R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(84738
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+ ,-2765
+ ,-28)
+ ,dim=c(6
+ ,211)
+ ,dimnames=list(c('Costs'
+ ,'Orders'
+ ,'Dividends'
+ ,'Wealth'
+ ,'Profit/Trades'
+ ,'Profit/Cost')
+ ,1:211))
> y <- array(NA,dim=c(6,211),dimnames=list(c('Costs','Orders','Dividends','Wealth','Profit/Trades','Profit/Cost'),1:211))
> 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 = '4'
> #'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
Wealth Costs Orders Dividends Profit/Trades Profit/Cost
1 -1212617 84738 428 -26007 -2402 -17
2 1367203 40949 263 129352 2427 29
3 1220017 25830 104 245546 8870 39
4 984885 12679 122 48020 7135 62
5 -572920 43556 190 32648 -3129 -18
6 1151176 6532 62 151352 9235 146
7 790090 7123 102 288170 5414 83
8 454195 17821 277 122844 681 14
9 702380 13326 103 165548 4925 38
10 264449 16189 290 116384 218 4
11 450033 7146 83 134028 2381 35
12 541063 15824 56 63838 5329 22
13 -37216 11326 64 31080 -1839 -21
14 783310 8568 34 32168 15765 68
15 467359 14416 139 49857 741 19
16 821730 2220 12 301670 28260 280
17 377934 18562 211 102313 1148 10
18 651939 10327 74 88577 4966 44
19 225986 4069 131 79804 179 6
20 348695 7710 187 128294 182 19
21 373683 13718 56 96448 2847 13
22 501709 4525 89 93811 1335 67
23 413743 6869 88 117520 2036 31
24 379825 4628 39 69159 2900 39
25 469107 4901 58 121920 3204 55
26 211928 2284 41 76403 361 5
27 423262 2384 77 61348 2302 94
28 509665 3748 6 50350 34407 83
29 455881 5371 47 87720 3877 48
30 367772 1285 51 99489 1568 131
31 232942 1528 32 60326 867 22
32 361517 2675 54 59017 2045 60
33 360962 13253 251 90829 170 12
34 235561 880 15 80791 481 40
35 450296 1424 73 131116 2663 176
36 378519 5119 38 39039 3643 35
37 326638 1431 35 106885 3725 89
38 328233 554 9 79285 11658 232
39 386225 1975 34 118881 5321 94
40 370225 1012 29 114768 3622 168
41 269236 810 11 74015 1610 86
42 365732 1280 52 69465 1417 129
43 345811 1380 29 60982 5608 106
44 418876 876 33 138971 3710 250
45 297476 814 15 39625 5415 120
46 416776 514 15 102725 14452 422
47 458343 3642 100 90262 3004 71
48 388386 540 13 103960 13456 349
49 358934 2099 45 106611 2483 76
50 407560 567 14 103345 18869 366
51 392558 2001 36 95551 3703 96
52 428370 2253 68 63593 2307 101
53 358649 1889 43 37527 3526 84
54 467427 272 9 112995 33428 985
55 436230 2564 19 130140 10738 92
56 286849 975 19 90534 3776 89
57 376685 3366 55 108479 2209 52
58 407198 576 8 113761 11511 360
59 377772 1306 26 68696 6349 136
60 271483 746 29 71561 3108 96
61 324881 5477 45 101481 2117 23
62 420968 936 22 67939 7366 236
63 191521 5131 44 86111 -119 -2
64 354624 1503 35 56364 3965 103
65 363713 402 8 84990 6297 407
66 456657 2239 17 88590 12222 115
67 338381 837 21 61262 2006 165
68 418530 10579 92 110309 2375 21
69 351483 875 12 67000 10820 173
70 372928 1395 108 93099 1679 124
71 325314 94 10 60793 17902 1326
72 322046 422 23 57935 4359 289
73 325599 34 7 60630 15700 3668
74 377028 1558 25 55637 2810 114
75 323850 43 20 60887 41283 2868
76 331514 316 4 60505 14613 416
77 325632 115 10 60945 9664 1096
78 322265 389 7 58990 8733 314
79 325906 1002 11 56750 8394 126
80 325985 36 4 60894 41995 3497
81 346145 460 15 63346 9743 317
82 325898 309 9 56535 11445 407
83 325356 9 7 60835 20893 13581
84 325930 14 0 61016 125930 8739
85 318020 520 7 58650 11802 227
86 326389 1766 46 60438 1731 72
87 302925 458 7 58625 9357 225
88 325540 20 2 60938 41847 6181
89 326736 98 2 61490 63368 1296
90 340580 405 5 60845 20083 347
91 331828 483 7 60830 4883 273
92 323299 454 24 63261 2418 272
93 387722 757 18 45689 9880 248
94 324598 36 3 61564 31150 3487
95 328726 203 9 61938 14303 635
96 325043 90 6 60951 15630 1394
97 387732 972 19 71642 5522 193
98 332202 604 8 55792 3479 219
99 328451 149 6 62041 25690 862
100 307062 226 5 65745 21412 474
101 331345 275 7 59500 32836 477
102 331824 141 7 61630 21971 936
103 325685 28 3 60890 62842 4506
104 322741 267 11 57640 3836 460
105 310902 474 10 61977 5545 234
106 324295 534 5 62620 17756 233
107 326156 15 6 60831 15769 8382
108 326960 397 7 60646 4534 320
109 333411 1061 22 56225 6671 126
110 297761 288 3 60510 24440 339
111 325536 3 1 60698 62768 39727
112 325762 20 1 60805 62881 6446
113 327957 278 22 61404 4921 460
114 318521 192 2 65276 29630 618
115 319775 317 7 63915 13308 378
116 325486 2 0 60743 125486 56781
117 325838 53 6 60349 20973 2388
118 331767 94 3 61360 43922 1400
119 324523 24 7 59818 15565 5139
120 339995 2332 2 72680 34999 60
121 319582 131 15 61808 10871 916
122 307245 206 9 53110 11916 520
123 317967 167 1 64245 58984 706
124 331488 622 38 73007 1801 211
125 335452 885 49 82732 1594 153
126 334184 365 6 54820 16773 367
127 313213 364 26 47705 3235 311
128 348678 226 13 72835 12390 657
129 328727 307 10 58856 8582 420
130 387978 188 9 77655 17089 1001
131 336704 138 26 69817 22784 993
132 322076 125 19 60798 10173 978
133 334272 282 12 62452 4476 475
134 338197 335 23 64175 4188 412
135 322145 176 8 68136 4362 694
136 323351 249 26 56726 1713 495
137 327748 333 9 70811 9827 384
138 328157 30 3 62045 32039 4245
139 311594 249 13 54323 1800 449
