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(30
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+ ,12
+ ,56613
+ ,19
+ ,15
+ ,8019
+ ,819
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+ ,37
+ ,3080
+ ,16
+ ,15
+ ,62792
+ ,35
+ ,28
+ ,30884
+ ,757
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+ ,46
+ ,10205
+ ,72
+ ,16
+ ,72535
+ ,14
+ ,17
+ ,19540
+ ,894
+ ,329
+ ,44
+ ,6095
+ ,27)
+ ,dim=c(10
+ ,289)
+ ,dimnames=list(c('compendiums_reviewed'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'blogged_computations'
+ ,'totsize'
+ ,'pageviews'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'totrevisions'
+ ,'tothyperlinks')
+ ,1:289))
> y <- array(NA,dim=c(10,289),dimnames=list(c('compendiums_reviewed','time_in_rfc','logins','blogged_computations','totsize','pageviews','compendium_views_info','compendium_views_pr','totrevisions','tothyperlinks'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
compendiums_reviewed time_in_rfc logins blogged_computations totsize
1 30 210907 56 79 112285
2 28 120982 56 58 84786
3 38 176508 54 60 83123
4 30 179321 89 108 101193
5 22 123185 40 49 38361
6 26 52746 25 0 68504
7 25 385534 92 121 119182
8 18 33170 18 1 22807
9 11 101645 63 20 17140
10 26 149061 44 43 116174
11 25 165446 33 69 57635
12 38 237213 84 78 66198
13 44 173326 88 86 71701
14 30 133131 55 44 57793
15 40 258873 60 104 80444
16 34 180083 66 63 53855
17 47 324799 154 158 97668
18 30 230964 53 102 133824
19 31 236785 119 77 101481
20 23 135473 41 82 99645
21 36 202925 61 115 114789
22 36 215147 58 101 99052
23 30 344297 75 80 67654
24 25 153935 33 50 65553
25 39 132943 40 83 97500
26 34 174724 92 123 69112
27 31 174415 100 73 82753
28 31 225548 112 81 85323
29 33 223632 73 105 72654
30 25 124817 40 47 30727
31 33 221698 45 105 77873
32 35 210767 60 94 117478
33 42 170266 62 44 74007
34 43 260561 75 114 90183
35 30 84853 31 38 61542
36 33 294424 77 107 101494
37 13 101011 34 30 27570
38 32 215641 46 71 55813
39 36 325107 99 84 79215
40 0 7176 17 0 1423
41 28 167542 66 59 55461
42 14 106408 30 33 31081
43 17 96560 76 42 22996
44 32 265769 146 96 83122
45 30 269651 67 106 70106
46 35 149112 56 56 60578
47 20 175824 107 57 39992
48 28 152871 58 59 79892
49 28 111665 34 39 49810
50 39 116408 61 34 71570
51 34 362301 119 76 100708
52 26 78800 42 20 33032
53 39 183167 66 91 82875
54 39 277965 89 115 139077
55 33 150629 44 85 71595
56 28 168809 66 76 72260
57 4 24188 24 8 5950
58 39 329267 259 79 115762
59 18 65029 17 21 32551
60 14 101097 64 30 31701
61 29 218946 41 76 80670
62 44 244052 68 101 143558
63 21 341570 168 94 117105
64 16 103597 43 27 23789
65 28 233328 132 92 120733
66 35 256462 105 123 105195
67 28 206161 71 75 73107
68 38 311473 112 128 132068
69 23 235800 94 105 149193
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78 40 182192 52 77 70054
79 23 73566 32 22 22618
80 40 194979 62 66 74011
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82 34 143756 46 105 69094
83 33 275541 63 116 93133
84 28 243199 75 88 95536
85 34 182999 88 73 225920
86 30 135649 46 99 62133
87 33 152299 53 62 61370
88 22 120221 37 53 43836
89 38 346485 90 118 106117
90 26 145790 63 30 38692
91 35 193339 78 100 84651
92 8 80953 25 49 56622
93 24 122774 45 24 15986
94 29 130585 46 67 95364
95 20 112611 41 46 26706
96 29 286468 144 57 89691
97 45 241066 82 75 67267
98 37 148446 91 135 126846
99 33 204713 71 68 41140
100 33 182079 63 124 102860
101 25 140344 53 33 51715
102 32 220516 62 98 55801
103 29 243060 63 58 111813
104 28 162765 32 68 120293
105 28 182613 39 81 138599
106 31 232138 62 131 161647
107 52 265318 117 110 115929
108 21 85574 34 37 24266
109 24 310839 92 130 162901
110 41 225060 93 93 109825
111 33 232317 54 118 129838
112 32 144966 144 39 37510
113 19 43287 14 13 43750
114 20 155754 61 74 40652
115 31 164709 109 81 87771
116 31 201940 38 109 85872
117 32 235454 73 151 89275
118 18 220801 75 51 44418
119 23 99466 50 28 192565
120 17 92661 61 40 35232
121 20 133328 55 56 40909
122 12 61361 77 27 13294
123 17 125930 75 37 32387
124 30 100750 72 83 140867
125 31 224549 50 54 120662
126 10 82316 32 27 21233
127 13 102010 53 28 44332
128 22 101523 42 59 61056
129 42 243511 71 133 101338
130 1 22938 10 12 1168
131 9 41566 35 0 13497
132 32 152474 65 106 65567
133 11 61857 25 23 25162
134 25 99923 66 44 32334
135 36 132487 41 71 40735
136 31 317394 86 116 91413
137 0 21054 16 4 855
138 24 209641 42 62 97068
139 13 22648 19 12 44339
140 8 31414 19 18 14116
141 13 46698 45 14 10288
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148 24 97839 38 25 94785
149 8 38214 34 16 8773
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152 43 172494 52 46 86687
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155 38 250579 83 130 103487
156 45 351067 95 136 213688
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158 13 98866 18 25 23517
159 28 85439 33 32 56926
160 31 229242 247 63 91721
161 40 351619 139 95 115168
162 30 84207 29 14 111194
163 16 120445 118 36 51009
164 37 324598 110 113 135777
165 30 131069 67 47 51513
166 35 204271 42 92 74163
167 32 165543 65 70 51633
168 27 141722 94 19 75345
169 20 116048 64 50 33416
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171 31 299775 95 91 98952
172 31 195838 67 111 102372
173 21 173260 63 41 37238
174 39 254488 83 120 103772
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178 18 92499 32 25 21399
179 39 224330 83 131 130115
180 14 135781 31 45 24874
181 7 74408 67 29 34988
182 17 81240 66 58 45549
183 0 14688 10 4 6023
184 30 181633 70 47 64466
185 37 271856 103 109 54990
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191 24 152601 48 46 73224
192 17 98146 40 15 27114
193 11 79619 43 42 20760
194 24 59194 31 7 37636
195 22 139942 42 54 65461
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198 13 65475 18 16 69008
199 17 99643 55 33 54968
200 15 71965 35 32 46090
201 16 77272 59 21 27507
202 24 49289 19 15 10672
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209 18 134019 53 32 28987
210 22 124064 40 43 22827
211 8 92630 40 27 18513
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213 18 52915 14 20 24006
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215 23 58981 36 0 42744
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218 13 56375 30 10 41385
219 16 65490 22 27 18653
220 16 80949 17 11 18472
221 20 76302 31 29 30976
