R version 2.12.0 (2010-10-15)
Copyright (C) 2010 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(115
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+ ,124
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+ ,81
+ ,982
+ ,99611
+ ,81
+ ,41
+ ,35
+ ,2
+ ,222
+ ,19349
+ ,15
+ ,13
+ ,11
+ ,72
+ ,1212
+ ,99373
+ ,92
+ ,12
+ ,63
+ ,61
+ ,1143
+ ,86230
+ ,42
+ ,21
+ ,44
+ ,15
+ ,435
+ ,30837
+ ,10
+ ,8
+ ,19
+ ,32
+ ,532
+ ,31706
+ ,24
+ ,26
+ ,13
+ ,62
+ ,882
+ ,89806
+ ,64
+ ,27
+ ,42
+ ,58
+ ,608
+ ,62088
+ ,45
+ ,13
+ ,38
+ ,36
+ ,459
+ ,40151
+ ,22
+ ,16
+ ,29
+ ,59
+ ,578
+ ,27634
+ ,56
+ ,2
+ ,20
+ ,68
+ ,826
+ ,76990
+ ,94
+ ,42
+ ,27
+ ,21
+ ,509
+ ,37460
+ ,19
+ ,5
+ ,20
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+ ,717
+ ,54157
+ ,35
+ ,37
+ ,19
+ ,54
+ ,637
+ ,49862
+ ,32
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+ ,857
+ ,84337
+ ,35
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+ ,830
+ ,64175
+ ,48
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+ ,71
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+ ,62215
+ ,26
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+ ,69
+ ,1090
+ ,69304
+ ,48
+ ,40
+ ,30
+ ,48
+ ,616
+ ,53117
+ ,29
+ ,3
+ ,22
+ ,8
+ ,285
+ ,19764
+ ,19
+ ,10
+ ,12
+ ,52
+ ,1145
+ ,86680
+ ,45
+ ,37
+ ,31
+ ,66
+ ,733
+ ,84105
+ ,45
+ ,17
+ ,20
+ ,76
+ ,888
+ ,77945
+ ,67
+ ,28
+ ,20
+ ,43
+ ,849
+ ,89113
+ ,30
+ ,19
+ ,39
+ ,39
+ ,1182
+ ,91005
+ ,36
+ ,29
+ ,29
+ ,14
+ ,528
+ ,40248
+ ,34
+ ,8
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+ ,64187
+ ,36
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+ ,34
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+ ,757
+ ,62792
+ ,46
+ ,28
+ ,35
+ ,64
+ ,894
+ ,72535
+ ,44
+ ,17
+ ,14)
+ ,dim=c(6
+ ,289)
+ ,dimnames=list(c('LFM'
+ ,'PV'
+ ,'Time'
+ ,'CV'
+ ,'blogs'
+ ,'logins')
+ ,1:289))
> y <- array(NA,dim=c(6,289),dimnames=list(c('LFM','PV','Time','CV','blogs','logins'),1:289))
> 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
LFM PV Time CV blogs logins
1 115 1418 210907 81 79 56
2 109 869 120982 55 58 56
3 146 1530 176508 50 60 54
4 116 2172 179321 125 108 89
5 68 901 123185 40 49 40
6 101 463 52746 37 0 25
7 96 3201 385534 63 121 92
8 67 371 33170 44 1 18
9 44 1192 101645 88 20 63
10 100 1583 149061 66 43 44
11 93 1439 165446 57 69 33
12 140 1764 237213 74 78 84
13 166 1495 173326 49 86 88
14 99 1373 133131 52 44 55
15 139 2187 258873 88 104 60
16 130 1491 180083 36 63 66
17 181 4041 324799 108 158 154
18 116 1706 230964 43 102 53
19 116 2152 236785 75 77 119
20 88 1036 135473 32 82 41
21 139 1882 202925 44 115 61
22 135 1929 215147 85 101 58
23 108 2242 344297 86 80 75
24 89 1220 153935 56 50 33
25 156 1289 132943 50 83 40
26 129 2515 174724 135 123 92
27 118 2147 174415 63 73 100
28 118 2352 225548 81 81 112
29 125 1638 223632 52 105 73
30 95 1222 124817 44 47 40
31 126 1812 221698 113 105 45
32 135 1677 210767 39 94 60
33 154 1579 170266 73 44 62
34 165 1731 260561 48 114 75
35 113 807 84853 33 38 31
36 127 2452 294424 59 107 77
37 52 829 101011 41 30 34
38 121 1940 215641 69 71 46
39 136 2662 325107 64 84 99
40 0 186 7176 1 0 17
41 108 1499 167542 59 59 66
42 46 865 106408 32 33 30
43 54 1793 96560 129 42 76
44 124 2527 265769 37 96 146
45 115 2747 269651 31 106 67
46 128 1324 149112 65 56 56
47 80 2702 175824 107 57 107
48 97 1383 152871 74 59 58
49 104 1179 111665 54 39 34
50 59 2099 116408 76 34 61
51 125 4308 362301 715 76 119
52 82 918 78800 57 20 42
53 149 1831 183167 66 91 66
54 149 3373 277965 106 115 89
55 122 1713 150629 54 85 44
56 118 1438 168809 32 76 66
57 12 496 24188 20 8 24
58 144 2253 329267 71 79 259
59 67 744 65029 21 21 17
60 52 1161 101097 70 30 64
61 108 2352 218946 112 76 41
62 166 2144 244052 66 101 68
63 80 4691 341570 190 94 168
64 60 1112 103597 66 27 43
65 107 2694 233328 165 92 132
66 127 1973 256462 56 123 105
67 107 1769 206161 61 75 71
68 146 3148 311473 53 128 112
69 84 2474 235800 127 105 94
70 141 2084 177939 63 55 82
71 123 1954 207176 38 56 70
72 111 1226 196553 50 41 57
73 98 1389 174184 52 72 53
74 105 1496 143246 42 67 103
75 135 2269 187559 76 75 121
76 107 1833 187681 67 114 62
77 85 1268 119016 50 118 52
78 155 1943 182192 53 77 52
79 88 893 73566 39 22 32
80 155 1762 194979 50 66 62
81 104 1403 167488 77 69 45
82 132 1425 143756 57 105 46
83 127 1857 275541 73 116 63
84 108 1840 243199 34 88 75
85 129 1502 182999 39 73 88
86 116 1441 135649 46 99 46
87 122 1420 152299 63 62 53
88 85 1416 120221 35 53 37
89 147 2970 346485 106 118 90
90 99 1317 145790 43 30 63
91 87 1644 193339 47 100 78
92 28 870 80953 31 49 25
93 90 1654 122774 162 24 45
94 109 1054 130585 57 67 46
95 78 937 112611 36 46 41
96 111 3004 286468 263 57 144
97 158 2008 241066 78 75 82
98 141 2547 148446 63 135 91
99 122 1885 204713 54 68 71
100 124 1626 182079 63 124 63
101 93 1468 140344 77 33 53
102 124 2445 220516 79 98 62
103 112 1964 243060 110 58 63
104 108 1381 162765 56 68 32
105 99 1369 182613 56 81 39
106 117 1659 232138 43 131 62
107 199 2888 265318 111 110 117
108 78 1290 85574 71 37 34
109 91 2845 310839 62 130 92
110 158 1982 225060 56 93 93
111 126 1904 232317 74 118 54
112 122 1391 144966 60 39 144
113 71 602 43287 43 13 14
114 75 1743 155754 68 74 61
115 115 1559 164709 53 81 109
116 119 2014 201940 87 109 38
117 124 2143 235454 46 151 73
118 72 2146 220801 105 51 75
119 91 874 99466 32 28 50
120 45 1590 92661 133 40 61
121 78 1590 133328 79 56 55
122 39 1210 61361 51 27 77
123 68 2072 125930 207 37 75
124 119 1281 100750 67 83 72
125 117 1401 224549 47 54 50
126 39 834 82316 34 27 32
127 50 1105 102010 66 28 53
128 88 1272 101523 76 59 42
129 155 1944 243511 65 133 71
130 0 391 22938 9 12 10
131 36 761 41566 42 0 35
132 123 1605 152474 45 106 65
133 32 530 61857 25 23 25
134 99 1988 99923 115 44 66
135 136 1386 132487 97 71 41
136 117 2395 317394 53 116 86
137 0 387 21054 2 4 16
138 88 1742 209641 52 62 42
139 39 620 22648 44 12 19
140 25 449 31414 22 18 19
141 52 800 46698 35 14 45
142 75 1684 131698 74 60 65
143 71 1050 91735 103 7 35
144 124 2699 244749 144 98 95
145 151 1606 184510 60 64 49
146 71 1502 79863 134 29 37
147 145 1204 128423 89 32 64
148 87 1138 97839 42 25 38
149 27 568 38214 52 16 34
150 131 1459 151101 98 48 32
151 162 2158 272458 99 100 65
152 165 1111 172494 52 46 52
153 54 1421 108043 29 45 62
154 159 2833 328107 125 129 65
155 147 1955 250579 106 130 83
156 170 2922 351067 95 136 95
157 119 1002 158015 40 59 29
158 49 1060 98866 140 25 18
159 104 956 85439 43 32 33
160 120 2186 229242 128 63 247
161 150 3604 351619 142 95 139
162 112 1035 84207 73 14 29
163 59 1417 120445 72 36 118
164 136 3261 324598 128 113 110
165 107 1587 131069 61 47 67
166 130 1424 204271 73 92 42
167 115 1701 165543 148 70 65
168 107 1249 141722 64 19 94
169 75 946 116048 45 50 64
