R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(210907
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+ ,1926
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+ ,46
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+ ,1018
+ ,459
+ ,15
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+ ,21
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+ ,48
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+ ,1383
+ ,426
+ ,42
+ ,11
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+ ,43
+ ,29668
+ ,32
+ ,59194
+ ,1314
+ ,288
+ ,7
+ ,24
+ ,37636
+ ,20
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+ ,68
+ ,139942
+ ,1335
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+ ,22
+ ,65461
+ ,82
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+ ,87
+ ,118612
+ ,1403
+ ,454
+ ,54
+ ,12
+ ,30080
+ ,90
+ ,41907
+ ,43
+ ,72880
+ ,910
+ ,376
+ ,14
+ ,19
+ ,24094
+ ,25
+ ,27080
+ ,67)
+ ,dim=c(9
+ ,197)
+ ,dimnames=list(c('time_in_rfc'
+ ,'pageviews'
+ ,'compendium_views_info'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'totale_size'
+ ,'totale_hyperlinks'
+ ,'totale_seconds'
+ ,'feedback_messages_p120')
+ ,1:197))
> y <- array(NA,dim=c(9,197),dimnames=list(c('time_in_rfc','pageviews','compendium_views_info','blogged_computations','compendiums_reviewed','totale_size','totale_hyperlinks','totale_seconds','feedback_messages_p120'),1:197))
> 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
time_in_rfc pageviews compendium_views_info blogged_computations
1 210907 1418 396 79
2 120982 869 297 58
3 176508 1530 559 60
4 179321 2172 967 108
5 123185 901 270 49
6 52746 463 143 0
7 385534 3201 1562 121
8 33170 371 109 1
9 101645 1192 371 20
10 149061 1583 656 43
11 165446 1439 511 69
12 237213 1764 655 78
13 173326 1495 465 86
14 133131 1373 525 44
15 258873 2187 885 104
16 180083 1491 497 63
17 324799 4041 1436 158
18 230964 1706 612 102
19 236785 2152 865 77
20 135473 1036 385 82
21 202925 1882 567 115
22 215147 1929 639 101
23 344297 2242 963 80
24 153935 1220 398 50
25 132943 1289 410 83
26 174724 2515 966 123
27 174415 2147 801 73
28 225548 2352 892 81
29 223632 1638 513 105
30 124817 1222 469 47
31 221698 1812 683 105
32 210767 1677 643 94
33 170266 1579 535 44
34 260561 1731 625 114
35 84853 807 264 38
36 294424 2452 992 107
37 101011 829 238 30
38 215641 1940 818 71
39 325107 2662 937 84
40 7176 186 70 0
41 167542 1499 507 59
42 106408 865 260 33
43 96560 1793 503 42
44 265769 2527 927 96
45 269651 2747 1269 106
46 149112 1324 537 56
47 175824 2702 910 57
48 152871 1383 532 59
49 111665 1179 345 39
50 116408 2099 918 34
51 362301 4308 1635 76
52 78800 918 330 20
53 183167 1831 557 91
54 277965 3373 1178 115
55 150629 1713 740 85
56 168809 1438 452 76
57 24188 496 218 8
58 329267 2253 764 79
59 65029 744 255 21
60 101097 1161 454 30
61 218946 2352 866 76
62 244052 2144 574 101
63 341570 4691 1276 94
64 103597 1112 379 27
65 233328 2694 825 92
66 256462 1973 798 123
67 206161 1769 663 75
68 311473 3148 1069 128
69 235800 2474 921 105
70 177939 2084 858 55
71 207176 1954 711 56
72 196553 1226 503 41
73 174184 1389 382 72
74 143246 1496 464 67
75 187559 2269 717 75
76 187681 1833 690 114
77 119016 1268 462 118
78 182192 1943 657 77
79 73566 893 385 22
80 194979 1762 577 66
81 167488 1403 619 69
82 143756 1425 479 105
83 275541 1857 817 116
84 243199 1840 752 88
85 182999 1502 430 73
86 135649 1441 451 99
87 152299 1420 537 62
88 120221 1416 519 53
89 346485 2970 1000 118
90 145790 1317 637 30
91 193339 1644 465 100
92 80953 870 437 49
93 122774 1654 711 24
94 130585 1054 299 67
95 112611 937 248 46
96 286468 3004 1162 57
97 241066 2008 714 75
98 148446 2547 905 135
99 204713 1885 649 68
100 182079 1626 512 124
101 140344 1468 472 33
102 220516 2445 905 98
103 243060 1964 786 58
104 162765 1381 489 68
105 182613 1369 479 81
106 232138 1659 617 131
107 265318 2888 925 110
108 85574 1290 351 37
109 310839 2845 1144 130
110 225060 1982 669 93
111 232317 1904 707 118
112 144966 1391 458 39
113 43287 602 214 13
114 155754 1743 599 74
115 164709 1559 572 81
116 201940 2014 897 109
117 235454 2143 819 151
118 220801 2146 720 51
119 99466 874 273 28
120 92661 1590 508 40
121 133328 1590 506 56
122 61361 1210 451 27
123 125930 2072 699 37
124 100750 1281 407 83
125 224549 1401 465 54
126 82316 834 245 27
127 102010 1105 370 28
128 101523 1272 316 59
129 243511 1944 603 133
130 22938 391 154 12
131 41566 761 229 0
132 152474 1605 577 106
133 61857 530 192 23
134 99923 1988 617 44
135 132487 1386 411 71
136 317394 2395 975 116
137 21054 387 146 4
138 209641 1742 705 62
139 22648 620 184 12
140 31414 449 200 18
141 46698 800 274 14
142 131698 1684 502 60
143 91735 1050 382 7
144 244749 2699 964 98
145 184510 1606 537 64
146 79863 1502 438 29
147 128423 1204 369 32
148 97839 1138 417 25
149 38214 568 276 16
150 151101 1459 514 48
151 272458 2158 822 100
152 172494 1111 389 46
153 108043 1421 466 45
154 328107 2833 1255 129
155 250579 1955 694 130
156 351067 2922 1024 136
157 158015 1002 400 59
158 98866 1060 397 25
159 85439 956 350 32
160 229242 2186 719 63
161 351619 3604 1277 95
162 84207 1035 356 14
163 120445 1417 457 36
164 324598 3261 1402 113
165 131069 1587 600 47
166 204271 1424 480 92
167 165543 1701 595 70
168 141722 1249 436 19
169 116048 946 230 50
