572e-08
[95,] 0.99999996 7.620374e-08 3.810187e-08
[96,] 0.99999997 5.730821e-08 2.865411e-08
[97,] 0.99999995 9.491222e-08 4.745611e-08
[98,] 0.99999992 1.585953e-07 7.929765e-08
[99,] 0.99999988 2.434403e-07 1.217201e-07
[100,] 0.99999996 7.815500e-08 3.907750e-08
[101,] 0.99999998 4.171912e-08 2.085956e-08
[102,] 0.99999997 6.947700e-08 3.473850e-08
[103,] 0.99999995 1.056675e-07 5.283376e-08
[104,] 0.99999991 1.757384e-07 8.786918e-08
[105,] 0.99999993 1.345203e-07 6.726014e-08
[106,] 0.99999989 2.146756e-07 1.073378e-07
[107,] 0.99999985 2.967513e-07 1.483756e-07
[108,] 0.99999984 3.202286e-07 1.601143e-07
[109,] 0.99999988 2.455960e-07 1.227980e-07
[110,] 0.99999980 4.056150e-07 2.028075e-07
[111,] 0.99999972 5.528493e-07 2.764246e-07
[112,] 0.99999955 8.981945e-07 4.490972e-07
[113,] 0.99999934 1.314101e-06 6.570504e-07
[114,] 0.99999923 1.539634e-06 7.698170e-07
[115,] 0.99999887 2.260524e-06 1.130262e-06
[116,] 0.99999840 3.199837e-06 1.599918e-06
[117,] 0.99999747 5.063780e-06 2.531890e-06
[118,] 0.99999602 7.960604e-06 3.980302e-06
[119,] 0.99999407 1.185215e-05 5.926077e-06
[120,] 0.99999107 1.786995e-05 8.934974e-06
[121,] 0.99999445 1.109642e-05 5.548212e-06
[122,] 0.99999500 1.000546e-05 5.002732e-06
[123,] 0.99999257 1.486980e-05 7.434898e-06
[124,] 0.99998865 2.270330e-05 1.135165e-05
[125,] 0.99998291 3.417242e-05 1.708621e-05
[126,] 0.99997732 4.535935e-05 2.267967e-05
[127,] 0.99998883 2.233223e-05 1.116611e-05
[128,] 0.99998588 2.824763e-05 1.412381e-05
[129,] 0.99998497 3.006486e-05 1.503243e-05
[130,] 0.99997778 4.444731e-05 2.222365e-05
[131,] 0.99996959 6.082318e-05 3.041159e-05
[132,] 0.99995464 9.072431e-05 4.536215e-05
[133,] 0.99995001 9.998769e-05 4.999384e-05
[134,] 0.99992638 1.472416e-04 7.362082e-05
[135,] 0.99994726 1.054839e-04 5.274194e-05
[136,] 0.99993897 1.220628e-04 6.103141e-05
[137,] 0.99991426 1.714817e-04 8.574085e-05
[138,] 0.99988613 2.277455e-04 1.138727e-04
[139,] 0.99989548 2.090364e-04 1.045182e-04
[140,] 0.99984749 3.050209e-04 1.525105e-04
[141,] 0.99977591 4.481712e-04 2.240856e-04
[142,] 0.99988454 2.309185e-04 1.154593e-04
[143,] 0.99983012 3.397595e-04 1.698798e-04
[144,] 0.99977670 4.465978e-04 2.232989e-04
[145,] 0.99973421 5.315713e-04 2.657857e-04
[146,] 0.99970219 5.956264e-04 2.978132e-04
[147,] 0.99993899 1.220186e-04 6.100931e-05
[148,] 0.99992680 1.463903e-04 7.319517e-05
[149,] 0.99990823 1.835323e-04 9.176616e-05
[150,] 0.99991672 1.665641e-04 8.328206e-05
[151,] 0.99994863 1.027432e-04 5.137159e-05
[152,] 0.99992436 1.512777e-04 7.563886e-05
[153,] 0.99998710 2.579943e-05 1.289972e-05
[154,] 0.99998346 3.307416e-05 1.653708e-05
[155,] 0.99997399 5.202375e-05 2.601187e-05
[156,] 0.99997473 5.054898e-05 2.527449e-05
[157,] 0.99999714 5.720252e-06 2.860126e-06
[158,] 0.99999598 8.048121e-06 4.024061e-06
[159,] 0.99999341 1.318048e-05 6.590241e-06
[160,] 0.99999542 9.153444e-06 4.576722e-06
[161,] 0.99999860 2.805815e-06 1.402907e-06
[162,] 0.99999758 4.842447e-06 2.421223e-06
[163,] 0.99999600 7.996585e-06 3.998292e-06
[164,] 0.99999582 8.351861e-06 4.175930e-06
[165,] 0.99999311 1.378224e-05 6.891121e-06
[166,] 0.99999346 1.308012e-05 6.540058e-06
[167,] 0.99999556 8.876357e-06 4.438179e-06
[168,] 0.99999325 1.350667e-05 6.753335e-06
[169,] 0.99999208 1.583414e-05 7.917070e-06
[170,] 0.99998691 2.617372e-05 1.308686e-05
[171,] 0.99997792 4.416773e-05 2.208386e-05
[172,] 0.99996711 6.577759e-05 3.288880e-05
[173,] 0.99995318 9.363710e-05 4.681855e-05
[174,] 0.99992389 1.522188e-04 7.610940e-05
[175,] 0.99989349 2.130266e-04 1.065133e-04
[176,] 0.99983283 3.343358e-04 1.671679e-04
[177,] 0.99973143 5.371390e-04 2.685695e-04
[178,] 0.99958864 8.227178e-04 4.113589e-04
[179,] 0.99938200 1.235993e-03 6.179966e-04
[180,] 0.99955229 8.954154e-04 4.477077e-04
[181,] 0.99939047 1.219051e-03 6.095257e-04
[182,] 0.99957572 8.485695e-04 4.242847e-04
[183,] 0.99932269 1.354617e-03 6.773084e-04
[184,] 0.99902830 1.943398e-03 9.716989e-04
[185,] 0.99948570 1.028600e-03 5.143001e-04
[186,] 0.99920077 1.598456e-03 7.992280e-04
[187,] 0.99890030 2.199395e-03 1.099697e-03
[188,] 0.99829924 3.401527e-03 1.700763e-03
[189,] 0.99750426 4.991475e-03 2.495738e-03