170 71 1926 250047 58 41 81
171 120 3352 299775 97 91 95
172 116 1641 195838 50 111 67
173 79 2035 173260 37 41 63
174 150 2312 254488 50 120 83
175 156 1369 104389 105 135 45
176 51 1577 136084 69 27 30
177 118 2201 199476 46 87 70
178 71 961 92499 57 25 32
179 144 1900 224330 52 131 83
180 47 1254 135781 98 45 31
181 28 1335 74408 61 29 67
182 68 1597 81240 89 58 66
183 0 207 14688 0 4 10
184 110 1645 181633 48 47 70
185 147 2429 271856 91 109 103
186 0 151 7199 0 7 5
187 15 474 46660 7 12 20
188 4 141 17547 3 0 5
189 64 1639 133368 54 37 36
190 111 872 95227 70 37 34
191 85 1318 152601 36 46 48
192 68 1018 98146 37 15 40
193 40 1383 79619 123 42 43
194 80 1314 59194 247 7 31
195 88 1335 139942 46 54 42
196 48 1403 118612 72 54 46
197 76 910 72880 41 14 33
198 51 616 65475 24 16 18
199 67 1407 99643 45 33 55
200 59 771 71965 33 32 35
201 61 766 77272 27 21 59
202 76 473 49289 36 15 19
203 60 1376 135131 87 38 66
204 68 1232 108446 90 22 60
205 71 1521 89746 114 28 36
206 76 572 44296 31 10 25
207 62 1059 77648 45 31 47
208 61 1544 181528 69 32 54
209 67 1230 134019 51 32 53
210 88 1206 124064 34 43 40
211 30 1205 92630 60 27 40
212 64 1255 121848 45 37 39
213 68 613 52915 54 20 14
214 64 721 81872 25 32 45
215 91 1109 58981 38 0 36
216 88 740 53515 52 5 28
217 52 1126 60812 67 26 44
218 49 728 56375 74 10 30
219 62 689 65490 38 27 22
220 61 592 80949 30 11 17
221 76 995 76302 26 29 31
222 88 1613 104011 67 25 55
223 66 2048 98104 132 55 54
224 71 705 67989 42 23 21
225 68 301 30989 35 5 14
226 48 1803 135458 118 43 81
227 25 799 73504 68 23 35
228 68 861 63123 43 34 43
229 41 1186 61254 76 36 46
230 90 1451 74914 64 35 30
231 66 628 31774 48 0 23
232 54 1161 81437 64 37 38
233 59 1463 87186 56 28 54
234 60 742 50090 71 16 20
235 77 979 65745 75 26 53
236 68 675 56653 39 38 45
237 72 1241 158399 42 23 39
238 67 676 46455 39 22 20
239 64 1049 73624 93 30 24
240 63 620 38395 38 16 31
241 59 1081 91899 60 18 35
242 84 1688 139526 71 28 151
243 64 736 52164 52 32 52
244 56 617 51567 27 21 30
245 54 812 70551 59 23 31
246 67 1051 84856 40 29 29
247 58 1656 102538 79 50 57
248 59 705 86678 44 12 40
249 40 945 85709 65 21 44
250 22 554 34662 10 18 25
251 83 1597 150580 124 27 77
252 81 982 99611 81 41 35
253 2 222 19349 15 13 11
254 72 1212 99373 92 12 63
255 61 1143 86230 42 21 44
256 15 435 30837 10 8 19
257 32 532 31706 24 26 13
258 62 882 89806 64 27 42
259 58 608 62088 45 13 38
260 36 459 40151 22 16 29
261 59 578 27634 56 2 20
262 68 826 76990 94 42 27
263 21 509 37460 19 5 20
264 55 717 54157 35 37 19
265 54 637 49862 32 17 37
266 55 857 84337 35 38 26
267 72 830 64175 48 37 42
268 41 652 59382 49 29 49
269 61 707 119308 48 32 30
270 67 954 76702 62 35 49
271 76 1461 103425 96 17 67
272 64 672 70344 45 20 28
273 3 778 43410 63 7 19
274 63 1141 104838 71 46 49
275 40 680 62215 26 24 27
276 69 1090 69304 48 40 30
277 48 616 53117 29 3 22
278 8 285 19764 19 10 12
279 52 1145 86680 45 37 31
280 66 733 84105 45 17 20
281 76 888 77945 67 28 20
282 43 849 89113 30 19 39
283 39 1182 91005 36 29 29
284 14 528 40248 34 8 16
285 61 642 64187 36 10 27
286 71 947 50857 34 15 21
287 44 819 56613 37 15 19
288 60 757 62792 46 28 35
289 64 894 72535 44 17 14
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) PV Time CV blogs logins
36.9421598 -0.0126444 0.0002448 0.0375444 0.5093704 0.1016905
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-68.218 -16.151 -0.528 14.057 69.200
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.694e+01 3.112e+00 11.870 < 2e-16 ***
PV -1.264e-02 5.486e-03 -2.305 0.0219 *
Time 2.448e-04 4.577e-05 5.349 1.83e-07 ***
CV 3.754e-02 3.557e-02 1.056 0.2921
blogs 5.094e-01 7.242e-02 7.034 1.51e-11 ***
logins 1.017e-01 6.543e-02 1.554 0.1213
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 24.08 on 283 degrees of freedom
Multiple R-squared: 0.6476, Adjusted R-squared: 0.6414
F-statistic: 104 on 5 and 283 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,] 0.9649711 7.005772e-02 3.502886e-02
[2,] 0.9300509 1.398982e-01 6.994909e-02
[3,] 0.9154503 1.690994e-01 8.454969e-02
[4,] 0.9279123 1.441753e-01 7.208766e-02
[5,] 0.9088746 1.822507e-01 9.112537e-02
[6,] 0.8622644 2.754711e-01 1.377356e-01
[7,] 0.8732871 2.534257e-01 1.267129e-01
[8,] 0.8258051 3.483899e-01 1.741949e-01
[9,] 0.7784828 4.430344e-01 2.215172e-01
[10,] 0.7590370 4.819259e-01 2.409630e-01
[11,] 0.7203367 5.593265e-01 2.796633e-01
[12,] 0.8098157 3.803686e-01 1.901843e-01
[13,] 0.7556305 4.887391e-01 2.443695e-01
[14,] 0.7273213 5.453574e-01 2.726787e-01
[15,] 0.6787030 6.425940e-01 3.212970e-01
[16,] 0.6144006 7.711988e-01 3.855994e-01
[17,] 0.7048912 5.902177e-01 2.951088e-01
[18,] 0.6519557 6.960886e-01 3.480443e-01
[19,] 0.6000073 7.999855e-01 3.999927e-01
[20,] 0.5424712 9.150576e-01 4.575288e-01
[21,] 0.4994123 9.988245e-01 5.005877e-01
[22,] 0.4415067 8.830134e-01 5.584933e-01
[23,] 0.3961075 7.922150e-01 6.038925e-01
[24,] 0.3430795 6.861591e-01 6.569205e-01
[25,] 0.6396029 7.207941e-01 3.603971e-01
[26,] 0.6318693 7.362614e-01 3.681307e-01
[27,] 0.6110091 7.779818e-01 3.889909e-01
[28,] 0.5619844 8.760313e-01 4.380156e-01
[29,] 0.6505061 6.989878e-01 3.494939e-01
[30,] 0.6235807 7.528385e-01 3.764193e-01
[31,] 0.5856626 8.286748e-01 4.143374e-01
[32,] 0.8629318 2.741364e-01 1.370682e-01
[33,] 0.8343005 3.313990e-01 1.656995e-01
[34,] 0.8645195 2.709611e-01 1.354805e-01
[35,] 0.8762254 2.475491e-01 1.237746e-01
[36,] 0.8676471 2.647058e-01 1.323529e-01
[37,] 0.8456300 3.087400e-01 1.543700e-01
[38,] 0.8540124 2.919753e-01 1.459876e-01
[39,] 0.8310854 3.378292e-01 1.689146e-01
[40,] 0.8017180 3.965641e-01 1.982820e-01
[41,] 0.7982197 4.035606e-01 2.017803e-01
[42,] 0.7679728 4.640544e-01 2.320272e-01
[43,] 0.7500037 4.999925e-01 2.499963e-01
[44,] 0.7219315 5.561369e-01 2.780685e-01
[45,] 0.7366144 5.267712e-01 2.633856e-01
[46,] 0.7291110 5.417779e-01 2.708890e-01
[47,] 0.7016312 5.967376e-01 2.983688e-01
[48,] 0.6653644 6.692712e-01 3.346356e-01
[49,] 0.7557452 4.885096e-01 2.442548e-01
[50,] 0.7285628 5.428743e-01 2.714372e-01
[51,] 0.6940716 6.118568e-01 3.059284e-01
[52,] 0.6987220 6.025560e-01 3.012780e-01
[53,] 0.6609943 6.780113e-01 3.390057e-01
[54,] 0.6957768 6.084464e-01 3.042232e-01
[55,] 0.7532091 4.935817e-01 2.467909e-01
[56,] 0.7287266 5.425469e-01 2.712734e-01
[57,] 0.7202825 5.594349e-01 2.797175e-01
[58,] 0.7399597 5.200805e-01 2.600403e-01
[59,] 0.7087337 5.825327e-01 2.912663e-01
[60,] 0.6737783 6.524435e-01 3.262217e-01
[61,] 0.7820538 4.358923e-01 2.179462e-01
[62,] 0.8634658 2.730685e-01 1.365342e-01
[63,] 0.8649967 2.700065e-01 1.350033e-01
[64,] 0.8493082 3.013837e-01 1.506918e-01
[65,] 0.8326726 3.346548e-01 1.673274e-01
[66,] 0.8079882 3.840237e-01 1.920118e-01
[67,] 0.8134512 3.730977e-01 1.865488e-01
[68,] 0.8188157 3.623685e-01 1.811843e-01
