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(146283
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+ ,dim=c(4
+ ,289)
+ ,dimnames=list(c('Tot._Sec'
+ ,'Tot._Size'
+ ,'#Feedback>p120'
+ ,'#Blogged_comp.')
+ ,1:289))
> y <- array(NA,dim=c(4,289),dimnames=list(c('Tot._Sec','Tot._Size','#Feedback>p120','#Blogged_comp.'),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 = '2'
> #'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
Tot._Size Tot._Sec #Feedback>p120 #Blogged_comp.
1 112285 146283 94 79
2 84786 98364 103 58
3 83123 86146 93 60
4 101193 96933 103 108
5 38361 79234 51 49
6 68504 42551 70 0
7 119182 195663 91 121
8 22807 6853 22 1
9 17140 21529 38 20
10 116174 95757 93 43
11 57635 85584 60 69
12 66198 143983 123 78
13 71701 75851 148 86
14 57793 59238 90 44
15 80444 93163 124 104
16 53855 96037 70 63
17 97668 151511 168 158
18 133824 136368 115 102
19 101481 112642 71 77
20 99645 94728 66 82
21 114789 105499 134 115
22 99052 121527 117 101
23 67654 127766 108 80
24 65553 98958 84 50
25 97500 77900 156 83
26 69112 85646 120 123
27 82753 98579 114 73
28 85323 130767 94 81
29 72654 131741 120 105
30 30727 53907 81 47
31 77873 178812 110 105
32 117478 146761 133 94
33 74007 82036 122 44
34 90183 163253 158 114
35 61542 27032 109 38
36 101494 171975 124 107
37 27570 65990 39 30
38 55813 86572 92 71
39 79215 159676 126 84
40 1423 1929 0 0
41 55461 85371 70 59
42 31081 58391 37 33
43 22996 31580 38 42
44 83122 136815 120 96
45 70106 120642 93 106
46 60578 69107 95 56
47 39992 50495 77 57
48 79892 108016 90 59
49 49810 46341 80 39
50 71570 78348 31 34
51 100708 79336 110 76
52 33032 56968 66 20
53 82875 93176 138 91
54 139077 161632 133 115
55 71595 87850 113 85
56 72260 127969 100 76
57 5950 15049 7 8
58 115762 155135 140 79
59 32551 25109 61 21
60 31701 45824 41 30
61 80670 102996 96 76
62 143558 160604 164 101
63 117105 158051 78 94
64 23789 44547 49 27
65 120733 162647 102 92
66 105195 174141 124 123
67 73107 60622 99 75
68 132068 179566 129 128
69 149193 184301 62 105
70 46821 75661 73 55
71 87011 96144 114 56
72 95260 129847 99 41
73 55183 117286 70 72
74 106671 71180 104 67
75 73511 109377 116 75
76 92945 85298 91 114
77 78664 73631 74 118
78 70054 86767 138 77
79 22618 23824 67 22
80 74011 93487 151 66
81 83737 82981 72 69
82 69094 73815 120 105
83 93133 94552 115 116
84 95536 132190 105 88
85 225920 128754 104 73
86 62133 66363 108 99
87 61370 67808 98 62
88 43836 61724 69 53
89 106117 131722 111 118
90 38692 68580 99 30
91 84651 106175 71 100
92 56622 55792 27 49
93 15986 25157 69 24
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95 26706 57283 73 46
96 89691 105805 107 57
97 67267 129484 93 75
98 126846 72413 129 135
99 41140 87831 69 68
100 102860 96971 118 124
101 51715 71299 73 33
102 55801 77494 119 98
103 111813 120336 104 58
104 120293 93913 107 68
105 138599 136048 99 81
106 161647 181248 90 131
107 115929 146123 197 110
108 24266 32036 36 37
109 162901 186646 85 130
110 109825 102255 139 93
111 129838 168237 106 118
112 37510 64219 50 39
113 43750 19630 64 13
114 40652 76825 31 74
115 87771 115338 63 81
116 85872 109427 92 109
117 89275 118168 106 151
118 44418 84845 63 51
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121 40909 63506 56 56
122 13294 22445 25 27
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124 140867 68370 93 83
125 120662 146304 114 54
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129 101338 103950 110 133
130 1168 5841 0 12
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134 32334 35753 80 44
135 40735 55515 98 71
136 91413 209056 82 116
137 855 6622 0 4
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139 44339 11609 28 12
140 14116 13155 9 18
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142 65622 72875 59 60
143 16563 10112 49 7
144 76643 142775 115 98
145 110681 68847 140 64
146 29011 17659 49 29
147 92696 20112 120 32
148 94785 61023 66 25
149 8773 13983 21 16
150 83209 65176 124 48
151 93815 132432 152 100
152 86687 112494 139 46
153 34553 45109 38 45
154 105547 170875 144 129
155 103487 180759 120 130
156 213688 214921 160 136
157 71220 100226 114 59
158 23517 32043 39 25
159 56926 54454 78 32
160 91721 78876 119 63
161 115168 170745 141 95
162 111194 6940 101 14
163 51009 49025 56 36
164 135777 122037 133 113
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166 74163 127748 116 92
167 51633 86839 90 70
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169 33416 77395 50 50
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171 98952 103300 97 91
172 102372 112283 98 111
173 37238 10901 78 41
174 103772 120691 117 120
175 123969 58106 148 135
176 27142 57140 41 27
177 135400 122422 105 87
178 21399 25899 55 25
179 130115 139296 132 131
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181 34988 23853 21 29
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183 6023 7953 0 4
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186 1644 4245 0 7
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193 20760 29668 32 42
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197 24094 27080 67 14
198 69008 35885 46 16
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200 46090 28313 56 32
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202 10672 16548 44 15
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210 22827 52785 86 43
211 18513 44683 24 27
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213 24006 21920 49 20
214 27913 45608 61 32
215 42744 7721 61 0
216 12934 20634 81 5
217 22574 29788 43 26
218 41385 31931 40 10
219 18653 37754 40 27
220 18472 32505 56 11
221 30976 40557 68 29
222 63339 94238 79 25
223 25568 44197 47 55
224 33747 43228 57 23
225 4154 4103 41 5
226 19474 44144 29 43
227 35130 32868 3 23
228 39067 27640 60 34
229 13310 14063 30 36
230 65892 28990 79 35
231 4143 4694 47 0
232 28579 42648 40 37
233 51776 64329 48 28
234 21152 21928 36 16
235 38084 25836 42 26
236 27717 22779 49 38
237 32928 40820 57 23
238 11342 27530 12 22
239 19499 32378 40 30
240 16380 10824 43 16
241 36874 39613 33 18
242 48259 60865 77 28
243 16734 19787 43 32
244 28207 20107 45 21
245 30143 36605 47 23
246 41369 40961 43 29
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250 36278 23430 7 18