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223 17 98104 54 55 25568
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229 14 61254 46 36 13310
230 23 74914 30 35 65892
231 17 31774 23 0 4143
232 14 81437 38 37 28579
233 15 87186 54 28 51776
234 17 50090 20 16 21152
235 21 65745 53 26 38084
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237 18 158399 39 23 32928
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239 17 73624 24 30 19499
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241 15 91899 35 18 36874
242 21 139526 151 28 48259
243 16 52164 52 32 16734
244 14 51567 30 21 28207
245 15 70551 31 23 30143
246 17 84856 29 29 41369
247 15 102538 57 50 45833
248 15 86678 40 12 29156
249 10 85709 44 21 35944
250 6 34662 25 18 36278
251 22 150580 77 27 45588
252 21 99611 35 41 45097
253 1 19349 11 13 3895
254 18 99373 63 12 28394
255 17 86230 44 21 18632
256 4 30837 19 8 2325
257 10 31706 13 26 25139
258 16 89806 42 27 27975
259 16 62088 38 13 14483
260 9 40151 29 16 13127
261 16 27634 20 2 5839
262 17 76990 27 42 24069
263 7 37460 20 5 3738
264 15 54157 19 37 18625
265 14 49862 37 17 36341
266 14 84337 26 38 24548
267 18 64175 42 37 21792
268 12 59382 49 29 26263
269 16 119308 30 32 23686
270 21 76702 49 35 49303
271 19 103425 67 17 25659
272 16 70344 28 20 28904
273 1 43410 19 7 2781
274 16 104838 49 46 29236
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pageviews compendium_views_info compendium_views_pr totrevisions
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> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time_in_rfc logins
8.971e+00 5.695e-05 1.166e-02
blogged_computations totsize pageviews
1.069e-01 7.522e-05 1.641e-03
compendium_views_info compendium_views_pr totrevisions
-1.182e-02 1.035e-02 4.819e-05
tothyperlinks
-2.172e-02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-19.8838 -3.8806 -0.8112 3.4351 20.7950
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.971e+00 8.169e-01 10.982 < 2e-16 ***
time_in_rfc 5.695e-05 1.319e-05 4.318 2.19e-05 ***
logins 1.166e-02 1.762e-02 0.662 0.5086
blogged_computations 1.069e-01 2.455e-02 4.353 1.89e-05 ***
totsize 7.522e-05 1.564e-05 4.809 2.49e-06 ***
pageviews 1.641e-03 2.277e-03 0.721 0.4717
compendium_views_info -1.182e-02 5.115e-03 -2.311 0.0216 *
compendium_views_pr 1.035e-02 9.111e-03 1.136 0.2569
totrevisions 4.819e-05 4.822e-05 0.999 0.3185
tothyperlinks -2.172e-02 1.777e-02 -1.222 0.2226
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.143 on 279 degrees of freedom
Multiple R-squared: 0.6743, Adjusted R-squared: 0.6638
F-statistic: 64.19 on 9 and 279 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,] 0.7567849 4.864303e-01 2.432151e-01
[2,] 0.6236469 7.527063e-01 3.763531e-01
[3,] 0.8757903 2.484194e-01 1.242097e-01
[4,] 0.8686233 2.627535e-01 1.313767e-01
[5,] 0.8471135 3.057730e-01 1.528865e-01
[6,] 0.8811166 2.377669e-01 1.188834e-01
[7,] 0.8345328 3.309343e-01 1.654672e-01
[8,] 0.9343493 1.313013e-01 6.565066e-02
[9,] 0.9096922 1.806156e-01 9.030781e-02
[10,] 0.8745465 2.509070e-01 1.254535e-01
[11,] 0.8302615 3.394770e-01 1.697385e-01
[12,] 0.7810448 4.379104e-01 2.189552e-01
[13,] 0.8032666 3.934669e-01 1.967334e-01
[14,] 0.7502416 4.995168e-01 2.497584e-01
[15,] 0.6975852 6.048295e-01 3.024148e-01
[16,] 0.6400333 7.199333e-01 3.599667e-01
[17,] 0.6061713 7.876573e-01 3.938287e-01
[18,] 0.5439983 9.120034e-01 4.560017e-01
[19,] 0.4827555 9.655111e-01 5.172445e-01
[20,] 0.4212286 8.424571e-01 5.787714e-01
[21,] 0.5991431 8.017138e-01 4.008569e-01
[22,] 0.6016177 7.967646e-01 3.983823e-01
[23,] 0.6138978 7.722044e-01 3.861022e-01
[24,] 0.5631547 8.736905e-01 4.368453e-01
[25,] 0.6951343 6.097313e-01 3.048657e-01
[26,] 0.7003652 5.992696e-01 2.996348e-01
[27,] 0.6516897 6.966207e-01 3.483103e-01
[28,] 0.8031390 3.937219e-01 1.968610e-01
[29,] 0.7664215 4.671570e-01 2.335785e-01
[30,] 0.7809011 4.381979e-01 2.190989e-01
[31,] 0.8173295 3.653409e-01 1.826705e-01
[32,] 0.7979824 4.040351e-01 2.020176e-01
[33,] 0.7709606 4.580788e-01 2.290394e-01
[34,] 0.8290111 3.419777e-01 1.709889e-01
[35,] 0.8272752 3.454496e-01 1.727248e-01
[36,] 0.7951911 4.096177e-01 2.048089e-01
[37,] 0.7807033 4.385934e-01 2.192967e-01
[38,] 0.9366156 1.267688e-01 6.338438e-02
[39,] 0.9322721 1.354557e-01 6.772785e-02
[40,] 0.9340435 1.319130e-01 6.595650e-02
[41,] 0.9321830 1.356340e-01 6.781702e-02
[42,] 0.9240416 1.519168e-01 7.595842e-02
[43,] 0.9210703 1.578594e-01 7.892971e-02
[44,] 0.9073633 1.852734e-01 9.263668e-02
[45,] 0.9303926 1.392149e-01 6.960744e-02
[46,] 0.9147625 1.704750e-01 8.523750e-02
[47,] 0.8983932 2.032136e-01 1.016068e-01
[48,] 0.8939330 2.121340e-01 1.060670e-01
[49,] 0.8756031 2.487938e-01 1.243969e-01
[50,] 0.8569929 2.860141e-01 1.430071e-01
[51,] 0.9720073 5.598536e-02 2.799268e-02
[52,] 0.9663023 6.739541e-02 3.369770e-02
[53,] 0.9651295 6.974093e-02 3.487047e-02
[54,] 0.9607399 7.852016e-02 3.926008e-02
[55,] 0.9527488 9.450243e-02 4.725122e-02
[56,] 0.9456848 1.086304e-01 5.431521e-02
[57,] 0.9814114 3.717710e-02 1.858855e-02
[58,] 0.9917351 1.652981e-02 8.264905e-03
[59,] 0.9906469 1.870611e-02 9.353057e-03
[60,] 0.9881735 2.365296e-02 1.182648e-02
[61,] 0.9856809 2.863815e-02 1.431907e-02
[62,] 0.9830022 3.399558e-02 1.699779e-02
[63,] 0.9843318 3.133634e-02 1.566817e-02
[64,] 0.9836342 3.273164e-02 1.636582e-02
[65,] 0.9893024 2.139528e-02 1.069764e-02
[66,] 0.9941211 1.175780e-02 5.878898e-03
[67,] 0.9944874 1.102516e-02 5.512582e-03
[68,] 0.9967104 6.579169e-03 3.289584e-03
[69,] 0.9957382 8.523534e-03 4.261767e-03
[70,] 0.9950280 9.944063e-03 4.972032e-03
[71,] 0.9943374 1.132511e-02 5.662553e-03
[72,] 0.9936866 1.262671e-02 6.313353e-03
[73,] 0.9945544 1.089118e-02 5.445588e-03
[74,] 0.9930292 1.394154e-02 6.970769e-03
[75,] 0.9938104 1.237923e-02 6.189613e-03
[76,] 0.9924171 1.516581e-02 7.582906e-03
[77,] 0.9911322 1.773568e-02 8.867842e-03
[78,] 0.9917188 1.656237e-02 8.281185e-03
[79,] 0.9897315 2.053702e-02 1.026851e-02
[80,] 0.9958888 8.222493e-03 4.111247e-03
[81,] 0.9958943 8.211369e-03 4.105685e-03
[82,] 0.9946470 1.070605e-02 5.353026e-03
[83,] 0.9934712 1.305758e-02 6.528790e-03
[84,] 0.9931838 1.363237e-02 6.816183e-03
[85,] 0.9972129 5.574178e-03 2.787089e-03
[86,] 0.9968605 6.279082e-03 3.139541e-03
[87,] 0.9968767 6.246679e-03 3.123340e-03
[88,] 0.9959521 8.095864e-03 4.047932e-03
[89,] 0.9949467 1.010665e-02 5.053324e-03
[90,] 0.9939631 1.207390e-02 6.036950e-03