[190,] 0.99754097 4.918065e-03 2.459032e-03
[191,] 0.99639599 7.208025e-03 3.604013e-03
[192,] 0.99614802 7.703969e-03 3.851984e-03
[193,] 0.99421589 1.156822e-02 5.784110e-03
[194,] 0.99123301 1.753397e-02 8.766987e-03
[195,] 0.98702042 2.595917e-02 1.297958e-02
[196,] 0.98579567 2.840865e-02 1.420433e-02
[197,] 0.98120606 3.758789e-02 1.879394e-02
[198,] 0.98197104 3.605792e-02 1.802896e-02
[199,] 0.97367245 5.265509e-02 2.632755e-02
[200,] 0.97280460 5.439080e-02 2.719540e-02
[201,] 0.98705947 2.588107e-02 1.294053e-02
[202,] 0.98303284 3.393432e-02 1.696716e-02
[203,] 0.98029028 3.941944e-02 1.970972e-02
[204,] 0.97047667 5.904666e-02 2.952333e-02
[205,] 0.97294373 5.411253e-02 2.705627e-02
[206,] 0.95931466 8.137068e-02 4.068534e-02
[207,] 0.94261061 1.147788e-01 5.738939e-02
[208,] 0.91759003 1.648199e-01 8.240997e-02
[209,] 0.88375395 2.324921e-01 1.162460e-01
[210,] 0.86939961 2.612008e-01 1.306004e-01
[211,] 0.83831147 3.233771e-01 1.616885e-01
[212,] 0.78428771 4.314246e-01 2.157123e-01
[213,] 0.73101542 5.379692e-01 2.689846e-01
[214,] 0.65188076 6.962385e-01 3.481192e-01
[215,] 0.96214051 7.571897e-02 3.785949e-02
[216,] 0.93670152 1.265970e-01 6.329848e-02
[217,] 0.90429365 1.914127e-01 9.570635e-02
[218,] 0.86961600 2.607680e-01 1.303840e-01
[219,] 0.79663949 4.067210e-01 2.033605e-01
[220,] 0.70020110 5.995978e-01 2.997989e-01
[221,] 0.62613595 7.477281e-01 3.738641e-01
[222,] 0.49303004 9.860601e-01 5.069700e-01
> postscript(file="/var/wessaorg/rcomp/tmp/12w6t1323861281.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2liiq1323861281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3afnz1323861281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4cmzr1323861281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5t5sj1323861281.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 = 237
Frequency = 1
1 2 3 4 5
71.03467614 -163.78901554 -23.17859274 -323.01664975 -16.26228137
6 7 8 9 10
-95.13326095 -525.17317052 -90.97462891 -16.19781951 -102.15291531
11 12 13 14 15
41.19413302 -155.92945590 8.74670015 -75.34568316 -113.02592388
16 17 18 19 20
25.49795989 357.36068087 7.76435947 -254.81868506 -94.17987204
21 22 23 24 25
270.14075076 130.12823466 -339.95575259 39.21973702 96.60461970
26 27 28 29 30
4.62017871 1.39607013 -76.24228032 51.24221152 -59.04850896
31 32 33 34 35
-68.95706223 -70.42149873 20.98313256 -99.82627728 -18.34919906
36 37 38 39 40
-96.00595016 11.96044151 -121.87973782 102.05280798 -117.22605201
41 42 43 44 45
-0.01806502 26.59649912 259.91298793 -59.23535374 -201.42207494
46 47 48 49 50
-184.19219211 280.19755678 -138.51007976 141.05077929 -84.71322931
51 52 53 54 55
-455.69969685 -84.43096306 215.36927057 411.64319983 -108.89927115
56 57 58 59 60
71.26556858 -138.64196014 -511.95292067 16.94040343 -175.05391174
61 62 63 64 65
159.99163118 421.97868312 1124.38616187 -21.47985446 204.96407671
66 67 68 69 70
-267.64005992 -72.09915388 340.62863764 -21.43921634 -111.41959711
71 72 73 74 75
58.76880552 -259.12679849 156.28666070 8.07056634 176.22229253
76 77 78 79 80
-14.97126725 -39.26749322 210.01201013 -147.27515954 130.36309840
81 82 83 84 85
-254.36058788 68.64227681 -330.07602408 -180.39216550 80.43560071
86 87 88 89 90
158.42535498 -79.83654074 71.69599310 246.19356191 -359.93783245
91 92 93 94 95
168.78284679 -239.59477570 -227.75937047 35.36452415 73.34366709
96 97 98 99 100
-315.06247283 -21.03731670 272.87663415 79.76415935 105.58080738
101 102 103 104 105
80.13122267 158.45294342 -178.51011391 30.13115546 -8.57893973
106 107 108 109 110
-77.73619879 300.39482460 249.01579556 -45.14495420 46.11269533
111 112 113 114 115
-9.55688678 -240.01470890 -45.93096910 96.50405291 -180.19037611
116 117 118 119 120
-172.18273997 2.01473660 116.17578785 -42.42001356 94.19571697
121 122 123 124 125
140.34280459 -91.21343425 55.58400026 8.43457057 -22.20382834
126 127 128 129 130
41.17671177 -41.85924261 243.93834904 162.51767019 -69.31361543
131 132 133 134 135
23.66354047 19.09847350 -110.77035600 296.26829144 128.02415340
136 137 138 139 140
-169.19563362 -66.50326240 -75.80147405 32.49026319 -148.58244481
141 142 143 144 145
-46.08731204 218.55815205 -98.38574311 90.98399756 85.75020830