170 250047 1926 651 41
171 299775 3352 1367 91
172 195838 1641 564 111
173 173260 2035 716 41
174 254488 2312 747 120
175 104389 1369 467 135
176 136084 1577 671 27
177 199476 2201 861 87
178 92499 961 319 25
179 224330 1900 612 131
180 135781 1254 433 45
181 74408 1335 434 29
182 81240 1597 503 58
183 14688 207 85 4
184 181633 1645 564 47
185 271856 2429 824 109
186 7199 151 74 7
187 46660 474 259 12
188 17547 141 69 0
189 133368 1639 535 37
190 95227 872 239 37
191 152601 1318 438 46
192 98146 1018 459 15
193 79619 1383 426 42
194 59194 1314 288 7
195 139942 1335 498 54
196 118612 1403 454 54
197 72880 910 376 14
compendiums_reviewed totale_size totale_hyperlinks totale_seconds
1 30 112285 144 146283
2 28 84786 103 98364
3 38 83123 98 86146
4 30 101193 135 96933
5 22 38361 61 79234
6 26 68504 39 42551
7 25 119182 150 195663
8 18 22807 5 6853
9 11 17140 28 21529
10 26 116174 84 95757
11 25 57635 80 85584
12 38 66198 130 143983
13 44 71701 82 75851
14 30 57793 60 59238
15 40 80444 131 93163
16 34 53855 84 96037
17 47 97668 140 151511
18 30 133824 151 136368
19 31 101481 91 112642
20 23 99645 138 94728
21 36 114789 150 105499
22 36 99052 124 121527
23 30 67654 119 127766
24 25 65553 73 98958
25 39 97500 110 77900
26 34 69112 123 85646
27 31 82753 90 98579
28 31 85323 116 130767
29 33 72654 113 131741
30 25 30727 56 53907
31 33 77873 115 178812
32 35 117478 119 146761
33 42 74007 129 82036
34 43 90183 127 163253
35 30 61542 27 27032
36 33 101494 175 171975
37 13 27570 35 65990
38 32 55813 64 86572
39 36 79215 96 159676
40 0 1423 0 1929
41 28 55461 84 85371
42 14 31081 41 58391
43 17 22996 47 31580
44 32 83122 126 136815
45 30 70106 105 120642
46 35 60578 80 69107
47 20 39992 70 50495
48 28 79892 73 108016
49 28 49810 57 46341
50 39 71570 40 78348
51 34 100708 68 79336
52 26 33032 21 56968
53 39 82875 127 93176
54 39 139077 154 161632
55 33 71595 116 87850
56 28 72260 102 127969
57 4 5950 7 15049
58 39 115762 148 155135
59 18 32551 21 25109
60 14 31701 35 45824
61 29 80670 112 102996
62 44 143558 137 160604
63 21 117105 135 158051
64 16 23789 26 44547
65 28 120733 230 162647
66 35 105195 181 174141
67 28 73107 71 60622
68 38 132068 147 179566
69 23 149193 190 184301
70 36 46821 64 75661
71 32 87011 105 96144
72 29 95260 107 129847
73 25 55183 94 117286
74 27 106671 116 71180
75 36 73511 106 109377
76 28 92945 143 85298
77 23 78664 81 73631
78 40 70054 89 86767
79 23 22618 26 23824
80 40 74011 84 93487
81 28 83737 113 82981
82 34 69094 120 73815
83 33 93133 110 94552
84 28 95536 134 132190
85 34 225920 54 128754
86 30 62133 96 66363
87 33 61370 78 67808
88 22 43836 51 61724
89 38 106117 121 131722
90 26 38692 38 68580
91 35 84651 145 106175
92 8 56622 59 55792
93 24 15986 27 25157
94 29 95364 91 76669
95 20 26706 48 57283
96 29 89691 68 105805
97 45 67267 58 129484
98 37 126846 150 72413
99 33 41140 74 87831
100 33 102860 181 96971
101 25 51715 65 71299
102 32 55801 97 77494
103 29 111813 121 120336
104 28 120293 99 93913
105 28 138599 152 136048
106 31 161647 188 181248
107 52 115929 138 146123
108 21 24266 40 32036
109 24 162901 254 186646
110 41 109825 87 102255
111 33 129838 178 168237
112 32 37510 51 64219
113 19 43750 49 19630
114 20 40652 73 76825
115 31 87771 176 115338
116 31 85872 94 109427
117 32 89275 120 118168
118 18 44418 66 84845
119 23 192565 56 153197
120 17 35232 39 29877
121 20 40909 66 63506
122 12 13294 27 22445
123 17 32387 65 47695
124 30 140867 58 68370
125 31 120662 98 146304
126 10 21233 25 38233
127 13 44332 26 42071
128 22 61056 77 50517
129 42 101338 130 103950
130 1 1168 11 5841
131 9 13497 2 2341
132 32 65567 101 84396
133 11 25162 31 24610
134 25 32334 36 35753
135 36 40735 120 55515
136 31 91413 195 209056
137 0 855 4 6622
138 24 97068 89 115814
139 13 44339 24 11609
140 8 14116 39 13155
141 13 10288 14 18274
142 19 65622 78 72875
143 18 16563 15 10112
144 33 76643 106 142775
145 40 110681 83 68847
146 22 29011 24 17659
147 38 92696 37 20112
148 24 94785 77 61023
149 8 8773 16 13983
150 35 83209 56 65176
151 43 93815 132 132432
152 43 86687 144 112494
153 14 34553 40 45109
154 41 105547 153 170875
155 38 103487 143 180759
156 45 213688 220 214921
157 31 71220 79 100226
158 13 23517 50 32043
159 28 56926 39 54454
160 31 91721 95 78876
161 40 115168 169 170745
162 30 111194 12 6940
163 16 51009 63 49025
164 37 135777 134 122037
165 30 51513 69 53782
166 35 74163 119 127748
167 32 51633 119 86839
168 27 75345 75 44830
169 20 33416 63 77395
170 18 83305 55 89324
171 31 98952 103 103300
172 31 102372 197 112283
173 21 37238 16 10901
174 39 103772 140 120691
175 41 123969 89 58106
176 13 27142 40 57140
177 32 135400 125 122422
178 18 21399 21 25899
179 39 130115 167 139296
180 14 24874 32 52678
181 7 34988 36 23853
182 17 45549 13 17306
183 0 6023 5 7953
184 30 64466 96 89455
185 37 54990 151 147866
186 0 1644 6 4245
187 5 6179 13 21509
188 1 3926 3 7670
189 16 32755 57 66675
190 32 34777 23 14336
191 24 73224 61 53608
192 17 27114 21 30059
193 11 20760 43 29668
194 24 37636 20 22097
195 22 65461 82 96841
196 12 30080 90 41907
197 19 24094 25 27080
feedback_messages_p120
1 94
2 103
3 93
4 103
5 51
6 70
7 91
8 22
9 38
10 93
11 60
12 123
13 148
14 90
15 124
16 70
17 168
18 115
19 71
20 66
21 134
22 117
23 108
24 84
25 156
26 120
27 114
28 94
29 120
30 81
31 110