[91,] 0.9925477 1.490452e-02 7.452261e-03
[92,] 0.9908397 1.832052e-02 9.160259e-03
[93,] 0.9904785 1.904293e-02 9.521467e-03
[94,] 0.9928564 1.428714e-02 7.143570e-03
[95,] 0.9979522 4.095541e-03 2.047770e-03
[96,] 0.9974490 5.101977e-03 2.550989e-03
[97,] 0.9994545 1.091034e-03 5.455168e-04
[98,] 0.9994630 1.073961e-03 5.369803e-04
[99,] 0.9994234 1.153292e-03 5.766462e-04
[100,] 0.9996969 6.062569e-04 3.031284e-04
[101,] 0.9996144 7.712896e-04 3.856448e-04
[102,] 0.9996209 7.581454e-04 3.790727e-04
[103,] 0.9995229 9.541778e-04 4.770889e-04
[104,] 0.9993739 1.252164e-03 6.260820e-04
[105,] 0.9993213 1.357408e-03 6.787041e-04
[106,] 0.9995621 8.758716e-04 4.379358e-04
[107,] 0.9997322 5.356601e-04 2.678301e-04
[108,] 0.9996925 6.149966e-04 3.074983e-04
[109,] 0.9996307 7.385590e-04 3.692795e-04
[110,] 0.9996212 7.575950e-04 3.787975e-04
[111,] 0.9996043 7.914059e-04 3.957030e-04
[112,] 0.9995124 9.751399e-04 4.875699e-04
[113,] 0.9994153 1.169320e-03 5.846601e-04
[114,] 0.9995664 8.671410e-04 4.335705e-04
[115,] 0.9996512 6.975029e-04 3.487515e-04
[116,] 0.9995729 8.542235e-04 4.271117e-04
[117,] 0.9994530 1.094099e-03 5.470496e-04
[118,] 0.9997209 5.582843e-04 2.791422e-04
[119,] 0.9996734 6.532565e-04 3.266282e-04
[120,] 0.9996388 7.224107e-04 3.612053e-04
[121,] 0.9996127 7.746642e-04 3.873321e-04
[122,] 0.9996178 7.644106e-04 3.822053e-04
[123,] 0.9998417 3.166784e-04 1.583392e-04
[124,] 0.9998164 3.672158e-04 1.836079e-04
[125,] 0.9999023 1.953977e-04 9.769883e-05
[126,] 0.9999011 1.977939e-04 9.889693e-05
[127,] 0.9998675 2.649031e-04 1.324515e-04
[128,] 0.9998453 3.093505e-04 1.546752e-04
[129,] 0.9998054 3.891481e-04 1.945740e-04
[130,] 0.9998066 3.867061e-04 1.933530e-04
[131,] 0.9997440 5.119062e-04 2.559531e-04
[132,] 0.9996478 7.044115e-04 3.522058e-04
[133,] 0.9997320 5.359253e-04 2.679626e-04
[134,] 0.9996650 6.699782e-04 3.349891e-04
[135,] 0.9998492 3.016319e-04 1.508159e-04
[136,] 0.9997976 4.047436e-04 2.023718e-04
[137,] 0.9997628 4.744320e-04 2.372160e-04
[138,] 0.9998128 3.744962e-04 1.872481e-04
[139,] 0.9998496 3.007437e-04 1.503719e-04
[140,] 0.9999830 3.401465e-05 1.700732e-05
[141,] 0.9999812 3.765118e-05 1.882559e-05
[142,] 0.9999761 4.775674e-05 2.387837e-05
[143,] 0.9999655 6.891136e-05 3.445568e-05
[144,] 0.9999809 3.815816e-05 1.907908e-05
[145,] 0.9999799 4.022111e-05 2.011055e-05
[146,] 0.9999796 4.075703e-05 2.037851e-05
[147,] 0.9999870 2.593290e-05 1.296645e-05
[148,] 0.9999814 3.723603e-05 1.861801e-05
[149,] 0.9999730 5.401564e-05 2.700782e-05
[150,] 0.9999727 5.459233e-05 2.729616e-05
[151,] 0.9999688 6.240015e-05 3.120007e-05
[152,] 0.9999548 9.036213e-05 4.518107e-05
[153,] 0.9999809 3.823915e-05 1.911957e-05
[154,] 0.9999727 5.459125e-05 2.729563e-05
[155,] 0.9999704 5.913686e-05 2.956843e-05
[156,] 0.9999673 6.548721e-05 3.274361e-05
[157,] 0.9999545 9.096067e-05 4.548033e-05
[158,] 0.9999889 2.222697e-05 1.111349e-05
[159,] 0.9999835 3.290231e-05 1.645116e-05
[160,] 0.9999762 4.762502e-05 2.381251e-05
[161,] 0.9999670 6.607060e-05 3.303530e-05
[162,] 0.9999541 9.184753e-05 4.592376e-05
[163,] 0.9999619 7.628339e-05 3.814170e-05
[164,] 0.9999523 9.543351e-05 4.771676e-05
[165,] 0.9999307 1.385385e-04 6.926923e-05
[166,] 0.9999052 1.896673e-04 9.483363e-05
[167,] 0.9998708 2.583265e-04 1.291633e-04
[168,] 0.9998929 2.141717e-04 1.070858e-04
[169,] 0.9999337 1.326543e-04 6.632717e-05
[170,] 0.9999116 1.768572e-04 8.842859e-05
[171,] 0.9999513 9.743475e-05 4.871738e-05
[172,] 0.9999533 9.335612e-05 4.667806e-05
[173,] 0.9999691 6.173022e-05 3.086511e-05
[174,] 0.9999840 3.200505e-05 1.600253e-05
[175,] 0.9999825 3.503754e-05 1.751877e-05
[176,] 0.9999915 1.709068e-05 8.545342e-06
[177,] 0.9999879 2.414340e-05 1.207170e-05
[178,] 0.9999988 2.409734e-06 1.204867e-06
[179,] 0.9999983 3.492611e-06 1.746305e-06
[180,] 0.9999976 4.773454e-06 2.386727e-06
[181,] 0.9999979 4.139093e-06 2.069547e-06
[182,] 0.9999970 6.015837e-06 3.007919e-06
[183,] 0.9999959 8.176621e-06 4.088311e-06
[184,] 0.9999964 7.229757e-06 3.614878e-06
[185,] 0.9999967 6.692146e-06 3.346073e-06
[186,] 0.9999963 7.372653e-06 3.686327e-06
[187,] 0.9999942 1.151675e-05 5.758376e-06
[188,] 0.9999917 1.662565e-05 8.312827e-06
[189,] 0.9999873 2.545442e-05 1.272721e-05
[190,] 0.9999968 6.459044e-06 3.229522e-06
[191,] 0.9999957 8.679893e-06 4.339947e-06
[192,] 0.9999935 1.296933e-05 6.484664e-06
[193,] 0.9999902 1.958118e-05 9.790591e-06
[194,] 0.9999933 1.344172e-05 6.720858e-06
[195,] 0.9999895 2.095004e-05 1.047502e-05
[196,] 0.9999870 2.607172e-05 1.303586e-05
[197,] 0.9999796 4.085521e-05 2.042760e-05
[198,] 0.9999871 2.583450e-05 1.291725e-05
[199,] 0.9999913 1.748667e-05 8.743335e-06
[200,] 0.9999868 2.645763e-05 1.322881e-05
[201,] 0.9999821 3.577184e-05 1.788592e-05
[202,] 0.9999754 4.922403e-05 2.461201e-05
[203,] 0.9999885 2.295907e-05 1.147954e-05
[204,] 0.9999954 9.154188e-06 4.577094e-06
[205,] 0.9999925 1.504953e-05 7.524765e-06
[206,] 0.9999900 1.998421e-05 9.992104e-06
[207,] 0.9999850 2.997734e-05 1.498867e-05
[208,] 0.9999784 4.324290e-05 2.162145e-05
[209,] 0.9999831 3.382067e-05 1.691034e-05
[210,] 0.9999721 5.571720e-05 2.785860e-05
[211,] 0.9999607 7.866805e-05 3.933402e-05
[212,] 0.9999403 1.194777e-04 5.973886e-05
[213,] 0.9999589 8.216737e-05 4.108369e-05
[214,] 0.9999839 3.211597e-05 1.605799e-05
[215,] 0.9999969 6.185329e-06 3.092664e-06
[216,] 0.9999946 1.080624e-05 5.403119e-06
[217,] 0.9999914 1.710096e-05 8.550478e-06
[218,] 0.9999874 2.512633e-05 1.256317e-05
[219,] 0.9999921 1.589803e-05 7.949013e-06
[220,] 0.9999897 2.062105e-05 1.031052e-05
[221,] 0.9999834 3.318498e-05 1.659249e-05
[222,] 0.9999743 5.138788e-05 2.569394e-05
[223,] 0.9999723 5.547854e-05 2.773927e-05
[224,] 0.9999683 6.333539e-05 3.166769e-05
[225,] 0.9999451 1.097573e-04 5.487865e-05
[226,] 0.9999463 1.074882e-04 5.374410e-05
[227,] 0.9999072 1.856056e-04 9.280278e-05
[228,] 0.9999221 1.558418e-04 7.792088e-05
[229,] 0.9998776 2.448431e-04 1.224216e-04
[230,] 0.9998208 3.584503e-04 1.792251e-04
[231,] 0.9997474 5.052050e-04 2.526025e-04
[232,] 0.9996395 7.209044e-04 3.604522e-04
[233,] 0.9993943 1.211402e-03 6.057011e-04
[234,] 0.9990548 1.890442e-03 9.452210e-04
[235,] 0.9994719 1.056212e-03 5.281058e-04
[236,] 0.9991513 1.697394e-03 8.486970e-04
[237,] 0.9992746 1.450700e-03 7.253501e-04
[238,] 0.9990685 1.862990e-03 9.314950e-04
