R version 2.12.1 (2010-12-16)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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Type 'license()' or 'licence()' for distribution details.
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(609
+ ,59
+ ,32
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+ ,1.106
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+ ,39
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+ ,338
+ ,217
+ ,213
+ ,77
+ ,35
+ ,234
+ ,110
+ ,62)
+ ,dim=c(3
+ ,310)
+ ,dimnames=list(c('dichtheid'
+ ,'huwelijken'
+ ,'echtscheidingen')
+ ,1:310))
> y <- array(NA,dim=c(3,310),dimnames=list(c('dichtheid','huwelijken','echtscheidingen'),1:310))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> 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
dichtheid huwelijken echtscheidingen t
1 609.000 59.000 32.000 1
2 985.000 2.110 1.106 2
3 1.308 59.000 15.000 3
4 2.364 65.000 51.000 4
5 617.000 36.000 30.000 5
6 2.269 134.000 94.000 6
7 2.584 109.000 46.000 7
8 960.000 92.000 62.000 8
9 304.000 88.000 33.000 9
10 2.447 33.000 19.000 10
11 375.000 21.000 15.000 11
12 1.869 61.000 33.000 12
13 1.369 101.000 57.000 13
14 298.000 75.000 50.000 14
15 712.000 37.000 16.000 15
16 866.000 83.000 58.000 16
17 1.501 46.000 19.000 17
18 3.178 64.000 38.000 18
19 1.758 61.000 28.000 19
20 419.000 21.000 14.000 20
21 734.000 49.000 45.000 21
22 1.039 158.000 84.000 22
23 542.000 93.000 42.000 23
24 1.128 47.000 18.000 24
25 835.000 44.000 35.000 25
26 1.143 82.000 42.000 26
27 948.000 52.000 25.000 27
28 215.000 69.000 48.000 28
29 309.000 84.000 42.000 29
30 550.000 59.000 18.000 30
31 1.042 42.000 34.000 31
32 280.000 37.000 24.000 32
33 636.000 79.000 51.000 33
34 443.000 76.000 45.000 34
35 501.000 144.000 101.000 35
36 449.000 178.000 84.000 36
37 730.000 380.000 206.000 37
38 461.000 87.000 45.000 38
39 683.000 56.000 34.000 39
40 1.242 54.000 35.000 40
41 552.000 36.000 14.000 41
42 468.000 75.000 45.000 42
43 495.000 89.000 65.000 43
44 518.000 51.000 28.000 44
45 558.000 7.000 2.000 45
46 883.000 78.000 49.000 46
47 321.000 79.000 39.000 47
48 230.000 31.000 22.000 48
49 335.000 158.000 72.000 49
50 288.000 30.000 21.000 50
51 454.000 115.000 76.000 51
52 337.000 31.000 20.000 52
53 337.000 57.000 45.000 53
54 387.000 62.000 34.000 54
55 551.000 47.000 27.000 55
56 370.000 41.000 37.000 56
57 272.000 69.000 35.000 57
58 188.000 47.000 26.000 58
59 569.000 37.000 13.000 59
60 254.000 154.000 59.000 60
61 273.000 49.000 25.000 61
62 268.000 48.000 22.000 62
63 190.000 44.000 33.000 63
64 299.000 45.000 29.000 64
65 507.000 37.000 30.000 65
66 332.000 150.000 117.000 66
67 152.000 27.000 17.000 67
68 222.000 35.000 25.000 68
69 241.000 100.000 47.000 69
70 727.000 63.000 47.000 70
71 272.000 398.000 230.000 71
72 869.000 127.000 69.000 72
73 433.000 88.000 32.000 73
74 361.000 797.000 4.600 74
75 511.000 212.000 122.000 75
76 629.000 147.000 105.000 76
77 609.000 206.000 113.000 77
78 797.000 109.000 67.000 78
79 108.000 386.000 270.000 79
80 971.000 219.000 126.000 80
81 240.000 86.000 43.000 81
82 227.000 534.000 254.000 82
83 911.000 204.000 144.000 83
84 811.000 133.000 112.000 84
85 147.000 676.000 412.000 85
86 504.000 303.000 179.000 86
87 335.000 95.000 75.000 87
88 592.000 226.000 119.000 88
89 1.226 124.000 101.000 89
90 486.000 96.000 71.000 90
91 1.150 67.000 30.000 91
92 528.000 7.000 3.000 92
93 418.000 122.000 72.000 93
94 674.000 34.000 22.000 94
95 550.000 26.000 24.000 95
96 122.000 99.000 76.000 96
97 782.000 118.000 98.000 97
98 487.000 25.000 6.000 98
99 613.000 34.000 20.000 99
100 1.846 45.000 23.000 100
101 1.102 39.000 23.000 101
102 512.000 37.000 21.000 102
103 515.000 55.000 36.000 103
104 1.988 43.000 29.000 104
105 2.303 48.000 35.000 105
106 1.146 59.000 40.000 106
107 792.000 44.000 30.000 107
108 1.733 57.000 29.000 108
109 2.007 17.000 3.000 109
110 286.000 102.000 62.000 110
111 701.000 31.000 29.000 111
112 416.000 47.000 30.000 112
113 454.000 144.000 96.000 113
114 557.000 72.000 37.000 114
115 161.000 69.000 40.000 115
116 322.000 32.000 27.000 116
117 238.000 22.000 13.000 117
118 632.000 39.000 24.000 118
119 250.000 13.000 11.000 119
120 396.000 23.000 20.000 120
121 168.000 52.000 39.000 121
122 463.000 39.000 26.000 122
123 612.000 27.000 27.000 123
124 193.000 48.000 23.000 124
125 251.000 117.000 74.000 125
126 237.000 40.000 27.000 126
127 688.000 30.000 14.000 127
128 158.000 28.000 16.000 128
129 549.000 42.000 15.000 129
130 284.000 47.000 24.000 130
131 1.686 34.000 14.000 131
132 299.000 99.000 73.000 132
133 355.000 26.000 12.000 133
134 413.000 45.000 25.000 134
135 643.000 80.000 40.000 135
136 454.000 23.000 10.000 136
137 666.000 37.000 18.000 137
138 175.000 31.000 16.000 138
139 195.000 41.000 27.000 139
140 447.000 17.000 14.000 140
141 235.000 74.000 36.000 141
142 196.000 68.000 29.000 142
143 369.000 569.000 255.000 143
144 418.000 52.000 29.000 144
145 210.000 39.000 15.000 145
146 1.086 55.000 36.000 146
147 843.000 49.000 28.000 147
148 121.000 145.000 95.000 148
149 253.000 62.000 25.000 149
150 282.000 43.000 21.000 150
151 440.000 31.000 10.000 151
152 368.000 97.000 55.000 152
153 57.000 35.000 26.000 153
154 599.000 19.000 12.000 154
155 137.000 15.000 15.000 155
156 109.000 130.000 89.000 156
157 172.000 38.000 26.000 157
158 215.000 48.000 18.000 158
159 219.000 40.000 20.000 159
160 53.000 71.000 40.000 160
161 193.000 49.000 27.000 161
162 268.000 19.000 7.000 162
163 265.000 28.000 20.000 163
164 167.000 50.000 33.000 164
165 416.000 20.000 12.000 165
166 180.000 32.000 24.000 166
167 86.000 119.000 86.000 167
168 149.000 29.000 21.000 168
169 96.000 68.000 62.000 169
170 698.000 94.000 53.000 170
171 341.000 25.000 22.000 171
172 442.000 87.000 52.000 172
173 670.000 135.000 67.000 173
174 912.000 17.000 18.000 174
175 936.000 13.000 7.000 175
176 1.289 49.000 37.000 176
177 425.000 37.000 21.000 177
178 984.000 140.000 71.000 178
179 819.000 16.000 20.000 179
180 799.000 38.000 28.000 180
181 381.000 23.000 16.000 181
182 196.000 63.000 37.000 182
183 517.000 75.000 45.000 183
184 1.239 474.000 360.000 184
185 278.000 43.000 35.000 185
186 305.000 52.000 26.000 186
187 246.000 97.000 54.000 187
188 1.831 102.000 54.000 188
189 254.000 89.000 55.000 189
190 294.000 8.000 7.000 190
191 534.000 116.000 87.000 191
192 263.000 60.000 28.000 192
193 659.000 44.000 21.000 193
194 1.064 36.000 21.000 194
195 385.000 53.000 31.000 195
196 328.000 17.000 1.000 196
197 306.000 149.000 86.000 197
198 960.000 10.000 6.000 198