140 335962 165 12 62841 5665 825
141 372426 453 19 81125 8211 380
142 319844 53 10 59506 8560 2260
143 311464 290 1 58790 55732 384
144 353417 366 14 61808 2895 419
145 325590 2 12 60735 13954 68628
146 326126 384 17 54683 5733 328
147 369376 365 32 87192 2041 464
148 325871 3 8 60761 31468 41269
149 342165 133 4 65990 10155 1072
150 324967 32 0 59988 124967 3916
151 314832 368 20 61167 6755 312
152 325557 1 5 60719 20926 91647
153 322649 22 1 60722 61325 5618
154 324598 96 4 60379 24920 1302
155 325567 1 1 60727 62784 128130
156 324005 81 4 60925 17715 1535
157 325748 26 1 60896 125748 4779
158 323385 125 10 59734 9491 990
159 315409 304 12 62969 7694 379
160 312275 119 3 59118 18713 945
161 320576 312 3 58598 8613 387
162 325246 60 7 61124 12525 2104
163 332961 587 10 59595 11080 227
164 323010 135 1 62065 61505 912
165 345253 514 15 78780 2793 283
166 325559 1 4 60722 31390 187401
167 319951 180 9 59635 10905 667
168 318519 448 7 59781 2963 265
169 343222 227 7 76644 15914 632
170 317234 174 3 64820 117234 675
171 314025 121 11 56178 4751 943
172 320249 607 7 60436 10932 198
173 349365 530 18 73433 2489 282
174 289197 571 14 41477 1115 156
175 329245 78 12 62700 8078 1664
176 240869 2489 29 67804 1022 16
177 327182 131 3 59661 21197 970
178 322876 923 6 58620 15360 133
179 323117 72 3 60398 41039 1715
180 306351 572 8 58580 6647 186
181 335137 397 10 62710 13514 340
182 308271 450 6 59325 13534 241
183 301731 622 8 60950 14533 164
184 382409 694 6 68060 22801 263
185 298731 562 8 58456 7595 176
186 243650 4917 26 52811 1039 9
187 319771 529 7 63870 13308 226
188 347262 1061 3 70415 29452 139
189 343945 776 8 64230 15994 186
190 311874 611 6 59190 13984 183
191 316708 592 7 64270 16673 197
192 333463 1182 11 70694 10266 113
193 344282 621 11 68005 9018 232
194 319635 989 12 58930 10876 121
195 301186 438 9 58320 9199 231
196 300381 726 3 69980 33460 138
197 318765 1303 57 69863 1947 91
198 312448 1366 5 79420 16064 82
199 299715 965 2 73490 33238 103
200 373399 3256 23 35250 2627 53
201 325586 1270 24 69206 4830 99
202 291221 661 1 65920 30407 138
203 261173 1013 1 69770 30587 60
204 255027 2844 74 72683 821 19
205 -58143 6526 20 55830 -9929 -40
206 227033 2264 20 55174 1126 12
207 21267 3999 21 51252 -5958 -45
208 238675 35624 244 157278 173 1
209 197687 9252 32 79510 -48 0
210 418341 15236 86 77440 2426 14
211 -297706 18073 69 27284 -2765 -28
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Costs Orders Dividends
1.122e+05 -9.559e+00 3.678e+02 3.342e+00
`Profit/Trades` `Profit/Cost`
3.261e-01 -6.048e-02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-584520 -33503 -1272 14443 1116582
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.122e+05 2.724e+04 4.119 5.51e-05 ***
Costs -9.559e+00 2.445e+00 -3.909 0.000126 ***
Orders 3.678e+02 3.752e+02 0.980 0.328119
Dividends 3.342e+00 3.266e-01 10.234 < 2e-16 ***
`Profit/Trades` 3.261e-01 5.181e-01 0.629 0.529804
`Profit/Cost` -6.048e-02 6.074e-01 -0.100 0.920778
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 154000 on 205 degrees of freedom
Multiple R-squared: 0.418, Adjusted R-squared: 0.4038
F-statistic: 29.45 on 5 and 205 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,] 1.0000000 3.871884e-27 1.935942e-27
[2,] 1.0000000 1.804892e-27 9.024462e-28
[3,] 1.0000000 1.310356e-26 6.551782e-27
[4,] 1.0000000 2.728190e-27 1.364095e-27
[5,] 1.0000000 4.921273e-28 2.460637e-28
[6,] 1.0000000 8.683466e-40 4.341733e-40
[7,] 1.0000000 1.025889e-41 5.129444e-42
[8,] 1.0000000 2.223659e-54 1.111829e-54
[9,] 1.0000000 9.160301e-54 4.580150e-54
[10,] 1.0000000 4.516099e-58 2.258050e-58
[11,] 1.0000000 1.550681e-59 7.753404e-60
[12,] 1.0000000 5.195688e-60 2.597844e-60
[13,] 1.0000000 2.009526e-60 1.004763e-60
[14,] 1.0000000 2.968375e-60 1.484188e-60
[15,] 1.0000000 1.230496e-59 6.152480e-60
[16,] 1.0000000 3.285017e-59 1.642509e-59
[17,] 1.0000000 1.070718e-58 5.353589e-59
[18,] 1.0000000 2.239906e-59 1.119953e-59
[19,] 1.0000000 5.567263e-59 2.783631e-59
[20,] 1.0000000 4.714836e-64 2.357418e-64
[21,] 1.0000000 2.412319e-64 1.206159e-64
[22,] 1.0000000 9.386998e-64 4.693499e-64
[23,] 1.0000000 1.301019e-63 6.505094e-64
[24,] 1.0000000 7.154834e-63 3.577417e-63
[25,] 1.0000000 2.213705e-62 1.106853e-62
[26,] 1.0000000 1.243658e-62 6.218292e-63
[27,] 1.0000000 5.084780e-62 2.542390e-62
[28,] 1.0000000 1.002625e-62 5.013126e-63
[29,] 1.0000000 1.057186e-62 5.285932e-63
[30,] 1.0000000 5.760709e-62 2.880354e-62
[31,] 1.0000000 1.670588e-61 8.352942e-62
[32,] 1.0000000 5.317124e-61 2.658562e-61
[33,] 1.0000000 1.597222e-60 7.986112e-61
[34,] 1.0000000 8.603145e-60 4.301572e-60
[35,] 1.0000000 4.737719e-59 2.368860e-59
[36,] 1.0000000 1.024906e-58 5.124528e-59
[37,] 1.0000000 5.081329e-58 2.540665e-58
[38,] 1.0000000 2.514359e-57 1.257180e-57
[39,] 1.0000000 1.298778e-56 6.493889e-57
[40,] 1.0000000 6.584027e-56 3.292013e-56
[41,] 1.0000000 1.347844e-55 6.739218e-56
[42,] 1.0000000 6.789974e-55 3.394987e-55
[43,] 1.0000000 3.528572e-54 1.764286e-54
[44,] 1.0000000 6.883036e-54 3.441518e-54
[45,] 1.0000000 8.345046e-54 4.172523e-54
[46,] 1.0000000 2.347449e-53 1.173725e-53