[69,] 0.8634320 2.731360e-01 1.365680e-01
[70,] 0.9176532 1.646936e-01 8.234678e-02
[71,] 0.9152215 1.695571e-01 8.477853e-02
[72,] 0.9514766 9.704688e-02 4.852344e-02
[73,] 0.9415529 1.168943e-01 5.844713e-02
[74,] 0.9341469 1.317061e-01 6.585307e-02
[75,] 0.9311935 1.376130e-01 6.880648e-02
[76,] 0.9257781 1.484438e-01 7.422192e-02
[77,] 0.9194360 1.611280e-01 8.056401e-02
[78,] 0.9062837 1.874326e-01 9.371631e-02
[79,] 0.9046452 1.907096e-01 9.535482e-02
[80,] 0.8900259 2.199482e-01 1.099741e-01
[81,] 0.8739920 2.520160e-01 1.260080e-01
[82,] 0.8634889 2.730223e-01 1.365111e-01
[83,] 0.8915058 2.169884e-01 1.084942e-01
[84,] 0.9439416 1.121168e-01 5.605839e-02
[85,] 0.9368017 1.263966e-01 6.319831e-02
[86,] 0.9269401 1.461198e-01 7.305988e-02
[87,] 0.9162311 1.675378e-01 8.376892e-02
[88,] 0.9138540 1.722920e-01 8.614600e-02
[89,] 0.9323763 1.352473e-01 6.762367e-02
[90,] 0.9301437 1.397126e-01 6.985628e-02
[91,] 0.9220748 1.558503e-01 7.792516e-02
[92,] 0.9101681 1.796638e-01 8.983189e-02
[93,] 0.8979532 2.040935e-01 1.020468e-01
[94,] 0.8822100 2.355801e-01 1.177900e-01
[95,] 0.8644337 2.711326e-01 1.355663e-01
[96,] 0.8463156 3.073688e-01 1.536844e-01
[97,] 0.8327550 3.344901e-01 1.672450e-01
[98,] 0.8389428 3.221144e-01 1.610572e-01
[99,] 0.9355242 1.289515e-01 6.447577e-02
[100,] 0.9257634 1.484732e-01 7.423662e-02
[101,] 0.9706329 5.873415e-02 2.936707e-02
[102,] 0.9757282 4.854365e-02 2.427182e-02
[103,] 0.9714454 5.710925e-02 2.855462e-02
[104,] 0.9735182 5.296368e-02 2.648184e-02
[105,] 0.9709275 5.814495e-02 2.907247e-02
[106,] 0.9723724 5.525527e-02 2.762763e-02
[107,] 0.9669390 6.612201e-02 3.306100e-02
[108,] 0.9603490 7.930191e-02 3.965095e-02
[109,] 0.9607412 7.851761e-02 3.925881e-02
[110,] 0.9673159 6.536822e-02 3.268411e-02
[111,] 0.9648620 7.027597e-02 3.513799e-02
[112,] 0.9712646 5.747073e-02 2.873537e-02
[113,] 0.9669643 6.607137e-02 3.303568e-02
[114,] 0.9688585 6.228309e-02 3.114155e-02
[115,] 0.9670910 6.581800e-02 3.290900e-02
[116,] 0.9660075 6.798503e-02 3.399251e-02
[117,] 0.9596507 8.069864e-02 4.034932e-02
[118,] 0.9639943 7.201137e-02 3.600568e-02
[119,] 0.9644546 7.109085e-02 3.554543e-02
[120,] 0.9574294 8.514128e-02 4.257064e-02
[121,] 0.9502641 9.947175e-02 4.973588e-02
[122,] 0.9720633 5.587340e-02 2.793670e-02
[123,] 0.9677622 6.447564e-02 3.223782e-02
[124,] 0.9626422 7.471568e-02 3.735784e-02
[125,] 0.9667790 6.644201e-02 3.322101e-02
[126,] 0.9681837 6.363252e-02 3.181626e-02
[127,] 0.9763733 4.725343e-02 2.362672e-02
[128,] 0.9816885 3.662295e-02 1.831147e-02
[129,] 0.9884283 2.314349e-02 1.157175e-02
[130,] 0.9872528 2.549447e-02 1.274723e-02
[131,] 0.9846621 3.067572e-02 1.533786e-02
[132,] 0.9854271 2.914581e-02 1.457291e-02
[133,] 0.9823228 3.535441e-02 1.767721e-02
[134,] 0.9795133 4.097348e-02 2.048674e-02
[135,] 0.9755967 4.880667e-02 2.440333e-02
[136,] 0.9709796 5.804078e-02 2.902039e-02
[137,] 0.9846649 3.067030e-02 1.533515e-02
[138,] 0.9812334 3.753329e-02 1.876664e-02
[139,] 0.9953245 9.351074e-03 4.675537e-03
[140,] 0.9952350 9.530005e-03 4.765002e-03
[141,] 0.9955835 8.832934e-03 4.416467e-03
[142,] 0.9973573 5.285349e-03 2.642675e-03
[143,] 0.9973179 5.364294e-03 2.682147e-03
[144,] 0.9997448 5.104059e-04 2.552029e-04
[145,] 0.9997261 5.478053e-04 2.739027e-04
[146,] 0.9996263 7.474058e-04 3.737029e-04
[147,] 0.9994941 1.011773e-03 5.058863e-04
[148,] 0.9993192 1.361606e-03 6.808032e-04
[149,] 0.9993535 1.293015e-03 6.465074e-04
[150,] 0.9993694 1.261128e-03 6.305638e-04
[151,] 0.9996405 7.190117e-04 3.595059e-04
[152,] 0.9995171 9.657440e-04 4.828720e-04
[153,] 0.9993502 1.299526e-03 6.497628e-04
[154,] 0.9998467 3.066352e-04 1.533176e-04
[155,] 0.9998487 3.026388e-04 1.513194e-04
[156,] 0.9998160 3.679413e-04 1.839706e-04
[157,] 0.9998321 3.358493e-04 1.679247e-04
[158,] 0.9997835 4.330249e-04 2.165124e-04
[159,] 0.9997102 5.795319e-04 2.897659e-04
[160,] 0.9997896 4.208454e-04 2.104227e-04
[161,] 0.9997249 5.502297e-04 2.751148e-04
[162,] 0.9997966 4.067140e-04 2.033570e-04
[163,] 0.9997406 5.188818e-04 2.594409e-04
[164,] 0.9996617 6.766490e-04 3.383245e-04
[165,] 0.9995384 9.231033e-04 4.615517e-04
[166,] 0.9994153 1.169401e-03 5.847005e-04
[167,] 0.9997515 4.969052e-04 2.484526e-04
[168,] 0.9997643 4.713848e-04 2.356924e-04
[169,] 0.9996972 6.055338e-04 3.027669e-04
[170,] 0.9995936 8.128978e-04 4.064489e-04
[171,] 0.9996078 7.844588e-04 3.922294e-04
[172,] 0.9997823 4.353566e-04 2.176783e-04
[173,] 0.9998634 2.732976e-04 1.366488e-04
[174,] 0.9998104 3.791369e-04 1.895685e-04
[175,] 0.9998991 2.018501e-04 1.009251e-04
[176,] 0.9998886 2.227326e-04 1.113663e-04
[177,] 0.9998948 2.103736e-04 1.051868e-04
[178,] 0.9999499 1.001639e-04 5.008195e-05
[179,] 0.9999707 5.858477e-05 2.929238e-05
[180,] 0.9999868 2.636763e-05 1.318382e-05
[181,] 0.9999814 3.714581e-05 1.857290e-05
[182,] 0.9999961 7.744370e-06 3.872185e-06
[183,] 0.9999947 1.053157e-05 5.265783e-06
[184,] 0.9999920 1.596733e-05 7.983664e-06
[185,] 0.9999940 1.198570e-05 5.992852e-06
[186,] 0.9999921 1.571094e-05 7.855469e-06
[187,] 0.9999909 1.825046e-05 9.125230e-06
[188,] 0.9999919 1.610646e-05 8.053229e-06
[189,] 0.9999910 1.792128e-05 8.960639e-06
[190,] 0.9999863 2.741084e-05 1.370542e-05
[191,] 0.9999790 4.204444e-05 2.102222e-05
[192,] 0.9999688 6.243126e-05 3.121563e-05
[193,] 0.9999538 9.239678e-05 4.619839e-05
[194,] 0.9999618 7.639072e-05 3.819536e-05
[195,] 0.9999538 9.231018e-05 4.615509e-05
[196,] 0.9999305 1.389069e-04 6.945343e-05
[197,] 0.9998970 2.059272e-04 1.029636e-04
[198,] 0.9999192 1.615797e-04 8.078987e-05
[199,] 0.9998804 2.392569e-04 1.196284e-04
[200,] 0.9998882 2.236105e-04 1.118052e-04
[201,] 0.9998408 3.184919e-04 1.592459e-04
[202,] 0.9998258 3.484708e-04 1.742354e-04
[203,] 0.9999128 1.744811e-04 8.724054e-05
[204,] 0.9998741 2.517709e-04 1.258855e-04
[205,] 0.9998513 2.974911e-04 1.487456e-04
[206,] 0.9997938 4.124844e-04 2.062422e-04
[207,] 0.9999171 1.657726e-04 8.288631e-05
[208,] 0.9999710 5.804794e-05 2.902397e-05
[209,] 0.9999556 8.885272e-05 4.442636e-05
[210,] 0.9999318 1.364829e-04 6.824144e-05
[211,] 0.9999021 1.957925e-04 9.789624e-05
[212,] 0.9998590 2.819612e-04 1.409806e-04
[213,] 0.9998579 2.841928e-04 1.420964e-04
[214,] 0.9998688 2.623340e-04 1.311670e-04
[215,] 0.9998322 3.356936e-04 1.678468e-04
[216,] 0.9998143 3.714040e-04 1.857020e-04
[217,] 0.9998754 2.492505e-04 1.246252e-04
[218,] 0.9999735 5.309117e-05 2.654558e-05
[219,] 0.9999912 1.763989e-05 8.819945e-06
[220,] 0.9999880 2.402846e-05 1.201423e-05
[221,] 0.9999917 1.662866e-05 8.314331e-06
[222,] 0.9999946 1.074036e-05 5.370179e-06
[223,] 0.9999968 6.461757e-06 3.230879e-06
[224,] 0.9999953 9.377029e-06 4.688514e-06
[225,] 0.9999919 1.629374e-05 8.146872e-06
[226,] 0.9999869 2.623590e-05 1.311795e-05
[227,] 0.9999836 3.283341e-05 1.641671e-05