251 45588 62991 71 27
252 45097 49363 67 41
253 3895 9604 0 13
254 28394 24552 62 12
255 18632 31493 54 21
256 2325 3439 4 8
257 25139 19555 25 26
258 27975 21228 40 27
259 14483 23177 38 13
260 13127 22094 19 16
261 5839 2342 17 2
262 24069 38798 67 42
263 3738 3255 14 5
264 18625 24261 30 37
265 36341 18511 54 17
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267 21792 28893 59 37
268 26263 21425 24 29
269 23686 50276 58 32
270 49303 37643 42 35
271 25659 30377 46 17
272 28904 27126 61 20
273 2781 13 3 7
274 29236 42097 52 46
275 19546 24451 25 24
276 22818 14335 40 40
277 32689 5084 32 3
278 5752 9927 4 10
279 22197 43527 49 37
280 20055 27184 63 17
281 25272 21610 67 28
282 82206 20484 32 19
283 32073 20156 23 29
284 5444 6012 7 8
285 20154 18475 54 10
286 36944 12645 37 15
287 8019 11017 35 15
288 30884 37623 51 28
289 19540 35873 39 17
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Tot._Sec `#Feedback>p120` `#Blogged_comp.`
1409.9189 0.4382 303.6250 93.0656
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-47467 -11282 -3829 9156 129722
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.410e+03 2.629e+03 0.536 0.592
Tot._Sec 4.382e-01 4.869e-02 9.000 < 2e-16 ***
`#Feedback>p120` 3.036e+02 5.277e+01 5.754 2.25e-08 ***
`#Blogged_comp.` 9.307e+01 6.880e+01 1.353 0.177
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 21280 on 285 degrees of freedom
Multiple R-squared: 0.7257, Adjusted R-squared: 0.7228
F-statistic: 251.3 on 3 and 285 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,] 0.24605984 4.921197e-01 7.539402e-01
[2,] 0.17985943 3.597189e-01 8.201406e-01
[3,] 0.12375929 2.475186e-01 8.762407e-01
[4,] 0.17311716 3.462343e-01 8.268828e-01
[5,] 0.10155929 2.031186e-01 8.984407e-01
[6,] 0.72065688 5.586862e-01 2.793431e-01
[7,] 0.70189383 5.962123e-01 2.981062e-01
[8,] 0.62056976 7.588605e-01 3.794302e-01
[9,] 0.53236988 9.352602e-01 4.676301e-01
[10,] 0.49703408 9.940682e-01 5.029659e-01
[11,] 0.45248685 9.049737e-01 5.475131e-01
[12,] 0.60037567 7.992487e-01 3.996243e-01
[13,] 0.60312150 7.937570e-01 3.968785e-01
[14,] 0.64922219 7.015556e-01 3.507778e-01
[15,] 0.65684506 6.863099e-01 3.431549e-01
[16,] 0.59076393 8.184721e-01 4.092361e-01
[17,] 0.64295344 7.140931e-01 3.570466e-01
[18,] 0.59807178 8.038564e-01 4.019282e-01
[19,] 0.55376301 8.924740e-01 4.462370e-01
[20,] 0.51875306 9.624939e-01 4.812469e-01
[21,] 0.45646910 9.129382e-01 5.435309e-01
[22,] 0.40458578 8.091716e-01 5.954142e-01
[23,] 0.44171474 8.834295e-01 5.582853e-01
[24,] 0.47682536 9.536507e-01 5.231746e-01
[25,] 0.57816001 8.436800e-01 4.218400e-01
[26,] 0.54289904 9.142019e-01 4.571010e-01
[27,] 0.48840110 9.768022e-01 5.115989e-01
[28,] 0.52280254 9.543949e-01 4.771975e-01
[29,] 0.47405417 9.481083e-01 5.259458e-01
[30,] 0.43379319 8.675864e-01 5.662068e-01
[31,] 0.44835008 8.967002e-01 5.516499e-01
[32,] 0.42778038 8.555608e-01 5.722196e-01
[33,] 0.45162287 9.032457e-01 5.483771e-01
[34,] 0.43104024 8.620805e-01 5.689598e-01
[35,] 0.38957623 7.791525e-01 6.104238e-01
[36,] 0.35945262 7.189052e-01 6.405474e-01
[37,] 0.33009237 6.601847e-01 6.699076e-01
[38,] 0.30698807 6.139761e-01 6.930119e-01
[39,] 0.28472904 5.694581e-01 7.152710e-01
[40,] 0.24621544 4.924309e-01 7.537846e-01
[41,] 0.22328853 4.465771e-01 7.767115e-01
[42,] 0.19169502 3.833900e-01 8.083050e-01
[43,] 0.16091654 3.218331e-01 8.390835e-01
[44,] 0.17341095 3.468219e-01 8.265890e-01
[45,] 0.20148508 4.029702e-01 7.985149e-01
[46,] 0.19237265 3.847453e-01 8.076274e-01
[47,] 0.16463791 3.292758e-01 8.353621e-01
[48,] 0.19817159 3.963432e-01 8.018284e-01
[49,] 0.17175325 3.435065e-01 8.282467e-01
[50,] 0.16140563 3.228113e-01 8.385944e-01
[51,] 0.14291036 2.858207e-01 8.570896e-01
[52,] 0.12436381 2.487276e-01 8.756362e-01
[53,] 0.10386607 2.077321e-01 8.961339e-01
[54,] 0.08696884 1.739377e-01 9.130312e-01
[55,] 0.07182738 1.436548e-01 9.281726e-01
[56,] 0.07678636 1.535727e-01 9.232136e-01
[57,] 0.08316447 1.663289e-01 9.168355e-01
[58,] 0.07639874 1.527975e-01 9.236013e-01
[59,] 0.07195557 1.439111e-01 9.280444e-01
[60,] 0.06539093 1.307819e-01 9.346091e-01
[61,] 0.05645365 1.129073e-01 9.435464e-01
[62,] 0.04978454 9.956908e-02 9.502155e-01
[63,] 0.10174142 2.034828e-01 8.982586e-01
[64,] 0.09220959 1.844192e-01 9.077904e-01
[65,] 0.07878730 1.575746e-01 9.212127e-01
[66,] 0.06590470 1.318094e-01 9.340953e-01
[67,] 0.07133034 1.426607e-01 9.286697e-01
[68,] 0.11598957 2.319791e-01 8.840104e-01
[69,] 0.10775117 2.155023e-01 8.922488e-01
[70,] 0.10507521 2.101504e-01 8.949248e-01
[71,] 0.09335700 1.867140e-01 9.066430e-01
[72,] 0.08624867 1.724973e-01 9.137513e-01
[73,] 0.07645423 1.529085e-01 9.235458e-01
[74,] 0.07138210 1.427642e-01 9.286179e-01
[75,] 0.06872930 1.374586e-01 9.312707e-01
[76,] 0.05915222 1.183044e-01 9.408478e-01
[77,] 0.04981871 9.963741e-02 9.501813e-01
[78,] 0.04116438 8.232875e-02 9.588356e-01
[79,] 0.96416059 7.167882e-02 3.583941e-02
[80,] 0.95806574 8.386853e-02 4.193426e-02
[81,] 0.94983960 1.003208e-01 5.016040e-02
[82,] 0.94240317 1.151937e-01 5.759683e-02
[83,] 0.93183332 1.363334e-01 6.816668e-02
[84,] 0.93557006 1.288599e-01 6.442994e-02
[85,] 0.92407193 1.518561e-01 7.592807e-02
[86,] 0.91806191 1.638762e-01 8.193809e-02
[87,] 0.91552574 1.689485e-01 8.447426e-02
[88,] 0.91754466 1.649107e-01 8.245534e-02
[89,] 0.92399669 1.520066e-01 7.600331e-02
[90,] 0.91180987 1.763803e-01 8.819013e-02
[91,] 0.91858832 1.628234e-01 8.141168e-02
[92,] 0.94939424 1.012115e-01 5.060576e-02
[93,] 0.95415817 9.168366e-02 4.584183e-02
[94,] 0.94736037 1.052793e-01 5.263963e-02
[95,] 0.93823908 1.235218e-01 6.176092e-02
[96,] 0.94208946 1.158211e-01 5.791054e-02
[97,] 0.94272333 1.145533e-01 5.727667e-02
[98,] 0.96255736 7.488528e-02 3.744264e-02
[99,] 0.97661929 4.676142e-02 2.338071e-02
[100,] 0.98579483 2.841034e-02 1.420517e-02
[101,] 0.98574931 2.850139e-02 1.425069e-02
[102,] 0.98265902 3.468195e-02 1.734098e-02
[103,] 0.99012710 1.974580e-02 9.872898e-03
[104,] 0.98873338 2.253324e-02 1.126662e-02
[105,] 0.98674834 2.650331e-02 1.325166e-02
[106,] 0.98443406 3.113188e-02 1.556594e-02
[107,] 0.98244950 3.510101e-02 1.755050e-02
[108,] 0.98009881 3.980238e-02 1.990119e-02