199 239.000 89.000 68.000 199
200 274.000 57.000 47.000 200
201 318.000 51.000 33.000 201
202 377.000 40.000 21.000 202
203 455.000 28.000 16.000 203
204 194.000 10.000 8.000 204
205 171.000 45.000 19.000 205
206 287.000 35.000 19.000 206
207 421.000 41.000 33.000 207
208 200.000 109.000 72.000 208
209 262.000 299.000 217.000 209
210 219.000 44.000 31.000 210
211 61.000 18.000 10.000 211
212 444.000 138.000 91.000 212
213 497.000 152.000 87.000 213
214 363.000 142.000 73.000 214
215 121.000 94.000 57.000 215
216 480.000 9.000 4.000 216
217 583.000 86.000 43.000 217
218 1.025 42.000 32.000 218
219 1.342 55.000 39.000 219
220 402.000 48.000 48.000 220
221 583.000 297.000 239.000 221
222 362.000 42.000 24.000 222
223 594.000 40.000 23.000 223
224 505.000 40.000 23.000 224
225 364.000 30.000 25.000 225
226 439.000 126.000 75.000 226
227 567.000 35.000 25.000 227
228 562.000 44.000 19.000 228
229 385.000 36.000 28.000 229
230 558.000 253.000 127.000 230
231 792.000 36.000 35.000 231
232 594.000 18.000 17.000 232
233 378.000 47.000 25.000 233
234 668.000 26.000 18.000 234
235 326.000 38.000 22.000 235
236 642.000 28.000 15.000 236
237 492.000 69.000 51.000 237
238 621.000 44.000 30.000 238
239 245.000 58.000 31.000 239
240 158.000 37.000 27.000 240
241 667.000 24.000 14.000 241
242 183.000 34.000 24.000 242
243 241.000 66.000 62.000 243
244 89.000 48.000 28.000 244
245 912.000 50.000 25.000 245
246 559.000 355.000 210.000 246
247 238.000 81.000 36.000 247
248 388.000 106.000 81.000 248
249 569.000 64.000 39.000 249
250 665.000 70.000 36.000 250
251 441.000 68.000 38.000 251
252 397.000 137.000 88.000 252
253 1.558 29.000 19.000 253
254 219.000 76.000 71.000 254
255 354.000 74.000 47.000 255
256 484.000 57.000 38.000 256
257 708.000 40.000 28.000 257
258 631.000 181.000 130.000 258
259 159.000 85.000 73.000 259
260 318.000 49.000 22.000 260
261 227.000 84.000 52.000 261
262 309.000 46.000 31.000 262
263 580.000 100.000 58.000 263
264 360.000 40.000 37.000 264
265 205.000 86.000 56.000 265
266 211.000 57.000 33.000 266
267 460.000 86.000 67.000 267
268 287.000 21.000 14.000 268
269 174.000 75.000 59.000 269
270 436.000 30.000 11.000 270
271 729.000 64.000 34.000 271
272 298.000 85.000 44.000 272
273 250.000 110.000 79.000 273
274 212.000 35.000 18.000 274
275 149.000 47.000 47.000 275
276 183.000 157.000 75.000 276
277 250.000 50.000 23.000 277
278 141.000 1.105 664.000 278
279 238.000 22.000 19.000 279
280 500.000 86.000 35.000 280
281 308.000 29.000 20.000 281
282 473.000 38.000 39.000 282
283 580.000 79.000 57.000 283
284 336.000 24.000 21.000 284
285 857.000 34.000 23.000 285
286 387.000 55.000 20.000 286
287 705.000 36.000 37.000 287
288 346.000 39.000 18.000 288
289 451.000 31.000 16.000 289
290 353.000 30.000 16.000 290
291 546.000 40.000 26.000 291
292 442.000 57.000 30.000 292
293 737.000 31.000 11.000 293
294 144.000 139.000 63.000 294
295 252.000 104.000 68.000 295
296 715.000 28.000 14.000 296
297 285.000 44.000 26.000 297
298 663.000 23.000 16.000 298
299 268.000 17.000 8.000 299
300 300.000 6.000 5.000 300
301 402.000 20.000 14.000 301
302 368.000 24.000 15.000 302
303 344.000 27.000 14.000 303
304 523.000 181.000 100.000 304
305 219.000 65.000 35.000 305
306 313.000 155.000 86.000 306
307 592.000 73.000 39.000 307
308 263.000 338.000 217.000 308
309 213.000 77.000 35.000 309
310 234.000 110.000 62.000 310
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) huwelijken echtscheidingen t
376.88529 0.07394 -0.25925 0.04450
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-383.80 -167.65 -34.83 167.87 608.16
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 376.88529 31.12203 12.110 <2e-16 ***
huwelijken 0.07394 0.20080 0.368 0.713
echtscheidingen -0.25925 0.30118 -0.861 0.390
t 0.04450 0.15496 0.287 0.774
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 241.9 on 306 degrees of freedom
Multiple R-squared: 0.002874, Adjusted R-squared: -0.006902
F-statistic: 0.294 on 3 and 306 DF, p-value: 0.8297
> 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,] 0.8874445 0.2251110570 0.1125555285
[2,] 0.9880202 0.0239595744 0.0119797872
[3,] 0.9760556 0.0478888877 0.0239444438
[4,] 0.9977797 0.0044405618 0.0022202809
[5,] 0.9955485 0.0089029653 0.0044514826
[6,] 0.9936026 0.0127948693 0.0063974347
[7,] 0.9891894 0.0216211749 0.0108105874
[8,] 0.9841821 0.0316358127 0.0158179063
[9,] 0.9914102 0.0171796017 0.0085898009
[10,] 0.9977715 0.0044570780 0.0022285390
[11,] 0.9982128 0.0035744862 0.0017872431
[12,] 0.9981747 0.0036506940 0.0018253470
[13,] 0.9975222 0.0049555111 0.0024777555
[14,] 0.9959756 0.0080487227 0.0040243614
[15,] 0.9959588 0.0080824886 0.0040412443
[16,] 0.9951365 0.0097269899 0.0048634950
[17,] 0.9975284 0.0049432912 0.0024716456
[18,] 0.9975504 0.0048992860 0.0024496430
[19,] 0.9982504 0.0034992596 0.0017496298
[20,] 0.9980456 0.0039088014 0.0019544007
[21,] 0.9996602 0.0006795095 0.0003397548
[22,] 0.9996083 0.0007833855 0.0003916927
[23,] 0.9993898 0.0012204974 0.0006102487
[24,] 0.9993746 0.0012507423 0.0006253712
[25,] 0.9997994 0.0004011455 0.0002005728
[26,] 0.9997204 0.0005592924 0.0002796462
[27,] 0.9997321 0.0005357322 0.0002678661
[28,] 0.9995994 0.0008012688 0.0004006344
[29,] 0.9994805 0.0010389197 0.0005194599
[30,] 0.9996295 0.0007410105 0.0003705053
[31,] 0.9998699 0.0002602890 0.0001301445
[32,] 0.9998001 0.0003998399 0.0001999200
[33,] 0.9997784 0.0004432920 0.0002216460
[34,] 0.9998933 0.0002134590 0.0001067295
[35,] 0.9998590 0.0002820137 0.0001410069
[36,] 0.9997855 0.0004290644 0.0002145322
[37,] 0.9996826 0.0006348116 0.0003174058
[38,] 0.9995479 0.0009041294 0.0004520647
[39,] 0.9993897 0.0012205996 0.0006102998
[40,] 0.9996361 0.0007277818 0.0003638909
[41,] 0.9995111 0.0009778482 0.0004889241
[42,] 0.9994923 0.0010153015 0.0005076508
[43,] 0.9992706 0.0014587002 0.0007293501
[44,] 0.9991092 0.0017815049 0.0008907525
[45,] 0.9987743 0.0024513455 0.0012256728
[46,] 0.9983733 0.0032533104 0.0016266552
[47,] 0.9979724 0.0040551112 0.0020275556
[48,] 0.9972199 0.0055602701 0.0027801351
[49,] 0.9964827 0.0070346563 0.0035173281
[50,] 0.9955357 0.0089285118 0.0044642559
[51,] 0.9944686 0.0110628871 0.0055314436
[52,] 0.9939933 0.0120133436 0.0060066718
[53,] 0.9931563 0.0136873257 0.0068436629
[54,] 0.9912094 0.0175812051 0.0087906025
[55,] 0.9892572 0.0214855028 0.0107427514
[56,] 0.9868200 0.0263600539 0.0131800269
[57,] 0.9863648 0.0272703975 0.0136351987
[58,] 0.9832133 0.0335734816 0.0167867408
[59,] 0.9793015 0.0413969851 0.0206984925
[60,] 0.9770881 0.0458238596 0.0229119298