[47,] 1.0000000 5.225576e-53 2.612788e-53
[48,] 1.0000000 3.849142e-53 1.924571e-53
[49,] 1.0000000 1.027495e-52 5.137476e-53
[50,] 1.0000000 2.961473e-52 1.480736e-52
[51,] 1.0000000 1.159317e-51 5.796585e-52
[52,] 1.0000000 1.725595e-51 8.627974e-52
[53,] 1.0000000 4.530593e-51 2.265297e-51
[54,] 1.0000000 6.635715e-51 3.317857e-51
[55,] 1.0000000 6.554831e-52 3.277416e-52
[56,] 1.0000000 1.931246e-51 9.656228e-52
[57,] 1.0000000 6.329222e-51 3.164611e-51
[58,] 1.0000000 1.278862e-50 6.394312e-51
[59,] 1.0000000 5.363239e-50 2.681619e-50
[60,] 1.0000000 1.408684e-49 7.043418e-50
[61,] 1.0000000 6.018358e-49 3.009179e-49
[62,] 1.0000000 2.263404e-49 1.131702e-49
[63,] 1.0000000 2.475338e-49 1.237669e-49
[64,] 1.0000000 1.174603e-48 5.873016e-49
[65,] 1.0000000 9.284084e-49 4.642042e-49
[66,] 1.0000000 1.221060e-48 6.105300e-49
[67,] 1.0000000 4.550841e-48 2.275420e-48
[68,] 1.0000000 1.924380e-47 9.621898e-48
[69,] 1.0000000 9.074039e-47 4.537019e-47
[70,] 1.0000000 4.036160e-46 2.018080e-46
[71,] 1.0000000 1.498559e-45 7.492797e-46
[72,] 1.0000000 6.833557e-45 3.416778e-45
[73,] 1.0000000 2.938505e-44 1.469253e-44
[74,] 1.0000000 1.192122e-43 5.960609e-44
[75,] 1.0000000 1.757723e-43 8.788616e-44
[76,] 1.0000000 4.015696e-43 2.007848e-43
[77,] 1.0000000 1.697935e-42 8.489674e-43
[78,] 1.0000000 7.529518e-42 3.764759e-42
[79,] 1.0000000 3.260309e-41 1.630154e-41
[80,] 1.0000000 1.408709e-40 7.043546e-41
[81,] 1.0000000 5.515692e-40 2.757846e-40
[82,] 1.0000000 2.015943e-39 1.007972e-39
[83,] 1.0000000 7.649703e-39 3.824851e-39
[84,] 1.0000000 3.119780e-38 1.559890e-38
[85,] 1.0000000 1.152955e-38 5.764777e-39
[86,] 1.0000000 4.799064e-38 2.399532e-38
[87,] 1.0000000 1.956570e-37 9.782849e-38
[88,] 1.0000000 7.898325e-37 3.949162e-37
[89,] 1.0000000 2.475426e-36 1.237713e-36
[90,] 1.0000000 7.067420e-36 3.533710e-36
[91,] 1.0000000 2.769248e-35 1.384624e-35
[92,] 1.0000000 9.941961e-35 4.970980e-35
[93,] 1.0000000 3.650119e-34 1.825060e-34
[94,] 1.0000000 1.380047e-33 6.900236e-34
[95,] 1.0000000 5.263501e-33 2.631751e-33
[96,] 1.0000000 1.878900e-32 9.394498e-33
[97,] 1.0000000 7.087766e-32 3.543883e-32
[98,] 1.0000000 2.560198e-31 1.280099e-31
[99,] 1.0000000 9.147878e-31 4.573939e-31
[100,] 1.0000000 3.119582e-30 1.559791e-30
[101,] 1.0000000 9.028954e-30 4.514477e-30
[102,] 1.0000000 3.168709e-29 1.584354e-29
[103,] 1.0000000 1.050366e-28 5.251829e-29
[104,] 1.0000000 3.696307e-28 1.848154e-28
[105,] 1.0000000 1.302184e-27 6.510919e-28
[106,] 1.0000000 4.453490e-27 2.226745e-27
[107,] 1.0000000 1.530483e-26 7.652416e-27
[108,] 1.0000000 4.997640e-26 2.498820e-26
[109,] 1.0000000 1.656255e-25 8.281276e-26
[110,] 1.0000000 5.430605e-25 2.715302e-25
[111,] 1.0000000 1.763368e-24 8.816839e-25
[112,] 1.0000000 5.103914e-24 2.551957e-24
[113,] 1.0000000 1.660806e-23 8.304032e-24
[114,] 1.0000000 5.030794e-23 2.515397e-23
[115,] 1.0000000 1.556814e-22 7.784068e-23
[116,] 1.0000000 3.826510e-22 1.913255e-22
[117,] 1.0000000 4.483946e-22 2.241973e-22
[118,] 1.0000000 1.062463e-21 5.312317e-22
[119,] 1.0000000 3.006831e-21 1.503415e-21
[120,] 1.0000000 9.187865e-21 4.593933e-21
[121,] 1.0000000 2.619375e-20 1.309688e-20
[122,] 1.0000000 7.859508e-20 3.929754e-20
[123,] 1.0000000 2.025544e-19 1.012772e-19
[124,] 1.0000000 6.057454e-19 3.028727e-19
[125,] 1.0000000 1.746824e-18 8.734118e-19
[126,] 1.0000000 5.137591e-18 2.568795e-18
[127,] 1.0000000 1.464996e-17 7.324981e-18
[128,] 1.0000000 4.204345e-17 2.102172e-17
[129,] 1.0000000 1.157805e-16 5.789026e-17
[130,] 1.0000000 3.224675e-16 1.612338e-16
[131,] 1.0000000 8.547010e-16 4.273505e-16
[132,] 1.0000000 2.312145e-15 1.156073e-15
[133,] 1.0000000 6.022381e-15 3.011191e-15
[134,] 1.0000000 1.611517e-14 8.057585e-15
[135,] 1.0000000 4.255694e-14 2.127847e-14
[136,] 1.0000000 9.850649e-14 4.925325e-14
[137,] 1.0000000 2.546954e-13 1.273477e-13
[138,] 1.0000000 5.955751e-13 2.977876e-13
[139,] 1.0000000 1.018221e-12 5.091103e-13
[140,] 1.0000000 2.599305e-12 1.299653e-12
[141,] 1.0000000 6.398470e-12 3.199235e-12
[142,] 1.0000000 1.572400e-11 7.861998e-12
[143,] 1.0000000 3.856168e-11 1.928084e-11
[144,] 1.0000000 9.325384e-11 4.662692e-11
[145,] 1.0000000 2.240062e-10 1.120031e-10
[146,] 1.0000000 5.216104e-10 2.608052e-10
[147,] 1.0000000 1.222941e-09 6.114704e-10
[148,] 1.0000000 2.780509e-09 1.390255e-09
[149,] 1.0000000 6.137014e-09 3.068507e-09
[150,] 1.0000000 1.364415e-08 6.822076e-09
[151,] 1.0000000 3.038262e-08 1.519131e-08
[152,] 1.0000000 6.602806e-08 3.301403e-08
[153,] 0.9999999 1.337374e-07 6.686872e-08
[154,] 0.9999999 2.829342e-07 1.414671e-07
[155,] 0.9999997 5.519319e-07 2.759659e-07
[156,] 0.9999994 1.153046e-06 5.765229e-07
[157,] 0.9999989 2.256200e-06 1.128100e-06
[158,] 0.9999981 3.849608e-06 1.924804e-06
[159,] 0.9999961 7.738127e-06 3.869063e-06
[160,] 0.9999926 1.478662e-05 7.393308e-06
[161,] 0.9999863 2.737956e-05 1.368978e-05
[162,] 0.9999818 3.632505e-05 1.816253e-05
[163,] 0.9999656 6.888960e-05 3.444480e-05
[164,] 0.9999374 1.251892e-04 6.259461e-05
[165,] 0.9998834 2.331049e-04 1.165525e-04
[166,] 0.9998299 3.402636e-04 1.701318e-04