146 147 148 149 150
220.19809289 -35.68105581 -10.10566660 -259.63409908 21.99289412
151 152 153 154 155
-74.61975324 -129.19490659 115.12214534 -273.28820917 -88.64815633
156 157 158 159 160
148.58531459 -153.67559899 -118.33495737 -43.45869928 -420.46119520
161 162 163 164 165
177.42626859 -0.32244259 -118.33803738 -249.65456006 -42.73410618
166 167 168 169 170
-11.67418746 -66.18625093 -187.43634406 26.90893573 28.78307093
171 172 173 174 175
19.82337599 16.01942476 192.83688300 241.76763765 19.84251986
176 177 178 179 180
-80.24139276 35.28557453 -6.05711690 103.65597945 -17.15373118
181 182 183 184 185
67.64510447 164.83202236 -108.47664663 29.47484607 84.85191714
186 187 188 189 190
-120.52766251 -230.39106764 -137.30799354 229.37718017 22.03737022
191 192 193 194 195
46.08601619 -205.50032238 118.50893833 196.43407837 -24.20348273
196 197 198 199 200
100.69550813 -119.09367844 -64.83170470 -47.69992789 -30.62613976
201 202 203 204 205
-30.20270483 -37.77741213 -75.78015127 -9.44857361 29.40664308
206 207 208 209 210
-22.43247916 151.05407162 -129.27881174 -27.16420139 -18.15010675
211 212 213 214 215
86.93422828 212.20753037 -1.10997260 -100.32657610 75.97310674
216 217 218 219 220
28.37989264 1.18103707 -52.26637039 -20.81028328 -71.77534945
221 222 223 224 225
64.86024411 431.18909569 339.75660086 60.16561583 -105.55338880
226 227 228 229 230
84.25101134 -42.77386272 -61.80075706 141.28408350 343.47181942
231 232 233 234 235
37.40793653 191.23740540 97.40684634 13.11881340 -84.31120709
236 237
2.32544556 -26.12442622
> postscript(file="/var/wessaorg/rcomp/tmp/63yk01323861281.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 = 237
Frequency = 1
lag(myerror, k = 1) myerror
0 71.03467614 NA
1 -163.78901554 71.03467614
2 -23.17859274 -163.78901554
3 -323.01664975 -23.17859274
4 -16.26228137 -323.01664975
5 -95.13326095 -16.26228137
6 -525.17317052 -95.13326095
7 -90.97462891 -525.17317052
8 -16.19781951 -90.97462891
9 -102.15291531 -16.19781951
10 41.19413302 -102.15291531
11 -155.92945590 41.19413302
12 8.74670015 -155.92945590
13 -75.34568316 8.74670015
14 -113.02592388 -75.34568316
15 25.49795989 -113.02592388
16 357.36068087 25.49795989
17 7.76435947 357.36068087
18 -254.81868506 7.76435947
19 -94.17987204 -254.81868506
20 270.14075076 -94.17987204
21 130.12823466 270.14075076
22 -339.95575259 130.12823466
23 39.21973702 -339.95575259
24 96.60461970 39.21973702
25 4.62017871 96.60461970
26 1.39607013 4.62017871
27 -76.24228032 1.39607013
28 51.24221152 -76.24228032
29 -59.04850896 51.24221152
30 -68.95706223 -59.04850896
31 -70.42149873 -68.95706223
32 20.98313256 -70.42149873
33 -99.82627728 20.98313256
34 -18.34919906 -99.82627728
35 -96.00595016 -18.34919906
36 11.96044151 -96.00595016
37 -121.87973782 11.96044151
38 102.05280798 -121.87973782
39 -117.22605201 102.05280798
40 -0.01806502 -117.22605201
41 26.59649912 -0.01806502
42 259.91298793 26.59649912
43 -59.23535374 259.91298793
44 -201.42207494 -59.23535374
45 -184.19219211 -201.42207494
46 280.19755678 -184.19219211
47 -138.51007976 280.19755678
48 141.05077929 -138.51007976
49 -84.71322931 141.05077929
50 -455.69969685 -84.71322931
51 -84.43096306 -455.69969685
52 215.36927057 -84.43096306
53 411.64319983 215.36927057
54 -108.89927115 411.64319983
55 71.26556858 -108.89927115
56 -138.64196014 71.26556858
57 -511.95292067 -138.64196014
58 16.94040343 -511.95292067
59 -175.05391174 16.94040343
60 159.99163118 -175.05391174
61 421.97868312 159.99163118
62 1124.38616187 421.97868312
63 -21.47985446 1124.38616187
64 204.96407671 -21.47985446
65 -267.64005992 204.96407671
66 -72.09915388 -267.64005992
67 340.62863764 -72.09915388
68 -21.43921634 340.62863764
69 -111.41959711 -21.43921634
70 58.76880552 -111.41959711
71 -259.12679849 58.76880552
72 156.28666070 -259.12679849
73 8.07056634 156.28666070
74 176.22229253 8.07056634
75 -14.97126725 176.22229253
76 -39.26749322 -14.97126725
77 210.01201013 -39.26749322
78 -147.27515954 210.01201013
79 130.36309840 -147.27515954
80 -254.36058788 130.36309840
81 68.64227681 -254.36058788
82 -330.07602408 68.64227681
83 -180.39216550 -330.07602408
84 80.43560071 -180.39216550
85 158.42535498 80.43560071