[109,] 0.97663412 4.673175e-02 2.336588e-02
[110,] 0.97162793 5.674415e-02 2.837207e-02
[111,] 0.96749478 6.501044e-02 3.250522e-02
[112,] 0.96564118 6.871764e-02 3.435882e-02
[113,] 0.99991970 1.605955e-04 8.029776e-05
[114,] 0.99988883 2.223305e-04 1.111653e-04
[115,] 0.99985717 2.856624e-04 1.428312e-04
[116,] 0.99981108 3.778491e-04 1.889245e-04
[117,] 0.99977132 4.573597e-04 2.286799e-04
[118,] 0.99999546 9.088063e-06 4.544032e-06
[119,] 0.99999539 9.219415e-06 4.609707e-06
[120,] 0.99999381 1.238102e-05 6.190508e-06
[121,] 0.99999162 1.676246e-05 8.381229e-06
[122,] 0.99998808 2.383636e-05 1.191818e-05
[123,] 0.99998342 3.316689e-05 1.658344e-05
[124,] 0.99997642 4.715631e-05 2.357816e-05
[125,] 0.99996639 6.721408e-05 3.360704e-05
[126,] 0.99995534 8.931778e-05 4.465889e-05
[127,] 0.99993702 1.259661e-04 6.298306e-05
[128,] 0.99992815 1.436957e-04 7.184784e-05
[129,] 0.99994043 1.191315e-04 5.956575e-05
[130,] 0.99996366 7.267322e-05 3.633661e-05
[131,] 0.99994890 1.022044e-04 5.110221e-05
[132,] 0.99996154 7.691919e-05 3.845960e-05
[133,] 0.99997213 5.574870e-05 2.787435e-05
[134,] 0.99996086 7.827983e-05 3.913991e-05
[135,] 0.99994904 1.019289e-04 5.096445e-05
[136,] 0.99993419 1.316215e-04 6.581077e-05
[137,] 0.99991065 1.787070e-04 8.935352e-05
[138,] 0.99993691 1.261865e-04 6.309323e-05
[139,] 0.99994979 1.004237e-04 5.021187e-05
[140,] 0.99992907 1.418574e-04 7.092872e-05
[141,] 0.99996823 6.353725e-05 3.176863e-05
[142,] 0.99999345 1.310911e-05 6.554553e-06
[143,] 0.99999073 1.854494e-05 9.272469e-06
[144,] 0.99998733 2.533677e-05 1.266839e-05
[145,] 0.99998851 2.298292e-05 1.149146e-05
[146,] 0.99998454 3.091931e-05 1.545965e-05
[147,] 0.99997765 4.470877e-05 2.235439e-05
[148,] 0.99998335 3.329815e-05 1.664907e-05
[149,] 0.99998657 2.686111e-05 1.343055e-05
[150,] 0.99999955 8.944771e-07 4.472386e-07
[151,] 0.99999942 1.165408e-06 5.827042e-07
[152,] 0.99999913 1.742610e-06 8.713050e-07
[153,] 0.99999870 2.596769e-06 1.298384e-06
[154,] 0.99999829 3.429945e-06 1.714972e-06
[155,] 0.99999754 4.910925e-06 2.455463e-06
[156,] 0.99999999 1.511753e-08 7.558766e-09
[157,] 0.99999999 2.253013e-08 1.126507e-08
[158,] 0.99999999 1.074222e-08 5.371111e-09
[159,] 0.99999999 1.792851e-08 8.964255e-09
[160,] 0.99999999 1.346775e-08 6.733876e-09
[161,] 0.99999999 1.189401e-08 5.947007e-09
[162,] 1.00000000 8.640325e-10 4.320163e-10
[163,] 1.00000000 8.168138e-10 4.084069e-10
[164,] 1.00000000 4.248542e-10 2.124271e-10
[165,] 1.00000000 5.330347e-10 2.665174e-10
[166,] 1.00000000 7.922641e-10 3.961321e-10
[167,] 1.00000000 1.387686e-09 6.938430e-10
[168,] 1.00000000 2.423869e-09 1.211934e-09
[169,] 1.00000000 8.397965e-10 4.198983e-10
[170,] 1.00000000 1.192275e-09 5.961373e-10
[171,] 1.00000000 2.115887e-11 1.057943e-11
[172,] 1.00000000 3.366540e-11 1.683270e-11
[173,] 1.00000000 5.315246e-12 2.657623e-12
[174,] 1.00000000 7.247157e-12 3.623578e-12
[175,] 1.00000000 9.543028e-12 4.771514e-12
[176,] 1.00000000 8.540862e-12 4.270431e-12
[177,] 1.00000000 1.572289e-11 7.861444e-12
[178,] 1.00000000 2.419588e-11 1.209794e-11
[179,] 1.00000000 6.809980e-12 3.404990e-12
[180,] 1.00000000 1.191005e-11 5.955025e-12
[181,] 1.00000000 1.627845e-11 8.139225e-12
[182,] 1.00000000 2.786151e-11 1.393075e-11
[183,] 1.00000000 3.445554e-11 1.722777e-11
[184,] 1.00000000 4.868825e-11 2.434413e-11
[185,] 1.00000000 6.241126e-12 3.120563e-12
[186,] 1.00000000 1.225107e-11 6.125537e-12
[187,] 1.00000000 2.265250e-11 1.132625e-11
[188,] 1.00000000 3.715930e-11 1.857965e-11
[189,] 1.00000000 6.856047e-11 3.428024e-11
[190,] 1.00000000 1.289101e-10 6.445506e-11
[191,] 1.00000000 2.209428e-10 1.104714e-10
[192,] 1.00000000 1.234317e-11 6.171583e-12
[193,] 1.00000000 6.851666e-12 3.425833e-12
[194,] 1.00000000 6.427802e-12 3.213901e-12
[195,] 1.00000000 1.269905e-11 6.349525e-12
[196,] 1.00000000 1.803405e-11 9.017025e-12
[197,] 1.00000000 3.592775e-11 1.796387e-11
[198,] 1.00000000 6.587701e-11 3.293851e-11
[199,] 1.00000000 1.246303e-10 6.231516e-11
[200,] 1.00000000 2.469486e-10 1.234743e-10
[201,] 1.00000000 4.410952e-10 2.205476e-10
[202,] 1.00000000 8.186974e-10 4.093487e-10
[203,] 1.00000000 1.389021e-09 6.945104e-10
[204,] 1.00000000 8.095025e-10 4.047513e-10
[205,] 1.00000000 1.138147e-09 5.690733e-10
[206,] 1.00000000 2.200415e-09 1.100208e-09
[207,] 1.00000000 4.233477e-09 2.116739e-09
[208,] 1.00000000 6.410305e-09 3.205153e-09
[209,] 1.00000000 3.588304e-09 1.794152e-09
[210,] 1.00000000 3.666880e-09 1.833440e-09
[211,] 1.00000000 6.655501e-09 3.327751e-09
[212,] 1.00000000 7.876483e-09 3.938241e-09
[213,] 0.99999999 1.068951e-08 5.344755e-09
[214,] 0.99999999 1.445782e-08 7.228910e-09
[215,] 0.99999999 2.501442e-08 1.250721e-08
[216,] 0.99999998 4.683962e-08 2.341981e-08
[217,] 0.99999997 6.414299e-08 3.207150e-08
[218,] 0.99999994 1.200823e-07 6.004117e-08
[219,] 0.99999992 1.625735e-07 8.128676e-08
[220,] 0.99999990 1.972619e-07 9.863093e-08
[221,] 0.99999988 2.418665e-07 1.209332e-07
[222,] 0.99999979 4.101216e-07 2.050608e-07
[223,] 0.99999967 6.566981e-07 3.283490e-07
[224,] 0.99999994 1.257291e-07 6.286455e-08
[225,] 0.99999992 1.697182e-07 8.485912e-08
[226,] 0.99999985 3.088014e-07 1.544007e-07
[227,] 0.99999976 4.790615e-07 2.395307e-07
[228,] 0.99999955 9.077745e-07 4.538872e-07
[229,] 0.99999938 1.232255e-06 6.161277e-07
[230,] 0.99999884 2.321462e-06 1.160731e-06
[231,] 0.99999785 4.307407e-06 2.153703e-06
[232,] 0.99999697 6.056617e-06 3.028308e-06
[233,] 0.99999545 9.102034e-06 4.551017e-06
[234,] 0.99999189 1.621918e-05 8.109591e-06
[235,] 0.99998680 2.639918e-05 1.319959e-05
[236,] 0.99997756 4.487151e-05 2.243576e-05
[237,] 0.99996598 6.803002e-05 3.401501e-05
[238,] 0.99994178 1.164328e-04 5.821638e-05
[239,] 0.99989915 2.017015e-04 1.008507e-04
[240,] 0.99985452 2.909672e-04 1.454836e-04
[241,] 0.99979077 4.184676e-04 2.092338e-04
[242,] 0.99964827 7.034575e-04 3.517287e-04
[243,] 0.99955883 8.823379e-04 4.411689e-04
[244,] 0.99961264 7.747260e-04 3.873630e-04
[245,] 0.99941725 1.165491e-03 5.827457e-04
[246,] 0.99915521 1.689570e-03 8.447850e-04
[247,] 0.99874204 2.515925e-03 1.257963e-03
[248,] 0.99796304 4.073930e-03 2.036965e-03
[249,] 0.99710222 5.795567e-03 2.897783e-03