[239,] 0.9988330 2.333973e-03 1.166986e-03
[240,] 0.9980275 3.944952e-03 1.972476e-03
[241,] 0.9981093 3.781427e-03 1.890713e-03
[242,] 0.9968620 6.276044e-03 3.138022e-03
[243,] 0.9969684 6.063218e-03 3.031609e-03
[244,] 0.9951696 9.660794e-03 4.830397e-03
[245,] 0.9922051 1.558989e-02 7.794947e-03
[246,] 0.9874560 2.508809e-02 1.254405e-02
[247,] 0.9865266 2.694682e-02 1.347341e-02
[248,] 0.9789572 4.208559e-02 2.104280e-02
[249,] 0.9896735 2.065305e-02 1.032652e-02
[250,] 0.9860814 2.783710e-02 1.391855e-02
[251,] 0.9777471 4.450580e-02 2.225290e-02
[252,] 0.9642091 7.158184e-02 3.579092e-02
[253,] 0.9509246 9.815079e-02 4.907539e-02
[254,] 0.9262695 1.474610e-01 7.373048e-02
[255,] 0.9172387 1.655226e-01 8.276131e-02
[256,] 0.8824980 2.350040e-01 1.175020e-01
[257,] 0.8518389 2.963222e-01 1.481611e-01
[258,] 0.9395963 1.208074e-01 6.040369e-02
[259,] 0.9302323 1.395354e-01 6.976768e-02
[260,] 0.8861444 2.277111e-01 1.138556e-01
[261,] 0.8708654 2.582692e-01 1.291346e-01
[262,] 0.8784429 2.431142e-01 1.215571e-01
[263,] 0.7814338 4.371323e-01 2.185662e-01
[264,] 0.8258849 3.482302e-01 1.741151e-01
> postscript(file="/var/wessaorg/rcomp/tmp/124yu1324121809.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/24jn21324121809.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3qb7a1324121809.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4g72w1324121809.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5tp211324121809.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
-3.88063402 2.66263623 11.39129416 -1.42404764 -0.36715938 9.53058209
7 8 9 10 11 12
-14.67842479 5.37991406 -6.04744372 0.99118504 -0.66013742 8.13112975
13 14 15 16 17 18
13.01056493 8.47506838 6.33103392 7.67576832 4.35140229 -7.76698291
19 20 21 22 23 24
-0.81116874 -4.90597413 -0.51547958 2.05676175 -3.69157718 0.31215757
25 26 27 28 29 30
9.61893013 2.94962844 4.15229843 1.17031129 -0.95213534 5.04162264
31 32 33 34 35 36
-0.49221306 1.47309243 18.12054754 4.84373642 9.05465337 -1.81255596
37 38 39 40 41 42
-6.00055862 5.35872000 0.55542835 -9.20156997 2.20221485 -5.63644564
43 44 45 46 47 48
-1.88437964 -1.15558227 -0.32853991 11.58321147 -2.59442438 2.17088767
49 50 51 52 53 54
7.18161414 20.79499791 -6.35170711 9.30870861 8.52428848 0.12434429
55 56 57 58 59 60
7.40690914 -0.04424889 -6.22217274 -1.07869643 2.29428459 -3.82229289
61 62 63 64 65 66
0.54314591 4.30426041 -19.88382612 -1.50947530 -7.77086756 -1.31175958
67 68 69 70 71 72
-2.01187039 -4.70148978 -13.30043297 13.50119051 3.93831852 2.36386154
73 74 75 76 77 78
-2.61451612 -1.39892702 7.66015539 -3.99538670 -8.05358919 11.82538418
79 80 81 82 83 84
8.66141142 11.00687301 1.96565009 4.38976966 -4.70911976 -4.99229998
85 86 87 88 89 90
-7.82649814 1.35004177 8.55561244 0.73216137 -3.86656993 7.16061642
91 92 93 94 95 96
2.51631084 -11.04978744 8.34658796 0.91296542 -0.72272432 -4.09294231
97 98 99 100 101 102
12.56411908 3.66929687 6.33903523 -1.40067007 3.78790271 3.05306215
103 104 105 106 107 108
-1.59888485 -1.84443363 -6.25852956 -9.86446852 14.12299792 2.81224208
109 110 111 112 113 114
-16.16288447 5.89303478 -3.87491615 9.72341793 4.52510857 -5.13771474
115 116 117 118 119 120
3.59607653 -1.21203649 -6.95208735 -7.87435670 -8.10665089 -2.01693863
121 122 123 124 125 126
-2.27878006 -1.84375805 -2.71623080 -1.73869382 -2.40455246 -6.98851481
127 128 129 130 131 132
-6.28270284 -1.60654525 2.58576404 -9.45045834 -2.69714498 3.24241471
133 134 135 136 137 138
-4.50937402 6.05806815 12.54102938 -5.03952896 -9.70703773 -5.02086271
139 140 141 142 143 144
-0.87593441 -3.71974923 0.44347066 -5.47796773 3.38756020 0.52358479
145 146 147 148 149 150
8.70474352 4.46115233 12.84604909 3.51255872 -3.86389809 8.84824089
151 152 153 154 155 156
6.63933626 17.52717063 -5.74110346 3.07628122 -1.64829870 -6.64250267
157 158 159 160 161 162
5.41543951 -3.90026438 8.67294648 -1.88732273 0.82305344 8.03524813
163 164 165 166 167 168
-5.19000487 -1.22081795 9.24204239 2.36538387 6.16220692 4.84206928
169 170 171 172 173 174
-2.11397900 -11.67347499 -1.42564930 -1.73281997 -0.66512370 1.49753971
175 176 177 178 179 180
5.13562513 -4.03851187 -1.20807384 1.16741638 -0.29630581 -7.00323208
181 182 183 184 185 186
-9.62981068 -4.30434614 -10.12988461 5.55323426 2.84910426 -9.58002112
187 188 189 190 191 192
-6.21487797 -8.83309226 -3.60447043 11.80927989 -1.46109484 2.15982698
193 194 195 196 197 198
-6.97804902 6.84422953 -1.12410695 -8.02118135 5.25578797 -4.10633146
199 200 201 202 203 204
-1.05647552 -2.14548045 -1.00066992 10.41336595 -5.63830854 -2.47016991
205 206 207 208 209 210
2.14459730 6.68743774 -1.53103431 -5.40082607 -1.37962034 2.66553511
211 212 213 214 215 216
-8.66688947 -3.24712632 2.73505188 -1.72376448 9.66616581 9.24913428
217 218 219 220 221 222
-1.95698471 -2.50990056 0.57373725 0.76375355 3.68807706 1.13957574
223 224 225 226 227 228
-1.71956955 0.74764443 5.56660895 -7.52396906 -10.17712289 0.92117076
229 230 231 232 233 234
-1.67417890 3.13595951 6.12254044 -4.25292030 -2.75426562 2.53615030
235 236 237 238 239 240
4.74638783 0.25835450 -1.96342413 3.43506502 1.25523856 3.19613908
241 242 243 244 245 246
-1.94067560 -1.69917380 -0.40651447 -0.82839640 -1.07740571 -0.38067889
247 248 249 250 251 252
-5.90066571 -1.23492042 -6.83350931 -7.83202606 0.49339975 0.33758461
253 254 255 256 257 258
-10.34430280 1.51248086 2.71327781 -6.54587594 -4.08539869 -1.70526966
259 260 261 262 263 264
0.89694131 -4.90894141 5.31602143 -2.56346804 -4.52803654 -1.30929271
265 266 267 268 269 270
-1.24981676 -3.82456522 1.50531983 -3.87110805 -3.34467180 2.47782689
271 272 273 274 275 276
2.05897935 -0.28671765 -10.07659020 -4.42708350 -5.66374912 1.73234964
277 278 279 280 281 282
-2.44454643 -9.29797881 -3.40847771 1.83644634 2.30649064 -6.56471148
283 284 285 286 287 288
-5.37109803 -7.67554656 1.85403191 4.00722825 -1.38379920 -1.83567688
289
1.70861636
> postscript(file="/var/wessaorg/rcomp/tmp/6pobf1324121809.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 -3.88063402 NA
1 2.66263623 -3.88063402
2 11.39129416 2.66263623
3 -1.42404764 11.39129416
4 -0.36715938 -1.42404764
5 9.53058209 -0.36715938
6 -14.67842479 9.53058209
7 5.37991406 -14.67842479
8 -6.04744372 5.37991406
9 0.99118504 -6.04744372
10 -0.66013742 0.99118504
11 8.13112975 -0.66013742
12 13.01056493 8.13112975
13 8.47506838 13.01056493
14 6.33103392 8.47506838
15 7.67576832 6.33103392