86 -79.83654074 158.42535498
87 71.69599310 -79.83654074
88 246.19356191 71.69599310
89 -359.93783245 246.19356191
90 168.78284679 -359.93783245
91 -239.59477570 168.78284679
92 -227.75937047 -239.59477570
93 35.36452415 -227.75937047
94 73.34366709 35.36452415
95 -315.06247283 73.34366709
96 -21.03731670 -315.06247283
97 272.87663415 -21.03731670
98 79.76415935 272.87663415
99 105.58080738 79.76415935
100 80.13122267 105.58080738
101 158.45294342 80.13122267
102 -178.51011391 158.45294342
103 30.13115546 -178.51011391
104 -8.57893973 30.13115546
105 -77.73619879 -8.57893973
106 300.39482460 -77.73619879
107 249.01579556 300.39482460
108 -45.14495420 249.01579556
109 46.11269533 -45.14495420
110 -9.55688678 46.11269533
111 -240.01470890 -9.55688678
112 -45.93096910 -240.01470890
113 96.50405291 -45.93096910
114 -180.19037611 96.50405291
115 -172.18273997 -180.19037611
116 2.01473660 -172.18273997
117 116.17578785 2.01473660
118 -42.42001356 116.17578785
119 94.19571697 -42.42001356
120 140.34280459 94.19571697
121 -91.21343425 140.34280459
122 55.58400026 -91.21343425
123 8.43457057 55.58400026
124 -22.20382834 8.43457057
125 41.17671177 -22.20382834
126 -41.85924261 41.17671177
127 243.93834904 -41.85924261
128 162.51767019 243.93834904
129 -69.31361543 162.51767019
130 23.66354047 -69.31361543
131 19.09847350 23.66354047
132 -110.77035600 19.09847350
133 296.26829144 -110.77035600
134 128.02415340 296.26829144
135 -169.19563362 128.02415340
136 -66.50326240 -169.19563362
137 -75.80147405 -66.50326240
138 32.49026319 -75.80147405
139 -148.58244481 32.49026319
140 -46.08731204 -148.58244481
141 218.55815205 -46.08731204
142 -98.38574311 218.55815205
143 90.98399756 -98.38574311
144 85.75020830 90.98399756
145 220.19809289 85.75020830
146 -35.68105581 220.19809289
147 -10.10566660 -35.68105581
148 -259.63409908 -10.10566660
149 21.99289412 -259.63409908
150 -74.61975324 21.99289412
151 -129.19490659 -74.61975324
152 115.12214534 -129.19490659
153 -273.28820917 115.12214534
154 -88.64815633 -273.28820917
155 148.58531459 -88.64815633
156 -153.67559899 148.58531459
157 -118.33495737 -153.67559899
158 -43.45869928 -118.33495737
159 -420.46119520 -43.45869928
160 177.42626859 -420.46119520
161 -0.32244259 177.42626859
162 -118.33803738 -0.32244259
163 -249.65456006 -118.33803738
164 -42.73410618 -249.65456006
165 -11.67418746 -42.73410618
166 -66.18625093 -11.67418746
167 -187.43634406 -66.18625093
168 26.90893573 -187.43634406
169 28.78307093 26.90893573
170 19.82337599 28.78307093
171 16.01942476 19.82337599
172 192.83688300 16.01942476
173 241.76763765 192.83688300
174 19.84251986 241.76763765
175 -80.24139276 19.84251986
176 35.28557453 -80.24139276
177 -6.05711690 35.28557453
178 103.65597945 -6.05711690
179 -17.15373118 103.65597945
180 67.64510447 -17.15373118
181 164.83202236 67.64510447
182 -108.47664663 164.83202236
183 29.47484607 -108.47664663
184 84.85191714 29.47484607
185 -120.52766251 84.85191714
186 -230.39106764 -120.52766251
187 -137.30799354 -230.39106764
188 229.37718017 -137.30799354
189 22.03737022 229.37718017
190 46.08601619 22.03737022
191 -205.50032238 46.08601619
192 118.50893833 -205.50032238
193 196.43407837 118.50893833
194 -24.20348273 196.43407837
195 100.69550813 -24.20348273
196 -119.09367844 100.69550813
197 -64.83170470 -119.09367844
198 -47.69992789 -64.83170470
199 -30.62613976 -47.69992789
200 -30.20270483 -30.62613976
201 -37.77741213 -30.20270483
202 -75.78015127 -37.77741213
203 -9.44857361 -75.78015127
204 29.40664308 -9.44857361
205 -22.43247916 29.40664308
206 151.05407162 -22.43247916
207 -129.27881174 151.05407162
208 -27.16420139 -129.27881174
209 -18.15010675 -27.16420139
210 86.93422828 -18.15010675
211 212.20753037 86.93422828
212 -1.10997260 212.20753037
213 -100.32657610 -1.10997260
214 75.97310674 -100.32657610
215 28.37989264 75.97310674
216 1.18103707 28.37989264
217 -52.26637039 1.18103707
218 -20.81028328 -52.26637039
219 -71.77534945 -20.81028328
220 64.86024411 -71.77534945
221 431.18909569 64.86024411
222 339.75660086 431.18909569
223 60.16561583 339.75660086
224 -105.55338880 60.16561583
225 84.25101134 -105.55338880
226 -42.77386272 84.25101134
227 -61.80075706 -42.77386272