32 133
33 122
34 158
35 109
36 124
37 39
38 92
39 126
40 0
41 70
42 37
43 38
44 120
45 93
46 95
47 77
48 90
49 80
50 31
51 110
52 66
53 138
54 133
55 113
56 100
57 7
58 140
59 61
60 41
61 96
62 164
63 78
64 49
65 102
66 124
67 99
68 129
69 62
70 73
71 114
72 99
73 70
74 104
75 116
76 91
77 74
78 138
79 67
80 151
81 72
82 120
83 115
84 105
85 104
86 108
87 98
88 69
89 111
90 99
91 71
92 27
93 69
94 107
95 73
96 107
97 93
98 129
99 69
100 118
101 73
102 119
103 104
104 107
105 99
106 90
107 197
108 36
109 85
110 139
111 106
112 50
113 64
114 31
115 63
116 92
117 106
118 63
119 69
120 41
121 56
122 25
123 65
124 93
125 114
126 38
127 44
128 87
129 110
130 0
131 27
132 83
133 30
134 80
135 98
136 82
137 0
138 60
139 28
140 9
141 33
142 59
143 49
144 115
145 140
146 49
147 120
148 66
149 21
150 124
151 152
152 139
153 38
154 144
155 120
156 160
157 114
158 39
159 78
160 119
161 141
162 101
163 56
164 133
165 83
166 116
167 90
168 36
169 50
170 61
171 97
172 98
173 78
174 117
175 148
176 41
177 105
178 55
179 132
180 44
181 21
182 50
183 0
184 73
185 86
186 0
187 13
188 4
189 57
190 48
191 46
192 48
193 32
194 68
195 87
196 43
197 67
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) pageviews compendium_views_info
-7385.3967 25.2125 82.3213
blogged_computations compendiums_reviewed totale_size
-54.5041 472.3263 -0.1558
totale_hyperlinks totale_seconds feedback_messages_p120
-8.6824 0.8149 214.3081
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-80257 -13858 919 11778 90382
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -7385.3967 5205.7833 -1.419 0.15764
pageviews 25.2125 8.1867 3.080 0.00238 **
compendium_views_info 82.3213 20.4488 4.026 8.23e-05 ***
blogged_computations -54.5041 103.8192 -0.525 0.60021
compendiums_reviewed 472.3263 388.0813 1.217 0.22510
totale_size -0.1558 0.0738 -2.112 0.03604 *
totale_hyperlinks -8.6824 81.6090 -0.106 0.91539
totale_seconds 0.8149 0.0795 10.250 < 2e-16 ***
feedback_messages_p120 214.3081 109.8976 1.950 0.05265 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 24400 on 188 degrees of freedom
Multiple R-squared: 0.9159, Adjusted R-squared: 0.9123
F-statistic: 255.8 on 8 and 188 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,] 0.13723973 0.274479451 0.862760274
[2,] 0.17669745 0.353394894 0.823302553
[3,] 0.09330694 0.186613875 0.906693063
[4,] 0.33555213 0.671104262 0.664447869
[5,] 0.30187887 0.603757743 0.698121129
[6,] 0.57257915 0.854841706 0.427420853
[7,] 0.60359147 0.792817069 0.396408534
[8,] 0.55034304 0.899313920 0.449656960
[9,] 0.49588741 0.991774820 0.504112590
[10,] 0.43799708 0.875994164 0.562002918
[11,] 0.35457188 0.709143767 0.645428117
[12,] 0.88685534 0.226289327 0.113144663
[13,] 0.84816589 0.303668219 0.151834109
[14,] 0.80669667 0.386606664 0.193303332
[15,] 0.91128149 0.177437011 0.088718506
[16,] 0.92603581 0.147928372 0.073964186
[17,] 0.93566354 0.128672923 0.064336462
[18,] 0.91747451 0.165050982 0.082525491
[19,] 0.89291668 0.214166646 0.107083323
[20,] 0.94243774 0.115124524 0.057562262
[21,] 0.92451536 0.150969290 0.075484645
[22,] 0.92515952 0.149680953 0.074840476
[23,] 0.90791772 0.184164568 0.092082284
[24,] 0.90024781 0.199504371 0.099752185
[25,] 0.87777873 0.244442530 0.122221265
[26,] 0.84701949 0.305961029 0.152980514
[27,] 0.82469058 0.350618835 0.175309418
[28,] 0.85757811 0.284843789 0.142421894
[29,] 0.82624281 0.347514388 0.173757194
[30,] 0.79098750 0.418024998 0.209012499
[31,] 0.75710186 0.485796270 0.242898135
[32,] 0.73281889 0.534362221 0.267181111
[33,] 0.68740361 0.625192773 0.312596386
[34,] 0.65238127 0.695237466 0.347618733
[35,] 0.60475216 0.790495686 0.395247843
[36,] 0.56244007 0.875119851 0.437559926
[37,] 0.55638016 0.887239674 0.443619837
[38,] 0.50735444 0.985291110 0.492645555
[39,] 0.79986307 0.400273856 0.200136928
[40,] 0.92556524 0.148869513 0.074434756
[41,] 0.93038693 0.139226137 0.069613069
[42,] 0.91391178 0.172176436 0.086088218
[43,] 0.94429413 0.111411747 0.055705873
[44,] 0.96329345 0.073413091 0.036706545
[45,] 0.96077703 0.078445932 0.039222966
[46,] 0.95512548 0.089749032 0.044874516
[47,] 0.98672291 0.026554182 0.013277091
[48,] 0.98228388 0.035432246 0.017716123
[49,] 0.97683092 0.046338162 0.023169081
[50,] 0.97059708 0.058805833 0.029402917
[51,] 0.96247178 0.075056436 0.037528218
[52,] 0.95484114 0.090317725 0.045158862
[53,] 0.94317199 0.113656019 0.056828009
[54,] 0.96705536 0.065889283 0.032944641
[55,] 0.95970626 0.080587476 0.040293738
[56,] 0.98081284 0.038374329 0.019187164
[57,] 0.97588943 0.048221145 0.024110573
[58,] 0.98081866 0.038362686 0.019181343
[59,] 0.97989138 0.040217249 0.020108624
[60,] 0.97408798 0.051824033 0.025912017
[61,] 0.96738450 0.065230995 0.032615497
[62,] 0.95995538 0.080089242 0.040044621
[63,] 0.95035080 0.099298396 0.049649198
[64,] 0.96175526 0.076489484 0.038244742
[65,] 0.95849762 0.083004754 0.041502377
[66,] 0.94907916 0.101841673 0.050920836
[67,] 0.94270569 0.114588624 0.057294312
[68,] 0.93413638 0.131727242 0.065863621
[69,] 0.91966722 0.160665570 0.080332785
[70,] 0.90838697 0.183226058 0.091613029
[71,] 0.89049354 0.219012930 0.109506465
[72,] 0.98295092 0.034098162 0.017049081
[73,] 0.98130238 0.037395237 0.018697619
[74,] 0.97742172 0.045156563 0.022578281
[75,] 0.97120652 0.057586960 0.028793480