[228,] 0.9999786 4.289045e-05 2.144523e-05
[229,] 0.9999632 7.367317e-05 3.683659e-05
[230,] 0.9999698 6.046138e-05 3.023069e-05
[231,] 0.9999480 1.040916e-04 5.204581e-05
[232,] 0.9999587 8.250444e-05 4.125222e-05
[233,] 0.9999288 1.424135e-04 7.120674e-05
[234,] 0.9998783 2.434833e-04 1.217417e-04
[235,] 0.9998454 3.092664e-04 1.546332e-04
[236,] 0.9998145 3.710199e-04 1.855100e-04
[237,] 0.9996905 6.190147e-04 3.095073e-04
[238,] 0.9995511 8.978603e-04 4.489301e-04
[239,] 0.9995875 8.249888e-04 4.124944e-04
[240,] 0.9993843 1.231339e-03 6.156695e-04
[241,] 0.9994308 1.138318e-03 5.691591e-04
[242,] 0.9991992 1.601574e-03 8.007871e-04
[243,] 0.9991720 1.656079e-03 8.280396e-04
[244,] 0.9986663 2.667330e-03 1.333665e-03
[245,] 0.9989105 2.178985e-03 1.089492e-03
[246,] 0.9981989 3.602257e-03 1.801128e-03
[247,] 0.9970591 5.881737e-03 2.940869e-03
[248,] 0.9962754 7.449116e-03 3.724558e-03
[249,] 0.9943341 1.133188e-02 5.665938e-03
[250,] 0.9910850 1.782991e-02 8.914957e-03
[251,] 0.9877122 2.457554e-02 1.228777e-02
[252,] 0.9813868 3.722632e-02 1.861316e-02
[253,] 0.9841404 3.171916e-02 1.585958e-02
[254,] 0.9756013 4.879738e-02 2.439869e-02
[255,] 0.9667894 6.642120e-02 3.321060e-02
[256,] 0.9521075 9.578500e-02 4.789250e-02
[257,] 0.9391668 1.216665e-01 6.083325e-02
[258,] 0.9146042 1.707916e-01 8.539581e-02
[259,] 0.9080593 1.838814e-01 9.194068e-02
[260,] 0.8729454 2.541092e-01 1.270546e-01
[261,] 0.8444150 3.111700e-01 1.555850e-01
[262,] 0.8001215 3.997570e-01 1.998785e-01
[263,] 0.7560182 4.879636e-01 2.439818e-01
[264,] 0.7101999 5.796003e-01 2.898001e-01
[265,] 0.9421704 1.156593e-01 5.782965e-02
[266,] 0.9483923 1.032154e-01 5.160769e-02
[267,] 0.9360727 1.278547e-01 6.392734e-02
[268,] 0.9144495 1.711009e-01 8.555045e-02
[269,] 0.8495430 3.009140e-01 1.504570e-01
[270,] 0.8403262 3.193476e-01 1.596738e-01
[271,] 0.7367476 5.265047e-01 2.632524e-01
[272,] 0.7717442 4.565117e-01 2.282558e-01
> postscript(file="/var/www/rcomp/tmp/1ybrx1324309741.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/23qpm1324309741.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3n95y1324309741.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4va441324309741.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5cfu71324309741.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 = 289
Frequency = 1
1 2 3 4 5 6
-4.62768789 16.12104377 47.25615143 -6.13967832 -18.23918018 53.06626091
7 8 9 10 11 12
-68.21768552 22.63568898 -22.65500623 17.72201645 -6.89767120 16.23125814
13 14 15 16 17 18
50.92912980 16.86471250 3.94783587 27.66492979 15.43315593 -14.88069662
19 20 21 22 23 24
-5.84527142 -16.15138553 9.73700030 9.23574396 -36.49762288 -1.13281299
25 26 27 28 29 30
54.58361665 4.00181736 15.78253533 -0.11600352 -8.84514054 13.28864252
31 32 33 34 35 36
-4.61436683 12.21103020 63.87692095 18.65142002 41.73869270 -15.57390148
37 38 39 40 41 42
-19.46977755 12.35598630 -2.14051257 -38.11358601 10.01062898 -27.11945079
43 44 45 46 47 48
-17.87815149 -11.19717063 -15.20078241 34.63008043 -9.75868175 1.38633987
49 50 51 52 53 54
29.27477936 -6.27845622 -23.83482919 20.77326300 34.82021730 15.04161370
55 56 57 58 59 60
20.03884734 11.28350744 -31.85924891 -14.31704315 10.32937221 -19.43240273
61 62 63 64 65 66
0.10345217 35.57351891 -53.35687509 -8.85029783 -19.48712268 -23.22042955
67 68 69 70 71 72
-5.76447217 -5.97843287 -47.20502918 48.12220581 22.96946943 12.87733718
73 74 75 76 77 78
-8.04353167 5.72216087 27.46460725 -19.60601917 -32.32022689 51.51803849
79 80 81 82 83 84
28.41262791 50.79739419 1.17598738 17.57665597 -22.16021102 -18.95011723
85 86 87 88 89 90
18.64652699 7.23312363 26.38756173 4.45370106 -10.46055481 19.71271340
91 92 93 94 95 96
-37.12610537 -46.42766422 21.02805614 12.46650234 -3.61840816 -11.65002842
97 98 99 100 101 102
37.95441762 19.53287971 14.88521219 -8.89700748 15.16771643 4.79229161
103 104 105 106 107 108
0.29984154 8.67398600 -12.67105047 -30.44938359 61.51742621 11.44700560
109 110 111 112 113 114
-63.97727867 32.08334548 -12.12387638 30.39063326 21.41131848 -24.48793001
115 116 117 118 119 120
3.10936186 -4.57207732 -29.56004333 -29.41587933 20.20709564 -26.09639429
121 122 123 124 125 126
-8.56583542 -21.16424420 -7.82134780 21.47236264 8.43811263 -25.83490168
127 128 129 130 131 132
-20.07651659 5.10700233 5.60972540 -45.08168055 -6.63299043 6.72714048
133 134 135 136 137 138
-28.58232202 29.28787780 40.16793737 -37.19296962 -40.94334170 -16.04918841
139 140 141 142 143 144
-5.34438187 -25.88311466 0.71832371 -12.84483324 13.88187451 -3.72550279
145 146 147 148 149 150
49.35341225 9.93050991 65.68862482 22.31652380 -25.67631841 44.12664616
151 152 153 154 155 156
24.37098952 69.20043806 -21.74340371 0.53274554 -5.21323545 1.54651106
157 158 159 160 161 162
21.53489012 -18.56673292 36.95662361 -7.44355325 4.68003984 54.70627339
163 164 165 166 167 168
-22.55527260 -12.73508361 24.98918008 7.17516718 11.21140063 29.51115748
169 170 171 172 173 174
-12.06039778 -34.11019054 -7.61131147 -13.37301493 -3.31228724 8.53990225
175 176 177 178 179 180
33.52577775 -18.71555509 6.88708902 5.43291123 -0.96374952 -37.08464502
181 182 183 184 185 186
-34.15545199 -8.23669068 -40.97542322 16.52528738 4.79679531 -40.86953327
187 188 189 190 191 192
-35.78219328 -36.07665921 -9.40728926 36.83572604 -2.30403044 6.80207664
193 194 195 196 197 198
-29.33339815 29.18781486 0.17013499 -35.13044938 20.69372875 -5.06577976
199 200 201 202 203 204
-0.64017121 -6.91149996 -2.88633735 22.04626052 -21.96346803 -0.60317077
205 206 207 208 209 210
9.11291230 26.64498882 -2.82281406 -25.24691516 -10.80748441 8.68362516
211 212 213 214 215 216
-34.45883343 -11.40930264 12.21447144 -5.68593375 48.55178765 39.96537886
217 218 219 220 221 222
-5.82750734 -3.46281572 0.31812953 3.26532127 14.05663693 25.14407951
223 224 225 226 227 228
-7.52913247 10.89756974 21.99176650 -33.88046873 -37.66399207 3.18369263
229 230 231 232 233 234
-21.81204990 29.78109608 25.07783547 -13.31515182 -2.64651538 7.32636309
235 236 237 238 239 240
14.89038684 0.32529222 -5.29178414 12.52703911 1.08211301 11.76756521
241 242 243 244 245 246
-1.75496956 1.95621439 0.05201401 -0.52762102 -7.03193069 3.34808915
247 248 249 250 251 252
-17.33973071 -2.08244576 -23.59006978 -28.51031741 3.14368655 4.60105264
253 254 255 256 257 258
-45.17616334 10.07895137 0.64947386 -30.37462472 -21.44503493 -6.20508658
259 260 261 262 263 264
1.36822034 -16.89403332 17.44524477 -5.01678638 -23.97201904 -8.22901459
265 266 267 268 269 270
-0.71934883 -15.06938576 4.91999892 -23.83157896 -17.36708439 -1.79796839
271 272 273 274 275 276
13.13150311 3.60734344 -42.59650518 -16.26336368 -19.52361551 3.64390783
277 278 279 280 281 282
0.98732863 -37.20493472 -15.37600023 5.35099220 12.39005619 -19.79613069