16 4.35140229 7.67576832
17 -7.76698291 4.35140229
18 -0.81116874 -7.76698291
19 -4.90597413 -0.81116874
20 -0.51547958 -4.90597413
21 2.05676175 -0.51547958
22 -3.69157718 2.05676175
23 0.31215757 -3.69157718
24 9.61893013 0.31215757
25 2.94962844 9.61893013
26 4.15229843 2.94962844
27 1.17031129 4.15229843
28 -0.95213534 1.17031129
29 5.04162264 -0.95213534
30 -0.49221306 5.04162264
31 1.47309243 -0.49221306
32 18.12054754 1.47309243
33 4.84373642 18.12054754
34 9.05465337 4.84373642
35 -1.81255596 9.05465337
36 -6.00055862 -1.81255596
37 5.35872000 -6.00055862
38 0.55542835 5.35872000
39 -9.20156997 0.55542835
40 2.20221485 -9.20156997
41 -5.63644564 2.20221485
42 -1.88437964 -5.63644564
43 -1.15558227 -1.88437964
44 -0.32853991 -1.15558227
45 11.58321147 -0.32853991
46 -2.59442438 11.58321147
47 2.17088767 -2.59442438
48 7.18161414 2.17088767
49 20.79499791 7.18161414
50 -6.35170711 20.79499791
51 9.30870861 -6.35170711
52 8.52428848 9.30870861
53 0.12434429 8.52428848
54 7.40690914 0.12434429
55 -0.04424889 7.40690914
56 -6.22217274 -0.04424889
57 -1.07869643 -6.22217274
58 2.29428459 -1.07869643
59 -3.82229289 2.29428459
60 0.54314591 -3.82229289
61 4.30426041 0.54314591
62 -19.88382612 4.30426041
63 -1.50947530 -19.88382612
64 -7.77086756 -1.50947530
65 -1.31175958 -7.77086756
66 -2.01187039 -1.31175958
67 -4.70148978 -2.01187039
68 -13.30043297 -4.70148978
69 13.50119051 -13.30043297
70 3.93831852 13.50119051
71 2.36386154 3.93831852
72 -2.61451612 2.36386154
73 -1.39892702 -2.61451612
74 7.66015539 -1.39892702
75 -3.99538670 7.66015539
76 -8.05358919 -3.99538670
77 11.82538418 -8.05358919
78 8.66141142 11.82538418
79 11.00687301 8.66141142
80 1.96565009 11.00687301
81 4.38976966 1.96565009
82 -4.70911976 4.38976966
83 -4.99229998 -4.70911976
84 -7.82649814 -4.99229998
85 1.35004177 -7.82649814
86 8.55561244 1.35004177
87 0.73216137 8.55561244
88 -3.86656993 0.73216137
89 7.16061642 -3.86656993
90 2.51631084 7.16061642
91 -11.04978744 2.51631084
92 8.34658796 -11.04978744
93 0.91296542 8.34658796
94 -0.72272432 0.91296542
95 -4.09294231 -0.72272432
96 12.56411908 -4.09294231
97 3.66929687 12.56411908
98 6.33903523 3.66929687
99 -1.40067007 6.33903523
100 3.78790271 -1.40067007
101 3.05306215 3.78790271
102 -1.59888485 3.05306215
103 -1.84443363 -1.59888485
104 -6.25852956 -1.84443363
105 -9.86446852 -6.25852956
106 14.12299792 -9.86446852
107 2.81224208 14.12299792
108 -16.16288447 2.81224208
109 5.89303478 -16.16288447
110 -3.87491615 5.89303478
111 9.72341793 -3.87491615
112 4.52510857 9.72341793
113 -5.13771474 4.52510857
114 3.59607653 -5.13771474
115 -1.21203649 3.59607653
116 -6.95208735 -1.21203649
117 -7.87435670 -6.95208735
118 -8.10665089 -7.87435670
119 -2.01693863 -8.10665089
120 -2.27878006 -2.01693863
121 -1.84375805 -2.27878006
122 -2.71623080 -1.84375805
123 -1.73869382 -2.71623080
124 -2.40455246 -1.73869382
125 -6.98851481 -2.40455246
126 -6.28270284 -6.98851481
127 -1.60654525 -6.28270284
128 2.58576404 -1.60654525
129 -9.45045834 2.58576404
130 -2.69714498 -9.45045834
131 3.24241471 -2.69714498
132 -4.50937402 3.24241471
133 6.05806815 -4.50937402
134 12.54102938 6.05806815
135 -5.03952896 12.54102938
136 -9.70703773 -5.03952896
137 -5.02086271 -9.70703773
138 -0.87593441 -5.02086271
139 -3.71974923 -0.87593441
140 0.44347066 -3.71974923
141 -5.47796773 0.44347066
142 3.38756020 -5.47796773
143 0.52358479 3.38756020
144 8.70474352 0.52358479
145 4.46115233 8.70474352
146 12.84604909 4.46115233
147 3.51255872 12.84604909
148 -3.86389809 3.51255872
149 8.84824089 -3.86389809
150 6.63933626 8.84824089
151 17.52717063 6.63933626
152 -5.74110346 17.52717063
153 3.07628122 -5.74110346
154 -1.64829870 3.07628122
155 -6.64250267 -1.64829870
156 5.41543951 -6.64250267
157 -3.90026438 5.41543951
158 8.67294648 -3.90026438
159 -1.88732273 8.67294648
160 0.82305344 -1.88732273
161 8.03524813 0.82305344
162 -5.19000487 8.03524813
163 -1.22081795 -5.19000487
164 9.24204239 -1.22081795
165 2.36538387 9.24204239
166 6.16220692 2.36538387
167 4.84206928 6.16220692
168 -2.11397900 4.84206928
169 -11.67347499 -2.11397900
170 -1.42564930 -11.67347499
171 -1.73281997 -1.42564930
172 -0.66512370 -1.73281997
173 1.49753971 -0.66512370
174 5.13562513 1.49753971
175 -4.03851187 5.13562513
176 -1.20807384 -4.03851187
177 1.16741638 -1.20807384
178 -0.29630581 1.16741638
179 -7.00323208 -0.29630581
180 -9.62981068 -7.00323208
181 -4.30434614 -9.62981068
182 -10.12988461 -4.30434614
183 5.55323426 -10.12988461
184 2.84910426 5.55323426
185 -9.58002112 2.84910426
186 -6.21487797 -9.58002112
187 -8.83309226 -6.21487797
188 -3.60447043 -8.83309226
189 11.80927989 -3.60447043
190 -1.46109484 11.80927989
191 2.15982698 -1.46109484
192 -6.97804902 2.15982698
193 6.84422953 -6.97804902
194 -1.12410695 6.84422953
195 -8.02118135 -1.12410695
196 5.25578797 -8.02118135
197 -4.10633146 5.25578797
198 -1.05647552 -4.10633146
199 -2.14548045 -1.05647552
200 -1.00066992 -2.14548045
201 10.41336595 -1.00066992
202 -5.63830854 10.41336595
203 -2.47016991 -5.63830854
204 2.14459730 -2.47016991
205 6.68743774 2.14459730
206 -1.53103431 6.68743774
207 -5.40082607 -1.53103431
208 -1.37962034 -5.40082607
209 2.66553511 -1.37962034
210 -8.66688947 2.66553511
211 -3.24712632 -8.66688947
212 2.73505188 -3.24712632
213 -1.72376448 2.73505188
214 9.66616581 -1.72376448
215 9.24913428 9.66616581
216 -1.95698471 9.24913428
217 -2.50990056 -1.95698471
218 0.57373725 -2.50990056
219 0.76375355 0.57373725
220 3.68807706 0.76375355
221 1.13957574 3.68807706
222 -1.71956955 1.13957574
223 0.74764443 -1.71956955
224 5.56660895 0.74764443
225 -7.52396906 5.56660895
226 -10.17712289 -7.52396906
227 0.92117076 -10.17712289
228 -1.67417890 0.92117076
229 3.13595951 -1.67417890
230 6.12254044 3.13595951
231 -4.25292030 6.12254044
232 -2.75426562 -4.25292030
233 2.53615030 -2.75426562
234 4.74638783 2.53615030
235 0.25835450 4.74638783
236 -1.96342413 0.25835450
237 3.43506502 -1.96342413
238 1.25523856 3.43506502
239 3.19613908 1.25523856
240 -1.94067560 3.19613908
241 -1.69917380 -1.94067560
242 -0.40651447 -1.69917380
243 -0.82839640 -0.40651447
244 -1.07740571 -0.82839640
245 -0.38067889 -1.07740571
246 -5.90066571 -0.38067889
247 -1.23492042 -5.90066571
248 -6.83350931 -1.23492042
249 -7.83202606 -6.83350931
250 0.49339975 -7.83202606
251 0.33758461 0.49339975
252 -10.34430280 0.33758461