228 141.28408350 -61.80075706
229 343.47181942 141.28408350
230 37.40793653 343.47181942
231 191.23740540 37.40793653
232 97.40684634 191.23740540
233 13.11881340 97.40684634
234 -84.31120709 13.11881340
235 2.32544556 -84.31120709
236 -26.12442622 2.32544556
237 NA -26.12442622
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -163.78901554 71.03467614
[2,] -23.17859274 -163.78901554
[3,] -323.01664975 -23.17859274
[4,] -16.26228137 -323.01664975
[5,] -95.13326095 -16.26228137
[6,] -525.17317052 -95.13326095
[7,] -90.97462891 -525.17317052
[8,] -16.19781951 -90.97462891
[9,] -102.15291531 -16.19781951
[10,] 41.19413302 -102.15291531
[11,] -155.92945590 41.19413302
[12,] 8.74670015 -155.92945590
[13,] -75.34568316 8.74670015
[14,] -113.02592388 -75.34568316
[15,] 25.49795989 -113.02592388
[16,] 357.36068087 25.49795989
[17,] 7.76435947 357.36068087
[18,] -254.81868506 7.76435947
[19,] -94.17987204 -254.81868506
[20,] 270.14075076 -94.17987204
[21,] 130.12823466 270.14075076
[22,] -339.95575259 130.12823466
[23,] 39.21973702 -339.95575259
[24,] 96.60461970 39.21973702
[25,] 4.62017871 96.60461970
[26,] 1.39607013 4.62017871
[27,] -76.24228032 1.39607013
[28,] 51.24221152 -76.24228032
[29,] -59.04850896 51.24221152
[30,] -68.95706223 -59.04850896
[31,] -70.42149873 -68.95706223
[32,] 20.98313256 -70.42149873
[33,] -99.82627728 20.98313256
[34,] -18.34919906 -99.82627728
[35,] -96.00595016 -18.34919906
[36,] 11.96044151 -96.00595016
[37,] -121.87973782 11.96044151
[38,] 102.05280798 -121.87973782
[39,] -117.22605201 102.05280798
[40,] -0.01806502 -117.22605201
[41,] 26.59649912 -0.01806502
[42,] 259.91298793 26.59649912
[43,] -59.23535374 259.91298793
[44,] -201.42207494 -59.23535374
[45,] -184.19219211 -201.42207494
[46,] 280.19755678 -184.19219211
[47,] -138.51007976 280.19755678
[48,] 141.05077929 -138.51007976
[49,] -84.71322931 141.05077929
[50,] -455.69969685 -84.71322931
[51,] -84.43096306 -455.69969685
[52,] 215.36927057 -84.43096306
[53,] 411.64319983 215.36927057
[54,] -108.89927115 411.64319983
[55,] 71.26556858 -108.89927115
[56,] -138.64196014 71.26556858
[57,] -511.95292067 -138.64196014
[58,] 16.94040343 -511.95292067
[59,] -175.05391174 16.94040343
[60,] 159.99163118 -175.05391174
[61,] 421.97868312 159.99163118
[62,] 1124.38616187 421.97868312
[63,] -21.47985446 1124.38616187
[64,] 204.96407671 -21.47985446
[65,] -267.64005992 204.96407671
[66,] -72.09915388 -267.64005992
[67,] 340.62863764 -72.09915388
[68,] -21.43921634 340.62863764
[69,] -111.41959711 -21.43921634
[70,] 58.76880552 -111.41959711
[71,] -259.12679849 58.76880552
[72,] 156.28666070 -259.12679849
[73,] 8.07056634 156.28666070
[74,] 176.22229253 8.07056634
[75,] -14.97126725 176.22229253
[76,] -39.26749322 -14.97126725
[77,] 210.01201013 -39.26749322
[78,] -147.27515954 210.01201013
[79,] 130.36309840 -147.27515954
[80,] -254.36058788 130.36309840
[81,] 68.64227681 -254.36058788
[82,] -330.07602408 68.64227681
[83,] -180.39216550 -330.07602408
[84,] 80.43560071 -180.39216550
[85,] 158.42535498 80.43560071
[86,] -79.83654074 158.42535498
[87,] 71.69599310 -79.83654074
[88,] 246.19356191 71.69599310
[89,] -359.93783245 246.19356191
[90,] 168.78284679 -359.93783245
[91,] -239.59477570 168.78284679
[92,] -227.75937047 -239.59477570
[93,] 35.36452415 -227.75937047
[94,] 73.34366709 35.36452415
[95,] -315.06247283 73.34366709
[96,] -21.03731670 -315.06247283
[97,] 272.87663415 -21.03731670
[98,] 79.76415935 272.87663415
[99,] 105.58080738 79.76415935
[100,] 80.13122267 105.58080738
[101,] 158.45294342 80.13122267
[102,] -178.51011391 158.45294342
[103,] 30.13115546 -178.51011391
[104,] -8.57893973 30.13115546
[105,] -77.73619879 -8.57893973
[106,] 300.39482460 -77.73619879
[107,] 249.01579556 300.39482460
[108,] -45.14495420 249.01579556
[109,] 46.11269533 -45.14495420
[110,] -9.55688678 46.11269533
[111,] -240.01470890 -9.55688678
[112,] -45.93096910 -240.01470890
[113,] 96.50405291 -45.93096910
[114,] -180.19037611 96.50405291
[115,] -172.18273997 -180.19037611
[116,] 2.01473660 -172.18273997
[117,] 116.17578785 2.01473660
[118,] -42.42001356 116.17578785
[119,] 94.19571697 -42.42001356
[120,] 140.34280459 94.19571697
[121,] -91.21343425 140.34280459