283 284 285 286 287 288
-24.35086355 -33.09891505 7.26880800 22.52748721 -7.40956481 -2.29316637
289
8.86726418
> postscript(file="/var/www/rcomp/tmp/64l061324309741.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 = 289
Frequency = 1
lag(myerror, k = 1) myerror
0 -4.62768789 NA
1 16.12104377 -4.62768789
2 47.25615143 16.12104377
3 -6.13967832 47.25615143
4 -18.23918018 -6.13967832
5 53.06626091 -18.23918018
6 -68.21768552 53.06626091
7 22.63568898 -68.21768552
8 -22.65500623 22.63568898
9 17.72201645 -22.65500623
10 -6.89767120 17.72201645
11 16.23125814 -6.89767120
12 50.92912980 16.23125814
13 16.86471250 50.92912980
14 3.94783587 16.86471250
15 27.66492979 3.94783587
16 15.43315593 27.66492979
17 -14.88069662 15.43315593
18 -5.84527142 -14.88069662
19 -16.15138553 -5.84527142
20 9.73700030 -16.15138553
21 9.23574396 9.73700030
22 -36.49762288 9.23574396
23 -1.13281299 -36.49762288
24 54.58361665 -1.13281299
25 4.00181736 54.58361665
26 15.78253533 4.00181736
27 -0.11600352 15.78253533
28 -8.84514054 -0.11600352
29 13.28864252 -8.84514054
30 -4.61436683 13.28864252
31 12.21103020 -4.61436683
32 63.87692095 12.21103020
33 18.65142002 63.87692095
34 41.73869270 18.65142002
35 -15.57390148 41.73869270
36 -19.46977755 -15.57390148
37 12.35598630 -19.46977755
38 -2.14051257 12.35598630
39 -38.11358601 -2.14051257
40 10.01062898 -38.11358601
41 -27.11945079 10.01062898
42 -17.87815149 -27.11945079
43 -11.19717063 -17.87815149
44 -15.20078241 -11.19717063
45 34.63008043 -15.20078241
46 -9.75868175 34.63008043
47 1.38633987 -9.75868175
48 29.27477936 1.38633987
49 -6.27845622 29.27477936
50 -23.83482919 -6.27845622
51 20.77326300 -23.83482919
52 34.82021730 20.77326300
53 15.04161370 34.82021730
54 20.03884734 15.04161370
55 11.28350744 20.03884734
56 -31.85924891 11.28350744
57 -14.31704315 -31.85924891
58 10.32937221 -14.31704315
59 -19.43240273 10.32937221
60 0.10345217 -19.43240273
61 35.57351891 0.10345217
62 -53.35687509 35.57351891
63 -8.85029783 -53.35687509
64 -19.48712268 -8.85029783
65 -23.22042955 -19.48712268
66 -5.76447217 -23.22042955
67 -5.97843287 -5.76447217
68 -47.20502918 -5.97843287
69 48.12220581 -47.20502918
70 22.96946943 48.12220581
71 12.87733718 22.96946943
72 -8.04353167 12.87733718
73 5.72216087 -8.04353167
74 27.46460725 5.72216087
75 -19.60601917 27.46460725
76 -32.32022689 -19.60601917
77 51.51803849 -32.32022689
78 28.41262791 51.51803849
79 50.79739419 28.41262791
80 1.17598738 50.79739419
81 17.57665597 1.17598738
82 -22.16021102 17.57665597
83 -18.95011723 -22.16021102
84 18.64652699 -18.95011723
85 7.23312363 18.64652699
86 26.38756173 7.23312363
87 4.45370106 26.38756173
88 -10.46055481 4.45370106
89 19.71271340 -10.46055481
90 -37.12610537 19.71271340
91 -46.42766422 -37.12610537
92 21.02805614 -46.42766422
93 12.46650234 21.02805614
94 -3.61840816 12.46650234
95 -11.65002842 -3.61840816
96 37.95441762 -11.65002842
97 19.53287971 37.95441762
98 14.88521219 19.53287971
99 -8.89700748 14.88521219
100 15.16771643 -8.89700748
101 4.79229161 15.16771643
102 0.29984154 4.79229161
103 8.67398600 0.29984154
104 -12.67105047 8.67398600
105 -30.44938359 -12.67105047
106 61.51742621 -30.44938359
107 11.44700560 61.51742621
108 -63.97727867 11.44700560
109 32.08334548 -63.97727867
110 -12.12387638 32.08334548
111 30.39063326 -12.12387638
112 21.41131848 30.39063326
113 -24.48793001 21.41131848
114 3.10936186 -24.48793001
115 -4.57207732 3.10936186
116 -29.56004333 -4.57207732
117 -29.41587933 -29.56004333
118 20.20709564 -29.41587933
119 -26.09639429 20.20709564
120 -8.56583542 -26.09639429
121 -21.16424420 -8.56583542
122 -7.82134780 -21.16424420
123 21.47236264 -7.82134780
124 8.43811263 21.47236264
125 -25.83490168 8.43811263
126 -20.07651659 -25.83490168
127 5.10700233 -20.07651659
128 5.60972540 5.10700233
129 -45.08168055 5.60972540
130 -6.63299043 -45.08168055
131 6.72714048 -6.63299043
132 -28.58232202 6.72714048
133 29.28787780 -28.58232202
134 40.16793737 29.28787780
135 -37.19296962 40.16793737
136 -40.94334170 -37.19296962
137 -16.04918841 -40.94334170
138 -5.34438187 -16.04918841
139 -25.88311466 -5.34438187
140 0.71832371 -25.88311466
141 -12.84483324 0.71832371
142 13.88187451 -12.84483324
143 -3.72550279 13.88187451
144 49.35341225 -3.72550279
145 9.93050991 49.35341225
146 65.68862482 9.93050991
147 22.31652380 65.68862482
148 -25.67631841 22.31652380
149 44.12664616 -25.67631841
150 24.37098952 44.12664616
151 69.20043806 24.37098952
152 -21.74340371 69.20043806
153 0.53274554 -21.74340371
154 -5.21323545 0.53274554
155 1.54651106 -5.21323545
156 21.53489012 1.54651106
157 -18.56673292 21.53489012
158 36.95662361 -18.56673292
159 -7.44355325 36.95662361
160 4.68003984 -7.44355325
161 54.70627339 4.68003984
162 -22.55527260 54.70627339
163 -12.73508361 -22.55527260
164 24.98918008 -12.73508361
165 7.17516718 24.98918008
166 11.21140063 7.17516718
167 29.51115748 11.21140063
168 -12.06039778 29.51115748
169 -34.11019054 -12.06039778
170 -7.61131147 -34.11019054
171 -13.37301493 -7.61131147
172 -3.31228724 -13.37301493
173 8.53990225 -3.31228724
174 33.52577775 8.53990225
175 -18.71555509 33.52577775
176 6.88708902 -18.71555509
177 5.43291123 6.88708902
178 -0.96374952 5.43291123
179 -37.08464502 -0.96374952
180 -34.15545199 -37.08464502
181 -8.23669068 -34.15545199
182 -40.97542322 -8.23669068
183 16.52528738 -40.97542322
184 4.79679531 16.52528738
185 -40.86953327 4.79679531
186 -35.78219328 -40.86953327
187 -36.07665921 -35.78219328
188 -9.40728926 -36.07665921
189 36.83572604 -9.40728926
190 -2.30403044 36.83572604
191 6.80207664 -2.30403044
192 -29.33339815 6.80207664
193 29.18781486 -29.33339815
194 0.17013499 29.18781486
195 -35.13044938 0.17013499
196 20.69372875 -35.13044938
197 -5.06577976 20.69372875
198 -0.64017121 -5.06577976
199 -6.91149996 -0.64017121
200 -2.88633735 -6.91149996
201 22.04626052 -2.88633735
202 -21.96346803 22.04626052
203 -0.60317077 -21.96346803
204 9.11291230 -0.60317077
205 26.64498882 9.11291230
206 -2.82281406 26.64498882
207 -25.24691516 -2.82281406
208 -10.80748441 -25.24691516
209 8.68362516 -10.80748441
210 -34.45883343 8.68362516
211 -11.40930264 -34.45883343
212 12.21447144 -11.40930264
213 -5.68593375 12.21447144
214 48.55178765 -5.68593375
215 39.96537886 48.55178765
216 -5.82750734 39.96537886
217 -3.46281572 -5.82750734
218 0.31812953 -3.46281572
219 3.26532127 0.31812953
220 14.05663693 3.26532127
221 25.14407951 14.05663693
222 -7.52913247 25.14407951
223 10.89756974 -7.52913247
224 21.99176650 10.89756974
225 -33.88046873 21.99176650
226 -37.66399207 -33.88046873
227 3.18369263 -37.66399207
228 -21.81204990 3.18369263
229 29.78109608 -21.81204990
230 25.07783547 29.78109608
231 -13.31515182 25.07783547
232 -2.64651538 -13.31515182
233 7.32636309 -2.64651538
234 14.89038684 7.32636309