[61,] 0.9761010 0.0477980026 0.0238990013
[62,] 0.9726727 0.0546545730 0.0273272865
[63,] 0.9673722 0.0652556635 0.0326278318
[64,] 0.9713812 0.0572375363 0.0286187682
[65,] 0.9669578 0.0660843784 0.0330421892
[66,] 0.9821417 0.0357166572 0.0178583286
[67,] 0.9780956 0.0438088634 0.0219044317
[68,] 0.9776624 0.0446751931 0.0223375965
[69,] 0.9731550 0.0536899589 0.0268449795
[70,] 0.9714472 0.0571055269 0.0285527634
[71,] 0.9686394 0.0627212852 0.0313606426
[72,] 0.9758263 0.0483474770 0.0241737385
[73,] 0.9798576 0.0402848203 0.0201424101
[74,] 0.9918621 0.0162758583 0.0081379292
[75,] 0.9910082 0.0179836389 0.0089918194
[76,] 0.9898819 0.0202362907 0.0101181454
[77,] 0.9951105 0.0097789483 0.0048894742
[78,] 0.9966191 0.0067618571 0.0033809286
[79,] 0.9965012 0.0069976155 0.0034988078
[80,] 0.9957522 0.0084956081 0.0042478041
[81,] 0.9949126 0.0101748697 0.0050874348
[82,] 0.9944079 0.0111842052 0.0055921026
[83,] 0.9966527 0.0066946057 0.0033473029
[84,] 0.9958447 0.0083105076 0.0041552538
[85,] 0.9975006 0.0049987886 0.0024993943
[86,] 0.9969367 0.0061266928 0.0030633464
[87,] 0.9961011 0.0077977473 0.0038988737
[88,] 0.9962171 0.0075658259 0.0037829130
[89,] 0.9955451 0.0089097089 0.0044548544
[90,] 0.9960182 0.0079635714 0.0039817857
[91,] 0.9972889 0.0054222138 0.0027111069
[92,] 0.9966355 0.0067289063 0.0033644531
[93,] 0.9963963 0.0072073014 0.0036036507
[94,] 0.9978204 0.0043591108 0.0021795554
[95,] 0.9986350 0.0027299113 0.0013649556
[96,] 0.9983347 0.0033306329 0.0016653164
[97,] 0.9979938 0.0040123048 0.0020061524
[98,] 0.9986917 0.0026165799 0.0013082899
[99,] 0.9991210 0.0017580206 0.0008790103
[100,] 0.9993971 0.0012058519 0.0006029259
[101,] 0.9996577 0.0006845535 0.0003422768
[102,] 0.9997698 0.0004604588 0.0002302294
[103,] 0.9998433 0.0003133401 0.0001566700
[104,] 0.9997914 0.0004171876 0.0002085938
[105,] 0.9998421 0.0003158389 0.0001579194
[106,] 0.9997868 0.0004264105 0.0002132053
[107,] 0.9997252 0.0005496313 0.0002748157
[108,] 0.9996925 0.0006150222 0.0003075111
[109,] 0.9996631 0.0006737220 0.0003368610
[110,] 0.9995508 0.0008983116 0.0004491558
[111,] 0.9994426 0.0011148532 0.0005574266
[112,] 0.9994784 0.0010432771 0.0005216386
[113,] 0.9993466 0.0013067906 0.0006533953
[114,] 0.9991388 0.0017224542 0.0008612271
[115,] 0.9990432 0.0019136605 0.0009568303
[116,] 0.9988028 0.0023943778 0.0011971889
[117,] 0.9988296 0.0023408510 0.0011704255
[118,] 0.9986502 0.0026995240 0.0013497620
[119,] 0.9983277 0.0033446581 0.0016723291
[120,] 0.9979626 0.0040747200 0.0020373600
[121,] 0.9983692 0.0032615619 0.0016307810
[122,] 0.9982257 0.0035485007 0.0017742503
[123,] 0.9980453 0.0039093944 0.0019546972
[124,] 0.9975332 0.0049336182 0.0024668091
[125,] 0.9981585 0.0036830093 0.0018415046
[126,] 0.9976493 0.0047013005 0.0023506502
[127,] 0.9969739 0.0060521705 0.0030260853
[128,] 0.9961863 0.0076273000 0.0038136500
[129,] 0.9965820 0.0068359428 0.0034179714
[130,] 0.9958173 0.0083654289 0.0041827144
[131,] 0.9964495 0.0071010511 0.0035505255
[132,] 0.9960463 0.0079073933 0.0039536966
[133,] 0.9954689 0.0090621733 0.0045310866
[134,] 0.9944701 0.0110598418 0.0055299209
[135,] 0.9934037 0.0131925207 0.0065962603
[136,] 0.9924695 0.0150610771 0.0075305385
[137,] 0.9907989 0.0184021737 0.0092010868
[138,] 0.9887697 0.0224605022 0.0112302511
[139,] 0.9871001 0.0257997094 0.0128998547
[140,] 0.9897861 0.0204278644 0.0102139322
[141,] 0.9950470 0.0099060199 0.0049530100
[142,] 0.9948620 0.0102760233 0.0051380117
[143,] 0.9937547 0.0124905811 0.0062452906
[144,] 0.9923033 0.0153934140 0.0076967070
[145,] 0.9906649 0.0186702652 0.0093351326
[146,] 0.9884336 0.0231328460 0.0115664230
[147,] 0.9896108 0.0207784396 0.0103892198
[148,] 0.9897160 0.0205679902 0.0102839951
[149,] 0.9892890 0.0214220980 0.0107110490
[150,] 0.9891757 0.0216486845 0.0108243422
[151,] 0.9881410 0.0237180540 0.0118590270
[152,] 0.9863957 0.0272085277 0.0136042638
[153,] 0.9843954 0.0312091575 0.0156045788
[154,] 0.9862449 0.0275102335 0.0137551167
[155,] 0.9847539 0.0304922210 0.0152461105
[156,] 0.9820272 0.0359456344 0.0179728172
[157,] 0.9789226 0.0421547666 0.0210773833
[158,] 0.9776982 0.0446036673 0.0223018336
[159,] 0.9733464 0.0533071001 0.0266535500
[160,] 0.9716283 0.0567434212 0.0283717106
[161,] 0.9734171 0.0531657702 0.0265828851
[162,] 0.9732972 0.0534055585 0.0267027792
[163,] 0.9752840 0.0494319798 0.0247159899
[164,] 0.9793826 0.0412348795 0.0206174398
[165,] 0.9753690 0.0492619182 0.0246309591
[166,] 0.9708816 0.0582367513 0.0291183757
[167,] 0.9742073 0.0515853716 0.0257926858
[168,] 0.9887642 0.0224716074 0.0112358037
[169,] 0.9961505 0.0076989139 0.0038494570
[170,] 0.9973583 0.0052834721 0.0026417361
[171,] 0.9966392 0.0067216581 0.0033608291
[172,] 0.9993645 0.0012710795 0.0006355398
[173,] 0.9997245 0.0005509043 0.0002754521
[174,] 0.9998821 0.0002357040 0.0001178520
[175,] 0.9998367 0.0003265104 0.0001632552
[176,] 0.9998067 0.0003866184 0.0001933092
[177,] 0.9997736 0.0004527249 0.0002263625
[178,] 0.9998170 0.0003660374 0.0001830187
[179,] 0.9997564 0.0004872518 0.0002436259
[180,] 0.9996717 0.0006566394 0.0003283197
[181,] 0.9995846 0.0008308279 0.0004154140
[182,] 0.9997413 0.0005174250 0.0002587125
[183,] 0.9996719 0.0006561958 0.0003280979
[184,] 0.9995682 0.0008636863 0.0004318432
[185,] 0.9995034 0.0009932406 0.0004966203
[186,] 0.9993734 0.0012532119 0.0006266059
[187,] 0.9994720 0.0010559718 0.0005279859
[188,] 0.9996856 0.0006288740 0.0003144370
[189,] 0.9995692 0.0008616927 0.0004308464
[190,] 0.9994237 0.0011525696 0.0005762848
[191,] 0.9992418 0.0015164860 0.0007582430
[192,] 0.9998777 0.0002445093 0.0001222546
[193,] 0.9998451 0.0003098114 0.0001549057
[194,] 0.9997951 0.0004098180 0.0002049090
[195,] 0.9997200 0.0005599791 0.0002799895
[196,] 0.9996124 0.0007752192 0.0003876096
[197,] 0.9994879 0.0010242244 0.0005121122
[198,] 0.9994267 0.0011465850 0.0005732925
[199,] 0.9994076 0.0011847107 0.0005923554
[200,] 0.9992411 0.0015177167 0.0007588584
[201,] 0.9989790 0.0020420167 0.0010210084
[202,] 0.9988791 0.0022418355 0.0011209177
[203,] 0.9986213 0.0027574962 0.0013787481
[204,] 0.9984617 0.0030765954 0.0015382977
[205,] 0.9989828 0.0020344914 0.0010172457
[206,] 0.9986448 0.0027103924 0.0013551962
[207,] 0.9982689 0.0034621050 0.0017310525
[208,] 0.9977362 0.0045276685 0.0022638342
[209,] 0.9981804 0.0036391341 0.0018195670
[210,] 0.9976323 0.0047353797 0.0023676899
[211,] 0.9973032 0.0053935046 0.0026967523
[212,] 0.9987332 0.0025335765 0.0012667882
[213,] 0.9995049 0.0009902970 0.0004951485