[76,] 0.96363920 0.072721600 0.036360800
[77,] 0.95864844 0.082703116 0.041351558
[78,] 0.99470078 0.010598442 0.005299221
[79,] 0.99361937 0.012761259 0.006380629
[80,] 0.99364617 0.012707652 0.006353826
[81,] 0.99210282 0.015794352 0.007897176
[82,] 0.99052850 0.018942992 0.009471496
[83,] 0.98792321 0.024153590 0.012076795
[84,] 0.98537439 0.029251212 0.014625606
[85,] 0.98281994 0.034360117 0.017180058
[86,] 0.97853067 0.042938658 0.021469329
[87,] 0.99469952 0.010600950 0.005300475
[88,] 0.99407807 0.011843852 0.005921926
[89,] 0.99257024 0.014859526 0.007429763
[90,] 0.99012195 0.019756100 0.009878050
[91,] 0.98696764 0.026064727 0.013032364
[92,] 0.98673381 0.026532388 0.013266194
[93,] 0.98301883 0.033962335 0.016981168
[94,] 0.97797974 0.044040520 0.022020260
[95,] 0.97170023 0.056599541 0.028299770
[96,] 0.97979306 0.040413875 0.020206937
[97,] 0.97490973 0.050180545 0.025090273
[98,] 0.96822752 0.063544963 0.031772482
[99,] 0.96429522 0.071409553 0.035704776
[100,] 0.95774771 0.084504586 0.042252293
[101,] 0.94880522 0.102389556 0.051194778
[102,] 0.94011045 0.119779100 0.059889550
[103,] 0.92619876 0.147602472 0.073801236
[104,] 0.92625253 0.147494932 0.073747466
[105,] 0.92125506 0.157489882 0.078744941
[106,] 0.90744785 0.185104302 0.092552151
[107,] 0.92545665 0.149086706 0.074543353
[108,] 0.97915677 0.041686467 0.020843233
[109,] 0.97625644 0.047487130 0.023743565
[110,] 0.96957356 0.060852878 0.030426439
[111,] 0.97084436 0.058311276 0.029155638
[112,] 0.97438854 0.051222929 0.025611465
[113,] 0.97861004 0.042779912 0.021389956
[114,] 0.97655214 0.046895719 0.023447859
[115,] 0.97165118 0.056697640 0.028348820
[116,] 0.96468280 0.070634391 0.035317195
[117,] 0.95495068 0.090098635 0.045049318
[118,] 0.97778960 0.044420800 0.022210400
[119,] 0.97112769 0.057744630 0.028872315
[120,] 0.96258322 0.074833552 0.037416776
[121,] 0.95506840 0.089863205 0.044931603
[122,] 0.94735180 0.105296410 0.052648205
[123,] 0.97357670 0.052846604 0.026423302
[124,] 0.96543658 0.069126834 0.034563417
[125,] 0.95528455 0.089430894 0.044715447
[126,] 0.94302598 0.113948043 0.056974022
[127,] 0.93102857 0.137942869 0.068971435
[128,] 0.92736290 0.145274210 0.072637105
[129,] 0.90955777 0.180884452 0.090442226
[130,] 0.89737710 0.205245808 0.102622904
[131,] 0.88609868 0.227802637 0.113901319
[132,] 0.87024235 0.259515310 0.129757655
[133,] 0.89922108 0.201557831 0.100778916
[134,] 0.89590923 0.208181543 0.104090771
[135,] 0.90378349 0.192433017 0.096216509
[136,] 0.91310992 0.173780151 0.086890075
[137,] 0.91980650 0.160386992 0.080193496
[138,] 0.90113614 0.197727719 0.098863859
[139,] 0.87579913 0.248401746 0.124200873
[140,] 0.88252068 0.234958647 0.117479324
[141,] 0.85434930 0.291301410 0.145650705
[142,] 0.82895384 0.342092329 0.171046165
[143,] 0.79407200 0.411856001 0.205928001
[144,] 0.76733176 0.465336487 0.232668243
[145,] 0.72961176 0.540776485 0.270388242
[146,] 0.70221613 0.595567741 0.297783871
[147,] 0.66099459 0.678010820 0.339005410
[148,] 0.66467217 0.670655661 0.335327831
[149,] 0.75167396 0.496652076 0.248326038
[150,] 0.70624239 0.587515217 0.293757608
[151,] 0.66611377 0.667772463 0.333886232
[152,] 0.60906557 0.781868859 0.390934430
[153,] 0.57204637 0.855907263 0.427953632
[154,] 0.53324686 0.933506283 0.466753141
[155,] 0.50292216 0.994155678 0.497077839
[156,] 0.44703026 0.894060522 0.552969739
[157,] 0.40765701 0.815314024 0.592342988
[158,] 0.34478897 0.689577950 0.655211025
[159,] 0.89600984 0.207980312 0.103990156
[160,] 0.85808071 0.283838584 0.141919292
[161,] 0.81038216 0.379235677 0.189617839
[162,] 0.98217583 0.035648348 0.017824174
[163,] 0.98915529 0.021689423 0.010844712
[164,] 0.98580970 0.028380596 0.014190298
[165,] 0.97463810 0.050723803 0.025361901
[166,] 0.97935493 0.041290144 0.020645072
[167,] 0.98286773 0.034264534 0.017132267
[168,] 0.96677854 0.066442926 0.033221463
[169,] 0.99895854 0.002082915 0.001041457
[170,] 0.99866613 0.002667748 0.001333874
[171,] 0.99565983 0.008680337 0.004340169
[172,] 0.98592091 0.028158177 0.014079088
[173,] 0.97754942 0.044901155 0.022450577
[174,] 0.96042445 0.079151104 0.039575552
> postscript(file="/var/wessaorg/rcomp/tmp/1uyc61324117679.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2jpw21324117679.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/36ega1324117679.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4tue71324117679.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5az301324117679.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 = 197
Frequency = 1
1 2 3 4 5 6
19471.92074 -16181.24030 8294.16223 -40067.89108 8914.79039 -14257.30344
7 8 9 10 11 12
19337.70038 7079.49743 21556.31608 -26535.83438 13510.31399 255.30772
13 14 15 16 17 18
6999.70725 -7125.46950 36218.37856 12194.85844 -44538.48501 22737.07740
19 20 21 22 23 24
17854.13741 4036.85154 9948.73702 2198.73758 90382.14768 918.53021
25 26 27 28 29 30
-20584.13443 -53851.28493 -40021.53292 -22430.89487 16851.83304 -2476.99215
31 32 33 34 35 36
-38849.60103 -17230.85313 -3986.04062 7012.94072 2497.25739 -814.28605
37 38 39 40 41 42
5862.88221 14518.02640 31867.34886 2759.14213 10187.24049 15452.90890
43 44 45 46 47 48
-18295.96292 84.98338 -11488.61530 -1110.90838 -16978.30376 -22645.39826
49 50 51 52 53 54