[250,] 0.99602537 7.949268e-03 3.974634e-03
[251,] 0.99385429 1.229143e-02 6.145714e-03
[252,] 0.99061078 1.877844e-02 9.389219e-03
[253,] 0.98682581 2.634838e-02 1.317419e-02
[254,] 0.98113758 3.772483e-02 1.886242e-02
[255,] 0.97510599 4.978802e-02 2.489401e-02
[256,] 0.96736847 6.526305e-02 3.263153e-02
[257,] 0.96051816 7.896369e-02 3.948184e-02
[258,] 0.94586586 1.082683e-01 5.413414e-02
[259,] 0.92973637 1.405273e-01 7.026363e-02
[260,] 0.90392187 1.921563e-01 9.607813e-02
[261,] 0.87880547 2.423891e-01 1.211945e-01
[262,] 0.83680479 3.263904e-01 1.631952e-01
[263,] 0.80165846 3.966831e-01 1.983415e-01
[264,] 0.79761676 4.047665e-01 2.023832e-01
[265,] 0.73549814 5.290037e-01 2.645019e-01
[266,] 0.66299313 6.740137e-01 3.370069e-01
[267,] 0.61975110 7.604978e-01 3.802489e-01
[268,] 0.53383484 9.323303e-01 4.661652e-01
[269,] 0.44802647 8.960529e-01 5.519735e-01
[270,] 0.37207259 7.441452e-01 6.279274e-01
[271,] 0.31429597 6.285919e-01 6.857040e-01
[272,] 0.26819980 5.363996e-01 7.318002e-01
[273,] 0.22774037 4.554807e-01 7.722596e-01
[274,] 0.15080412 3.016082e-01 8.491959e-01
[275,] 0.10292040 2.058408e-01 8.970796e-01
[276,] 0.81987376 3.602525e-01 1.801262e-01
> postscript(file="/var/wessaorg/rcomp/tmp/10tkf1324667123.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/218cl1324667123.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ytph1324667123.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4u68f1324667123.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/502ky1324667123.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
10884.1044 3603.9246 10144.7069 15984.6799 -17812.6318 27195.4016
7 8 9 10 11 12
-6854.0213 11621.4286 -7102.5231 40566.4892 -5915.0008 -42907.1457
13 14 15 16 17 18
-15885.3280 -994.8658 -9116.2511 -16753.1362 -35844.1234 28251.0094
19 20 21 22 23 24
21990.3694 29056.6938 15763.4092 -532.1701 -29976.9629 -9375.9533
25 26 27 28 29 30
6866.0409 -17708.2099 -3259.1425 -9465.2513 -32688.8612 -23271.5084
31 32 33 34 35 36
-45059.1044 2630.2956 -4486.4570 -41343.0788 11655.6242 -22879.1605
37 38 39 40 41 42
-17388.6517 -18072.0531 -38235.7471 -832.1650 -10101.2636 -10219.8810
43 44 45 46 47 48
-7698.0961 -23606.5882 -22268.7094 -5169.1598 -12227.5993 -1665.3131
49 50 51 52 53 54
174.8986 23253.0782 24063.0271 -15240.6268 -9731.8456 15758.7685
55 56 57 58 59 60
-10529.0885 -22658.6507 -4923.9647 -3484.4018 -336.6429 -5028.5970
61 62 63 64 65 66
-2091.5224 12580.7577 14009.6386 -14530.8468 8522.9013 -21616.3038
67 68 69 70 71 72
8095.0378 896.1257 38429.7361 -15025.1646 3647.9363 3079.3700
73 74 75 76 77 78
-25573.5781 36259.1500 -18025.9736 15919.9921 11540.5823 -18441.6427
79 80 81 82 83 84
-11621.3994 -20352.6055 17684.0771 -10866.9417 4579.9577 -3867.1134
85 86 87 88 89 90
129722.0759 -10360.7428 -5277.2346 -10502.6416 2305.2372 -25619.0355
91 92 93 94 95 96
5853.5610 18007.1460 -19630.8724 21636.1139 -26249.7327 4127.0049
97 98 99 100 101 102
-26097.0501 41974.7924 -26034.1473 11591.6047 -6172.3883 -24816.9159
103 104 105 106 107 108
20699.6447 38916.1008 39978.6036 41300.2892 -19560.1975 -5555.3276
109 110 111 112 113 114
41800.1932 12750.1770 11544.2796 -10850.1032 13096.7857 -10720.1985
115 116 117 118 119 120
9155.7785 -1564.1107 -10150.7316 -18043.8821 100471.5085 4559.3777
121 122 123 124 125 126
-10542.5467 -8054.2280 -13100.8883 73537.2576 15506.0410 -10980.3133
127 128 129 130 131 132
8522.1424 5604.3794 8602.9682 -3918.1054 2863.4297 -7889.2463
133 134 135 136 137 138
1719.2529 -13126.9967 -21363.2981 -37293.5909 -3828.7983 20923.3263
139 140 141 142 143 144
28223.9810 2534.0394 -10451.7341 8782.0230 -4806.8639 -31365.1372
145 146 147 148 149 150
30640.1157 2286.7618 43060.3364 44270.2322 -6629.1415 11123.7179
151 152 153 154 155 156
-21081.3156 -10500.2500 -2348.4077 -26464.1072 -25661.1269 56867.4295
157 158 159 160 161 162
-14210.9044 -6101.4832 4994.6665 13754.8161 -12711.0399 74774.0774
163 164 165 166 167 168
7764.0253 29994.5717 -3037.9861 -27005.8627 -21668.7311 41592.7986
169 170 171 172 173 174
-21741.2624 20418.4227 14357.6630 11676.5706 3553.0585 2785.9014
175 176 177 178 179 180
39597.9346 -14266.8266 40370.0784 -10385.3158 15398.4964 -17165.7299
181 182 183 184 185 186
14051.1859 15976.9125 755.9863 -2679.8724 -47467.4984 -2277.4450
187 188 189 190 191 192
-9719.6093 -2059.2471 -18620.5133 9067.9290 30076.4486 -3437.1070
193 194 195 196 197 198
-7274.5489 5245.6929 -9823.4671 -7774.0758 -10827.5837 36418.2504
199 200 201 202 203 204
18446.6235 12292.8377 -6575.9787 -12744.3791 -4968.0487 -1327.5661
205 206 207 208 209 210
-8622.8676 -944.1868 -9897.6907 -11282.1887 -12604.5441 -31825.7352
211 212 213 214 215 216
-12275.8133 -5655.3211 -3747.7262 -14980.5822 19429.7791 -22576.2464
217 218 219 220 221 222
-7363.9567 12907.9511 -13957.6759 -15207.6293 -11550.5218 -5676.9874
223 224 225 226 227 228
-14597.0699 -6051.6276 -11967.7188 -14085.8092 16266.6519 4164.1005
229 230 231 232 233 234
-6721.1322 24535.6185 -13594.1046 -7106.7764 4998.6684 -2285.8440
235 236 237 238 239 240
10181.3492 -2088.3014 -5815.4941 -7821.9118 -11035.2258 -4317.6867
241 242 243 244 245 246
6411.7157 -5805.6076 -9380.1283 2369.1257 -3717.3220 6256.0799
247 248 249 250 251 252
4972.8964 -5958.5924 12551.7116 20801.0069 -7493.3591 -2101.2821
253 254 255 256 257 258
-2933.0361 -3715.6126 -14927.5983 -2550.8389 5150.1730 2605.6596
259 260 261 262 263 264
-9830.1821 -5221.9561 -1944.8893 -18592.9933 -3814.2677 -5967.7406
265 266 267 268 269 270
8842.0954 -8902.0869 -13635.5087 5479.2078 -20342.1237 15389.1873
271 272 273 274 275 276
-4610.3288 -4774.3831 -196.9493 -10689.4305 -2402.0171 -740.8292
277 278 279 280 281 282
19056.1846 -2152.8712 -16606.5605 -13976.8508 -8555.6659 60336.1890
283 284 285 286 287 288
12148.8812 -1470.1469 -6677.6713 17363.2062 -10241.1893 -5102.2155
289
-11012.1818
> postscript(file="/var/wessaorg/rcomp/tmp/6lnqh1324667123.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 10884.1044 NA
1 3603.9246 10884.1044
2 10144.7069 3603.9246
3 15984.6799 10144.7069
4 -17812.6318 15984.6799
5 27195.4016 -17812.6318
6 -6854.0213 27195.4016
7 11621.4286 -6854.0213
8 -7102.5231 11621.4286
9 40566.4892 -7102.5231
10 -5915.0008 40566.4892
11 -42907.1457 -5915.0008