[167,] 0.9996895 6.209418e-04 3.104709e-04
[168,] 0.9994988 1.002382e-03 5.011912e-04
[169,] 0.9991154 1.769125e-03 8.845624e-04
[170,] 0.9985688 2.862439e-03 1.431219e-03
[171,] 0.9990812 1.837622e-03 9.188108e-04
[172,] 0.9983785 3.242935e-03 1.621467e-03
[173,] 0.9974953 5.009425e-03 2.504713e-03
[174,] 0.9958570 8.286006e-03 4.143003e-03
[175,] 0.9930714 1.385721e-02 6.928603e-03
[176,] 0.9886483 2.270333e-02 1.135166e-02
[177,] 0.9818031 3.639385e-02 1.819692e-02
[178,] 0.9783125 4.337506e-02 2.168753e-02
[179,] 0.9672242 6.555153e-02 3.277576e-02
[180,] 0.9502309 9.953827e-02 4.976914e-02
[181,] 0.9258378 1.483244e-01 7.416218e-02
[182,] 0.8923369 2.153263e-01 1.076631e-01
[183,] 0.8504982 2.990035e-01 1.495018e-01
[184,] 0.7964419 4.071162e-01 2.035581e-01
[185,] 0.7360298 5.279405e-01 2.639702e-01
[186,] 0.6600139 6.799721e-01 3.399861e-01
[187,] 0.6343797 7.312405e-01 3.656203e-01
[188,] 0.5549825 8.900350e-01 4.450175e-01
[189,] 0.5002648 9.994705e-01 4.997352e-01
[190,] 0.3982383 7.964765e-01 6.017617e-01
[191,] 0.2950316 5.900632e-01 7.049684e-01
[192,] 0.4026756 8.053511e-01 5.973244e-01
[193,] 0.2863564 5.727127e-01 7.136436e-01
[194,] 0.3937115 7.874230e-01 6.062885e-01
> postscript(file="/var/www/wessaorg/rcomp/tmp/1ecu41291299719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/2ecu41291299719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/3o3tp1291299719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/4o3tp1291299719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/5o3tp1291299719.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 = 211
Frequency = 1
1 2 3 4 5
-584519.62724 1116581.94581 492896.70613 786192.90955 -446751.03013
6 7 8 9 10
569746.38679 -256445.18194 -332.85782 124766.38319 -188718.47681
11 12 13 14 15
-73120.46566 344425.07400 -167970.24176 627853.86512 274961.20868
16 17 18 19 20
-291131.70219 23230.72101 313570.54018 -162284.61633 -187435.28381
21 22 23 24 25
48730.68673 86055.10057 -58610.31056 65426.74078 -26110.41052
26 27 28 29 30
-148997.50829 99743.03148 251584.83208 83288.39165 -83926.81057
31 32 33 34 35
-78329.94836 57111.19785 -20498.58471 -143925.97259 -114226.33744
36 37 38 39 40
169609.29589 -143206.32698 -50763.28378 -118665.83600 -127726.77369
41 42 43 44 45
-87166.99009 14015.77842 30494.13598 -162764.17739 53342.85395
46 47 48 49 50
-44052.32963 41520.81712 -75265.58996 -106882.73916 -55909.95046
51 52 53 54 55
-34316.37683 99404.15900 122119.85491 -33987.41147 -96911.50999
56 57 58 59 60
-126836.51671 -86853.90548 -86393.46468 36828.82402 -84437.67093
61 62 63 64 65
-91383.68590 80163.66052 -175584.56217 54246.53829 -33677.40661
66 67 68 69 70
59534.17839 21058.24017 4159.19381 15781.57925 -77362.02626
71 72 73 74 75
1388.51568 10380.72997 3607.84846 83661.22057 -12086.35982
76 77 78 79 80
13897.35913 4071.77385 11217.73468 26833.14194 -4351.36701
81 82 83 84 85
17945.97484 20677.02550 1346.81524 -30607.96406 8355.24795
86 87 88 89 90
11590.11078 -6451.63768 -4150.21192 -11367.15707 20521.96929
91 92 93 94 95
16782.47758 -5597.27844 120224.67053 -4073.91127 3515.14693
96 97 98 99 100
2767.33449 36597.33728 35238.39043 -216.59574 -31510.02714
101 102 103 104 105
9653.17625 5303.10242 -11083.99528 15174.30793 -9384.73821
106 107 108 109 110
289.44768 3941.82646 11824.04880 33173.14630 -22981.52478
111 112 113 114 115
-7940.25241 -9959.19504 3515.68007 -20376.38987 -9909.36840
116 117 118 119 120
-27203.66057 3538.45318 40.07608 5283.19870 -4977.32176
121 122 123 124 125
-6953.06966 12340.05597 -26922.87297 -33327.75442 -63335.13629
126 127 128 129 130
34593.77890 34449.52417 -13579.91770 16296.09305 9206.53183
131 132 133 134 135
-24458.39068 -2380.44492 10189.99339 4907.39446 -20426.31603
136 137 138 139 140
13844.87840 -24431.90426 -2423.96950 14869.36868 9094.88000
141 142 143 144 145
-16230.29156 2931.10834 -12976.89367 32067.00872 5601.55665
146 147 148 149 150
26727.58849 -43163.12874 -89.87613 5960.05669 -27940.69988
151 152 153 154 155
-7828.37056 7305.58896 -12318.32662 1991.94606 -2683.54650
156 157 158 159 160
1794.35681 -30822.12520 6017.88604 -11245.89276 -3526.24138
161 162 163 164 165
11617.53846 2793.07597 19910.34095 -15709.20980 -31750.43278
166 167 168 169 170
10044.55220 3327.63968 7270.62267 -30701.20049 -49243.88675
171 172 173 174 175
9679.97063 5728.49232 -10618.50112 38323.32567 1281.37216
176 177 178 179 180
-85158.10563 8872.06430 16365.55699 -4645.71639 -1271.91012
181 182 183 184 185
9071.99787 -4515.11412 -15908.20555 39739.62185 -8882.80791
186 187 188 189 190
-7959.73483 -7745.67376 -843.46575 16340.02858 927.82131
191 192 193 194 195
-12642.48211 -11105.46431 3752.60459 11974.19971 -8046.08365
196 197 198 199 200
-50779.88985 -36075.62354 -59212.45844 -60454.71099 165194.11274
201 202 203 204 205
-16177.19342 -45260.34622 -84874.86586 -100398.02290 -298682.43094
206 207 208 209 210
-55655.83794 -229789.77392 -148462.93078 -103573.58651 160533.42971
211
-352816.39111
> postscript(file="/var/www/wessaorg/rcomp/tmp/6huas1291299719.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 = 211
Frequency = 1