3172.80001 -80256.71163 42616.94390 -30555.19233 -6413.56455 -46028.72960
55 56 57 58 59 60
-40689.80096 -19922.87309 -13107.32843 65738.93727 -2972.51169 -4026.30360
61 62 63 64 65 66
-4777.45028 -7613.18302 -5248.10809 2790.03137 -36927.62731 -11937.98449
67 68 69 70 71 72
46619.83792 -11604.87720 -38727.57952 -21306.61904 6393.70612 8899.62277
73 74 75 76 77 78
6053.26963 2952.11498 -35820.77854 11751.28803 -10932.65597 -16785.05237
79 80 81 82 83 84
-12944.37160 -1137.48933 10056.33252 -8615.60971 73356.76474 19683.34314
85 86 87 88 89 90
13501.10841 -5907.40371 1449.10458 -16135.30243 71607.05316 -13858.04845
91 92 93 94 95 96
22625.00174 -12595.10175 -12663.00435 6978.09657 11269.84816 17280.64065
97 98 99 100 101 102
7416.10379 -58590.01107 19956.32500 10781.03875 -3272.03328 2866.63082
103 104 105 106 107 108
23809.99833 5701.30428 -1925.92921 -766.25339 -36856.56620 -6054.88444
109 110 111 112 113 114
5342.13621 17856.46198 -13696.51520 9827.99218 -12856.97557 2188.94878
115 116 117 118 119 120
-16813.93875 -18688.74126 10443.21398 33938.01131 -56130.62347 -15015.02420
121 122 123 124 125 126
-4229.07732 -24426.55965 -29666.84583 -20502.61990 22630.31118 9478.96742
127 128 129 130 131 132
9882.80305 -5979.59823 48290.86655 3487.05703 1088.91646 -12912.23253
133 134 135 136 137 138
13837.96842 -43945.48363 -892.94566 3812.47901 1652.75199 15774.71171
139 140 141 142 143 144
-14574.31278 -1893.45927 -14259.16384 -11531.77242 17050.01392 -33649.62248
145 146 147 148 149 150
23654.10226 -15650.40562 31532.57526 -16201.94830 -8738.03426 -761.05134
151 152 153 154 155 156
18176.14297 -4661.01125 -2092.36443 -3916.38384 -14973.29754 12420.07776
157 158 159 160 161 162
1459.51069 11695.24394 -23454.12848 36453.60476 -647.93033 12917.16960
163 164 165 166 167 168
5431.70786 17403.01680 -15547.70199 8348.23765 -11213.91489 38152.72314
169 170 171 172 173 174
5894.89650 76609.41381 11777.97880 11988.03424 43054.44221 24167.03988
175 176 177 178 179 180
-32169.84099 -6971.49891 -29963.35612 12879.84957 2073.04557 23540.74835
181 182 183 184 185 186
-7492.09527 -15521.95024 4576.04263 11842.69268 9582.22348 1915.97968
187 188 189 190 191 192
-172.66012 8755.08212 -11103.84048 31504.47094 40267.34595 4492.75194
193 194 195 196 197
-13266.33236 -27754.05214 -21424.95812 12628.38584 -14296.88818
> postscript(file="/var/wessaorg/rcomp/tmp/66g5e1324117679.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 = 197
Frequency = 1
lag(myerror, k = 1) myerror
0 19471.92074 NA
1 -16181.24030 19471.92074
2 8294.16223 -16181.24030
3 -40067.89108 8294.16223
4 8914.79039 -40067.89108
5 -14257.30344 8914.79039
6 19337.70038 -14257.30344
7 7079.49743 19337.70038
8 21556.31608 7079.49743
9 -26535.83438 21556.31608
10 13510.31399 -26535.83438
11 255.30772 13510.31399
12 6999.70725 255.30772
13 -7125.46950 6999.70725
14 36218.37856 -7125.46950
15 12194.85844 36218.37856
16 -44538.48501 12194.85844
17 22737.07740 -44538.48501
18 17854.13741 22737.07740
19 4036.85154 17854.13741
20 9948.73702 4036.85154
21 2198.73758 9948.73702
22 90382.14768 2198.73758
23 918.53021 90382.14768
24 -20584.13443 918.53021
25 -53851.28493 -20584.13443
26 -40021.53292 -53851.28493
27 -22430.89487 -40021.53292
28 16851.83304 -22430.89487
29 -2476.99215 16851.83304
30 -38849.60103 -2476.99215
31 -17230.85313 -38849.60103
32 -3986.04062 -17230.85313
33 7012.94072 -3986.04062
34 2497.25739 7012.94072
35 -814.28605 2497.25739
36 5862.88221 -814.28605
37 14518.02640 5862.88221
38 31867.34886 14518.02640
39 2759.14213 31867.34886
40 10187.24049 2759.14213
41 15452.90890 10187.24049
42 -18295.96292 15452.90890
43 84.98338 -18295.96292
44 -11488.61530 84.98338
45 -1110.90838 -11488.61530
46 -16978.30376 -1110.90838
47 -22645.39826 -16978.30376
48 3172.80001 -22645.39826
49 -80256.71163 3172.80001
50 42616.94390 -80256.71163
51 -30555.19233 42616.94390
52 -6413.56455 -30555.19233
53 -46028.72960 -6413.56455
54 -40689.80096 -46028.72960
55 -19922.87309 -40689.80096
56 -13107.32843 -19922.87309
57 65738.93727 -13107.32843
58 -2972.51169 65738.93727
59 -4026.30360 -2972.51169
60 -4777.45028 -4026.30360
61 -7613.18302 -4777.45028
62 -5248.10809 -7613.18302
63 2790.03137 -5248.10809
64 -36927.62731 2790.03137
65 -11937.98449 -36927.62731
66 46619.83792 -11937.98449
67 -11604.87720 46619.83792
68 -38727.57952 -11604.87720
69 -21306.61904 -38727.57952
70 6393.70612 -21306.61904
71 8899.62277 6393.70612
72 6053.26963 8899.62277
73 2952.11498 6053.26963
74 -35820.77854 2952.11498
75 11751.28803 -35820.77854
76 -10932.65597 11751.28803
77 -16785.05237 -10932.65597
78 -12944.37160 -16785.05237
79 -1137.48933 -12944.37160
80 10056.33252 -1137.48933
81 -8615.60971 10056.33252
82 73356.76474 -8615.60971
83 19683.34314 73356.76474
84 13501.10841 19683.34314
85 -5907.40371 13501.10841
86 1449.10458 -5907.40371
87 -16135.30243 1449.10458
88 71607.05316 -16135.30243
89 -13858.04845 71607.05316
90 22625.00174 -13858.04845
91 -12595.10175 22625.00174
92 -12663.00435 -12595.10175
93 6978.09657 -12663.00435
94 11269.84816 6978.09657
95 17280.64065 11269.84816
96 7416.10379 17280.64065
97 -58590.01107 7416.10379
98 19956.32500 -58590.01107
99 10781.03875 19956.32500
100 -3272.03328 10781.03875
101 2866.63082 -3272.03328
102 23809.99833 2866.63082
103 5701.30428 23809.99833