12 -15885.3280 -42907.1457
13 -994.8658 -15885.3280
14 -9116.2511 -994.8658
15 -16753.1362 -9116.2511
16 -35844.1234 -16753.1362
17 28251.0094 -35844.1234
18 21990.3694 28251.0094
19 29056.6938 21990.3694
20 15763.4092 29056.6938
21 -532.1701 15763.4092
22 -29976.9629 -532.1701
23 -9375.9533 -29976.9629
24 6866.0409 -9375.9533
25 -17708.2099 6866.0409
26 -3259.1425 -17708.2099
27 -9465.2513 -3259.1425
28 -32688.8612 -9465.2513
29 -23271.5084 -32688.8612
30 -45059.1044 -23271.5084
31 2630.2956 -45059.1044
32 -4486.4570 2630.2956
33 -41343.0788 -4486.4570
34 11655.6242 -41343.0788
35 -22879.1605 11655.6242
36 -17388.6517 -22879.1605
37 -18072.0531 -17388.6517
38 -38235.7471 -18072.0531
39 -832.1650 -38235.7471
40 -10101.2636 -832.1650
41 -10219.8810 -10101.2636
42 -7698.0961 -10219.8810
43 -23606.5882 -7698.0961
44 -22268.7094 -23606.5882
45 -5169.1598 -22268.7094
46 -12227.5993 -5169.1598
47 -1665.3131 -12227.5993
48 174.8986 -1665.3131
49 23253.0782 174.8986
50 24063.0271 23253.0782
51 -15240.6268 24063.0271
52 -9731.8456 -15240.6268
53 15758.7685 -9731.8456
54 -10529.0885 15758.7685
55 -22658.6507 -10529.0885
56 -4923.9647 -22658.6507
57 -3484.4018 -4923.9647
58 -336.6429 -3484.4018
59 -5028.5970 -336.6429
60 -2091.5224 -5028.5970
61 12580.7577 -2091.5224
62 14009.6386 12580.7577
63 -14530.8468 14009.6386
64 8522.9013 -14530.8468
65 -21616.3038 8522.9013
66 8095.0378 -21616.3038
67 896.1257 8095.0378
68 38429.7361 896.1257
69 -15025.1646 38429.7361
70 3647.9363 -15025.1646
71 3079.3700 3647.9363
72 -25573.5781 3079.3700
73 36259.1500 -25573.5781
74 -18025.9736 36259.1500
75 15919.9921 -18025.9736
76 11540.5823 15919.9921
77 -18441.6427 11540.5823
78 -11621.3994 -18441.6427
79 -20352.6055 -11621.3994
80 17684.0771 -20352.6055
81 -10866.9417 17684.0771
82 4579.9577 -10866.9417
83 -3867.1134 4579.9577
84 129722.0759 -3867.1134
85 -10360.7428 129722.0759
86 -5277.2346 -10360.7428
87 -10502.6416 -5277.2346
88 2305.2372 -10502.6416
89 -25619.0355 2305.2372
90 5853.5610 -25619.0355
91 18007.1460 5853.5610
92 -19630.8724 18007.1460
93 21636.1139 -19630.8724
94 -26249.7327 21636.1139
95 4127.0049 -26249.7327
96 -26097.0501 4127.0049
97 41974.7924 -26097.0501
98 -26034.1473 41974.7924
99 11591.6047 -26034.1473
100 -6172.3883 11591.6047
101 -24816.9159 -6172.3883
102 20699.6447 -24816.9159
103 38916.1008 20699.6447
104 39978.6036 38916.1008
105 41300.2892 39978.6036
106 -19560.1975 41300.2892
107 -5555.3276 -19560.1975
108 41800.1932 -5555.3276
109 12750.1770 41800.1932
110 11544.2796 12750.1770
111 -10850.1032 11544.2796
112 13096.7857 -10850.1032
113 -10720.1985 13096.7857
114 9155.7785 -10720.1985
115 -1564.1107 9155.7785
116 -10150.7316 -1564.1107
117 -18043.8821 -10150.7316
118 100471.5085 -18043.8821
119 4559.3777 100471.5085
120 -10542.5467 4559.3777
121 -8054.2280 -10542.5467
122 -13100.8883 -8054.2280
123 73537.2576 -13100.8883
124 15506.0410 73537.2576
125 -10980.3133 15506.0410
126 8522.1424 -10980.3133
127 5604.3794 8522.1424
128 8602.9682 5604.3794
129 -3918.1054 8602.9682
130 2863.4297 -3918.1054
131 -7889.2463 2863.4297
132 1719.2529 -7889.2463
133 -13126.9967 1719.2529
134 -21363.2981 -13126.9967
135 -37293.5909 -21363.2981
136 -3828.7983 -37293.5909
137 20923.3263 -3828.7983
138 28223.9810 20923.3263
139 2534.0394 28223.9810
140 -10451.7341 2534.0394
141 8782.0230 -10451.7341
142 -4806.8639 8782.0230
143 -31365.1372 -4806.8639
144 30640.1157 -31365.1372
145 2286.7618 30640.1157
146 43060.3364 2286.7618
147 44270.2322 43060.3364
148 -6629.1415 44270.2322
149 11123.7179 -6629.1415
150 -21081.3156 11123.7179
151 -10500.2500 -21081.3156
152 -2348.4077 -10500.2500
153 -26464.1072 -2348.4077
154 -25661.1269 -26464.1072
155 56867.4295 -25661.1269
156 -14210.9044 56867.4295
157 -6101.4832 -14210.9044
158 4994.6665 -6101.4832
159 13754.8161 4994.6665
160 -12711.0399 13754.8161
161 74774.0774 -12711.0399
162 7764.0253 74774.0774
163 29994.5717 7764.0253
164 -3037.9861 29994.5717
165 -27005.8627 -3037.9861
166 -21668.7311 -27005.8627
167 41592.7986 -21668.7311
168 -21741.2624 41592.7986
169 20418.4227 -21741.2624
170 14357.6630 20418.4227
171 11676.5706 14357.6630
172 3553.0585 11676.5706
173 2785.9014 3553.0585
174 39597.9346 2785.9014
175 -14266.8266 39597.9346
176 40370.0784 -14266.8266
177 -10385.3158 40370.0784
178 15398.4964 -10385.3158
179 -17165.7299 15398.4964
180 14051.1859 -17165.7299
181 15976.9125 14051.1859
182 755.9863 15976.9125
183 -2679.8724 755.9863
184 -47467.4984 -2679.8724
185 -2277.4450 -47467.4984
186 -9719.6093 -2277.4450
187 -2059.2471 -9719.6093
188 -18620.5133 -2059.2471
189 9067.9290 -18620.5133
190 30076.4486 9067.9290
191 -3437.1070 30076.4486
192 -7274.5489 -3437.1070
193 5245.6929 -7274.5489
194 -9823.4671 5245.6929
195 -7774.0758 -9823.4671
196 -10827.5837 -7774.0758
197 36418.2504 -10827.5837
198 18446.6235 36418.2504
199 12292.8377 18446.6235
200 -6575.9787 12292.8377
201 -12744.3791 -6575.9787
202 -4968.0487 -12744.3791
203 -1327.5661 -4968.0487
204 -8622.8676 -1327.5661
205 -944.1868 -8622.8676
206 -9897.6907 -944.1868
207 -11282.1887 -9897.6907
208 -12604.5441 -11282.1887
209 -31825.7352 -12604.5441
210 -12275.8133 -31825.7352
211 -5655.3211 -12275.8133
212 -3747.7262 -5655.3211
213 -14980.5822 -3747.7262
214 19429.7791 -14980.5822
215 -22576.2464 19429.7791
216 -7363.9567 -22576.2464
217 12907.9511 -7363.9567
218 -13957.6759 12907.9511
219 -15207.6293 -13957.6759
220 -11550.5218 -15207.6293
221 -5676.9874 -11550.5218
222 -14597.0699 -5676.9874
223 -6051.6276 -14597.0699
224 -11967.7188 -6051.6276
225 -14085.8092 -11967.7188
226 16266.6519 -14085.8092
227 4164.1005 16266.6519
228 -6721.1322 4164.1005
229 24535.6185 -6721.1322
230 -13594.1046 24535.6185
231 -7106.7764 -13594.1046
232 4998.6684 -7106.7764
233 -2285.8440 4998.6684
234 10181.3492 -2285.8440
235 -2088.3014 10181.3492
236 -5815.4941 -2088.3014
237 -7821.9118 -5815.4941
238 -11035.2258 -7821.9118
239 -4317.6867 -11035.2258
240 6411.7157 -4317.6867
241 -5805.6076 6411.7157
242 -9380.1283 -5805.6076
243 2369.1257 -9380.1283
244 -3717.3220 2369.1257
245 6256.0799 -3717.3220
246 4972.8964 6256.0799
247 -5958.5924 4972.8964
248 12551.7116 -5958.5924
249 20801.0069 12551.7116
250 -7493.3591 20801.0069