lag(myerror, k = 1) myerror
0 -584519.62724 NA
1 1116581.94581 -584519.62724
2 492896.70613 1116581.94581
3 786192.90955 492896.70613
4 -446751.03013 786192.90955
5 569746.38679 -446751.03013
6 -256445.18194 569746.38679
7 -332.85782 -256445.18194
8 124766.38319 -332.85782
9 -188718.47681 124766.38319
10 -73120.46566 -188718.47681
11 344425.07400 -73120.46566
12 -167970.24176 344425.07400
13 627853.86512 -167970.24176
14 274961.20868 627853.86512
15 -291131.70219 274961.20868
16 23230.72101 -291131.70219
17 313570.54018 23230.72101
18 -162284.61633 313570.54018
19 -187435.28381 -162284.61633
20 48730.68673 -187435.28381
21 86055.10057 48730.68673
22 -58610.31056 86055.10057
23 65426.74078 -58610.31056
24 -26110.41052 65426.74078
25 -148997.50829 -26110.41052
26 99743.03148 -148997.50829
27 251584.83208 99743.03148
28 83288.39165 251584.83208
29 -83926.81057 83288.39165
30 -78329.94836 -83926.81057
31 57111.19785 -78329.94836
32 -20498.58471 57111.19785
33 -143925.97259 -20498.58471
34 -114226.33744 -143925.97259
35 169609.29589 -114226.33744
36 -143206.32698 169609.29589
37 -50763.28378 -143206.32698
38 -118665.83600 -50763.28378
39 -127726.77369 -118665.83600
40 -87166.99009 -127726.77369
41 14015.77842 -87166.99009
42 30494.13598 14015.77842
43 -162764.17739 30494.13598
44 53342.85395 -162764.17739
45 -44052.32963 53342.85395
46 41520.81712 -44052.32963
47 -75265.58996 41520.81712
48 -106882.73916 -75265.58996
49 -55909.95046 -106882.73916
50 -34316.37683 -55909.95046
51 99404.15900 -34316.37683
52 122119.85491 99404.15900
53 -33987.41147 122119.85491
54 -96911.50999 -33987.41147
55 -126836.51671 -96911.50999
56 -86853.90548 -126836.51671
57 -86393.46468 -86853.90548
58 36828.82402 -86393.46468
59 -84437.67093 36828.82402
60 -91383.68590 -84437.67093
61 80163.66052 -91383.68590
62 -175584.56217 80163.66052
63 54246.53829 -175584.56217
64 -33677.40661 54246.53829
65 59534.17839 -33677.40661
66 21058.24017 59534.17839
67 4159.19381 21058.24017
68 15781.57925 4159.19381
69 -77362.02626 15781.57925
70 1388.51568 -77362.02626
71 10380.72997 1388.51568
72 3607.84846 10380.72997
73 83661.22057 3607.84846
74 -12086.35982 83661.22057
75 13897.35913 -12086.35982
76 4071.77385 13897.35913
77 11217.73468 4071.77385
78 26833.14194 11217.73468
79 -4351.36701 26833.14194
80 17945.97484 -4351.36701
81 20677.02550 17945.97484
82 1346.81524 20677.02550
83 -30607.96406 1346.81524
84 8355.24795 -30607.96406
85 11590.11078 8355.24795
86 -6451.63768 11590.11078
87 -4150.21192 -6451.63768
88 -11367.15707 -4150.21192
89 20521.96929 -11367.15707
90 16782.47758 20521.96929
91 -5597.27844 16782.47758
92 120224.67053 -5597.27844
93 -4073.91127 120224.67053
94 3515.14693 -4073.91127
95 2767.33449 3515.14693
96 36597.33728 2767.33449
97 35238.39043 36597.33728
98 -216.59574 35238.39043
99 -31510.02714 -216.59574
100 9653.17625 -31510.02714
101 5303.10242 9653.17625
102 -11083.99528 5303.10242
103 15174.30793 -11083.99528
104 -9384.73821 15174.30793
105 289.44768 -9384.73821
106 3941.82646 289.44768
107 11824.04880 3941.82646
108 33173.14630 11824.04880
109 -22981.52478 33173.14630
110 -7940.25241 -22981.52478
111 -9959.19504 -7940.25241
112 3515.68007 -9959.19504
113 -20376.38987 3515.68007
114 -9909.36840 -20376.38987
115 -27203.66057 -9909.36840
116 3538.45318 -27203.66057
117 40.07608 3538.45318
118 5283.19870 40.07608
119 -4977.32176 5283.19870
120 -6953.06966 -4977.32176
121 12340.05597 -6953.06966
122 -26922.87297 12340.05597
123 -33327.75442 -26922.87297
124 -63335.13629 -33327.75442
125 34593.77890 -63335.13629
126 34449.52417 34593.77890
127 -13579.91770 34449.52417
128 16296.09305 -13579.91770
129 9206.53183 16296.09305
130 -24458.39068 9206.53183
131 -2380.44492 -24458.39068
132 10189.99339 -2380.44492
133 4907.39446 10189.99339
134 -20426.31603 4907.39446
135 13844.87840 -20426.31603
136 -24431.90426 13844.87840
137 -2423.96950 -24431.90426
138 14869.36868 -2423.96950
139 9094.88000 14869.36868
140 -16230.29156 9094.88000
141 2931.10834 -16230.29156
142 -12976.89367 2931.10834
143 32067.00872 -12976.89367
144 5601.55665 32067.00872
145 26727.58849 5601.55665
146 -43163.12874 26727.58849
147 -89.87613 -43163.12874
148 5960.05669 -89.87613
149 -27940.69988 5960.05669
150 -7828.37056 -27940.69988
151 7305.58896 -7828.37056
152 -12318.32662 7305.58896
153 1991.94606 -12318.32662
154 -2683.54650 1991.94606
155 1794.35681 -2683.54650
156 -30822.12520 1794.35681
157 6017.88604 -30822.12520
158 -11245.89276 6017.88604
159 -3526.24138 -11245.89276
160 11617.53846 -3526.24138
161 2793.07597 11617.53846
162 19910.34095 2793.07597
163 -15709.20980 19910.34095
164 -31750.43278 -15709.20980
165 10044.55220 -31750.43278
166 3327.63968 10044.55220
167 7270.62267 3327.63968
168 -30701.20049 7270.62267
169 -49243.88675 -30701.20049
170 9679.97063 -49243.88675
171 5728.49232 9679.97063
172 -10618.50112 5728.49232
173 38323.32567 -10618.50112
174 1281.37216 38323.32567
175 -85158.10563 1281.37216
176 8872.06430 -85158.10563
177 16365.55699 8872.06430
178 -4645.71639 16365.55699
179 -1271.91012 -4645.71639
180 9071.99787 -1271.91012
181 -4515.11412 9071.99787