104 -1925.92921 5701.30428
105 -766.25339 -1925.92921
106 -36856.56620 -766.25339
107 -6054.88444 -36856.56620
108 5342.13621 -6054.88444
109 17856.46198 5342.13621
110 -13696.51520 17856.46198
111 9827.99218 -13696.51520
112 -12856.97557 9827.99218
113 2188.94878 -12856.97557
114 -16813.93875 2188.94878
115 -18688.74126 -16813.93875
116 10443.21398 -18688.74126
117 33938.01131 10443.21398
118 -56130.62347 33938.01131
119 -15015.02420 -56130.62347
120 -4229.07732 -15015.02420
121 -24426.55965 -4229.07732
122 -29666.84583 -24426.55965
123 -20502.61990 -29666.84583
124 22630.31118 -20502.61990
125 9478.96742 22630.31118
126 9882.80305 9478.96742
127 -5979.59823 9882.80305
128 48290.86655 -5979.59823
129 3487.05703 48290.86655
130 1088.91646 3487.05703
131 -12912.23253 1088.91646
132 13837.96842 -12912.23253
133 -43945.48363 13837.96842
134 -892.94566 -43945.48363
135 3812.47901 -892.94566
136 1652.75199 3812.47901
137 15774.71171 1652.75199
138 -14574.31278 15774.71171
139 -1893.45927 -14574.31278
140 -14259.16384 -1893.45927
141 -11531.77242 -14259.16384
142 17050.01392 -11531.77242
143 -33649.62248 17050.01392
144 23654.10226 -33649.62248
145 -15650.40562 23654.10226
146 31532.57526 -15650.40562
147 -16201.94830 31532.57526
148 -8738.03426 -16201.94830
149 -761.05134 -8738.03426
150 18176.14297 -761.05134
151 -4661.01125 18176.14297
152 -2092.36443 -4661.01125
153 -3916.38384 -2092.36443
154 -14973.29754 -3916.38384
155 12420.07776 -14973.29754
156 1459.51069 12420.07776
157 11695.24394 1459.51069
158 -23454.12848 11695.24394
159 36453.60476 -23454.12848
160 -647.93033 36453.60476
161 12917.16960 -647.93033
162 5431.70786 12917.16960
163 17403.01680 5431.70786
164 -15547.70199 17403.01680
165 8348.23765 -15547.70199
166 -11213.91489 8348.23765
167 38152.72314 -11213.91489
168 5894.89650 38152.72314
169 76609.41381 5894.89650
170 11777.97880 76609.41381
171 11988.03424 11777.97880
172 43054.44221 11988.03424
173 24167.03988 43054.44221
174 -32169.84099 24167.03988
175 -6971.49891 -32169.84099
176 -29963.35612 -6971.49891
177 12879.84957 -29963.35612
178 2073.04557 12879.84957
179 23540.74835 2073.04557
180 -7492.09527 23540.74835
181 -15521.95024 -7492.09527
182 4576.04263 -15521.95024
183 11842.69268 4576.04263
184 9582.22348 11842.69268
185 1915.97968 9582.22348
186 -172.66012 1915.97968
187 8755.08212 -172.66012
188 -11103.84048 8755.08212
189 31504.47094 -11103.84048
190 40267.34595 31504.47094
191 4492.75194 40267.34595
192 -13266.33236 4492.75194
193 -27754.05214 -13266.33236
194 -21424.95812 -27754.05214
195 12628.38584 -21424.95812
196 -14296.88818 12628.38584
197 NA -14296.88818
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -16181.24030 19471.92074
[2,] 8294.16223 -16181.24030
[3,] -40067.89108 8294.16223
[4,] 8914.79039 -40067.89108
[5,] -14257.30344 8914.79039
[6,] 19337.70038 -14257.30344
[7,] 7079.49743 19337.70038
[8,] 21556.31608 7079.49743
[9,] -26535.83438 21556.31608
[10,] 13510.31399 -26535.83438
[11,] 255.30772 13510.31399
[12,] 6999.70725 255.30772
[13,] -7125.46950 6999.70725
[14,] 36218.37856 -7125.46950
[15,] 12194.85844 36218.37856
[16,] -44538.48501 12194.85844
[17,] 22737.07740 -44538.48501
[18,] 17854.13741 22737.07740
[19,] 4036.85154 17854.13741
[20,] 9948.73702 4036.85154
[21,] 2198.73758 9948.73702
[22,] 90382.14768 2198.73758
[23,] 918.53021 90382.14768
[24,] -20584.13443 918.53021
[25,] -53851.28493 -20584.13443
[26,] -40021.53292 -53851.28493
[27,] -22430.89487 -40021.53292
[28,] 16851.83304 -22430.89487
[29,] -2476.99215 16851.83304
[30,] -38849.60103 -2476.99215
[31,] -17230.85313 -38849.60103
[32,] -3986.04062 -17230.85313
[33,] 7012.94072 -3986.04062
[34,] 2497.25739 7012.94072
[35,] -814.28605 2497.25739
[36,] 5862.88221 -814.28605
[37,] 14518.02640 5862.88221
[38,] 31867.34886 14518.02640
[39,] 2759.14213 31867.34886
[40,] 10187.24049 2759.14213
[41,] 15452.90890 10187.24049
[42,] -18295.96292 15452.90890
[43,] 84.98338 -18295.96292
[44,] -11488.61530 84.98338
[45,] -1110.90838 -11488.61530
[46,] -16978.30376 -1110.90838
[47,] -22645.39826 -16978.30376
[48,] 3172.80001 -22645.39826
[49,] -80256.71163 3172.80001
[50,] 42616.94390 -80256.71163
[51,] -30555.19233 42616.94390
[52,] -6413.56455 -30555.19233
[53,] -46028.72960 -6413.56455
[54,] -40689.80096 -46028.72960
[55,] -19922.87309 -40689.80096
[56,] -13107.32843 -19922.87309
[57,] 65738.93727 -13107.32843
[58,] -2972.51169 65738.93727
[59,] -4026.30360 -2972.51169
[60,] -4777.45028 -4026.30360
[61,] -7613.18302 -4777.45028
[62,] -5248.10809 -7613.18302
[63,] 2790.03137 -5248.10809
[64,] -36927.62731 2790.03137
[65,] -11937.98449 -36927.62731
[66,] 46619.83792 -11937.98449
[67,] -11604.87720 46619.83792
[68,] -38727.57952 -11604.87720
[69,] -21306.61904 -38727.57952
[70,] 6393.70612 -21306.61904
[71,] 8899.62277 6393.70612
[72,] 6053.26963 8899.62277
[73,] 2952.11498 6053.26963
[74,] -35820.77854 2952.11498
[75,] 11751.28803 -35820.77854
[76,] -10932.65597 11751.28803
[77,] -16785.05237 -10932.65597
[78,] -12944.37160 -16785.05237
[79,] -1137.48933 -12944.37160
[80,] 10056.33252 -1137.48933
[81,] -8615.60971 10056.33252
[82,] 73356.76474 -8615.60971
[83,] 19683.34314 73356.76474
[84,] 13501.10841 19683.34314
[85,] -5907.40371 13501.10841
[86,] 1449.10458 -5907.40371