[122,] 55.58400026 -91.21343425
[123,] 8.43457057 55.58400026
[124,] -22.20382834 8.43457057
[125,] 41.17671177 -22.20382834
[126,] -41.85924261 41.17671177
[127,] 243.93834904 -41.85924261
[128,] 162.51767019 243.93834904
[129,] -69.31361543 162.51767019
[130,] 23.66354047 -69.31361543
[131,] 19.09847350 23.66354047
[132,] -110.77035600 19.09847350
[133,] 296.26829144 -110.77035600
[134,] 128.02415340 296.26829144
[135,] -169.19563362 128.02415340
[136,] -66.50326240 -169.19563362
[137,] -75.80147405 -66.50326240
[138,] 32.49026319 -75.80147405
[139,] -148.58244481 32.49026319
[140,] -46.08731204 -148.58244481
[141,] 218.55815205 -46.08731204
[142,] -98.38574311 218.55815205
[143,] 90.98399756 -98.38574311
[144,] 85.75020830 90.98399756
[145,] 220.19809289 85.75020830
[146,] -35.68105581 220.19809289
[147,] -10.10566660 -35.68105581
[148,] -259.63409908 -10.10566660
[149,] 21.99289412 -259.63409908
[150,] -74.61975324 21.99289412
[151,] -129.19490659 -74.61975324
[152,] 115.12214534 -129.19490659
[153,] -273.28820917 115.12214534
[154,] -88.64815633 -273.28820917
[155,] 148.58531459 -88.64815633
[156,] -153.67559899 148.58531459
[157,] -118.33495737 -153.67559899
[158,] -43.45869928 -118.33495737
[159,] -420.46119520 -43.45869928
[160,] 177.42626859 -420.46119520
[161,] -0.32244259 177.42626859
[162,] -118.33803738 -0.32244259
[163,] -249.65456006 -118.33803738
[164,] -42.73410618 -249.65456006
[165,] -11.67418746 -42.73410618
[166,] -66.18625093 -11.67418746
[167,] -187.43634406 -66.18625093
[168,] 26.90893573 -187.43634406
[169,] 28.78307093 26.90893573
[170,] 19.82337599 28.78307093
[171,] 16.01942476 19.82337599
[172,] 192.83688300 16.01942476
[173,] 241.76763765 192.83688300
[174,] 19.84251986 241.76763765
[175,] -80.24139276 19.84251986
[176,] 35.28557453 -80.24139276
[177,] -6.05711690 35.28557453
[178,] 103.65597945 -6.05711690
[179,] -17.15373118 103.65597945
[180,] 67.64510447 -17.15373118
[181,] 164.83202236 67.64510447
[182,] -108.47664663 164.83202236
[183,] 29.47484607 -108.47664663
[184,] 84.85191714 29.47484607
[185,] -120.52766251 84.85191714
[186,] -230.39106764 -120.52766251
[187,] -137.30799354 -230.39106764
[188,] 229.37718017 -137.30799354
[189,] 22.03737022 229.37718017
[190,] 46.08601619 22.03737022
[191,] -205.50032238 46.08601619
[192,] 118.50893833 -205.50032238
[193,] 196.43407837 118.50893833
[194,] -24.20348273 196.43407837
[195,] 100.69550813 -24.20348273
[196,] -119.09367844 100.69550813
[197,] -64.83170470 -119.09367844
[198,] -47.69992789 -64.83170470
[199,] -30.62613976 -47.69992789
[200,] -30.20270483 -30.62613976
[201,] -37.77741213 -30.20270483
[202,] -75.78015127 -37.77741213
[203,] -9.44857361 -75.78015127
[204,] 29.40664308 -9.44857361
[205,] -22.43247916 29.40664308
[206,] 151.05407162 -22.43247916
[207,] -129.27881174 151.05407162
[208,] -27.16420139 -129.27881174
[209,] -18.15010675 -27.16420139
[210,] 86.93422828 -18.15010675
[211,] 212.20753037 86.93422828
[212,] -1.10997260 212.20753037
[213,] -100.32657610 -1.10997260
[214,] 75.97310674 -100.32657610
[215,] 28.37989264 75.97310674
[216,] 1.18103707 28.37989264
[217,] -52.26637039 1.18103707
[218,] -20.81028328 -52.26637039
[219,] -71.77534945 -20.81028328
[220,] 64.86024411 -71.77534945
[221,] 431.18909569 64.86024411
[222,] 339.75660086 431.18909569
[223,] 60.16561583 339.75660086
[224,] -105.55338880 60.16561583
[225,] 84.25101134 -105.55338880
[226,] -42.77386272 84.25101134
[227,] -61.80075706 -42.77386272
[228,] 141.28408350 -61.80075706
[229,] 343.47181942 141.28408350
[230,] 37.40793653 343.47181942
[231,] 191.23740540 37.40793653
[232,] 97.40684634 191.23740540
[233,] 13.11881340 97.40684634
[234,] -84.31120709 13.11881340
[235,] 2.32544556 -84.31120709
[236,] -26.12442622 2.32544556
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -163.78901554 71.03467614
2 -23.17859274 -163.78901554
3 -323.01664975 -23.17859274
4 -16.26228137 -323.01664975
5 -95.13326095 -16.26228137
6 -525.17317052 -95.13326095
7 -90.97462891 -525.17317052
8 -16.19781951 -90.97462891
9 -102.15291531 -16.19781951
10 41.19413302 -102.15291531
11 -155.92945590 41.19413302
12 8.74670015 -155.92945590
13 -75.34568316 8.74670015