182 -15908.20555 -4515.11412
183 39739.62185 -15908.20555
184 -8882.80791 39739.62185
185 -7959.73483 -8882.80791
186 -7745.67376 -7959.73483
187 -843.46575 -7745.67376
188 16340.02858 -843.46575
189 927.82131 16340.02858
190 -12642.48211 927.82131
191 -11105.46431 -12642.48211
192 3752.60459 -11105.46431
193 11974.19971 3752.60459
194 -8046.08365 11974.19971
195 -50779.88985 -8046.08365
196 -36075.62354 -50779.88985
197 -59212.45844 -36075.62354
198 -60454.71099 -59212.45844
199 165194.11274 -60454.71099
200 -16177.19342 165194.11274
201 -45260.34622 -16177.19342
202 -84874.86586 -45260.34622
203 -100398.02290 -84874.86586
204 -298682.43094 -100398.02290
205 -55655.83794 -298682.43094
206 -229789.77392 -55655.83794
207 -148462.93078 -229789.77392
208 -103573.58651 -148462.93078
209 160533.42971 -103573.58651
210 -352816.39111 160533.42971
211 NA -352816.39111
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1116581.94581 -584519.62724
[2,] 492896.70613 1116581.94581
[3,] 786192.90955 492896.70613
[4,] -446751.03013 786192.90955
[5,] 569746.38679 -446751.03013
[6,] -256445.18194 569746.38679
[7,] -332.85782 -256445.18194
[8,] 124766.38319 -332.85782
[9,] -188718.47681 124766.38319
[10,] -73120.46566 -188718.47681
[11,] 344425.07400 -73120.46566
[12,] -167970.24176 344425.07400
[13,] 627853.86512 -167970.24176
[14,] 274961.20868 627853.86512
[15,] -291131.70219 274961.20868
[16,] 23230.72101 -291131.70219
[17,] 313570.54018 23230.72101
[18,] -162284.61633 313570.54018
[19,] -187435.28381 -162284.61633
[20,] 48730.68673 -187435.28381
[21,] 86055.10057 48730.68673
[22,] -58610.31056 86055.10057
[23,] 65426.74078 -58610.31056
[24,] -26110.41052 65426.74078
[25,] -148997.50829 -26110.41052
[26,] 99743.03148 -148997.50829
[27,] 251584.83208 99743.03148
[28,] 83288.39165 251584.83208
[29,] -83926.81057 83288.39165
[30,] -78329.94836 -83926.81057
[31,] 57111.19785 -78329.94836
[32,] -20498.58471 57111.19785
[33,] -143925.97259 -20498.58471
[34,] -114226.33744 -143925.97259
[35,] 169609.29589 -114226.33744
[36,] -143206.32698 169609.29589
[37,] -50763.28378 -143206.32698
[38,] -118665.83600 -50763.28378
[39,] -127726.77369 -118665.83600
[40,] -87166.99009 -127726.77369
[41,] 14015.77842 -87166.99009
[42,] 30494.13598 14015.77842
[43,] -162764.17739 30494.13598
[44,] 53342.85395 -162764.17739
[45,] -44052.32963 53342.85395
[46,] 41520.81712 -44052.32963
[47,] -75265.58996 41520.81712
[48,] -106882.73916 -75265.58996
[49,] -55909.95046 -106882.73916
[50,] -34316.37683 -55909.95046
[51,] 99404.15900 -34316.37683
[52,] 122119.85491 99404.15900
[53,] -33987.41147 122119.85491
[54,] -96911.50999 -33987.41147
[55,] -126836.51671 -96911.50999
[56,] -86853.90548 -126836.51671
[57,] -86393.46468 -86853.90548
[58,] 36828.82402 -86393.46468
[59,] -84437.67093 36828.82402
[60,] -91383.68590 -84437.67093
[61,] 80163.66052 -91383.68590
[62,] -175584.56217 80163.66052
[63,] 54246.53829 -175584.56217
[64,] -33677.40661 54246.53829
[65,] 59534.17839 -33677.40661
[66,] 21058.24017 59534.17839
[67,] 4159.19381 21058.24017
[68,] 15781.57925 4159.19381
[69,] -77362.02626 15781.57925
[70,] 1388.51568 -77362.02626
[71,] 10380.72997 1388.51568
[72,] 3607.84846 10380.72997
[73,] 83661.22057 3607.84846
[74,] -12086.35982 83661.22057
[75,] 13897.35913 -12086.35982
[76,] 4071.77385 13897.35913
[77,] 11217.73468 4071.77385
[78,] 26833.14194 11217.73468
[79,] -4351.36701 26833.14194
[80,] 17945.97484 -4351.36701
[81,] 20677.02550 17945.97484
[82,] 1346.81524 20677.02550
[83,] -30607.96406 1346.81524
[84,] 8355.24795 -30607.96406
[85,] 11590.11078 8355.24795
[86,] -6451.63768 11590.11078
[87,] -4150.21192 -6451.63768
[88,] -11367.15707 -4150.21192
[89,] 20521.96929 -11367.15707
[90,] 16782.47758 20521.96929
[91,] -5597.27844 16782.47758
[92,] 120224.67053 -5597.27844
[93,] -4073.91127 120224.67053
[94,] 3515.14693 -4073.91127
[95,] 2767.33449 3515.14693
[96,] 36597.33728 2767.33449
[97,] 35238.39043 36597.33728
[98,] -216.59574 35238.39043
[99,] -31510.02714 -216.59574
[100,] 9653.17625 -31510.02714
[101,] 5303.10242 9653.17625
[102,] -11083.99528 5303.10242
[103,] 15174.30793 -11083.99528
[104,] -9384.73821 15174.30793
[105,] 289.44768 -9384.73821
[106,] 3941.82646 289.44768
[107,] 11824.04880 3941.82646
[108,] 33173.14630 11824.04880
[109,] -22981.52478 33173.14630
[110,] -7940.25241 -22981.52478
[111,] -9959.19504 -7940.25241
[112,] 3515.68007 -9959.19504
[113,] -20376.38987 3515.68007
[114,] -9909.36840 -20376.38987
[115,] -27203.66057 -9909.36840
[116,] 3538.45318 -27203.66057
[117,] 40.07608 3538.45318
[118,] 5283.19870 40.07608
[119,] -4977.32176 5283.19870
[120,] -6953.06966 -4977.32176
[121,] 12340.05597 -6953.06966
[122,] -26922.87297 12340.05597
[123,] -33327.75442 -26922.87297
[124,] -63335.13629 -33327.75442
[125,] 34593.77890 -63335.13629
[126,] 34449.52417 34593.77890
[127,] -13579.91770 34449.52417
[128,] 16296.09305 -13579.91770
[129,] 9206.53183 16296.09305
[130,] -24458.39068 9206.53183
[131,] -2380.44492 -24458.39068
[132,] 10189.99339 -2380.44492
[133,] 4907.39446 10189.99339
[134,] -20426.31603 4907.39446
[135,] 13844.87840 -20426.31603