251 -2101.2821 -7493.3591
252 -2933.0361 -2101.2821
253 -3715.6126 -2933.0361
254 -14927.5983 -3715.6126
255 -2550.8389 -14927.5983
256 5150.1730 -2550.8389
257 2605.6596 5150.1730
258 -9830.1821 2605.6596
259 -5221.9561 -9830.1821
260 -1944.8893 -5221.9561
261 -18592.9933 -1944.8893
262 -3814.2677 -18592.9933
263 -5967.7406 -3814.2677
264 8842.0954 -5967.7406
265 -8902.0869 8842.0954
266 -13635.5087 -8902.0869
267 5479.2078 -13635.5087
268 -20342.1237 5479.2078
269 15389.1873 -20342.1237
270 -4610.3288 15389.1873
271 -4774.3831 -4610.3288
272 -196.9493 -4774.3831
273 -10689.4305 -196.9493
274 -2402.0171 -10689.4305
275 -740.8292 -2402.0171
276 19056.1846 -740.8292
277 -2152.8712 19056.1846
278 -16606.5605 -2152.8712
279 -13976.8508 -16606.5605
280 -8555.6659 -13976.8508
281 60336.1890 -8555.6659
282 12148.8812 60336.1890
283 -1470.1469 12148.8812
284 -6677.6713 -1470.1469
285 17363.2062 -6677.6713
286 -10241.1893 17363.2062
287 -5102.2155 -10241.1893
288 -11012.1818 -5102.2155
289 NA -11012.1818
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 3603.9246 10884.1044
[2,] 10144.7069 3603.9246
[3,] 15984.6799 10144.7069
[4,] -17812.6318 15984.6799
[5,] 27195.4016 -17812.6318
[6,] -6854.0213 27195.4016
[7,] 11621.4286 -6854.0213
[8,] -7102.5231 11621.4286
[9,] 40566.4892 -7102.5231
[10,] -5915.0008 40566.4892
[11,] -42907.1457 -5915.0008
[12,] -15885.3280 -42907.1457
[13,] -994.8658 -15885.3280
[14,] -9116.2511 -994.8658
[15,] -16753.1362 -9116.2511
[16,] -35844.1234 -16753.1362
[17,] 28251.0094 -35844.1234
[18,] 21990.3694 28251.0094
[19,] 29056.6938 21990.3694
[20,] 15763.4092 29056.6938
[21,] -532.1701 15763.4092
[22,] -29976.9629 -532.1701
[23,] -9375.9533 -29976.9629
[24,] 6866.0409 -9375.9533
[25,] -17708.2099 6866.0409
[26,] -3259.1425 -17708.2099
[27,] -9465.2513 -3259.1425
[28,] -32688.8612 -9465.2513
[29,] -23271.5084 -32688.8612
[30,] -45059.1044 -23271.5084
[31,] 2630.2956 -45059.1044
[32,] -4486.4570 2630.2956
[33,] -41343.0788 -4486.4570
[34,] 11655.6242 -41343.0788
[35,] -22879.1605 11655.6242
[36,] -17388.6517 -22879.1605
[37,] -18072.0531 -17388.6517
[38,] -38235.7471 -18072.0531
[39,] -832.1650 -38235.7471
[40,] -10101.2636 -832.1650
[41,] -10219.8810 -10101.2636
[42,] -7698.0961 -10219.8810
[43,] -23606.5882 -7698.0961
[44,] -22268.7094 -23606.5882
[45,] -5169.1598 -22268.7094
[46,] -12227.5993 -5169.1598
[47,] -1665.3131 -12227.5993
[48,] 174.8986 -1665.3131
[49,] 23253.0782 174.8986
[50,] 24063.0271 23253.0782
[51,] -15240.6268 24063.0271
[52,] -9731.8456 -15240.6268
[53,] 15758.7685 -9731.8456
[54,] -10529.0885 15758.7685
[55,] -22658.6507 -10529.0885
[56,] -4923.9647 -22658.6507
[57,] -3484.4018 -4923.9647
[58,] -336.6429 -3484.4018
[59,] -5028.5970 -336.6429
[60,] -2091.5224 -5028.5970
[61,] 12580.7577 -2091.5224
[62,] 14009.6386 12580.7577
[63,] -14530.8468 14009.6386
[64,] 8522.9013 -14530.8468
[65,] -21616.3038 8522.9013
[66,] 8095.0378 -21616.3038
[67,] 896.1257 8095.0378
[68,] 38429.7361 896.1257
[69,] -15025.1646 38429.7361
[70,] 3647.9363 -15025.1646
[71,] 3079.3700 3647.9363
[72,] -25573.5781 3079.3700
[73,] 36259.1500 -25573.5781
[74,] -18025.9736 36259.1500
[75,] 15919.9921 -18025.9736
[76,] 11540.5823 15919.9921
[77,] -18441.6427 11540.5823
[78,] -11621.3994 -18441.6427
[79,] -20352.6055 -11621.3994
[80,] 17684.0771 -20352.6055
[81,] -10866.9417 17684.0771
[82,] 4579.9577 -10866.9417
[83,] -3867.1134 4579.9577
[84,] 129722.0759 -3867.1134
[85,] -10360.7428 129722.0759
[86,] -5277.2346 -10360.7428
[87,] -10502.6416 -5277.2346
[88,] 2305.2372 -10502.6416
[89,] -25619.0355 2305.2372
[90,] 5853.5610 -25619.0355
[91,] 18007.1460 5853.5610
[92,] -19630.8724 18007.1460
[93,] 21636.1139 -19630.8724
[94,] -26249.7327 21636.1139
[95,] 4127.0049 -26249.7327
[96,] -26097.0501 4127.0049
[97,] 41974.7924 -26097.0501
[98,] -26034.1473 41974.7924
[99,] 11591.6047 -26034.1473
[100,] -6172.3883 11591.6047
[101,] -24816.9159 -6172.3883
[102,] 20699.6447 -24816.9159
[103,] 38916.1008 20699.6447
[104,] 39978.6036 38916.1008
[105,] 41300.2892 39978.6036
[106,] -19560.1975 41300.2892
[107,] -5555.3276 -19560.1975
[108,] 41800.1932 -5555.3276
[109,] 12750.1770 41800.1932
[110,] 11544.2796 12750.1770
[111,] -10850.1032 11544.2796
[112,] 13096.7857 -10850.1032
[113,] -10720.1985 13096.7857
[114,] 9155.7785 -10720.1985
[115,] -1564.1107 9155.7785
[116,] -10150.7316 -1564.1107
[117,] -18043.8821 -10150.7316
[118,] 100471.5085 -18043.8821
[119,] 4559.3777 100471.5085
[120,] -10542.5467 4559.3777
[121,] -8054.2280 -10542.5467
[122,] -13100.8883 -8054.2280
[123,] 73537.2576 -13100.8883
[124,] 15506.0410 73537.2576
[125,] -10980.3133 15506.0410
[126,] 8522.1424 -10980.3133
[127,] 5604.3794 8522.1424
[128,] 8602.9682 5604.3794
[129,] -3918.1054 8602.9682
[130,] 2863.4297 -3918.1054
[131,] -7889.2463 2863.4297
[132,] 1719.2529 -7889.2463
[133,] -13126.9967 1719.2529
[134,] -21363.2981 -13126.9967
[135,] -37293.5909 -21363.2981
[136,] -3828.7983 -37293.5909
[137,] 20923.3263 -3828.7983
[138,] 28223.9810 20923.3263
[139,] 2534.0394 28223.9810
[140,] -10451.7341 2534.0394
[141,] 8782.0230 -10451.7341
[142,] -4806.8639 8782.0230
[143,] -31365.1372 -4806.8639
[144,] 30640.1157 -31365.1372
[145,] 2286.7618 30640.1157
[146,] 43060.3364 2286.7618
[147,] 44270.2322 43060.3364
[148,] -6629.1415 44270.2322
[149,] 11123.7179 -6629.1415
[150,] -21081.3156 11123.7179
[151,] -10500.2500 -21081.3156
[152,] -2348.4077 -10500.2500
[153,] -26464.1072 -2348.4077
[154,] -25661.1269 -26464.1072
[155,] 56867.4295 -25661.1269
[156,] -14210.9044 56867.4295
[157,] -6101.4832 -14210.9044
[158,] 4994.6665 -6101.4832
[159,] 13754.8161 4994.6665
[160,] -12711.0399 13754.8161
[161,] 74774.0774 -12711.0399
[162,] 7764.0253 74774.0774
[163,] 29994.5717 7764.0253
[164,] -3037.9861 29994.5717
[165,] -27005.8627 -3037.9861
[166,] -21668.7311 -27005.8627
[167,] 41592.7986 -21668.7311
[168,] -21741.2624 41592.7986
[169,] 20418.4227 -21741.2624
[170,] 14357.6630 20418.4227
[171,] 11676.5706 14357.6630
[172,] 3553.0585 11676.5706
[173,] 2785.9014 3553.0585
[174,] 39597.9346 2785.9014
[175,] -14266.8266 39597.9346
[176,] 40370.0784 -14266.8266
[177,] -10385.3158 40370.0784
[178,] 15398.4964 -10385.3158
[179,] -17165.7299 15398.4964