14 -113.02592388 -75.34568316
15 25.49795989 -113.02592388
16 357.36068087 25.49795989
17 7.76435947 357.36068087
18 -254.81868506 7.76435947
19 -94.17987204 -254.81868506
20 270.14075076 -94.17987204
21 130.12823466 270.14075076
22 -339.95575259 130.12823466
23 39.21973702 -339.95575259
24 96.60461970 39.21973702
25 4.62017871 96.60461970
26 1.39607013 4.62017871
27 -76.24228032 1.39607013
28 51.24221152 -76.24228032
29 -59.04850896 51.24221152
30 -68.95706223 -59.04850896
31 -70.42149873 -68.95706223
32 20.98313256 -70.42149873
33 -99.82627728 20.98313256
34 -18.34919906 -99.82627728
35 -96.00595016 -18.34919906
36 11.96044151 -96.00595016
37 -121.87973782 11.96044151
38 102.05280798 -121.87973782
39 -117.22605201 102.05280798
40 -0.01806502 -117.22605201
41 26.59649912 -0.01806502
42 259.91298793 26.59649912
43 -59.23535374 259.91298793
44 -201.42207494 -59.23535374
45 -184.19219211 -201.42207494
46 280.19755678 -184.19219211
47 -138.51007976 280.19755678
48 141.05077929 -138.51007976
49 -84.71322931 141.05077929
50 -455.69969685 -84.71322931
51 -84.43096306 -455.69969685
52 215.36927057 -84.43096306
53 411.64319983 215.36927057
54 -108.89927115 411.64319983
55 71.26556858 -108.89927115
56 -138.64196014 71.26556858
57 -511.95292067 -138.64196014
58 16.94040343 -511.95292067
59 -175.05391174 16.94040343
60 159.99163118 -175.05391174
61 421.97868312 159.99163118
62 1124.38616187 421.97868312
63 -21.47985446 1124.38616187
64 204.96407671 -21.47985446
65 -267.64005992 204.96407671
66 -72.09915388 -267.64005992
67 340.62863764 -72.09915388
68 -21.43921634 340.62863764
69 -111.41959711 -21.43921634
70 58.76880552 -111.41959711
71 -259.12679849 58.76880552
72 156.28666070 -259.12679849
73 8.07056634 156.28666070
74 176.22229253 8.07056634
75 -14.97126725 176.22229253
76 -39.26749322 -14.97126725
77 210.01201013 -39.26749322
78 -147.27515954 210.01201013
79 130.36309840 -147.27515954
80 -254.36058788 130.36309840
81 68.64227681 -254.36058788
82 -330.07602408 68.64227681
83 -180.39216550 -330.07602408
84 80.43560071 -180.39216550
85 158.42535498 80.43560071
86 -79.83654074 158.42535498
87 71.69599310 -79.83654074
88 246.19356191 71.69599310
89 -359.93783245 246.19356191
90 168.78284679 -359.93783245
91 -239.59477570 168.78284679
92 -227.75937047 -239.59477570
93 35.36452415 -227.75937047
94 73.34366709 35.36452415
95 -315.06247283 73.34366709
96 -21.03731670 -315.06247283
97 272.87663415 -21.03731670
98 79.76415935 272.87663415
99 105.58080738 79.76415935
100 80.13122267 105.58080738
101 158.45294342 80.13122267
102 -178.51011391 158.45294342
103 30.13115546 -178.51011391
104 -8.57893973 30.13115546
105 -77.73619879 -8.57893973
106 300.39482460 -77.73619879
107 249.01579556 300.39482460
108 -45.14495420 249.01579556
109 46.11269533 -45.14495420
110 -9.55688678 46.11269533
111 -240.01470890 -9.55688678
112 -45.93096910 -240.01470890
113 96.50405291 -45.93096910
114 -180.19037611 96.50405291
115 -172.18273997 -180.19037611
116 2.01473660 -172.18273997
117 116.17578785 2.01473660
118 -42.42001356 116.17578785
119 94.19571697 -42.42001356
120 140.34280459 94.19571697
121 -91.21343425 140.34280459
122 55.58400026 -91.21343425
123 8.43457057 55.58400026
124 -22.20382834 8.43457057
125 41.17671177 -22.20382834
126 -41.85924261 41.17671177
127 243.93834904 -41.85924261
128 162.51767019 243.93834904
129 -69.31361543 162.51767019
130 23.66354047 -69.31361543
131 19.09847350 23.66354047
132 -110.77035600 19.09847350
133 296.26829144 -110.77035600
134 128.02415340 296.26829144
135 -169.19563362 128.02415340
136 -66.50326240 -169.19563362
137 -75.80147405 -66.50326240
138 32.49026319 -75.80147405
139 -148.58244481 32.49026319
140 -46.08731204 -148.58244481
141 218.55815205 -46.08731204
142 -98.38574311 218.55815205
143 90.98399756 -98.38574311
144 85.75020830 90.98399756
145 220.19809289 85.75020830
146 -35.68105581 220.19809289
147 -10.10566660 -35.68105581
148 -259.63409908 -10.10566660
149 21.99289412 -259.63409908
150 -74.61975324 21.99289412
151 -129.19490659 -74.61975324
152 115.12214534 -129.19490659
153 -273.28820917 115.12214534
154 -88.64815633 -273.28820917
155 148.58531459 -88.64815633
156 -153.67559899 148.58531459