[136,] -24431.90426 13844.87840
[137,] -2423.96950 -24431.90426
[138,] 14869.36868 -2423.96950
[139,] 9094.88000 14869.36868
[140,] -16230.29156 9094.88000
[141,] 2931.10834 -16230.29156
[142,] -12976.89367 2931.10834
[143,] 32067.00872 -12976.89367
[144,] 5601.55665 32067.00872
[145,] 26727.58849 5601.55665
[146,] -43163.12874 26727.58849
[147,] -89.87613 -43163.12874
[148,] 5960.05669 -89.87613
[149,] -27940.69988 5960.05669
[150,] -7828.37056 -27940.69988
[151,] 7305.58896 -7828.37056
[152,] -12318.32662 7305.58896
[153,] 1991.94606 -12318.32662
[154,] -2683.54650 1991.94606
[155,] 1794.35681 -2683.54650
[156,] -30822.12520 1794.35681
[157,] 6017.88604 -30822.12520
[158,] -11245.89276 6017.88604
[159,] -3526.24138 -11245.89276
[160,] 11617.53846 -3526.24138
[161,] 2793.07597 11617.53846
[162,] 19910.34095 2793.07597
[163,] -15709.20980 19910.34095
[164,] -31750.43278 -15709.20980
[165,] 10044.55220 -31750.43278
[166,] 3327.63968 10044.55220
[167,] 7270.62267 3327.63968
[168,] -30701.20049 7270.62267
[169,] -49243.88675 -30701.20049
[170,] 9679.97063 -49243.88675
[171,] 5728.49232 9679.97063
[172,] -10618.50112 5728.49232
[173,] 38323.32567 -10618.50112
[174,] 1281.37216 38323.32567
[175,] -85158.10563 1281.37216
[176,] 8872.06430 -85158.10563
[177,] 16365.55699 8872.06430
[178,] -4645.71639 16365.55699
[179,] -1271.91012 -4645.71639
[180,] 9071.99787 -1271.91012
[181,] -4515.11412 9071.99787
[182,] -15908.20555 -4515.11412
[183,] 39739.62185 -15908.20555
[184,] -8882.80791 39739.62185
[185,] -7959.73483 -8882.80791
[186,] -7745.67376 -7959.73483
[187,] -843.46575 -7745.67376
[188,] 16340.02858 -843.46575
[189,] 927.82131 16340.02858
[190,] -12642.48211 927.82131
[191,] -11105.46431 -12642.48211
[192,] 3752.60459 -11105.46431
[193,] 11974.19971 3752.60459
[194,] -8046.08365 11974.19971
[195,] -50779.88985 -8046.08365
[196,] -36075.62354 -50779.88985
[197,] -59212.45844 -36075.62354
[198,] -60454.71099 -59212.45844
[199,] 165194.11274 -60454.71099
[200,] -16177.19342 165194.11274
[201,] -45260.34622 -16177.19342
[202,] -84874.86586 -45260.34622
[203,] -100398.02290 -84874.86586
[204,] -298682.43094 -100398.02290
[205,] -55655.83794 -298682.43094
[206,] -229789.77392 -55655.83794
[207,] -148462.93078 -229789.77392
[208,] -103573.58651 -148462.93078
[209,] 160533.42971 -103573.58651
[210,] -352816.39111 160533.42971
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1116581.94581 -584519.62724
2 492896.70613 1116581.94581
3 786192.90955 492896.70613
4 -446751.03013 786192.90955
5 569746.38679 -446751.03013
6 -256445.18194 569746.38679
7 -332.85782 -256445.18194
8 124766.38319 -332.85782
9 -188718.47681 124766.38319
10 -73120.46566 -188718.47681
11 344425.07400 -73120.46566
12 -167970.24176 344425.07400
13 627853.86512 -167970.24176
14 274961.20868 627853.86512
15 -291131.70219 274961.20868
16 23230.72101 -291131.70219
17 313570.54018 23230.72101
18 -162284.61633 313570.54018
19 -187435.28381 -162284.61633
20 48730.68673 -187435.28381
21 86055.10057 48730.68673
22 -58610.31056 86055.10057
23 65426.74078 -58610.31056
24 -26110.41052 65426.74078
25 -148997.50829 -26110.41052
26 99743.03148 -148997.50829
27 251584.83208 99743.03148
28 83288.39165 251584.83208
29 -83926.81057 83288.39165
30 -78329.94836 -83926.81057
31 57111.19785 -78329.94836
32 -20498.58471 57111.19785
33 -143925.97259 -20498.58471
34 -114226.33744 -143925.97259
35 169609.29589 -114226.33744
36 -143206.32698 169609.29589
37 -50763.28378 -143206.32698
38 -118665.83600 -50763.28378
39 -127726.77369 -118665.83600
40 -87166.99009 -127726.77369
41 14015.77842 -87166.99009
42 30494.13598 14015.77842
43 -162764.17739 30494.13598
44 53342.85395 -162764.17739
45 -44052.32963 53342.85395
46 41520.81712 -44052.32963
47 -75265.58996 41520.81712
48 -106882.73916 -75265.58996
49 -55909.95046 -106882.73916
50 -34316.37683 -55909.95046
51 99404.15900 -34316.37683
52 122119.85491 99404.15900
53 -33987.41147 122119.85491
54 -96911.50999 -33987.41147
55 -126836.51671 -96911.50999
56 -86853.90548 -126836.51671
57 -86393.46468 -86853.90548
58 36828.82402 -86393.46468
59 -84437.67093 36828.82402
60 -91383.68590 -84437.67093
61 80163.66052 -91383.68590
62 -175584.56217 80163.66052
63 54246.53829 -175584.56217
64 -33677.40661 54246.53829
65 59534.17839 -33677.40661
66 21058.24017 59534.17839
67 4159.19381 21058.24017
68 15781.57925 4159.19381
69 -77362.02626 15781.57925
70 1388.51568 -77362.02626
71 10380.72997 1388.51568
72 3607.84846 10380.72997
73 83661.22057 3607.84846
74 -12086.35982 83661.22057
75 13897.35913 -12086.35982
76 4071.77385 13897.35913
77 11217.73468 4071.77385
78 26833.14194 11217.73468
79 -4351.36701 26833.14194
80 17945.97484 -4351.36701
81 20677.02550 17945.97484
82 1346.81524 20677.02550
83 -30607.96406 1346.81524
84 8355.24795 -30607.96406
85 11590.11078 8355.24795
86 -6451.63768 11590.11078
87 -4150.21192 -6451.63768
88 -11367.15707 -4150.21192
89 20521.96929 -11367.15707
90 16782.47758 20521.96929
91 -5597.27844 16782.47758
92 120224.67053 -5597.27844
93 -4073.91127 120224.67053
94 3515.14693 -4073.91127
95 2767.33449 3515.14693
96 36597.33728 2767.33449