[214,] 0.9993291 0.0013418630 0.0006709315
[215,] 0.9992531 0.0014937150 0.0007468575
[216,] 0.9990325 0.0019350865 0.0009675433
[217,] 0.9988624 0.0022752817 0.0011376408
[218,] 0.9984986 0.0030028420 0.0015014210
[219,] 0.9980560 0.0038880043 0.0019440021
[220,] 0.9973969 0.0052061946 0.0026030973
[221,] 0.9968453 0.0063093281 0.0031546640
[222,] 0.9961644 0.0076711901 0.0038355950
[223,] 0.9950038 0.0099923422 0.0049961711
[224,] 0.9941637 0.0116725766 0.0058362883
[225,] 0.9964574 0.0070851974 0.0035425987
[226,] 0.9960546 0.0078907677 0.0039453838
[227,] 0.9947680 0.0104639546 0.0052319773
[228,] 0.9952634 0.0094732898 0.0047366449
[229,] 0.9939026 0.0121948705 0.0060974352
[230,] 0.9941532 0.0116935602 0.0058467801
[231,] 0.9926967 0.0146066581 0.0073033290
[232,] 0.9929499 0.0141001599 0.0070500799
[233,] 0.9915839 0.0168322008 0.0084161004
[234,] 0.9917629 0.0164741120 0.0082370560
[235,] 0.9928904 0.0142191150 0.0071095575
[236,] 0.9925633 0.0148733813 0.0074366906
[237,] 0.9912403 0.0175194467 0.0087597233
[238,] 0.9936373 0.0127254777 0.0063627389
[239,] 0.9984570 0.0030859548 0.0015429774
[240,] 0.9985540 0.0028920221 0.0014460111
[241,] 0.9982371 0.0035258976 0.0017629488
[242,] 0.9975094 0.0049811828 0.0024905914
[243,] 0.9972904 0.0054191216 0.0027095608
[244,] 0.9980303 0.0039394977 0.0019697488
[245,] 0.9973454 0.0053091523 0.0026545762
[246,] 0.9964152 0.0071696301 0.0035848150
[247,] 0.9982761 0.0034477326 0.0017238663
[248,] 0.9978911 0.0042178353 0.0021089177
[249,] 0.9969800 0.0060400732 0.0030200366
[250,] 0.9960204 0.0079592890 0.0039796445
[251,] 0.9976134 0.0047732290 0.0023866145
[252,] 0.9988975 0.0022050443 0.0011025222
[253,] 0.9986793 0.0026414878 0.0013207439
[254,] 0.9980576 0.0038848043 0.0019424022
[255,] 0.9974233 0.0051534050 0.0025767025
[256,] 0.9963385 0.0073229618 0.0036614809
[257,] 0.9969261 0.0061477194 0.0030738597
[258,] 0.9954995 0.0090009393 0.0045004697
[259,] 0.9942708 0.0114584464 0.0057292232
[260,] 0.9932026 0.0135947678 0.0067973839
[261,] 0.9912874 0.0174252356 0.0087126178
[262,] 0.9886498 0.0227003741 0.0113501871
[263,] 0.9878027 0.0243945861 0.0121972930
[264,] 0.9828638 0.0342724224 0.0171362112
[265,] 0.9911624 0.0176752931 0.0088376465
[266,] 0.9873860 0.0252279956 0.0126139978
[267,] 0.9827153 0.0345694075 0.0172847038
[268,] 0.9812548 0.0374903425 0.0187451713
[269,] 0.9842641 0.0314717125 0.0157358562
[270,] 0.9839502 0.0320995270 0.0160497635
[271,] 0.9849439 0.0301121828 0.0150560914
[272,] 0.9824694 0.0350611845 0.0175305923
[273,] 0.9877997 0.0244005200 0.0122002600
[274,] 0.9828224 0.0343551630 0.0171775815
[275,] 0.9836139 0.0327722068 0.0163861034
[276,] 0.9794470 0.0411059466 0.0205529733
[277,] 0.9700506 0.0598988178 0.0299494089
[278,] 0.9751748 0.0496504947 0.0248252474
[279,] 0.9864196 0.0271607792 0.0135803896
[280,] 0.9788747 0.0422506919 0.0211253459
[281,] 0.9747884 0.0504231602 0.0252115801
[282,] 0.9657796 0.0684407438 0.0342203719
[283,] 0.9484820 0.1030360877 0.0515180438
[284,] 0.9349200 0.1301599106 0.0650799553
[285,] 0.9069645 0.1860709341 0.0930354671
[286,] 0.8673250 0.2653500440 0.1326750220
[287,] 0.9158968 0.1682064313 0.0841032156
[288,] 0.9318701 0.1362598687 0.0681299343
[289,] 0.9416416 0.1167167039 0.0583583520
[290,] 0.9500481 0.0999037116 0.0499518558
[291,] 0.9448607 0.1102785742 0.0551392871
[292,] 0.9672266 0.0655468822 0.0327734411
[293,] 0.9548064 0.0903871701 0.0451935850
[294,] 0.9248594 0.1502812288 0.0751406144
[295,] 0.8568212 0.2863576906 0.1431788453
[296,] 0.7456719 0.5086562778 0.2543281389
[297,] 0.5933465 0.8133069426 0.4066534713
> postscript(file="/var/www/rcomp/tmp/1mxvj1321634523.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2dcbs1321634523.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3io2l1321634523.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4kdc41321634523.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5x4471321634523.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 310
Frequency = 1
1 2 3 4 5
236.00369397 608.15643299 -376.18457224 -366.28367225 245.00786391
6 7 8 9 10
-360.42184016 -370.74685653 592.02967735 -71.23734074 -372.39755988
11 12 13 14 15
-0.03876107 -371.50540425 -368.78553953 -72.09131018 335.85943461
16 17 18 19 20
497.30217253 -374.61628101 -369.38895439 -373.22413922 43.30151540
21 22 23 24 25
364.22344032 -366.73090589 168.10325559 -375.63395246 462.82264825
26 27 28 29 30
-372.07387591 572.54960727 -155.78911910 -64.49825014 172.08376508
31 32 33 34 35
-371.51370104 -94.82300237 265.02673280 70.64855324 138.09409111
36 37 38 39 40
79.12830235 376.77623273 87.65720635 309.05313918 -372.34222292
41 42 43 44 45
174.25795400 95.36651969 126.47186462 142.64485546 179.11326128
46 47 48 49 50
511.00371206 -53.70723977 -145.60980511 -37.08233833 -87.88410850
51 52 53 54 55
86.04516832 -39.30629539 -34.79199487 11.94203500 175.19190510
56 57 58 59 60
-2.81642815 -103.44979667 -188.20083695 190.12381652 -121.64630448
61 62 63 64 65
-103.74146250 -109.48977161 -184.38673705 -76.54218098 132.26410742
66 67 68 69 70
-28.58094261 -225.45573603 -154.01775640 -134.16493804 354.52640976
71 72 73 74 75
-77.84558218 497.40867296 54.65560555 -76.91707748 146.73045332
76 77 78 79 80
265.08489772 242.75184815 425.95414034 -230.94420383 607.02738178
81 82 83 84 85
-135.70072177 -127.16909449 552.66954098 449.57886612 -176.84060560
86 87 88 89 90
147.28961316 -33.33713686 225.33905503 -362.60390718 116.41842539
91 92 93 94 95
-376.96106477 147.28115771 46.62170049 296.12151168 173.18705139
96 97 98 99 100
-246.77412475 417.48001407 105.46097871 234.38052448 -376.85357772
101 102 103 104 105
-377.19842414 133.28445982 138.79778117 -375.18617397 -373.72987173
106 107 108 109 110
-374.44847130 414.87764486 -376.65434611 -380.20770729 -87.24842520
111 112 113 114 115
324.40164863 38.43333505 86.32707536 179.31055671 -215.73436100
116 117 118 119 120
-55.41328032 -142.34787817 253.20237967 -130.28989888 17.25944856
121 122 123 124 125
-208.00358406 84.54289465 234.64495004 -186.98932886 -120.91398932
126 127 128 129 130
-141.44978343 306.87487003 -222.50324075 167.15782654 -95.92311727
131 132 133 134 135
-379.91288461 -72.15376754 -26.61484708 33.30602989 264.56234151
136 137 138 139 140
71.95498480 284.94931393 -206.17003512 -184.10218504 66.25765291
141 142 143 144 145
-144.29799474 -184.71360037 9.78788396 38.38047379 -172.33229881
146 147 148 149 150
-377.02958607 463.20955698 -248.56350964 -128.61843353 -99.29504247
151 152 153 154 155