157 -118.33495737 -153.67559899
158 -43.45869928 -118.33495737
159 -420.46119520 -43.45869928
160 177.42626859 -420.46119520
161 -0.32244259 177.42626859
162 -118.33803738 -0.32244259
163 -249.65456006 -118.33803738
164 -42.73410618 -249.65456006
165 -11.67418746 -42.73410618
166 -66.18625093 -11.67418746
167 -187.43634406 -66.18625093
168 26.90893573 -187.43634406
169 28.78307093 26.90893573
170 19.82337599 28.78307093
171 16.01942476 19.82337599
172 192.83688300 16.01942476
173 241.76763765 192.83688300
174 19.84251986 241.76763765
175 -80.24139276 19.84251986
176 35.28557453 -80.24139276
177 -6.05711690 35.28557453
178 103.65597945 -6.05711690
179 -17.15373118 103.65597945
180 67.64510447 -17.15373118
181 164.83202236 67.64510447
182 -108.47664663 164.83202236
183 29.47484607 -108.47664663
184 84.85191714 29.47484607
185 -120.52766251 84.85191714
186 -230.39106764 -120.52766251
187 -137.30799354 -230.39106764
188 229.37718017 -137.30799354
189 22.03737022 229.37718017
190 46.08601619 22.03737022
191 -205.50032238 46.08601619
192 118.50893833 -205.50032238
193 196.43407837 118.50893833
194 -24.20348273 196.43407837
195 100.69550813 -24.20348273
196 -119.09367844 100.69550813
197 -64.83170470 -119.09367844
198 -47.69992789 -64.83170470
199 -30.62613976 -47.69992789
200 -30.20270483 -30.62613976
201 -37.77741213 -30.20270483
202 -75.78015127 -37.77741213
203 -9.44857361 -75.78015127
204 29.40664308 -9.44857361
205 -22.43247916 29.40664308
206 151.05407162 -22.43247916
207 -129.27881174 151.05407162
208 -27.16420139 -129.27881174
209 -18.15010675 -27.16420139
210 86.93422828 -18.15010675
211 212.20753037 86.93422828
212 -1.10997260 212.20753037
213 -100.32657610 -1.10997260
214 75.97310674 -100.32657610
215 28.37989264 75.97310674
216 1.18103707 28.37989264
217 -52.26637039 1.18103707
218 -20.81028328 -52.26637039
219 -71.77534945 -20.81028328
220 64.86024411 -71.77534945
221 431.18909569 64.86024411
222 339.75660086 431.18909569
223 60.16561583 339.75660086
224 -105.55338880 60.16561583
225 84.25101134 -105.55338880
226 -42.77386272 84.25101134
227 -61.80075706 -42.77386272
228 141.28408350 -61.80075706
229 343.47181942 141.28408350
230 37.40793653 343.47181942
231 191.23740540 37.40793653
232 97.40684634 191.23740540
233 13.11881340 97.40684634
234 -84.31120709 13.11881340
235 2.32544556 -84.31120709
236 -26.12442622 2.32544556
> 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/wessaorg/rcomp/tmp/7nubz1323861281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8hlzj1323861281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9h6c21323861281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10put01323861281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/119gzm1323861281.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/wessaorg/rcomp/tmp/122ydw1323861281.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/wessaorg/rcomp/tmp/1336f71323861281.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/wessaorg/rcomp/tmp/145z7s1323861281.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/wessaorg/rcomp/tmp/15ujsb1323861281.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/wessaorg/rcomp/tmp/164rum1323861281.tab")
+ }
>
> try(system("convert tmp/12w6t1323861281.ps tmp/12w6t1323861281.png",intern=TRUE))
character(0)
> try(system("convert tmp/2liiq1323861281.ps tmp/2liiq1323861281.png",intern=TRUE))
character(0)
> try(system("convert tmp/3afnz1323861281.ps tmp/3afnz1323861281.png",intern=TRUE))
character(0)
> try(system("convert tmp/4cmzr1323861281.ps tmp/4cmzr1323861281.png",intern=TRUE))
character(0)
> try(system("convert tmp/5t5sj1323861281.ps tmp/5t5sj1323861281.png",intern=TRUE))
character(0)
> try(system("convert tmp/63yk01323861281.ps tmp/63yk01323861281.png",intern=TRUE))
character(0)
> try(system("convert tmp/7nubz1323861281.ps tmp/7nubz1323861281.png",intern=TRUE))
character(0)
> try(system("convert tmp/8hlzj1323861281.ps tmp/8hlzj1323861281.png",intern=TRUE))
character(0)
> try(system("convert tmp/9h6c21323861281.ps tmp/9h6c21323861281.png",intern=TRUE))
character(0)
> try(system("convert tmp/10put01323861281.ps tmp/10put01323861281.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.869 0.629 7.521