[87,] -16135.30243 1449.10458
[88,] 71607.05316 -16135.30243
[89,] -13858.04845 71607.05316
[90,] 22625.00174 -13858.04845
[91,] -12595.10175 22625.00174
[92,] -12663.00435 -12595.10175
[93,] 6978.09657 -12663.00435
[94,] 11269.84816 6978.09657
[95,] 17280.64065 11269.84816
[96,] 7416.10379 17280.64065
[97,] -58590.01107 7416.10379
[98,] 19956.32500 -58590.01107
[99,] 10781.03875 19956.32500
[100,] -3272.03328 10781.03875
[101,] 2866.63082 -3272.03328
[102,] 23809.99833 2866.63082
[103,] 5701.30428 23809.99833
[104,] -1925.92921 5701.30428
[105,] -766.25339 -1925.92921
[106,] -36856.56620 -766.25339
[107,] -6054.88444 -36856.56620
[108,] 5342.13621 -6054.88444
[109,] 17856.46198 5342.13621
[110,] -13696.51520 17856.46198
[111,] 9827.99218 -13696.51520
[112,] -12856.97557 9827.99218
[113,] 2188.94878 -12856.97557
[114,] -16813.93875 2188.94878
[115,] -18688.74126 -16813.93875
[116,] 10443.21398 -18688.74126
[117,] 33938.01131 10443.21398
[118,] -56130.62347 33938.01131
[119,] -15015.02420 -56130.62347
[120,] -4229.07732 -15015.02420
[121,] -24426.55965 -4229.07732
[122,] -29666.84583 -24426.55965
[123,] -20502.61990 -29666.84583
[124,] 22630.31118 -20502.61990
[125,] 9478.96742 22630.31118
[126,] 9882.80305 9478.96742
[127,] -5979.59823 9882.80305
[128,] 48290.86655 -5979.59823
[129,] 3487.05703 48290.86655
[130,] 1088.91646 3487.05703
[131,] -12912.23253 1088.91646
[132,] 13837.96842 -12912.23253
[133,] -43945.48363 13837.96842
[134,] -892.94566 -43945.48363
[135,] 3812.47901 -892.94566
[136,] 1652.75199 3812.47901
[137,] 15774.71171 1652.75199
[138,] -14574.31278 15774.71171
[139,] -1893.45927 -14574.31278
[140,] -14259.16384 -1893.45927
[141,] -11531.77242 -14259.16384
[142,] 17050.01392 -11531.77242
[143,] -33649.62248 17050.01392
[144,] 23654.10226 -33649.62248
[145,] -15650.40562 23654.10226
[146,] 31532.57526 -15650.40562
[147,] -16201.94830 31532.57526
[148,] -8738.03426 -16201.94830
[149,] -761.05134 -8738.03426
[150,] 18176.14297 -761.05134
[151,] -4661.01125 18176.14297
[152,] -2092.36443 -4661.01125
[153,] -3916.38384 -2092.36443
[154,] -14973.29754 -3916.38384
[155,] 12420.07776 -14973.29754
[156,] 1459.51069 12420.07776
[157,] 11695.24394 1459.51069
[158,] -23454.12848 11695.24394
[159,] 36453.60476 -23454.12848
[160,] -647.93033 36453.60476
[161,] 12917.16960 -647.93033
[162,] 5431.70786 12917.16960
[163,] 17403.01680 5431.70786
[164,] -15547.70199 17403.01680
[165,] 8348.23765 -15547.70199
[166,] -11213.91489 8348.23765
[167,] 38152.72314 -11213.91489
[168,] 5894.89650 38152.72314
[169,] 76609.41381 5894.89650
[170,] 11777.97880 76609.41381
[171,] 11988.03424 11777.97880
[172,] 43054.44221 11988.03424
[173,] 24167.03988 43054.44221
[174,] -32169.84099 24167.03988
[175,] -6971.49891 -32169.84099
[176,] -29963.35612 -6971.49891
[177,] 12879.84957 -29963.35612
[178,] 2073.04557 12879.84957
[179,] 23540.74835 2073.04557
[180,] -7492.09527 23540.74835
[181,] -15521.95024 -7492.09527
[182,] 4576.04263 -15521.95024
[183,] 11842.69268 4576.04263
[184,] 9582.22348 11842.69268
[185,] 1915.97968 9582.22348
[186,] -172.66012 1915.97968
[187,] 8755.08212 -172.66012
[188,] -11103.84048 8755.08212
[189,] 31504.47094 -11103.84048
[190,] 40267.34595 31504.47094
[191,] 4492.75194 40267.34595
[192,] -13266.33236 4492.75194
[193,] -27754.05214 -13266.33236
[194,] -21424.95812 -27754.05214
[195,] 12628.38584 -21424.95812
[196,] -14296.88818 12628.38584
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -16181.24030 19471.92074
2 8294.16223 -16181.24030
3 -40067.89108 8294.16223
4 8914.79039 -40067.89108
5 -14257.30344 8914.79039
6 19337.70038 -14257.30344
7 7079.49743 19337.70038
8 21556.31608 7079.49743
9 -26535.83438 21556.31608
10 13510.31399 -26535.83438
11 255.30772 13510.31399
12 6999.70725 255.30772
13 -7125.46950 6999.70725
14 36218.37856 -7125.46950
15 12194.85844 36218.37856
16 -44538.48501 12194.85844
17 22737.07740 -44538.48501
18 17854.13741 22737.07740
19 4036.85154 17854.13741
20 9948.73702 4036.85154
21 2198.73758 9948.73702
22 90382.14768 2198.73758
23 918.53021 90382.14768
24 -20584.13443 918.53021
25 -53851.28493 -20584.13443
26 -40021.53292 -53851.28493
27 -22430.89487 -40021.53292
28 16851.83304 -22430.89487
29 -2476.99215 16851.83304
30 -38849.60103 -2476.99215
31 -17230.85313 -38849.60103
32 -3986.04062 -17230.85313
33 7012.94072 -3986.04062
34 2497.25739 7012.94072
35 -814.28605 2497.25739
36 5862.88221 -814.28605
37 14518.02640 5862.88221
38 31867.34886 14518.02640
39 2759.14213 31867.34886
40 10187.24049 2759.14213
41 15452.90890 10187.24049
42 -18295.96292 15452.90890
43 84.98338 -18295.96292
44 -11488.61530 84.98338
45 -1110.90838 -11488.61530
46 -16978.30376 -1110.90838
47 -22645.39826 -16978.30376
48 3172.80001 -22645.39826
49 -80256.71163 3172.80001
50 42616.94390 -80256.71163
51 -30555.19233 42616.94390
52 -6413.56455 -30555.19233
53 -46028.72960 -6413.56455
54 -40689.80096 -46028.72960
55 -19922.87309 -40689.80096
56 -13107.32843 -19922.87309
57 65738.93727 -13107.32843
58 -2972.51169 65738.93727
59 -4026.30360 -2972.51169
60 -4777.45028 -4026.30360
61 -7613.18302 -4777.45028
62 -5248.10809 -7613.18302
63 2790.03137 -5248.10809
64 -36927.62731 2790.03137
65 -11937.98449 -36927.62731
66 46619.83792 -11937.98449
67 -11604.87720 46619.83792
68 -38727.57952 -11604.87720