235 0.32529222 14.89038684
236 -5.29178414 0.32529222
237 12.52703911 -5.29178414
238 1.08211301 12.52703911
239 11.76756521 1.08211301
240 -1.75496956 11.76756521
241 1.95621439 -1.75496956
242 0.05201401 1.95621439
243 -0.52762102 0.05201401
244 -7.03193069 -0.52762102
245 3.34808915 -7.03193069
246 -17.33973071 3.34808915
247 -2.08244576 -17.33973071
248 -23.59006978 -2.08244576
249 -28.51031741 -23.59006978
250 3.14368655 -28.51031741
251 4.60105264 3.14368655
252 -45.17616334 4.60105264
253 10.07895137 -45.17616334
254 0.64947386 10.07895137
255 -30.37462472 0.64947386
256 -21.44503493 -30.37462472
257 -6.20508658 -21.44503493
258 1.36822034 -6.20508658
259 -16.89403332 1.36822034
260 17.44524477 -16.89403332
261 -5.01678638 17.44524477
262 -23.97201904 -5.01678638
263 -8.22901459 -23.97201904
264 -0.71934883 -8.22901459
265 -15.06938576 -0.71934883
266 4.91999892 -15.06938576
267 -23.83157896 4.91999892
268 -17.36708439 -23.83157896
269 -1.79796839 -17.36708439
270 13.13150311 -1.79796839
271 3.60734344 13.13150311
272 -42.59650518 3.60734344
273 -16.26336368 -42.59650518
274 -19.52361551 -16.26336368
275 3.64390783 -19.52361551
276 0.98732863 3.64390783
277 -37.20493472 0.98732863
278 -15.37600023 -37.20493472
279 5.35099220 -15.37600023
280 12.39005619 5.35099220
281 -19.79613069 12.39005619
282 -24.35086355 -19.79613069
283 -33.09891505 -24.35086355
284 7.26880800 -33.09891505
285 22.52748721 7.26880800
286 -7.40956481 22.52748721
287 -2.29316637 -7.40956481
288 8.86726418 -2.29316637
289 NA 8.86726418
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 16.12104377 -4.62768789
[2,] 47.25615143 16.12104377
[3,] -6.13967832 47.25615143
[4,] -18.23918018 -6.13967832
[5,] 53.06626091 -18.23918018
[6,] -68.21768552 53.06626091
[7,] 22.63568898 -68.21768552
[8,] -22.65500623 22.63568898
[9,] 17.72201645 -22.65500623
[10,] -6.89767120 17.72201645
[11,] 16.23125814 -6.89767120
[12,] 50.92912980 16.23125814
[13,] 16.86471250 50.92912980
[14,] 3.94783587 16.86471250
[15,] 27.66492979 3.94783587
[16,] 15.43315593 27.66492979
[17,] -14.88069662 15.43315593
[18,] -5.84527142 -14.88069662
[19,] -16.15138553 -5.84527142
[20,] 9.73700030 -16.15138553
[21,] 9.23574396 9.73700030
[22,] -36.49762288 9.23574396
[23,] -1.13281299 -36.49762288
[24,] 54.58361665 -1.13281299
[25,] 4.00181736 54.58361665
[26,] 15.78253533 4.00181736
[27,] -0.11600352 15.78253533
[28,] -8.84514054 -0.11600352
[29,] 13.28864252 -8.84514054
[30,] -4.61436683 13.28864252
[31,] 12.21103020 -4.61436683
[32,] 63.87692095 12.21103020
[33,] 18.65142002 63.87692095
[34,] 41.73869270 18.65142002
[35,] -15.57390148 41.73869270
[36,] -19.46977755 -15.57390148
[37,] 12.35598630 -19.46977755
[38,] -2.14051257 12.35598630
[39,] -38.11358601 -2.14051257
[40,] 10.01062898 -38.11358601
[41,] -27.11945079 10.01062898
[42,] -17.87815149 -27.11945079
[43,] -11.19717063 -17.87815149
[44,] -15.20078241 -11.19717063
[45,] 34.63008043 -15.20078241
[46,] -9.75868175 34.63008043
[47,] 1.38633987 -9.75868175
[48,] 29.27477936 1.38633987
[49,] -6.27845622 29.27477936
[50,] -23.83482919 -6.27845622
[51,] 20.77326300 -23.83482919
[52,] 34.82021730 20.77326300
[53,] 15.04161370 34.82021730
[54,] 20.03884734 15.04161370
[55,] 11.28350744 20.03884734
[56,] -31.85924891 11.28350744
[57,] -14.31704315 -31.85924891
[58,] 10.32937221 -14.31704315
[59,] -19.43240273 10.32937221
[60,] 0.10345217 -19.43240273
[61,] 35.57351891 0.10345217
[62,] -53.35687509 35.57351891
[63,] -8.85029783 -53.35687509
[64,] -19.48712268 -8.85029783
[65,] -23.22042955 -19.48712268
[66,] -5.76447217 -23.22042955
[67,] -5.97843287 -5.76447217
[68,] -47.20502918 -5.97843287
[69,] 48.12220581 -47.20502918
[70,] 22.96946943 48.12220581
[71,] 12.87733718 22.96946943
[72,] -8.04353167 12.87733718
[73,] 5.72216087 -8.04353167
[74,] 27.46460725 5.72216087
[75,] -19.60601917 27.46460725
[76,] -32.32022689 -19.60601917
[77,] 51.51803849 -32.32022689
[78,] 28.41262791 51.51803849
[79,] 50.79739419 28.41262791
[80,] 1.17598738 50.79739419
[81,] 17.57665597 1.17598738
[82,] -22.16021102 17.57665597
[83,] -18.95011723 -22.16021102
[84,] 18.64652699 -18.95011723
[85,] 7.23312363 18.64652699
[86,] 26.38756173 7.23312363
[87,] 4.45370106 26.38756173
[88,] -10.46055481 4.45370106
[89,] 19.71271340 -10.46055481
[90,] -37.12610537 19.71271340
[91,] -46.42766422 -37.12610537
[92,] 21.02805614 -46.42766422
[93,] 12.46650234 21.02805614
[94,] -3.61840816 12.46650234
[95,] -11.65002842 -3.61840816
[96,] 37.95441762 -11.65002842
[97,] 19.53287971 37.95441762
[98,] 14.88521219 19.53287971
[99,] -8.89700748 14.88521219
[100,] 15.16771643 -8.89700748
[101,] 4.79229161 15.16771643
[102,] 0.29984154 4.79229161
[103,] 8.67398600 0.29984154
[104,] -12.67105047 8.67398600
[105,] -30.44938359 -12.67105047
[106,] 61.51742621 -30.44938359
[107,] 11.44700560 61.51742621
[108,] -63.97727867 11.44700560
[109,] 32.08334548 -63.97727867
[110,] -12.12387638 32.08334548
[111,] 30.39063326 -12.12387638
[112,] 21.41131848 30.39063326
[113,] -24.48793001 21.41131848
[114,] 3.10936186 -24.48793001
[115,] -4.57207732 3.10936186
[116,] -29.56004333 -4.57207732
[117,] -29.41587933 -29.56004333
[118,] 20.20709564 -29.41587933
[119,] -26.09639429 20.20709564
[120,] -8.56583542 -26.09639429
[121,] -21.16424420 -8.56583542
[122,] -7.82134780 -21.16424420
[123,] 21.47236264 -7.82134780
[124,] 8.43811263 21.47236264
[125,] -25.83490168 8.43811263
[126,] -20.07651659 -25.83490168
[127,] 5.10700233 -20.07651659
[128,] 5.60972540 5.10700233
[129,] -45.08168055 5.60972540
[130,] -6.63299043 -45.08168055
[131,] 6.72714048 -6.63299043
[132,] -28.58232202 6.72714048
[133,] 29.28787780 -28.58232202
[134,] 40.16793737 29.28787780
[135,] -37.19296962 40.16793737
[136,] -40.94334170 -37.19296962
[137,] -16.04918841 -40.94334170
[138,] -5.34438187 -16.04918841
[139,] -25.88311466 -5.34438187
[140,] 0.71832371 -25.88311466
[141,] -12.84483324 0.71832371
[142,] 13.88187451 -12.84483324
[143,] -3.72550279 13.88187451
[144,] 49.35341225 -3.72550279
[145,] 9.93050991 49.35341225
[146,] 65.68862482 9.93050991
[147,] 22.31652380 65.68862482
[148,] -25.67631841 22.31652380
[149,] 44.12664616 -25.67631841
[150,] 24.37098952 44.12664616
[151,] 69.20043806 24.37098952
[152,] -21.74340371 69.20043806
[153,] 0.53274554 -21.74340371
[154,] -5.21323545 0.53274554
[155,] 1.54651106 -5.21323545
[156,] 21.53489012 1.54651106
[157,] -18.56673292 21.53489012
[158,] 36.95662361 -18.56673292
[159,] -7.44355325 36.95662361
[160,] 4.68003984 -7.44355325
[161,] 54.70627339 4.68003984
[162,] -22.55527260 54.70627339
[163,] -12.73508361 -22.55527260
[164,] 24.98918008 -12.73508361
[165,] 7.17516718 24.98918008
[166,] 11.21140063 7.17516718
[167,] 29.51115748 11.21140063
[168,] -12.06039778 29.51115748
[169,] -34.11019054 -12.06039778