56.69599712 -8.56234599 -322.54074264 216.96831001 -244.00266596
156 157 158 159 160
-261.36586660 -207.94055553 -167.79848047 -162.73294075 -325.88460556
161 162 163 164 165
-187.67265111 -115.68392187 -116.02362742 -212.32457569 33.40490222
166 167 168 169 170
-200.41587988 -284.81972735 -232.06080241 -277.35972356 320.34003220
171 172 173 174 175
-39.63927483 64.50937930 292.80444819 530.78176315 552.18126876
176 177 178 179 180
-377.45859163 42.94719139 607.24926014 438.15172297 418.55451811
181 182 183 184 185
-1.49186836 -184.04975759 138.09245504 -325.55163508 -101.22291598
186 187 188 189 190
-77.26615048 -132.37898924 -376.96219490 -123.61719775 -90.11647618
191 192 193 194 195
162.59342332 -119.60616331 275.71764855 -381.67131438 3.55569214
196 197 198 199 200
-58.60444130 -68.37288719 575.12041370 -135.69189977 -103.81453835
201 202 203 204 205
-63.04490320 -6.38705667 71.15949082 -190.62806514 -213.40875879
206 207 208 209 210
-96.71383821 40.42753282 -175.53420169 -90.03619005 -162.44628580
211 212 213 214 215
-324.01257488 71.06927495 121.95258828 -14.98200957 -257.62532359
216 217 218 219 220
93.87490840 201.24769815 -380.37012629 -379.24410672 24.22025046
221 222 223 224 225
236.28125946 -21.64712447 210.19701080 121.15251389 -18.63406290
226 227 228 229 230
62.18559810 183.90723453 176.64175398 2.52205291 185.09807678
231 232 233 234 235
411.24781830 209.86774917 -6.24704793 283.44647267 -58.44831996
236 237 238 239 240
256.43184140 112.68878017 238.04854934 -138.77188075 -225.30060620
241 242 243 244 245
281.24587252 -200.94552872 -135.50461158 -295.03270177 526.99716387
246 247 248 249 250
199.36192704 -146.53225969 13.24100891 186.41351017 281.14760881
251 252 253 254 255
57.76949803 21.58558625 -383.80354260 -156.40023326 -27.51887827
256 257 258 259 260
101.36037271 323.98037236 262.95372311 -216.76969093 -68.37410201
261 262 263 264 265
-154.22902065 -74.90800874 199.05442544 -21.99784418 -175.51788653
266 267 268 269 270
-173.38085300 82.24488412 -99.73371887 -205.10476099 47.73405761
271 272 273 274 275
344.13832151 -85.86643897 -126.68568353 -174.99887957 -231.41238929
276 277 278 279 280
-198.33144174 -136.94523996 -76.19426127 -148.00087007 113.37038214
281 282 283 284 285
-78.34820483 90.86759753 199.45801260 -49.85273550 470.88185273
286 287 288 289 290
-1.49317486 322.27449384 -41.91760333 63.11093111 -34.85962405
291 292 293 294 295
159.94897471 55.68447333 347.63668688 -239.91245047 -128.07272959
296 297 298 299 300
326.50277534 -101.61377376 275.30199289 -121.37286406 -89.38175568
301 302 303 304 305
13.87182477 -20.20918782 -44.73476130 145.12932565 -167.18926394
306 307 308 309 310
-66.66670113 206.16721351 -96.32511258 -174.25455258 -148.73934167
> postscript(file="/var/www/rcomp/tmp/6h2lc1321634523.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 = 310
Frequency = 1
lag(myerror, k = 1) myerror
0 236.00369397 NA
1 608.15643299 236.00369397
2 -376.18457224 608.15643299
3 -366.28367225 -376.18457224
4 245.00786391 -366.28367225
5 -360.42184016 245.00786391
6 -370.74685653 -360.42184016
7 592.02967735 -370.74685653
8 -71.23734074 592.02967735
9 -372.39755988 -71.23734074
10 -0.03876107 -372.39755988
11 -371.50540425 -0.03876107
12 -368.78553953 -371.50540425
13 -72.09131018 -368.78553953
14 335.85943461 -72.09131018
15 497.30217253 335.85943461
16 -374.61628101 497.30217253
17 -369.38895439 -374.61628101
18 -373.22413922 -369.38895439
19 43.30151540 -373.22413922
20 364.22344032 43.30151540
21 -366.73090589 364.22344032
22 168.10325559 -366.73090589
23 -375.63395246 168.10325559
24 462.82264825 -375.63395246
25 -372.07387591 462.82264825
26 572.54960727 -372.07387591
27 -155.78911910 572.54960727
28 -64.49825014 -155.78911910
29 172.08376508 -64.49825014
30 -371.51370104 172.08376508
31 -94.82300237 -371.51370104
32 265.02673280 -94.82300237
33 70.64855324 265.02673280
34 138.09409111 70.64855324
35 79.12830235 138.09409111
36 376.77623273 79.12830235
37 87.65720635 376.77623273
38 309.05313918 87.65720635
39 -372.34222292 309.05313918
40 174.25795400 -372.34222292
41 95.36651969 174.25795400
42 126.47186462 95.36651969
43 142.64485546 126.47186462
44 179.11326128 142.64485546
45 511.00371206 179.11326128
46 -53.70723977 511.00371206
47 -145.60980511 -53.70723977
48 -37.08233833 -145.60980511
49 -87.88410850 -37.08233833
50 86.04516832 -87.88410850
51 -39.30629539 86.04516832
52 -34.79199487 -39.30629539
53 11.94203500 -34.79199487
54 175.19190510 11.94203500
55 -2.81642815 175.19190510
56 -103.44979667 -2.81642815
57 -188.20083695 -103.44979667
58 190.12381652 -188.20083695
59 -121.64630448 190.12381652
60 -103.74146250 -121.64630448
61 -109.48977161 -103.74146250
62 -184.38673705 -109.48977161
63 -76.54218098 -184.38673705
64 132.26410742 -76.54218098
65 -28.58094261 132.26410742
66 -225.45573603 -28.58094261
67 -154.01775640 -225.45573603
68 -134.16493804 -154.01775640
69 354.52640976 -134.16493804
70 -77.84558218 354.52640976
71 497.40867296 -77.84558218
72 54.65560555 497.40867296
73 -76.91707748 54.65560555
74 146.73045332 -76.91707748
75 265.08489772 146.73045332
76 242.75184815 265.08489772
77 425.95414034 242.75184815
78 -230.94420383 425.95414034
79 607.02738178 -230.94420383
80 -135.70072177 607.02738178
81 -127.16909449 -135.70072177
82 552.66954098 -127.16909449
83 449.57886612 552.66954098
84 -176.84060560 449.57886612
85 147.28961316 -176.84060560
86 -33.33713686 147.28961316
87 225.33905503 -33.33713686
88 -362.60390718 225.33905503
89 116.41842539 -362.60390718
90 -376.96106477 116.41842539
91 147.28115771 -376.96106477
92 46.62170049 147.28115771
93 296.12151168 46.62170049
94 173.18705139 296.12151168
95 -246.77412475 173.18705139
96 417.48001407 -246.77412475
97 105.46097871 417.48001407
98 234.38052448 105.46097871
99 -376.85357772 234.38052448
100 -377.19842414 -376.85357772
101 133.28445982 -377.19842414
102 138.79778117 133.28445982
103 -375.18617397 138.79778117
104 -373.72987173 -375.18617397
105 -374.44847130 -373.72987173
106 414.87764486 -374.44847130
107 -376.65434611 414.87764486
108 -380.20770729 -376.65434611
109 -87.24842520 -380.20770729
110 324.40164863 -87.24842520
111 38.43333505 324.40164863
112 86.32707536 38.43333505
113 179.31055671 86.32707536
114 -215.73436100 179.31055671
115 -55.41328032 -215.73436100
116 -142.34787817 -55.41328032
117 253.20237967 -142.34787817
118 -130.28989888 253.20237967
119 17.25944856 -130.28989888
120 -208.00358406 17.25944856
121 84.54289465 -208.00358406
122 234.64495004 84.54289465
123 -186.98932886 234.64495004