253 1.51248086 -10.34430280
254 2.71327781 1.51248086
255 -6.54587594 2.71327781
256 -4.08539869 -6.54587594
257 -1.70526966 -4.08539869
258 0.89694131 -1.70526966
259 -4.90894141 0.89694131
260 5.31602143 -4.90894141
261 -2.56346804 5.31602143
262 -4.52803654 -2.56346804
263 -1.30929271 -4.52803654
264 -1.24981676 -1.30929271
265 -3.82456522 -1.24981676
266 1.50531983 -3.82456522
267 -3.87110805 1.50531983
268 -3.34467180 -3.87110805
269 2.47782689 -3.34467180
270 2.05897935 2.47782689
271 -0.28671765 2.05897935
272 -10.07659020 -0.28671765
273 -4.42708350 -10.07659020
274 -5.66374912 -4.42708350
275 1.73234964 -5.66374912
276 -2.44454643 1.73234964
277 -9.29797881 -2.44454643
278 -3.40847771 -9.29797881
279 1.83644634 -3.40847771
280 2.30649064 1.83644634
281 -6.56471148 2.30649064
282 -5.37109803 -6.56471148
283 -7.67554656 -5.37109803
284 1.85403191 -7.67554656
285 4.00722825 1.85403191
286 -1.38379920 4.00722825
287 -1.83567688 -1.38379920
288 1.70861636 -1.83567688
289 NA 1.70861636
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.66263623 -3.88063402
[2,] 11.39129416 2.66263623
[3,] -1.42404764 11.39129416
[4,] -0.36715938 -1.42404764
[5,] 9.53058209 -0.36715938
[6,] -14.67842479 9.53058209
[7,] 5.37991406 -14.67842479
[8,] -6.04744372 5.37991406
[9,] 0.99118504 -6.04744372
[10,] -0.66013742 0.99118504
[11,] 8.13112975 -0.66013742
[12,] 13.01056493 8.13112975
[13,] 8.47506838 13.01056493
[14,] 6.33103392 8.47506838
[15,] 7.67576832 6.33103392
[16,] 4.35140229 7.67576832
[17,] -7.76698291 4.35140229
[18,] -0.81116874 -7.76698291
[19,] -4.90597413 -0.81116874
[20,] -0.51547958 -4.90597413
[21,] 2.05676175 -0.51547958
[22,] -3.69157718 2.05676175
[23,] 0.31215757 -3.69157718
[24,] 9.61893013 0.31215757
[25,] 2.94962844 9.61893013
[26,] 4.15229843 2.94962844
[27,] 1.17031129 4.15229843
[28,] -0.95213534 1.17031129
[29,] 5.04162264 -0.95213534
[30,] -0.49221306 5.04162264
[31,] 1.47309243 -0.49221306
[32,] 18.12054754 1.47309243
[33,] 4.84373642 18.12054754
[34,] 9.05465337 4.84373642
[35,] -1.81255596 9.05465337
[36,] -6.00055862 -1.81255596
[37,] 5.35872000 -6.00055862
[38,] 0.55542835 5.35872000
[39,] -9.20156997 0.55542835
[40,] 2.20221485 -9.20156997
[41,] -5.63644564 2.20221485
[42,] -1.88437964 -5.63644564
[43,] -1.15558227 -1.88437964
[44,] -0.32853991 -1.15558227
[45,] 11.58321147 -0.32853991
[46,] -2.59442438 11.58321147
[47,] 2.17088767 -2.59442438
[48,] 7.18161414 2.17088767
[49,] 20.79499791 7.18161414
[50,] -6.35170711 20.79499791
[51,] 9.30870861 -6.35170711
[52,] 8.52428848 9.30870861
[53,] 0.12434429 8.52428848
[54,] 7.40690914 0.12434429
[55,] -0.04424889 7.40690914
[56,] -6.22217274 -0.04424889
[57,] -1.07869643 -6.22217274
[58,] 2.29428459 -1.07869643
[59,] -3.82229289 2.29428459
[60,] 0.54314591 -3.82229289
[61,] 4.30426041 0.54314591
[62,] -19.88382612 4.30426041
[63,] -1.50947530 -19.88382612
[64,] -7.77086756 -1.50947530
[65,] -1.31175958 -7.77086756
[66,] -2.01187039 -1.31175958
[67,] -4.70148978 -2.01187039
[68,] -13.30043297 -4.70148978
[69,] 13.50119051 -13.30043297
[70,] 3.93831852 13.50119051
[71,] 2.36386154 3.93831852
[72,] -2.61451612 2.36386154
[73,] -1.39892702 -2.61451612
[74,] 7.66015539 -1.39892702
[75,] -3.99538670 7.66015539
[76,] -8.05358919 -3.99538670
[77,] 11.82538418 -8.05358919
[78,] 8.66141142 11.82538418
[79,] 11.00687301 8.66141142
[80,] 1.96565009 11.00687301
[81,] 4.38976966 1.96565009
[82,] -4.70911976 4.38976966
[83,] -4.99229998 -4.70911976
[84,] -7.82649814 -4.99229998
[85,] 1.35004177 -7.82649814
[86,] 8.55561244 1.35004177
[87,] 0.73216137 8.55561244
[88,] -3.86656993 0.73216137
[89,] 7.16061642 -3.86656993
[90,] 2.51631084 7.16061642
[91,] -11.04978744 2.51631084
[92,] 8.34658796 -11.04978744
[93,] 0.91296542 8.34658796
[94,] -0.72272432 0.91296542
[95,] -4.09294231 -0.72272432
[96,] 12.56411908 -4.09294231
[97,] 3.66929687 12.56411908
[98,] 6.33903523 3.66929687
[99,] -1.40067007 6.33903523
[100,] 3.78790271 -1.40067007
[101,] 3.05306215 3.78790271
[102,] -1.59888485 3.05306215
[103,] -1.84443363 -1.59888485
[104,] -6.25852956 -1.84443363
[105,] -9.86446852 -6.25852956
[106,] 14.12299792 -9.86446852
[107,] 2.81224208 14.12299792
[108,] -16.16288447 2.81224208
[109,] 5.89303478 -16.16288447
[110,] -3.87491615 5.89303478
[111,] 9.72341793 -3.87491615
[112,] 4.52510857 9.72341793
[113,] -5.13771474 4.52510857
[114,] 3.59607653 -5.13771474
[115,] -1.21203649 3.59607653
[116,] -6.95208735 -1.21203649
[117,] -7.87435670 -6.95208735
[118,] -8.10665089 -7.87435670
[119,] -2.01693863 -8.10665089
[120,] -2.27878006 -2.01693863
[121,] -1.84375805 -2.27878006
[122,] -2.71623080 -1.84375805
[123,] -1.73869382 -2.71623080
[124,] -2.40455246 -1.73869382
[125,] -6.98851481 -2.40455246
[126,] -6.28270284 -6.98851481
[127,] -1.60654525 -6.28270284
[128,] 2.58576404 -1.60654525
[129,] -9.45045834 2.58576404
[130,] -2.69714498 -9.45045834
[131,] 3.24241471 -2.69714498
[132,] -4.50937402 3.24241471
[133,] 6.05806815 -4.50937402
[134,] 12.54102938 6.05806815
[135,] -5.03952896 12.54102938
[136,] -9.70703773 -5.03952896
[137,] -5.02086271 -9.70703773
[138,] -0.87593441 -5.02086271
[139,] -3.71974923 -0.87593441
[140,] 0.44347066 -3.71974923
[141,] -5.47796773 0.44347066
[142,] 3.38756020 -5.47796773
[143,] 0.52358479 3.38756020
[144,] 8.70474352 0.52358479
[145,] 4.46115233 8.70474352
[146,] 12.84604909 4.46115233
[147,] 3.51255872 12.84604909
[148,] -3.86389809 3.51255872
[149,] 8.84824089 -3.86389809
[150,] 6.63933626 8.84824089
[151,] 17.52717063 6.63933626
[152,] -5.74110346 17.52717063
[153,] 3.07628122 -5.74110346
[154,] -1.64829870 3.07628122
[155,] -6.64250267 -1.64829870
[156,] 5.41543951 -6.64250267
[157,] -3.90026438 5.41543951
[158,] 8.67294648 -3.90026438
[159,] -1.88732273 8.67294648
[160,] 0.82305344 -1.88732273
[161,] 8.03524813 0.82305344
[162,] -5.19000487 8.03524813
[163,] -1.22081795 -5.19000487
[164,] 9.24204239 -1.22081795
[165,] 2.36538387 9.24204239
[166,] 6.16220692 2.36538387
[167,] 4.84206928 6.16220692
[168,] -2.11397900 4.84206928
[169,] -11.67347499 -2.11397900
[170,] -1.42564930 -11.67347499
[171,] -1.73281997 -1.42564930
[172,] -0.66512370 -1.73281997
[173,] 1.49753971 -0.66512370
[174,] 5.13562513 1.49753971
[175,] -4.03851187 5.13562513
[176,] -1.20807384 -4.03851187
[177,] 1.16741638 -1.20807384
[178,] -0.29630581 1.16741638
[179,] -7.00323208 -0.29630581
[180,] -9.62981068 -7.00323208