[170,] -7.61131147 -34.11019054
[171,] -13.37301493 -7.61131147
[172,] -3.31228724 -13.37301493
[173,] 8.53990225 -3.31228724
[174,] 33.52577775 8.53990225
[175,] -18.71555509 33.52577775
[176,] 6.88708902 -18.71555509
[177,] 5.43291123 6.88708902
[178,] -0.96374952 5.43291123
[179,] -37.08464502 -0.96374952
[180,] -34.15545199 -37.08464502
[181,] -8.23669068 -34.15545199
[182,] -40.97542322 -8.23669068
[183,] 16.52528738 -40.97542322
[184,] 4.79679531 16.52528738
[185,] -40.86953327 4.79679531
[186,] -35.78219328 -40.86953327
[187,] -36.07665921 -35.78219328
[188,] -9.40728926 -36.07665921
[189,] 36.83572604 -9.40728926
[190,] -2.30403044 36.83572604
[191,] 6.80207664 -2.30403044
[192,] -29.33339815 6.80207664
[193,] 29.18781486 -29.33339815
[194,] 0.17013499 29.18781486
[195,] -35.13044938 0.17013499
[196,] 20.69372875 -35.13044938
[197,] -5.06577976 20.69372875
[198,] -0.64017121 -5.06577976
[199,] -6.91149996 -0.64017121
[200,] -2.88633735 -6.91149996
[201,] 22.04626052 -2.88633735
[202,] -21.96346803 22.04626052
[203,] -0.60317077 -21.96346803
[204,] 9.11291230 -0.60317077
[205,] 26.64498882 9.11291230
[206,] -2.82281406 26.64498882
[207,] -25.24691516 -2.82281406
[208,] -10.80748441 -25.24691516
[209,] 8.68362516 -10.80748441
[210,] -34.45883343 8.68362516
[211,] -11.40930264 -34.45883343
[212,] 12.21447144 -11.40930264
[213,] -5.68593375 12.21447144
[214,] 48.55178765 -5.68593375
[215,] 39.96537886 48.55178765
[216,] -5.82750734 39.96537886
[217,] -3.46281572 -5.82750734
[218,] 0.31812953 -3.46281572
[219,] 3.26532127 0.31812953
[220,] 14.05663693 3.26532127
[221,] 25.14407951 14.05663693
[222,] -7.52913247 25.14407951
[223,] 10.89756974 -7.52913247
[224,] 21.99176650 10.89756974
[225,] -33.88046873 21.99176650
[226,] -37.66399207 -33.88046873
[227,] 3.18369263 -37.66399207
[228,] -21.81204990 3.18369263
[229,] 29.78109608 -21.81204990
[230,] 25.07783547 29.78109608
[231,] -13.31515182 25.07783547
[232,] -2.64651538 -13.31515182
[233,] 7.32636309 -2.64651538
[234,] 14.89038684 7.32636309
[235,] 0.32529222 14.89038684
[236,] -5.29178414 0.32529222
[237,] 12.52703911 -5.29178414
[238,] 1.08211301 12.52703911
[239,] 11.76756521 1.08211301
[240,] -1.75496956 11.76756521
[241,] 1.95621439 -1.75496956
[242,] 0.05201401 1.95621439
[243,] -0.52762102 0.05201401
[244,] -7.03193069 -0.52762102
[245,] 3.34808915 -7.03193069
[246,] -17.33973071 3.34808915
[247,] -2.08244576 -17.33973071
[248,] -23.59006978 -2.08244576
[249,] -28.51031741 -23.59006978
[250,] 3.14368655 -28.51031741
[251,] 4.60105264 3.14368655
[252,] -45.17616334 4.60105264
[253,] 10.07895137 -45.17616334
[254,] 0.64947386 10.07895137
[255,] -30.37462472 0.64947386
[256,] -21.44503493 -30.37462472
[257,] -6.20508658 -21.44503493
[258,] 1.36822034 -6.20508658
[259,] -16.89403332 1.36822034
[260,] 17.44524477 -16.89403332
[261,] -5.01678638 17.44524477
[262,] -23.97201904 -5.01678638
[263,] -8.22901459 -23.97201904
[264,] -0.71934883 -8.22901459
[265,] -15.06938576 -0.71934883
[266,] 4.91999892 -15.06938576
[267,] -23.83157896 4.91999892
[268,] -17.36708439 -23.83157896
[269,] -1.79796839 -17.36708439
[270,] 13.13150311 -1.79796839
[271,] 3.60734344 13.13150311
[272,] -42.59650518 3.60734344
[273,] -16.26336368 -42.59650518
[274,] -19.52361551 -16.26336368
[275,] 3.64390783 -19.52361551
[276,] 0.98732863 3.64390783
[277,] -37.20493472 0.98732863
[278,] -15.37600023 -37.20493472
[279,] 5.35099220 -15.37600023
[280,] 12.39005619 5.35099220
[281,] -19.79613069 12.39005619
[282,] -24.35086355 -19.79613069
[283,] -33.09891505 -24.35086355
[284,] 7.26880800 -33.09891505
[285,] 22.52748721 7.26880800
[286,] -7.40956481 22.52748721
[287,] -2.29316637 -7.40956481
[288,] 8.86726418 -2.29316637
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 16.12104377 -4.62768789
2 47.25615143 16.12104377
3 -6.13967832 47.25615143
4 -18.23918018 -6.13967832
5 53.06626091 -18.23918018
6 -68.21768552 53.06626091
7 22.63568898 -68.21768552
8 -22.65500623 22.63568898
9 17.72201645 -22.65500623
10 -6.89767120 17.72201645
11 16.23125814 -6.89767120
12 50.92912980 16.23125814
13 16.86471250 50.92912980
14 3.94783587 16.86471250
15 27.66492979 3.94783587
16 15.43315593 27.66492979
17 -14.88069662 15.43315593
18 -5.84527142 -14.88069662
19 -16.15138553 -5.84527142
20 9.73700030 -16.15138553
21 9.23574396 9.73700030
22 -36.49762288 9.23574396
23 -1.13281299 -36.49762288
24 54.58361665 -1.13281299
25 4.00181736 54.58361665
26 15.78253533 4.00181736
27 -0.11600352 15.78253533
28 -8.84514054 -0.11600352
29 13.28864252 -8.84514054
30 -4.61436683 13.28864252
31 12.21103020 -4.61436683
32 63.87692095 12.21103020
33 18.65142002 63.87692095
34 41.73869270 18.65142002
35 -15.57390148 41.73869270
36 -19.46977755 -15.57390148
37 12.35598630 -19.46977755
38 -2.14051257 12.35598630
39 -38.11358601 -2.14051257
40 10.01062898 -38.11358601
41 -27.11945079 10.01062898
42 -17.87815149 -27.11945079
43 -11.19717063 -17.87815149
44 -15.20078241 -11.19717063
45 34.63008043 -15.20078241
46 -9.75868175 34.63008043
47 1.38633987 -9.75868175
48 29.27477936 1.38633987
49 -6.27845622 29.27477936
50 -23.83482919 -6.27845622
51 20.77326300 -23.83482919
52 34.82021730 20.77326300
53 15.04161370 34.82021730
54 20.03884734 15.04161370
55 11.28350744 20.03884734
56 -31.85924891 11.28350744
57 -14.31704315 -31.85924891
58 10.32937221 -14.31704315
59 -19.43240273 10.32937221
60 0.10345217 -19.43240273
61 35.57351891 0.10345217
62 -53.35687509 35.57351891
63 -8.85029783 -53.35687509
64 -19.48712268 -8.85029783
65 -23.22042955 -19.48712268
66 -5.76447217 -23.22042955
67 -5.97843287 -5.76447217
68 -47.20502918 -5.97843287
69 48.12220581 -47.20502918
70 22.96946943 48.12220581
71 12.87733718 22.96946943
72 -8.04353167 12.87733718
73 5.72216087 -8.04353167
74 27.46460725 5.72216087
75 -19.60601917 27.46460725
76 -32.32022689 -19.60601917
77 51.51803849 -32.32022689
78 28.41262791 51.51803849
79 50.79739419 28.41262791
80 1.17598738 50.79739419
81 17.57665597 1.17598738
82 -22.16021102 17.57665597
83 -18.95011723 -22.16021102
84 18.64652699 -18.95011723
85 7.23312363 18.64652699
86 26.38756173 7.23312363
87 4.45370106 26.38756173
88 -10.46055481 4.45370106
89 19.71271340 -10.46055481
90 -37.12610537 19.71271340
91 -46.42766422 -37.12610537
92 21.02805614 -46.42766422
93 12.46650234 21.02805614
94 -3.61840816 12.46650234
95 -11.65002842 -3.61840816
96 37.95441762 -11.65002842
97 19.53287971 37.95441762
98 14.88521219 19.53287971
99 -8.89700748 14.88521219
100 15.16771643 -8.89700748
101 4.79229161 15.16771643
102 0.29984154 4.79229161
103 8.67398600 0.29984154
104 -12.67105047 8.67398600
105 -30.44938359 -12.67105047
106 61.51742621 -30.44938359
107 11.44700560 61.51742621
108 -63.97727867 11.44700560
109 32.08334548 -63.97727867
110 -12.12387638 32.08334548
111 30.39063326 -12.12387638