124 -120.91398932 -186.98932886
125 -141.44978343 -120.91398932
126 306.87487003 -141.44978343
127 -222.50324075 306.87487003
128 167.15782654 -222.50324075
129 -95.92311727 167.15782654
130 -379.91288461 -95.92311727
131 -72.15376754 -379.91288461
132 -26.61484708 -72.15376754
133 33.30602989 -26.61484708
134 264.56234151 33.30602989
135 71.95498480 264.56234151
136 284.94931393 71.95498480
137 -206.17003512 284.94931393
138 -184.10218504 -206.17003512
139 66.25765291 -184.10218504
140 -144.29799474 66.25765291
141 -184.71360037 -144.29799474
142 9.78788396 -184.71360037
143 38.38047379 9.78788396
144 -172.33229881 38.38047379
145 -377.02958607 -172.33229881
146 463.20955698 -377.02958607
147 -248.56350964 463.20955698
148 -128.61843353 -248.56350964
149 -99.29504247 -128.61843353
150 56.69599712 -99.29504247
151 -8.56234599 56.69599712
152 -322.54074264 -8.56234599
153 216.96831001 -322.54074264
154 -244.00266596 216.96831001
155 -261.36586660 -244.00266596
156 -207.94055553 -261.36586660
157 -167.79848047 -207.94055553
158 -162.73294075 -167.79848047
159 -325.88460556 -162.73294075
160 -187.67265111 -325.88460556
161 -115.68392187 -187.67265111
162 -116.02362742 -115.68392187
163 -212.32457569 -116.02362742
164 33.40490222 -212.32457569
165 -200.41587988 33.40490222
166 -284.81972735 -200.41587988
167 -232.06080241 -284.81972735
168 -277.35972356 -232.06080241
169 320.34003220 -277.35972356
170 -39.63927483 320.34003220
171 64.50937930 -39.63927483
172 292.80444819 64.50937930
173 530.78176315 292.80444819
174 552.18126876 530.78176315
175 -377.45859163 552.18126876
176 42.94719139 -377.45859163
177 607.24926014 42.94719139
178 438.15172297 607.24926014
179 418.55451811 438.15172297
180 -1.49186836 418.55451811
181 -184.04975759 -1.49186836
182 138.09245504 -184.04975759
183 -325.55163508 138.09245504
184 -101.22291598 -325.55163508
185 -77.26615048 -101.22291598
186 -132.37898924 -77.26615048
187 -376.96219490 -132.37898924
188 -123.61719775 -376.96219490
189 -90.11647618 -123.61719775
190 162.59342332 -90.11647618
191 -119.60616331 162.59342332
192 275.71764855 -119.60616331
193 -381.67131438 275.71764855
194 3.55569214 -381.67131438
195 -58.60444130 3.55569214
196 -68.37288719 -58.60444130
197 575.12041370 -68.37288719
198 -135.69189977 575.12041370
199 -103.81453835 -135.69189977
200 -63.04490320 -103.81453835
201 -6.38705667 -63.04490320
202 71.15949082 -6.38705667
203 -190.62806514 71.15949082
204 -213.40875879 -190.62806514
205 -96.71383821 -213.40875879
206 40.42753282 -96.71383821
207 -175.53420169 40.42753282
208 -90.03619005 -175.53420169
209 -162.44628580 -90.03619005
210 -324.01257488 -162.44628580
211 71.06927495 -324.01257488
212 121.95258828 71.06927495
213 -14.98200957 121.95258828
214 -257.62532359 -14.98200957
215 93.87490840 -257.62532359
216 201.24769815 93.87490840
217 -380.37012629 201.24769815
218 -379.24410672 -380.37012629
219 24.22025046 -379.24410672
220 236.28125946 24.22025046
221 -21.64712447 236.28125946
222 210.19701080 -21.64712447
223 121.15251389 210.19701080
224 -18.63406290 121.15251389
225 62.18559810 -18.63406290
226 183.90723453 62.18559810
227 176.64175398 183.90723453
228 2.52205291 176.64175398
229 185.09807678 2.52205291
230 411.24781830 185.09807678
231 209.86774917 411.24781830
232 -6.24704793 209.86774917
233 283.44647267 -6.24704793
234 -58.44831996 283.44647267
235 256.43184140 -58.44831996
236 112.68878017 256.43184140
237 238.04854934 112.68878017
238 -138.77188075 238.04854934
239 -225.30060620 -138.77188075
240 281.24587252 -225.30060620
241 -200.94552872 281.24587252
242 -135.50461158 -200.94552872
243 -295.03270177 -135.50461158
244 526.99716387 -295.03270177
245 199.36192704 526.99716387
246 -146.53225969 199.36192704
247 13.24100891 -146.53225969
248 186.41351017 13.24100891
249 281.14760881 186.41351017
250 57.76949803 281.14760881
251 21.58558625 57.76949803
252 -383.80354260 21.58558625
253 -156.40023326 -383.80354260
254 -27.51887827 -156.40023326
255 101.36037271 -27.51887827
256 323.98037236 101.36037271
257 262.95372311 323.98037236
258 -216.76969093 262.95372311
259 -68.37410201 -216.76969093
260 -154.22902065 -68.37410201
261 -74.90800874 -154.22902065
262 199.05442544 -74.90800874
263 -21.99784418 199.05442544
264 -175.51788653 -21.99784418
265 -173.38085300 -175.51788653
266 82.24488412 -173.38085300
267 -99.73371887 82.24488412
268 -205.10476099 -99.73371887
269 47.73405761 -205.10476099
270 344.13832151 47.73405761
271 -85.86643897 344.13832151
272 -126.68568353 -85.86643897
273 -174.99887957 -126.68568353
274 -231.41238929 -174.99887957
275 -198.33144174 -231.41238929
276 -136.94523996 -198.33144174
277 -76.19426127 -136.94523996
278 -148.00087007 -76.19426127
279 113.37038214 -148.00087007
280 -78.34820483 113.37038214
281 90.86759753 -78.34820483
282 199.45801260 90.86759753
283 -49.85273550 199.45801260
284 470.88185273 -49.85273550
285 -1.49317486 470.88185273
286 322.27449384 -1.49317486
287 -41.91760333 322.27449384
288 63.11093111 -41.91760333
289 -34.85962405 63.11093111
290 159.94897471 -34.85962405
291 55.68447333 159.94897471
292 347.63668688 55.68447333
293 -239.91245047 347.63668688
294 -128.07272959 -239.91245047
295 326.50277534 -128.07272959
296 -101.61377376 326.50277534
297 275.30199289 -101.61377376
298 -121.37286406 275.30199289
299 -89.38175568 -121.37286406
300 13.87182477 -89.38175568
301 -20.20918782 13.87182477
302 -44.73476130 -20.20918782
303 145.12932565 -44.73476130
304 -167.18926394 145.12932565
305 -66.66670113 -167.18926394
306 206.16721351 -66.66670113
307 -96.32511258 206.16721351
308 -174.25455258 -96.32511258
309 -148.73934167 -174.25455258
310 NA -148.73934167
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 608.15643299 236.00369397
[2,] -376.18457224 608.15643299
[3,] -366.28367225 -376.18457224
[4,] 245.00786391 -366.28367225
[5,] -360.42184016 245.00786391
[6,] -370.74685653 -360.42184016
[7,] 592.02967735 -370.74685653
[8,] -71.23734074 592.02967735
[9,] -372.39755988 -71.23734074
[10,] -0.03876107 -372.39755988
[11,] -371.50540425 -0.03876107
[12,] -368.78553953 -371.50540425
[13,] -72.09131018 -368.78553953
[14,] 335.85943461 -72.09131018
[15,] 497.30217253 335.85943461
[16,] -374.61628101 497.30217253
[17,] -369.38895439 -374.61628101
[18,] -373.22413922 -369.38895439
[19,] 43.30151540 -373.22413922
[20,] 364.22344032 43.30151540
[21,] -366.73090589 364.22344032
[22,] 168.10325559 -366.73090589
[23,] -375.63395246 168.10325559
[24,] 462.82264825 -375.63395246
[25,] -372.07387591 462.82264825