[181,] -4.30434614 -9.62981068
[182,] -10.12988461 -4.30434614
[183,] 5.55323426 -10.12988461
[184,] 2.84910426 5.55323426
[185,] -9.58002112 2.84910426
[186,] -6.21487797 -9.58002112
[187,] -8.83309226 -6.21487797
[188,] -3.60447043 -8.83309226
[189,] 11.80927989 -3.60447043
[190,] -1.46109484 11.80927989
[191,] 2.15982698 -1.46109484
[192,] -6.97804902 2.15982698
[193,] 6.84422953 -6.97804902
[194,] -1.12410695 6.84422953
[195,] -8.02118135 -1.12410695
[196,] 5.25578797 -8.02118135
[197,] -4.10633146 5.25578797
[198,] -1.05647552 -4.10633146
[199,] -2.14548045 -1.05647552
[200,] -1.00066992 -2.14548045
[201,] 10.41336595 -1.00066992
[202,] -5.63830854 10.41336595
[203,] -2.47016991 -5.63830854
[204,] 2.14459730 -2.47016991
[205,] 6.68743774 2.14459730
[206,] -1.53103431 6.68743774
[207,] -5.40082607 -1.53103431
[208,] -1.37962034 -5.40082607
[209,] 2.66553511 -1.37962034
[210,] -8.66688947 2.66553511
[211,] -3.24712632 -8.66688947
[212,] 2.73505188 -3.24712632
[213,] -1.72376448 2.73505188
[214,] 9.66616581 -1.72376448
[215,] 9.24913428 9.66616581
[216,] -1.95698471 9.24913428
[217,] -2.50990056 -1.95698471
[218,] 0.57373725 -2.50990056
[219,] 0.76375355 0.57373725
[220,] 3.68807706 0.76375355
[221,] 1.13957574 3.68807706
[222,] -1.71956955 1.13957574
[223,] 0.74764443 -1.71956955
[224,] 5.56660895 0.74764443
[225,] -7.52396906 5.56660895
[226,] -10.17712289 -7.52396906
[227,] 0.92117076 -10.17712289
[228,] -1.67417890 0.92117076
[229,] 3.13595951 -1.67417890
[230,] 6.12254044 3.13595951
[231,] -4.25292030 6.12254044
[232,] -2.75426562 -4.25292030
[233,] 2.53615030 -2.75426562
[234,] 4.74638783 2.53615030
[235,] 0.25835450 4.74638783
[236,] -1.96342413 0.25835450
[237,] 3.43506502 -1.96342413
[238,] 1.25523856 3.43506502
[239,] 3.19613908 1.25523856
[240,] -1.94067560 3.19613908
[241,] -1.69917380 -1.94067560
[242,] -0.40651447 -1.69917380
[243,] -0.82839640 -0.40651447
[244,] -1.07740571 -0.82839640
[245,] -0.38067889 -1.07740571
[246,] -5.90066571 -0.38067889
[247,] -1.23492042 -5.90066571
[248,] -6.83350931 -1.23492042
[249,] -7.83202606 -6.83350931
[250,] 0.49339975 -7.83202606
[251,] 0.33758461 0.49339975
[252,] -10.34430280 0.33758461
[253,] 1.51248086 -10.34430280
[254,] 2.71327781 1.51248086
[255,] -6.54587594 2.71327781
[256,] -4.08539869 -6.54587594
[257,] -1.70526966 -4.08539869
[258,] 0.89694131 -1.70526966
[259,] -4.90894141 0.89694131
[260,] 5.31602143 -4.90894141
[261,] -2.56346804 5.31602143
[262,] -4.52803654 -2.56346804
[263,] -1.30929271 -4.52803654
[264,] -1.24981676 -1.30929271
[265,] -3.82456522 -1.24981676
[266,] 1.50531983 -3.82456522
[267,] -3.87110805 1.50531983
[268,] -3.34467180 -3.87110805
[269,] 2.47782689 -3.34467180
[270,] 2.05897935 2.47782689
[271,] -0.28671765 2.05897935
[272,] -10.07659020 -0.28671765
[273,] -4.42708350 -10.07659020
[274,] -5.66374912 -4.42708350
[275,] 1.73234964 -5.66374912
[276,] -2.44454643 1.73234964
[277,] -9.29797881 -2.44454643
[278,] -3.40847771 -9.29797881
[279,] 1.83644634 -3.40847771
[280,] 2.30649064 1.83644634
[281,] -6.56471148 2.30649064
[282,] -5.37109803 -6.56471148
[283,] -7.67554656 -5.37109803
[284,] 1.85403191 -7.67554656
[285,] 4.00722825 1.85403191
[286,] -1.38379920 4.00722825
[287,] -1.83567688 -1.38379920
[288,] 1.70861636 -1.83567688
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.66263623 -3.88063402
2 11.39129416 2.66263623
3 -1.42404764 11.39129416
4 -0.36715938 -1.42404764
5 9.53058209 -0.36715938
6 -14.67842479 9.53058209
7 5.37991406 -14.67842479
8 -6.04744372 5.37991406
9 0.99118504 -6.04744372
10 -0.66013742 0.99118504
11 8.13112975 -0.66013742
12 13.01056493 8.13112975
13 8.47506838 13.01056493
14 6.33103392 8.47506838
15 7.67576832 6.33103392
16 4.35140229 7.67576832
17 -7.76698291 4.35140229
18 -0.81116874 -7.76698291
19 -4.90597413 -0.81116874
20 -0.51547958 -4.90597413
21 2.05676175 -0.51547958
22 -3.69157718 2.05676175
23 0.31215757 -3.69157718
24 9.61893013 0.31215757
25 2.94962844 9.61893013
26 4.15229843 2.94962844
27 1.17031129 4.15229843
28 -0.95213534 1.17031129
29 5.04162264 -0.95213534
30 -0.49221306 5.04162264
31 1.47309243 -0.49221306
32 18.12054754 1.47309243
33 4.84373642 18.12054754
34 9.05465337 4.84373642
35 -1.81255596 9.05465337
36 -6.00055862 -1.81255596
37 5.35872000 -6.00055862
38 0.55542835 5.35872000
39 -9.20156997 0.55542835
40 2.20221485 -9.20156997
41 -5.63644564 2.20221485
42 -1.88437964 -5.63644564
43 -1.15558227 -1.88437964
44 -0.32853991 -1.15558227
45 11.58321147 -0.32853991
46 -2.59442438 11.58321147
47 2.17088767 -2.59442438
48 7.18161414 2.17088767
49 20.79499791 7.18161414
50 -6.35170711 20.79499791
51 9.30870861 -6.35170711
52 8.52428848 9.30870861
53 0.12434429 8.52428848
54 7.40690914 0.12434429
55 -0.04424889 7.40690914
56 -6.22217274 -0.04424889
57 -1.07869643 -6.22217274
58 2.29428459 -1.07869643
59 -3.82229289 2.29428459
60 0.54314591 -3.82229289
61 4.30426041 0.54314591
62 -19.88382612 4.30426041
63 -1.50947530 -19.88382612
64 -7.77086756 -1.50947530
65 -1.31175958 -7.77086756
66 -2.01187039 -1.31175958
67 -4.70148978 -2.01187039
68 -13.30043297 -4.70148978
69 13.50119051 -13.30043297
70 3.93831852 13.50119051
71 2.36386154 3.93831852
72 -2.61451612 2.36386154
73 -1.39892702 -2.61451612
74 7.66015539 -1.39892702
75 -3.99538670 7.66015539
76 -8.05358919 -3.99538670
77 11.82538418 -8.05358919
78 8.66141142 11.82538418
79 11.00687301 8.66141142
80 1.96565009 11.00687301
81 4.38976966 1.96565009
82 -4.70911976 4.38976966
83 -4.99229998 -4.70911976
84 -7.82649814 -4.99229998
85 1.35004177 -7.82649814
86 8.55561244 1.35004177
87 0.73216137 8.55561244
88 -3.86656993 0.73216137
89 7.16061642 -3.86656993
90 2.51631084 7.16061642
91 -11.04978744 2.51631084
92 8.34658796 -11.04978744
93 0.91296542 8.34658796
94 -0.72272432 0.91296542
95 -4.09294231 -0.72272432
96 12.56411908 -4.09294231
97 3.66929687 12.56411908
98 6.33903523 3.66929687
99 -1.40067007 6.33903523
100 3.78790271 -1.40067007
101 3.05306215 3.78790271
102 -1.59888485 3.05306215
103 -1.84443363 -1.59888485
104 -6.25852956 -1.84443363
105 -9.86446852 -6.25852956
106 14.12299792 -9.86446852
107 2.81224208 14.12299792
108 -16.16288447 2.81224208
109 5.89303478 -16.16288447
110 -3.87491615 5.89303478
111 9.72341793 -3.87491615
112 4.52510857 9.72341793
113 -5.13771474 4.52510857
114 3.59607653 -5.13771474
115 -1.21203649 3.59607653
116 -6.95208735 -1.21203649
117 -7.87435670 -6.95208735