112 21.41131848 30.39063326
113 -24.48793001 21.41131848
114 3.10936186 -24.48793001
115 -4.57207732 3.10936186
116 -29.56004333 -4.57207732
117 -29.41587933 -29.56004333
118 20.20709564 -29.41587933
119 -26.09639429 20.20709564
120 -8.56583542 -26.09639429
121 -21.16424420 -8.56583542
122 -7.82134780 -21.16424420
123 21.47236264 -7.82134780
124 8.43811263 21.47236264
125 -25.83490168 8.43811263
126 -20.07651659 -25.83490168
127 5.10700233 -20.07651659
128 5.60972540 5.10700233
129 -45.08168055 5.60972540
130 -6.63299043 -45.08168055
131 6.72714048 -6.63299043
132 -28.58232202 6.72714048
133 29.28787780 -28.58232202
134 40.16793737 29.28787780
135 -37.19296962 40.16793737
136 -40.94334170 -37.19296962
137 -16.04918841 -40.94334170
138 -5.34438187 -16.04918841
139 -25.88311466 -5.34438187
140 0.71832371 -25.88311466
141 -12.84483324 0.71832371
142 13.88187451 -12.84483324
143 -3.72550279 13.88187451
144 49.35341225 -3.72550279
145 9.93050991 49.35341225
146 65.68862482 9.93050991
147 22.31652380 65.68862482
148 -25.67631841 22.31652380
149 44.12664616 -25.67631841
150 24.37098952 44.12664616
151 69.20043806 24.37098952
152 -21.74340371 69.20043806
153 0.53274554 -21.74340371
154 -5.21323545 0.53274554
155 1.54651106 -5.21323545
156 21.53489012 1.54651106
157 -18.56673292 21.53489012
158 36.95662361 -18.56673292
159 -7.44355325 36.95662361
160 4.68003984 -7.44355325
161 54.70627339 4.68003984
162 -22.55527260 54.70627339
163 -12.73508361 -22.55527260
164 24.98918008 -12.73508361
165 7.17516718 24.98918008
166 11.21140063 7.17516718
167 29.51115748 11.21140063
168 -12.06039778 29.51115748
169 -34.11019054 -12.06039778
170 -7.61131147 -34.11019054
171 -13.37301493 -7.61131147
172 -3.31228724 -13.37301493
173 8.53990225 -3.31228724
174 33.52577775 8.53990225
175 -18.71555509 33.52577775
176 6.88708902 -18.71555509
177 5.43291123 6.88708902
178 -0.96374952 5.43291123
179 -37.08464502 -0.96374952
180 -34.15545199 -37.08464502
181 -8.23669068 -34.15545199
182 -40.97542322 -8.23669068
183 16.52528738 -40.97542322
184 4.79679531 16.52528738
185 -40.86953327 4.79679531
186 -35.78219328 -40.86953327
187 -36.07665921 -35.78219328
188 -9.40728926 -36.07665921
189 36.83572604 -9.40728926
190 -2.30403044 36.83572604
191 6.80207664 -2.30403044
192 -29.33339815 6.80207664
193 29.18781486 -29.33339815
194 0.17013499 29.18781486
195 -35.13044938 0.17013499
196 20.69372875 -35.13044938
197 -5.06577976 20.69372875
198 -0.64017121 -5.06577976
199 -6.91149996 -0.64017121
200 -2.88633735 -6.91149996
201 22.04626052 -2.88633735
202 -21.96346803 22.04626052
203 -0.60317077 -21.96346803
204 9.11291230 -0.60317077
205 26.64498882 9.11291230
206 -2.82281406 26.64498882
207 -25.24691516 -2.82281406
208 -10.80748441 -25.24691516
209 8.68362516 -10.80748441
210 -34.45883343 8.68362516
211 -11.40930264 -34.45883343
212 12.21447144 -11.40930264
213 -5.68593375 12.21447144
214 48.55178765 -5.68593375
215 39.96537886 48.55178765
216 -5.82750734 39.96537886
217 -3.46281572 -5.82750734
218 0.31812953 -3.46281572
219 3.26532127 0.31812953
220 14.05663693 3.26532127
221 25.14407951 14.05663693
222 -7.52913247 25.14407951
223 10.89756974 -7.52913247
224 21.99176650 10.89756974
225 -33.88046873 21.99176650
226 -37.66399207 -33.88046873
227 3.18369263 -37.66399207
228 -21.81204990 3.18369263
229 29.78109608 -21.81204990
230 25.07783547 29.78109608
231 -13.31515182 25.07783547
232 -2.64651538 -13.31515182
233 7.32636309 -2.64651538
234 14.89038684 7.32636309
235 0.32529222 14.89038684
236 -5.29178414 0.32529222
237 12.52703911 -5.29178414
238 1.08211301 12.52703911
239 11.76756521 1.08211301
240 -1.75496956 11.76756521
241 1.95621439 -1.75496956
242 0.05201401 1.95621439
243 -0.52762102 0.05201401
244 -7.03193069 -0.52762102
245 3.34808915 -7.03193069
246 -17.33973071 3.34808915
247 -2.08244576 -17.33973071
248 -23.59006978 -2.08244576
249 -28.51031741 -23.59006978
250 3.14368655 -28.51031741
251 4.60105264 3.14368655
252 -45.17616334 4.60105264
253 10.07895137 -45.17616334
254 0.64947386 10.07895137
255 -30.37462472 0.64947386
256 -21.44503493 -30.37462472
257 -6.20508658 -21.44503493
258 1.36822034 -6.20508658
259 -16.89403332 1.36822034
260 17.44524477 -16.89403332
261 -5.01678638 17.44524477
262 -23.97201904 -5.01678638
263 -8.22901459 -23.97201904
264 -0.71934883 -8.22901459
265 -15.06938576 -0.71934883
266 4.91999892 -15.06938576
267 -23.83157896 4.91999892
268 -17.36708439 -23.83157896
269 -1.79796839 -17.36708439
270 13.13150311 -1.79796839
271 3.60734344 13.13150311
272 -42.59650518 3.60734344
273 -16.26336368 -42.59650518
274 -19.52361551 -16.26336368
275 3.64390783 -19.52361551
276 0.98732863 3.64390783
277 -37.20493472 0.98732863
278 -15.37600023 -37.20493472
279 5.35099220 -15.37600023
280 12.39005619 5.35099220
281 -19.79613069 12.39005619
282 -24.35086355 -19.79613069
283 -33.09891505 -24.35086355
284 7.26880800 -33.09891505
285 22.52748721 7.26880800
286 -7.40956481 22.52748721
287 -2.29316637 -7.40956481
288 8.86726418 -2.29316637
> 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/rcomp/tmp/7vg8y1324309741.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8gu1f1324309741.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/95sc91324309741.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10i2w51324309741.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11c2481324309741.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/rcomp/tmp/12d8cp1324309741.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/rcomp/tmp/13n6xs1324309741.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/rcomp/tmp/14syyo1324309741.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/rcomp/tmp/15e6mv1324309741.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/rcomp/tmp/161na71324309741.tab")
+ }
>
> try(system("convert tmp/1ybrx1324309741.ps tmp/1ybrx1324309741.png",intern=TRUE))
character(0)
> try(system("convert tmp/23qpm1324309741.ps tmp/23qpm1324309741.png",intern=TRUE))
character(0)
> try(system("convert tmp/3n95y1324309741.ps tmp/3n95y1324309741.png",intern=TRUE))
character(0)
> try(system("convert tmp/4va441324309741.ps tmp/4va441324309741.png",intern=TRUE))
character(0)
> try(system("convert tmp/5cfu71324309741.ps tmp/5cfu71324309741.png",intern=TRUE))
character(0)
> try(system("convert tmp/64l061324309741.ps tmp/64l061324309741.png",intern=TRUE))
character(0)
> try(system("convert tmp/7vg8y1324309741.ps tmp/7vg8y1324309741.png",intern=TRUE))
character(0)
> try(system("convert tmp/8gu1f1324309741.ps tmp/8gu1f1324309741.png",intern=TRUE))
character(0)
> try(system("convert tmp/95sc91324309741.ps tmp/95sc91324309741.png",intern=TRUE))
character(0)
> try(system("convert tmp/10i2w51324309741.ps tmp/10i2w51324309741.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.940 0.290 7.233