[180,] 14051.1859 -17165.7299
[181,] 15976.9125 14051.1859
[182,] 755.9863 15976.9125
[183,] -2679.8724 755.9863
[184,] -47467.4984 -2679.8724
[185,] -2277.4450 -47467.4984
[186,] -9719.6093 -2277.4450
[187,] -2059.2471 -9719.6093
[188,] -18620.5133 -2059.2471
[189,] 9067.9290 -18620.5133
[190,] 30076.4486 9067.9290
[191,] -3437.1070 30076.4486
[192,] -7274.5489 -3437.1070
[193,] 5245.6929 -7274.5489
[194,] -9823.4671 5245.6929
[195,] -7774.0758 -9823.4671
[196,] -10827.5837 -7774.0758
[197,] 36418.2504 -10827.5837
[198,] 18446.6235 36418.2504
[199,] 12292.8377 18446.6235
[200,] -6575.9787 12292.8377
[201,] -12744.3791 -6575.9787
[202,] -4968.0487 -12744.3791
[203,] -1327.5661 -4968.0487
[204,] -8622.8676 -1327.5661
[205,] -944.1868 -8622.8676
[206,] -9897.6907 -944.1868
[207,] -11282.1887 -9897.6907
[208,] -12604.5441 -11282.1887
[209,] -31825.7352 -12604.5441
[210,] -12275.8133 -31825.7352
[211,] -5655.3211 -12275.8133
[212,] -3747.7262 -5655.3211
[213,] -14980.5822 -3747.7262
[214,] 19429.7791 -14980.5822
[215,] -22576.2464 19429.7791
[216,] -7363.9567 -22576.2464
[217,] 12907.9511 -7363.9567
[218,] -13957.6759 12907.9511
[219,] -15207.6293 -13957.6759
[220,] -11550.5218 -15207.6293
[221,] -5676.9874 -11550.5218
[222,] -14597.0699 -5676.9874
[223,] -6051.6276 -14597.0699
[224,] -11967.7188 -6051.6276
[225,] -14085.8092 -11967.7188
[226,] 16266.6519 -14085.8092
[227,] 4164.1005 16266.6519
[228,] -6721.1322 4164.1005
[229,] 24535.6185 -6721.1322
[230,] -13594.1046 24535.6185
[231,] -7106.7764 -13594.1046
[232,] 4998.6684 -7106.7764
[233,] -2285.8440 4998.6684
[234,] 10181.3492 -2285.8440
[235,] -2088.3014 10181.3492
[236,] -5815.4941 -2088.3014
[237,] -7821.9118 -5815.4941
[238,] -11035.2258 -7821.9118
[239,] -4317.6867 -11035.2258
[240,] 6411.7157 -4317.6867
[241,] -5805.6076 6411.7157
[242,] -9380.1283 -5805.6076
[243,] 2369.1257 -9380.1283
[244,] -3717.3220 2369.1257
[245,] 6256.0799 -3717.3220
[246,] 4972.8964 6256.0799
[247,] -5958.5924 4972.8964
[248,] 12551.7116 -5958.5924
[249,] 20801.0069 12551.7116
[250,] -7493.3591 20801.0069
[251,] -2101.2821 -7493.3591
[252,] -2933.0361 -2101.2821
[253,] -3715.6126 -2933.0361
[254,] -14927.5983 -3715.6126
[255,] -2550.8389 -14927.5983
[256,] 5150.1730 -2550.8389
[257,] 2605.6596 5150.1730
[258,] -9830.1821 2605.6596
[259,] -5221.9561 -9830.1821
[260,] -1944.8893 -5221.9561
[261,] -18592.9933 -1944.8893
[262,] -3814.2677 -18592.9933
[263,] -5967.7406 -3814.2677
[264,] 8842.0954 -5967.7406
[265,] -8902.0869 8842.0954
[266,] -13635.5087 -8902.0869
[267,] 5479.2078 -13635.5087
[268,] -20342.1237 5479.2078
[269,] 15389.1873 -20342.1237
[270,] -4610.3288 15389.1873
[271,] -4774.3831 -4610.3288
[272,] -196.9493 -4774.3831
[273,] -10689.4305 -196.9493
[274,] -2402.0171 -10689.4305
[275,] -740.8292 -2402.0171
[276,] 19056.1846 -740.8292
[277,] -2152.8712 19056.1846
[278,] -16606.5605 -2152.8712
[279,] -13976.8508 -16606.5605
[280,] -8555.6659 -13976.8508
[281,] 60336.1890 -8555.6659
[282,] 12148.8812 60336.1890
[283,] -1470.1469 12148.8812
[284,] -6677.6713 -1470.1469
[285,] 17363.2062 -6677.6713
[286,] -10241.1893 17363.2062
[287,] -5102.2155 -10241.1893
[288,] -11012.1818 -5102.2155
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 3603.9246 10884.1044
2 10144.7069 3603.9246
3 15984.6799 10144.7069
4 -17812.6318 15984.6799
5 27195.4016 -17812.6318
6 -6854.0213 27195.4016
7 11621.4286 -6854.0213
8 -7102.5231 11621.4286
9 40566.4892 -7102.5231
10 -5915.0008 40566.4892
11 -42907.1457 -5915.0008
12 -15885.3280 -42907.1457
13 -994.8658 -15885.3280
14 -9116.2511 -994.8658
15 -16753.1362 -9116.2511
16 -35844.1234 -16753.1362
17 28251.0094 -35844.1234
18 21990.3694 28251.0094
19 29056.6938 21990.3694
20 15763.4092 29056.6938
21 -532.1701 15763.4092
22 -29976.9629 -532.1701
23 -9375.9533 -29976.9629
24 6866.0409 -9375.9533
25 -17708.2099 6866.0409
26 -3259.1425 -17708.2099
27 -9465.2513 -3259.1425
28 -32688.8612 -9465.2513
29 -23271.5084 -32688.8612
30 -45059.1044 -23271.5084
31 2630.2956 -45059.1044
32 -4486.4570 2630.2956
33 -41343.0788 -4486.4570
34 11655.6242 -41343.0788
35 -22879.1605 11655.6242
36 -17388.6517 -22879.1605
37 -18072.0531 -17388.6517
38 -38235.7471 -18072.0531
39 -832.1650 -38235.7471
40 -10101.2636 -832.1650
41 -10219.8810 -10101.2636
42 -7698.0961 -10219.8810
43 -23606.5882 -7698.0961
44 -22268.7094 -23606.5882
45 -5169.1598 -22268.7094
46 -12227.5993 -5169.1598
47 -1665.3131 -12227.5993
48 174.8986 -1665.3131
49 23253.0782 174.8986
50 24063.0271 23253.0782
51 -15240.6268 24063.0271
52 -9731.8456 -15240.6268
53 15758.7685 -9731.8456
54 -10529.0885 15758.7685
55 -22658.6507 -10529.0885
56 -4923.9647 -22658.6507
57 -3484.4018 -4923.9647
58 -336.6429 -3484.4018
59 -5028.5970 -336.6429
60 -2091.5224 -5028.5970
61 12580.7577 -2091.5224
62 14009.6386 12580.7577
63 -14530.8468 14009.6386
64 8522.9013 -14530.8468
65 -21616.3038 8522.9013
66 8095.0378 -21616.3038
67 896.1257 8095.0378
68 38429.7361 896.1257
69 -15025.1646 38429.7361
70 3647.9363 -15025.1646
71 3079.3700 3647.9363
72 -25573.5781 3079.3700
73 36259.1500 -25573.5781
74 -18025.9736 36259.1500
75 15919.9921 -18025.9736
76 11540.5823 15919.9921
77 -18441.6427 11540.5823
78 -11621.3994 -18441.6427
79 -20352.6055 -11621.3994
80 17684.0771 -20352.6055
81 -10866.9417 17684.0771
82 4579.9577 -10866.9417
83 -3867.1134 4579.9577
84 129722.0759 -3867.1134
85 -10360.7428 129722.0759
86 -5277.2346 -10360.7428
87 -10502.6416 -5277.2346
88 2305.2372 -10502.6416
89 -25619.0355 2305.2372
90 5853.5610 -25619.0355
91 18007.1460 5853.5610
92 -19630.8724 18007.1460
93 21636.1139 -19630.8724
94 -26249.7327 21636.1139
95 4127.0049 -26249.7327
96 -26097.0501 4127.0049
97 41974.7924 -26097.0501
98 -26034.1473 41974.7924
99 11591.6047 -26034.1473
100 -6172.3883 11591.6047
101 -24816.9159 -6172.3883
102 20699.6447 -24816.9159
103 38916.1008 20699.6447
104 39978.6036 38916.1008
105 41300.2892 39978.6036
106 -19560.1975 41300.2892
107 -5555.3276 -19560.1975
108 41800.1932 -5555.3276
109 12750.1770 41800.1932
110 11544.2796 12750.1770
111 -10850.1032 11544.2796
112 13096.7857 -10850.1032
113 -10720.1985 13096.7857
114 9155.7785 -10720.1985
115 -1564.1107 9155.7785
116 -10150.7316 -1564.1107
117 -18043.8821 -10150.7316