118 -8.10665089 -7.87435670
119 -2.01693863 -8.10665089
120 -2.27878006 -2.01693863
121 -1.84375805 -2.27878006
122 -2.71623080 -1.84375805
123 -1.73869382 -2.71623080
124 -2.40455246 -1.73869382
125 -6.98851481 -2.40455246
126 -6.28270284 -6.98851481
127 -1.60654525 -6.28270284
128 2.58576404 -1.60654525
129 -9.45045834 2.58576404
130 -2.69714498 -9.45045834
131 3.24241471 -2.69714498
132 -4.50937402 3.24241471
133 6.05806815 -4.50937402
134 12.54102938 6.05806815
135 -5.03952896 12.54102938
136 -9.70703773 -5.03952896
137 -5.02086271 -9.70703773
138 -0.87593441 -5.02086271
139 -3.71974923 -0.87593441
140 0.44347066 -3.71974923
141 -5.47796773 0.44347066
142 3.38756020 -5.47796773
143 0.52358479 3.38756020
144 8.70474352 0.52358479
145 4.46115233 8.70474352
146 12.84604909 4.46115233
147 3.51255872 12.84604909
148 -3.86389809 3.51255872
149 8.84824089 -3.86389809
150 6.63933626 8.84824089
151 17.52717063 6.63933626
152 -5.74110346 17.52717063
153 3.07628122 -5.74110346
154 -1.64829870 3.07628122
155 -6.64250267 -1.64829870
156 5.41543951 -6.64250267
157 -3.90026438 5.41543951
158 8.67294648 -3.90026438
159 -1.88732273 8.67294648
160 0.82305344 -1.88732273
161 8.03524813 0.82305344
162 -5.19000487 8.03524813
163 -1.22081795 -5.19000487
164 9.24204239 -1.22081795
165 2.36538387 9.24204239
166 6.16220692 2.36538387
167 4.84206928 6.16220692
168 -2.11397900 4.84206928
169 -11.67347499 -2.11397900
170 -1.42564930 -11.67347499
171 -1.73281997 -1.42564930
172 -0.66512370 -1.73281997
173 1.49753971 -0.66512370
174 5.13562513 1.49753971
175 -4.03851187 5.13562513
176 -1.20807384 -4.03851187
177 1.16741638 -1.20807384
178 -0.29630581 1.16741638
179 -7.00323208 -0.29630581
180 -9.62981068 -7.00323208
181 -4.30434614 -9.62981068
182 -10.12988461 -4.30434614
183 5.55323426 -10.12988461
184 2.84910426 5.55323426
185 -9.58002112 2.84910426
186 -6.21487797 -9.58002112
187 -8.83309226 -6.21487797
188 -3.60447043 -8.83309226
189 11.80927989 -3.60447043
190 -1.46109484 11.80927989
191 2.15982698 -1.46109484
192 -6.97804902 2.15982698
193 6.84422953 -6.97804902
194 -1.12410695 6.84422953
195 -8.02118135 -1.12410695
196 5.25578797 -8.02118135
197 -4.10633146 5.25578797
198 -1.05647552 -4.10633146
199 -2.14548045 -1.05647552
200 -1.00066992 -2.14548045
201 10.41336595 -1.00066992
202 -5.63830854 10.41336595
203 -2.47016991 -5.63830854
204 2.14459730 -2.47016991
205 6.68743774 2.14459730
206 -1.53103431 6.68743774
207 -5.40082607 -1.53103431
208 -1.37962034 -5.40082607
209 2.66553511 -1.37962034
210 -8.66688947 2.66553511
211 -3.24712632 -8.66688947
212 2.73505188 -3.24712632
213 -1.72376448 2.73505188
214 9.66616581 -1.72376448
215 9.24913428 9.66616581
216 -1.95698471 9.24913428
217 -2.50990056 -1.95698471
218 0.57373725 -2.50990056
219 0.76375355 0.57373725
220 3.68807706 0.76375355
221 1.13957574 3.68807706
222 -1.71956955 1.13957574
223 0.74764443 -1.71956955
224 5.56660895 0.74764443
225 -7.52396906 5.56660895
226 -10.17712289 -7.52396906
227 0.92117076 -10.17712289
228 -1.67417890 0.92117076
229 3.13595951 -1.67417890
230 6.12254044 3.13595951
231 -4.25292030 6.12254044
232 -2.75426562 -4.25292030
233 2.53615030 -2.75426562
234 4.74638783 2.53615030
235 0.25835450 4.74638783
236 -1.96342413 0.25835450
237 3.43506502 -1.96342413
238 1.25523856 3.43506502
239 3.19613908 1.25523856
240 -1.94067560 3.19613908
241 -1.69917380 -1.94067560
242 -0.40651447 -1.69917380
243 -0.82839640 -0.40651447
244 -1.07740571 -0.82839640
245 -0.38067889 -1.07740571
246 -5.90066571 -0.38067889
247 -1.23492042 -5.90066571
248 -6.83350931 -1.23492042
249 -7.83202606 -6.83350931
250 0.49339975 -7.83202606
251 0.33758461 0.49339975
252 -10.34430280 0.33758461
253 1.51248086 -10.34430280
254 2.71327781 1.51248086
255 -6.54587594 2.71327781
256 -4.08539869 -6.54587594
257 -1.70526966 -4.08539869
258 0.89694131 -1.70526966
259 -4.90894141 0.89694131
260 5.31602143 -4.90894141
261 -2.56346804 5.31602143
262 -4.52803654 -2.56346804
263 -1.30929271 -4.52803654
264 -1.24981676 -1.30929271
265 -3.82456522 -1.24981676
266 1.50531983 -3.82456522
267 -3.87110805 1.50531983
268 -3.34467180 -3.87110805
269 2.47782689 -3.34467180
270 2.05897935 2.47782689
271 -0.28671765 2.05897935
272 -10.07659020 -0.28671765
273 -4.42708350 -10.07659020
274 -5.66374912 -4.42708350
275 1.73234964 -5.66374912
276 -2.44454643 1.73234964
277 -9.29797881 -2.44454643
278 -3.40847771 -9.29797881
279 1.83644634 -3.40847771
280 2.30649064 1.83644634
281 -6.56471148 2.30649064
282 -5.37109803 -6.56471148
283 -7.67554656 -5.37109803
284 1.85403191 -7.67554656
285 4.00722825 1.85403191
286 -1.38379920 4.00722825
287 -1.83567688 -1.38379920
288 1.70861636 -1.83567688
> 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/79v971324121809.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8ag8d1324121809.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9l77q1324121809.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10rvsi1324121809.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/116zsm1324121809.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/127vj01324121809.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/13km2a1324121809.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/14aepk1324121809.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/159zrk1324121809.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/16g0x11324121809.tab")
+ }
>
> try(system("convert tmp/124yu1324121809.ps tmp/124yu1324121809.png",intern=TRUE))
character(0)
> try(system("convert tmp/24jn21324121809.ps tmp/24jn21324121809.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qb7a1324121809.ps tmp/3qb7a1324121809.png",intern=TRUE))
character(0)
> try(system("convert tmp/4g72w1324121809.ps tmp/4g72w1324121809.png",intern=TRUE))
character(0)
> try(system("convert tmp/5tp211324121809.ps tmp/5tp211324121809.png",intern=TRUE))
character(0)
> try(system("convert tmp/6pobf1324121809.ps tmp/6pobf1324121809.png",intern=TRUE))
character(0)
> try(system("convert tmp/79v971324121809.ps tmp/79v971324121809.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ag8d1324121809.ps tmp/8ag8d1324121809.png",intern=TRUE))
character(0)
> try(system("convert tmp/9l77q1324121809.ps tmp/9l77q1324121809.png",intern=TRUE))
character(0)
> try(system("convert tmp/10rvsi1324121809.ps tmp/10rvsi1324121809.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
9.569 0.852 10.645