[26,] 572.54960727 -372.07387591
[27,] -155.78911910 572.54960727
[28,] -64.49825014 -155.78911910
[29,] 172.08376508 -64.49825014
[30,] -371.51370104 172.08376508
[31,] -94.82300237 -371.51370104
[32,] 265.02673280 -94.82300237
[33,] 70.64855324 265.02673280
[34,] 138.09409111 70.64855324
[35,] 79.12830235 138.09409111
[36,] 376.77623273 79.12830235
[37,] 87.65720635 376.77623273
[38,] 309.05313918 87.65720635
[39,] -372.34222292 309.05313918
[40,] 174.25795400 -372.34222292
[41,] 95.36651969 174.25795400
[42,] 126.47186462 95.36651969
[43,] 142.64485546 126.47186462
[44,] 179.11326128 142.64485546
[45,] 511.00371206 179.11326128
[46,] -53.70723977 511.00371206
[47,] -145.60980511 -53.70723977
[48,] -37.08233833 -145.60980511
[49,] -87.88410850 -37.08233833
[50,] 86.04516832 -87.88410850
[51,] -39.30629539 86.04516832
[52,] -34.79199487 -39.30629539
[53,] 11.94203500 -34.79199487
[54,] 175.19190510 11.94203500
[55,] -2.81642815 175.19190510
[56,] -103.44979667 -2.81642815
[57,] -188.20083695 -103.44979667
[58,] 190.12381652 -188.20083695
[59,] -121.64630448 190.12381652
[60,] -103.74146250 -121.64630448
[61,] -109.48977161 -103.74146250
[62,] -184.38673705 -109.48977161
[63,] -76.54218098 -184.38673705
[64,] 132.26410742 -76.54218098
[65,] -28.58094261 132.26410742
[66,] -225.45573603 -28.58094261
[67,] -154.01775640 -225.45573603
[68,] -134.16493804 -154.01775640
[69,] 354.52640976 -134.16493804
[70,] -77.84558218 354.52640976
[71,] 497.40867296 -77.84558218
[72,] 54.65560555 497.40867296
[73,] -76.91707748 54.65560555
[74,] 146.73045332 -76.91707748
[75,] 265.08489772 146.73045332
[76,] 242.75184815 265.08489772
[77,] 425.95414034 242.75184815
[78,] -230.94420383 425.95414034
[79,] 607.02738178 -230.94420383
[80,] -135.70072177 607.02738178
[81,] -127.16909449 -135.70072177
[82,] 552.66954098 -127.16909449
[83,] 449.57886612 552.66954098
[84,] -176.84060560 449.57886612
[85,] 147.28961316 -176.84060560
[86,] -33.33713686 147.28961316
[87,] 225.33905503 -33.33713686
[88,] -362.60390718 225.33905503
[89,] 116.41842539 -362.60390718
[90,] -376.96106477 116.41842539
[91,] 147.28115771 -376.96106477
[92,] 46.62170049 147.28115771
[93,] 296.12151168 46.62170049
[94,] 173.18705139 296.12151168
[95,] -246.77412475 173.18705139
[96,] 417.48001407 -246.77412475
[97,] 105.46097871 417.48001407
[98,] 234.38052448 105.46097871
[99,] -376.85357772 234.38052448
[100,] -377.19842414 -376.85357772
[101,] 133.28445982 -377.19842414
[102,] 138.79778117 133.28445982
[103,] -375.18617397 138.79778117
[104,] -373.72987173 -375.18617397
[105,] -374.44847130 -373.72987173
[106,] 414.87764486 -374.44847130
[107,] -376.65434611 414.87764486
[108,] -380.20770729 -376.65434611
[109,] -87.24842520 -380.20770729
[110,] 324.40164863 -87.24842520
[111,] 38.43333505 324.40164863
[112,] 86.32707536 38.43333505
[113,] 179.31055671 86.32707536
[114,] -215.73436100 179.31055671
[115,] -55.41328032 -215.73436100
[116,] -142.34787817 -55.41328032
[117,] 253.20237967 -142.34787817
[118,] -130.28989888 253.20237967
[119,] 17.25944856 -130.28989888
[120,] -208.00358406 17.25944856
[121,] 84.54289465 -208.00358406
[122,] 234.64495004 84.54289465
[123,] -186.98932886 234.64495004
[124,] -120.91398932 -186.98932886
[125,] -141.44978343 -120.91398932
[126,] 306.87487003 -141.44978343
[127,] -222.50324075 306.87487003
[128,] 167.15782654 -222.50324075
[129,] -95.92311727 167.15782654
[130,] -379.91288461 -95.92311727
[131,] -72.15376754 -379.91288461
[132,] -26.61484708 -72.15376754
[133,] 33.30602989 -26.61484708
[134,] 264.56234151 33.30602989
[135,] 71.95498480 264.56234151
[136,] 284.94931393 71.95498480
[137,] -206.17003512 284.94931393
[138,] -184.10218504 -206.17003512
[139,] 66.25765291 -184.10218504
[140,] -144.29799474 66.25765291
[141,] -184.71360037 -144.29799474
[142,] 9.78788396 -184.71360037
[143,] 38.38047379 9.78788396
[144,] -172.33229881 38.38047379
[145,] -377.02958607 -172.33229881
[146,] 463.20955698 -377.02958607
[147,] -248.56350964 463.20955698
[148,] -128.61843353 -248.56350964
[149,] -99.29504247 -128.61843353
[150,] 56.69599712 -99.29504247
[151,] -8.56234599 56.69599712
[152,] -322.54074264 -8.56234599
[153,] 216.96831001 -322.54074264
[154,] -244.00266596 216.96831001
[155,] -261.36586660 -244.00266596
[156,] -207.94055553 -261.36586660
[157,] -167.79848047 -207.94055553
[158,] -162.73294075 -167.79848047
[159,] -325.88460556 -162.73294075
[160,] -187.67265111 -325.88460556
[161,] -115.68392187 -187.67265111
[162,] -116.02362742 -115.68392187
[163,] -212.32457569 -116.02362742
[164,] 33.40490222 -212.32457569
[165,] -200.41587988 33.40490222
[166,] -284.81972735 -200.41587988
[167,] -232.06080241 -284.81972735
[168,] -277.35972356 -232.06080241
[169,] 320.34003220 -277.35972356
[170,] -39.63927483 320.34003220
[171,] 64.50937930 -39.63927483
[172,] 292.80444819 64.50937930
[173,] 530.78176315 292.80444819
[174,] 552.18126876 530.78176315
[175,] -377.45859163 552.18126876
[176,] 42.94719139 -377.45859163
[177,] 607.24926014 42.94719139
[178,] 438.15172297 607.24926014
[179,] 418.55451811 438.15172297
[180,] -1.49186836 418.55451811
[181,] -184.04975759 -1.49186836
[182,] 138.09245504 -184.04975759
[183,] -325.55163508 138.09245504
[184,] -101.22291598 -325.55163508
[185,] -77.26615048 -101.22291598
[186,] -132.37898924 -77.26615048
[187,] -376.96219490 -132.37898924
[188,] -123.61719775 -376.96219490
[189,] -90.11647618 -123.61719775
[190,] 162.59342332 -90.11647618
[191,] -119.60616331 162.59342332
[192,] 275.71764855 -119.60616331
[193,] -381.67131438 275.71764855
[194,] 3.55569214 -381.67131438
[195,] -58.60444130 3.55569214
[196,] -68.37288719 -58.60444130
[197,] 575.12041370 -68.37288719
[198,] -135.69189977 575.12041370
[199,] -103.81453835 -135.69189977
[200,] -63.04490320 -103.81453835
[201,] -6.38705667 -63.04490320
[202,] 71.15949082 -6.38705667
[203,] -190.62806514 71.15949082
[204,] -213.40875879 -190.62806514
[205,] -96.71383821 -213.40875879
[206,] 40.42753282 -96.71383821
[207,] -175.53420169 40.42753282
[208,] -90.03619005 -175.53420169
[209,] -162.44628580 -90.03619005
[210,] -324.01257488 -162.44628580
[211,] 71.06927495 -324.01257488
[212,] 121.95258828 71.06927495
[213,] -14.98200957 121.95258828
[214,] -257.62532359 -14.98200957
[215,] 93.87490840 -257.62532359
[216,] 201.24769815 93.87490840
[217,] -380.37012629 201.24769815
[218,] -379.24410672 -380.37012629
[219,] 24.22025046 -379.24410672
[220,] 236.28125946 24.22025046
[221,] -21.64712447 236.28125946
[222,] 210.19701080 -21.64712447
[223,] 121.15251389 210.19701080