69 -21306.61904 -38727.57952
70 6393.70612 -21306.61904
71 8899.62277 6393.70612
72 6053.26963 8899.62277
73 2952.11498 6053.26963
74 -35820.77854 2952.11498
75 11751.28803 -35820.77854
76 -10932.65597 11751.28803
77 -16785.05237 -10932.65597
78 -12944.37160 -16785.05237
79 -1137.48933 -12944.37160
80 10056.33252 -1137.48933
81 -8615.60971 10056.33252
82 73356.76474 -8615.60971
83 19683.34314 73356.76474
84 13501.10841 19683.34314
85 -5907.40371 13501.10841
86 1449.10458 -5907.40371
87 -16135.30243 1449.10458
88 71607.05316 -16135.30243
89 -13858.04845 71607.05316
90 22625.00174 -13858.04845
91 -12595.10175 22625.00174
92 -12663.00435 -12595.10175
93 6978.09657 -12663.00435
94 11269.84816 6978.09657
95 17280.64065 11269.84816
96 7416.10379 17280.64065
97 -58590.01107 7416.10379
98 19956.32500 -58590.01107
99 10781.03875 19956.32500
100 -3272.03328 10781.03875
101 2866.63082 -3272.03328
102 23809.99833 2866.63082
103 5701.30428 23809.99833
104 -1925.92921 5701.30428
105 -766.25339 -1925.92921
106 -36856.56620 -766.25339
107 -6054.88444 -36856.56620
108 5342.13621 -6054.88444
109 17856.46198 5342.13621
110 -13696.51520 17856.46198
111 9827.99218 -13696.51520
112 -12856.97557 9827.99218
113 2188.94878 -12856.97557
114 -16813.93875 2188.94878
115 -18688.74126 -16813.93875
116 10443.21398 -18688.74126
117 33938.01131 10443.21398
118 -56130.62347 33938.01131
119 -15015.02420 -56130.62347
120 -4229.07732 -15015.02420
121 -24426.55965 -4229.07732
122 -29666.84583 -24426.55965
123 -20502.61990 -29666.84583
124 22630.31118 -20502.61990
125 9478.96742 22630.31118
126 9882.80305 9478.96742
127 -5979.59823 9882.80305
128 48290.86655 -5979.59823
129 3487.05703 48290.86655
130 1088.91646 3487.05703
131 -12912.23253 1088.91646
132 13837.96842 -12912.23253
133 -43945.48363 13837.96842
134 -892.94566 -43945.48363
135 3812.47901 -892.94566
136 1652.75199 3812.47901
137 15774.71171 1652.75199
138 -14574.31278 15774.71171
139 -1893.45927 -14574.31278
140 -14259.16384 -1893.45927
141 -11531.77242 -14259.16384
142 17050.01392 -11531.77242
143 -33649.62248 17050.01392
144 23654.10226 -33649.62248
145 -15650.40562 23654.10226
146 31532.57526 -15650.40562
147 -16201.94830 31532.57526
148 -8738.03426 -16201.94830
149 -761.05134 -8738.03426
150 18176.14297 -761.05134
151 -4661.01125 18176.14297
152 -2092.36443 -4661.01125
153 -3916.38384 -2092.36443
154 -14973.29754 -3916.38384
155 12420.07776 -14973.29754
156 1459.51069 12420.07776
157 11695.24394 1459.51069
158 -23454.12848 11695.24394
159 36453.60476 -23454.12848
160 -647.93033 36453.60476
161 12917.16960 -647.93033
162 5431.70786 12917.16960
163 17403.01680 5431.70786
164 -15547.70199 17403.01680
165 8348.23765 -15547.70199
166 -11213.91489 8348.23765
167 38152.72314 -11213.91489
168 5894.89650 38152.72314
169 76609.41381 5894.89650
170 11777.97880 76609.41381
171 11988.03424 11777.97880
172 43054.44221 11988.03424
173 24167.03988 43054.44221
174 -32169.84099 24167.03988
175 -6971.49891 -32169.84099
176 -29963.35612 -6971.49891
177 12879.84957 -29963.35612
178 2073.04557 12879.84957
179 23540.74835 2073.04557
180 -7492.09527 23540.74835
181 -15521.95024 -7492.09527
182 4576.04263 -15521.95024
183 11842.69268 4576.04263
184 9582.22348 11842.69268
185 1915.97968 9582.22348
186 -172.66012 1915.97968
187 8755.08212 -172.66012
188 -11103.84048 8755.08212
189 31504.47094 -11103.84048
190 40267.34595 31504.47094
191 4492.75194 40267.34595
192 -13266.33236 4492.75194
193 -27754.05214 -13266.33236
194 -21424.95812 -27754.05214
195 12628.38584 -21424.95812
196 -14296.88818 12628.38584
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7i1ku1324117679.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8ubko1324117679.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9awvt1324117679.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10mrws1324117679.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/115d3y1324117679.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/128i6i1324117679.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13i9jo1324117679.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14qo281324117679.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/15qn2k1324117679.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/16zn991324117679.tab")
+ }
>
> try(system("convert tmp/1uyc61324117679.ps tmp/1uyc61324117679.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jpw21324117679.ps tmp/2jpw21324117679.png",intern=TRUE))
character(0)
> try(system("convert tmp/36ega1324117679.ps tmp/36ega1324117679.png",intern=TRUE))
character(0)
> try(system("convert tmp/4tue71324117679.ps tmp/4tue71324117679.png",intern=TRUE))
character(0)
> try(system("convert tmp/5az301324117679.ps tmp/5az301324117679.png",intern=TRUE))
character(0)
> try(system("convert tmp/66g5e1324117679.ps tmp/66g5e1324117679.png",intern=TRUE))
character(0)
> try(system("convert tmp/7i1ku1324117679.ps tmp/7i1ku1324117679.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ubko1324117679.ps tmp/8ubko1324117679.png",intern=TRUE))
character(0)
> try(system("convert tmp/9awvt1324117679.ps tmp/9awvt1324117679.png",intern=TRUE))
character(0)
> try(system("convert tmp/10mrws1324117679.ps tmp/10mrws1324117679.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.090 0.622 6.726