97 35238.39043 36597.33728
98 -216.59574 35238.39043
99 -31510.02714 -216.59574
100 9653.17625 -31510.02714
101 5303.10242 9653.17625
102 -11083.99528 5303.10242
103 15174.30793 -11083.99528
104 -9384.73821 15174.30793
105 289.44768 -9384.73821
106 3941.82646 289.44768
107 11824.04880 3941.82646
108 33173.14630 11824.04880
109 -22981.52478 33173.14630
110 -7940.25241 -22981.52478
111 -9959.19504 -7940.25241
112 3515.68007 -9959.19504
113 -20376.38987 3515.68007
114 -9909.36840 -20376.38987
115 -27203.66057 -9909.36840
116 3538.45318 -27203.66057
117 40.07608 3538.45318
118 5283.19870 40.07608
119 -4977.32176 5283.19870
120 -6953.06966 -4977.32176
121 12340.05597 -6953.06966
122 -26922.87297 12340.05597
123 -33327.75442 -26922.87297
124 -63335.13629 -33327.75442
125 34593.77890 -63335.13629
126 34449.52417 34593.77890
127 -13579.91770 34449.52417
128 16296.09305 -13579.91770
129 9206.53183 16296.09305
130 -24458.39068 9206.53183
131 -2380.44492 -24458.39068
132 10189.99339 -2380.44492
133 4907.39446 10189.99339
134 -20426.31603 4907.39446
135 13844.87840 -20426.31603
136 -24431.90426 13844.87840
137 -2423.96950 -24431.90426
138 14869.36868 -2423.96950
139 9094.88000 14869.36868
140 -16230.29156 9094.88000
141 2931.10834 -16230.29156
142 -12976.89367 2931.10834
143 32067.00872 -12976.89367
144 5601.55665 32067.00872
145 26727.58849 5601.55665
146 -43163.12874 26727.58849
147 -89.87613 -43163.12874
148 5960.05669 -89.87613
149 -27940.69988 5960.05669
150 -7828.37056 -27940.69988
151 7305.58896 -7828.37056
152 -12318.32662 7305.58896
153 1991.94606 -12318.32662
154 -2683.54650 1991.94606
155 1794.35681 -2683.54650
156 -30822.12520 1794.35681
157 6017.88604 -30822.12520
158 -11245.89276 6017.88604
159 -3526.24138 -11245.89276
160 11617.53846 -3526.24138
161 2793.07597 11617.53846
162 19910.34095 2793.07597
163 -15709.20980 19910.34095
164 -31750.43278 -15709.20980
165 10044.55220 -31750.43278
166 3327.63968 10044.55220
167 7270.62267 3327.63968
168 -30701.20049 7270.62267
169 -49243.88675 -30701.20049
170 9679.97063 -49243.88675
171 5728.49232 9679.97063
172 -10618.50112 5728.49232
173 38323.32567 -10618.50112
174 1281.37216 38323.32567
175 -85158.10563 1281.37216
176 8872.06430 -85158.10563
177 16365.55699 8872.06430
178 -4645.71639 16365.55699
179 -1271.91012 -4645.71639
180 9071.99787 -1271.91012
181 -4515.11412 9071.99787
182 -15908.20555 -4515.11412
183 39739.62185 -15908.20555
184 -8882.80791 39739.62185
185 -7959.73483 -8882.80791
186 -7745.67376 -7959.73483
187 -843.46575 -7745.67376
188 16340.02858 -843.46575
189 927.82131 16340.02858
190 -12642.48211 927.82131
191 -11105.46431 -12642.48211
192 3752.60459 -11105.46431
193 11974.19971 3752.60459
194 -8046.08365 11974.19971
195 -50779.88985 -8046.08365
196 -36075.62354 -50779.88985
197 -59212.45844 -36075.62354
198 -60454.71099 -59212.45844
199 165194.11274 -60454.71099
200 -16177.19342 165194.11274
201 -45260.34622 -16177.19342
202 -84874.86586 -45260.34622
203 -100398.02290 -84874.86586
204 -298682.43094 -100398.02290
205 -55655.83794 -298682.43094
206 -229789.77392 -55655.83794
207 -148462.93078 -229789.77392
208 -103573.58651 -148462.93078
209 160533.42971 -103573.58651
210 -352816.39111 160533.42971
> 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/wessaorg/rcomp/tmp/7smsv1291299719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/8smsv1291299719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/wessaorg/rcomp/tmp/9smsv1291299719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/wessaorg/rcomp/tmp/102v9y1291299719.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/www/wessaorg/rcomp/tmp/11ov7m1291299719.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/wessaorg/rcomp/tmp/12re6a1291299719.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/wessaorg/rcomp/tmp/13yfl41291299719.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/wessaorg/rcomp/tmp/149o2p1291299719.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/wessaorg/rcomp/tmp/15c7ic1291299719.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/wessaorg/rcomp/tmp/16qgg31291299719.tab")
+ }
>
> try(system("convert tmp/1ecu41291299719.ps tmp/1ecu41291299719.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ecu41291299719.ps tmp/2ecu41291299719.png",intern=TRUE))
character(0)
> try(system("convert tmp/3o3tp1291299719.ps tmp/3o3tp1291299719.png",intern=TRUE))
character(0)
> try(system("convert tmp/4o3tp1291299719.ps tmp/4o3tp1291299719.png",intern=TRUE))
character(0)
> try(system("convert tmp/5o3tp1291299719.ps tmp/5o3tp1291299719.png",intern=TRUE))
character(0)
> try(system("convert tmp/6huas1291299719.ps tmp/6huas1291299719.png",intern=TRUE))
character(0)
> try(system("convert tmp/7smsv1291299719.ps tmp/7smsv1291299719.png",intern=TRUE))
character(0)
> try(system("convert tmp/8smsv1291299719.ps tmp/8smsv1291299719.png",intern=TRUE))
character(0)
> try(system("convert tmp/9smsv1291299719.ps tmp/9smsv1291299719.png",intern=TRUE))
character(0)
> try(system("convert tmp/102v9y1291299719.ps tmp/102v9y1291299719.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.65 0.47 8.61