118 100471.5085 -18043.8821
119 4559.3777 100471.5085
120 -10542.5467 4559.3777
121 -8054.2280 -10542.5467
122 -13100.8883 -8054.2280
123 73537.2576 -13100.8883
124 15506.0410 73537.2576
125 -10980.3133 15506.0410
126 8522.1424 -10980.3133
127 5604.3794 8522.1424
128 8602.9682 5604.3794
129 -3918.1054 8602.9682
130 2863.4297 -3918.1054
131 -7889.2463 2863.4297
132 1719.2529 -7889.2463
133 -13126.9967 1719.2529
134 -21363.2981 -13126.9967
135 -37293.5909 -21363.2981
136 -3828.7983 -37293.5909
137 20923.3263 -3828.7983
138 28223.9810 20923.3263
139 2534.0394 28223.9810
140 -10451.7341 2534.0394
141 8782.0230 -10451.7341
142 -4806.8639 8782.0230
143 -31365.1372 -4806.8639
144 30640.1157 -31365.1372
145 2286.7618 30640.1157
146 43060.3364 2286.7618
147 44270.2322 43060.3364
148 -6629.1415 44270.2322
149 11123.7179 -6629.1415
150 -21081.3156 11123.7179
151 -10500.2500 -21081.3156
152 -2348.4077 -10500.2500
153 -26464.1072 -2348.4077
154 -25661.1269 -26464.1072
155 56867.4295 -25661.1269
156 -14210.9044 56867.4295
157 -6101.4832 -14210.9044
158 4994.6665 -6101.4832
159 13754.8161 4994.6665
160 -12711.0399 13754.8161
161 74774.0774 -12711.0399
162 7764.0253 74774.0774
163 29994.5717 7764.0253
164 -3037.9861 29994.5717
165 -27005.8627 -3037.9861
166 -21668.7311 -27005.8627
167 41592.7986 -21668.7311
168 -21741.2624 41592.7986
169 20418.4227 -21741.2624
170 14357.6630 20418.4227
171 11676.5706 14357.6630
172 3553.0585 11676.5706
173 2785.9014 3553.0585
174 39597.9346 2785.9014
175 -14266.8266 39597.9346
176 40370.0784 -14266.8266
177 -10385.3158 40370.0784
178 15398.4964 -10385.3158
179 -17165.7299 15398.4964
180 14051.1859 -17165.7299
181 15976.9125 14051.1859
182 755.9863 15976.9125
183 -2679.8724 755.9863
184 -47467.4984 -2679.8724
185 -2277.4450 -47467.4984
186 -9719.6093 -2277.4450
187 -2059.2471 -9719.6093
188 -18620.5133 -2059.2471
189 9067.9290 -18620.5133
190 30076.4486 9067.9290
191 -3437.1070 30076.4486
192 -7274.5489 -3437.1070
193 5245.6929 -7274.5489
194 -9823.4671 5245.6929
195 -7774.0758 -9823.4671
196 -10827.5837 -7774.0758
197 36418.2504 -10827.5837
198 18446.6235 36418.2504
199 12292.8377 18446.6235
200 -6575.9787 12292.8377
201 -12744.3791 -6575.9787
202 -4968.0487 -12744.3791
203 -1327.5661 -4968.0487
204 -8622.8676 -1327.5661
205 -944.1868 -8622.8676
206 -9897.6907 -944.1868
207 -11282.1887 -9897.6907
208 -12604.5441 -11282.1887
209 -31825.7352 -12604.5441
210 -12275.8133 -31825.7352
211 -5655.3211 -12275.8133
212 -3747.7262 -5655.3211
213 -14980.5822 -3747.7262
214 19429.7791 -14980.5822
215 -22576.2464 19429.7791
216 -7363.9567 -22576.2464
217 12907.9511 -7363.9567
218 -13957.6759 12907.9511
219 -15207.6293 -13957.6759
220 -11550.5218 -15207.6293
221 -5676.9874 -11550.5218
222 -14597.0699 -5676.9874
223 -6051.6276 -14597.0699
224 -11967.7188 -6051.6276
225 -14085.8092 -11967.7188
226 16266.6519 -14085.8092
227 4164.1005 16266.6519
228 -6721.1322 4164.1005
229 24535.6185 -6721.1322
230 -13594.1046 24535.6185
231 -7106.7764 -13594.1046
232 4998.6684 -7106.7764
233 -2285.8440 4998.6684
234 10181.3492 -2285.8440
235 -2088.3014 10181.3492
236 -5815.4941 -2088.3014
237 -7821.9118 -5815.4941
238 -11035.2258 -7821.9118
239 -4317.6867 -11035.2258
240 6411.7157 -4317.6867
241 -5805.6076 6411.7157
242 -9380.1283 -5805.6076
243 2369.1257 -9380.1283
244 -3717.3220 2369.1257
245 6256.0799 -3717.3220
246 4972.8964 6256.0799
247 -5958.5924 4972.8964
248 12551.7116 -5958.5924
249 20801.0069 12551.7116
250 -7493.3591 20801.0069
251 -2101.2821 -7493.3591
252 -2933.0361 -2101.2821
253 -3715.6126 -2933.0361
254 -14927.5983 -3715.6126
255 -2550.8389 -14927.5983
256 5150.1730 -2550.8389
257 2605.6596 5150.1730
258 -9830.1821 2605.6596
259 -5221.9561 -9830.1821
260 -1944.8893 -5221.9561
261 -18592.9933 -1944.8893
262 -3814.2677 -18592.9933
263 -5967.7406 -3814.2677
264 8842.0954 -5967.7406
265 -8902.0869 8842.0954
266 -13635.5087 -8902.0869
267 5479.2078 -13635.5087
268 -20342.1237 5479.2078
269 15389.1873 -20342.1237
270 -4610.3288 15389.1873
271 -4774.3831 -4610.3288
272 -196.9493 -4774.3831
273 -10689.4305 -196.9493
274 -2402.0171 -10689.4305
275 -740.8292 -2402.0171
276 19056.1846 -740.8292
277 -2152.8712 19056.1846
278 -16606.5605 -2152.8712
279 -13976.8508 -16606.5605
280 -8555.6659 -13976.8508
281 60336.1890 -8555.6659
282 12148.8812 60336.1890
283 -1470.1469 12148.8812
284 -6677.6713 -1470.1469
285 17363.2062 -6677.6713
286 -10241.1893 17363.2062
287 -5102.2155 -10241.1893
288 -11012.1818 -5102.2155
> 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/7v47d1324667123.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/88t081324667123.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9mkoo1324667123.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10t0ar1324667123.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11uz9o1324667123.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/126h371324667123.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/13ko551324667123.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/14bwm71324667123.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/150tl81324667123.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/16nmh91324667123.tab")
+ }
>
> try(system("convert tmp/10tkf1324667123.ps tmp/10tkf1324667123.png",intern=TRUE))
character(0)
> try(system("convert tmp/218cl1324667123.ps tmp/218cl1324667123.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ytph1324667123.ps tmp/3ytph1324667123.png",intern=TRUE))
character(0)
> try(system("convert tmp/4u68f1324667123.ps tmp/4u68f1324667123.png",intern=TRUE))
character(0)
> try(system("convert tmp/502ky1324667123.ps tmp/502ky1324667123.png",intern=TRUE))
character(0)
> try(system("convert tmp/6lnqh1324667123.ps tmp/6lnqh1324667123.png",intern=TRUE))
character(0)
> try(system("convert tmp/7v47d1324667123.ps tmp/7v47d1324667123.png",intern=TRUE))
character(0)
> try(system("convert tmp/88t081324667123.ps tmp/88t081324667123.png",intern=TRUE))
character(0)
> try(system("convert tmp/9mkoo1324667123.ps tmp/9mkoo1324667123.png",intern=TRUE))
character(0)
> try(system("convert tmp/10t0ar1324667123.ps tmp/10t0ar1324667123.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
7.996 0.889 8.903