[224,] -18.63406290 121.15251389
[225,] 62.18559810 -18.63406290
[226,] 183.90723453 62.18559810
[227,] 176.64175398 183.90723453
[228,] 2.52205291 176.64175398
[229,] 185.09807678 2.52205291
[230,] 411.24781830 185.09807678
[231,] 209.86774917 411.24781830
[232,] -6.24704793 209.86774917
[233,] 283.44647267 -6.24704793
[234,] -58.44831996 283.44647267
[235,] 256.43184140 -58.44831996
[236,] 112.68878017 256.43184140
[237,] 238.04854934 112.68878017
[238,] -138.77188075 238.04854934
[239,] -225.30060620 -138.77188075
[240,] 281.24587252 -225.30060620
[241,] -200.94552872 281.24587252
[242,] -135.50461158 -200.94552872
[243,] -295.03270177 -135.50461158
[244,] 526.99716387 -295.03270177
[245,] 199.36192704 526.99716387
[246,] -146.53225969 199.36192704
[247,] 13.24100891 -146.53225969
[248,] 186.41351017 13.24100891
[249,] 281.14760881 186.41351017
[250,] 57.76949803 281.14760881
[251,] 21.58558625 57.76949803
[252,] -383.80354260 21.58558625
[253,] -156.40023326 -383.80354260
[254,] -27.51887827 -156.40023326
[255,] 101.36037271 -27.51887827
[256,] 323.98037236 101.36037271
[257,] 262.95372311 323.98037236
[258,] -216.76969093 262.95372311
[259,] -68.37410201 -216.76969093
[260,] -154.22902065 -68.37410201
[261,] -74.90800874 -154.22902065
[262,] 199.05442544 -74.90800874
[263,] -21.99784418 199.05442544
[264,] -175.51788653 -21.99784418
[265,] -173.38085300 -175.51788653
[266,] 82.24488412 -173.38085300
[267,] -99.73371887 82.24488412
[268,] -205.10476099 -99.73371887
[269,] 47.73405761 -205.10476099
[270,] 344.13832151 47.73405761
[271,] -85.86643897 344.13832151
[272,] -126.68568353 -85.86643897
[273,] -174.99887957 -126.68568353
[274,] -231.41238929 -174.99887957
[275,] -198.33144174 -231.41238929
[276,] -136.94523996 -198.33144174
[277,] -76.19426127 -136.94523996
[278,] -148.00087007 -76.19426127
[279,] 113.37038214 -148.00087007
[280,] -78.34820483 113.37038214
[281,] 90.86759753 -78.34820483
[282,] 199.45801260 90.86759753
[283,] -49.85273550 199.45801260
[284,] 470.88185273 -49.85273550
[285,] -1.49317486 470.88185273
[286,] 322.27449384 -1.49317486
[287,] -41.91760333 322.27449384
[288,] 63.11093111 -41.91760333
[289,] -34.85962405 63.11093111
[290,] 159.94897471 -34.85962405
[291,] 55.68447333 159.94897471
[292,] 347.63668688 55.68447333
[293,] -239.91245047 347.63668688
[294,] -128.07272959 -239.91245047
[295,] 326.50277534 -128.07272959
[296,] -101.61377376 326.50277534
[297,] 275.30199289 -101.61377376
[298,] -121.37286406 275.30199289
[299,] -89.38175568 -121.37286406
[300,] 13.87182477 -89.38175568
[301,] -20.20918782 13.87182477
[302,] -44.73476130 -20.20918782
[303,] 145.12932565 -44.73476130
[304,] -167.18926394 145.12932565
[305,] -66.66670113 -167.18926394
[306,] 206.16721351 -66.66670113
[307,] -96.32511258 206.16721351
[308,] -174.25455258 -96.32511258
[309,] -148.73934167 -174.25455258
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 608.15643299 236.00369397
2 -376.18457224 608.15643299
3 -366.28367225 -376.18457224
4 245.00786391 -366.28367225
5 -360.42184016 245.00786391
6 -370.74685653 -360.42184016
7 592.02967735 -370.74685653
8 -71.23734074 592.02967735
9 -372.39755988 -71.23734074
10 -0.03876107 -372.39755988
11 -371.50540425 -0.03876107
12 -368.78553953 -371.50540425
13 -72.09131018 -368.78553953
14 335.85943461 -72.09131018
15 497.30217253 335.85943461
16 -374.61628101 497.30217253
17 -369.38895439 -374.61628101
18 -373.22413922 -369.38895439
19 43.30151540 -373.22413922
20 364.22344032 43.30151540
21 -366.73090589 364.22344032
22 168.10325559 -366.73090589
23 -375.63395246 168.10325559
24 462.82264825 -375.63395246
25 -372.07387591 462.82264825
26 572.54960727 -372.07387591
27 -155.78911910 572.54960727
28 -64.49825014 -155.78911910
29 172.08376508 -64.49825014
30 -371.51370104 172.08376508
31 -94.82300237 -371.51370104
32 265.02673280 -94.82300237
33 70.64855324 265.02673280
34 138.09409111 70.64855324
35 79.12830235 138.09409111
36 376.77623273 79.12830235
37 87.65720635 376.77623273
38 309.05313918 87.65720635
39 -372.34222292 309.05313918
40 174.25795400 -372.34222292
41 95.36651969 174.25795400
42 126.47186462 95.36651969
43 142.64485546 126.47186462
44 179.11326128 142.64485546
45 511.00371206 179.11326128
46 -53.70723977 511.00371206
47 -145.60980511 -53.70723977
48 -37.08233833 -145.60980511
49 -87.88410850 -37.08233833
50 86.04516832 -87.88410850
51 -39.30629539 86.04516832
52 -34.79199487 -39.30629539
53 11.94203500 -34.79199487
54 175.19190510 11.94203500
55 -2.81642815 175.19190510
56 -103.44979667 -2.81642815
57 -188.20083695 -103.44979667
58 190.12381652 -188.20083695
59 -121.64630448 190.12381652
60 -103.74146250 -121.64630448
61 -109.48977161 -103.74146250
62 -184.38673705 -109.48977161
63 -76.54218098 -184.38673705
64 132.26410742 -76.54218098
65 -28.58094261 132.26410742
66 -225.45573603 -28.58094261
67 -154.01775640 -225.45573603
68 -134.16493804 -154.01775640
69 354.52640976 -134.16493804
70 -77.84558218 354.52640976
71 497.40867296 -77.84558218
72 54.65560555 497.40867296
73 -76.91707748 54.65560555
74 146.73045332 -76.91707748
75 265.08489772 146.73045332
76 242.75184815 265.08489772
77 425.95414034 242.75184815
78 -230.94420383 425.95414034
79 607.02738178 -230.94420383
80 -135.70072177 607.02738178
81 -127.16909449 -135.70072177
82 552.66954098 -127.16909449
83 449.57886612 552.66954098
84 -176.84060560 449.57886612
85 147.28961316 -176.84060560
86 -33.33713686 147.28961316
87 225.33905503 -33.33713686
88 -362.60390718 225.33905503
89 116.41842539 -362.60390718
90 -376.96106477 116.41842539
91 147.28115771 -376.96106477
92 46.62170049 147.28115771
93 296.12151168 46.62170049
94 173.18705139 296.12151168
95 -246.77412475 173.18705139
96 417.48001407 -246.77412475
97 105.46097871 417.48001407
98 234.38052448 105.46097871
99 -376.85357772 234.38052448
100 -377.19842414 -376.85357772
101 133.28445982 -377.19842414
102 138.79778117 133.28445982
103 -375.18617397 138.79778117
104 -373.72987173 -375.18617397
105 -374.44847130 -373.72987173
106 414.87764486 -374.44847130
107 -376.65434611 414.87764486
108 -380.20770729 -376.65434611
109 -87.24842520 -380.20770729
110 324.40164863 -87.24842520
111 38.43333505 324.40164863
112 86.32707536 38.43333505
113 179.31055671 86.32707536
114 -215.73436100 179.31055671
115 -55.41328032 -215.73436100
116 -142.34787817 -55.41328032
117 253.20237967 -142.34787817
118 -130.28989888 253.20237967
119 17.25944856 -130.28989888
120 -208.00358406 17.25944856
121 84.54289465 -208.00358406
122 234.64495004 84.54289465
123 -186.98932886 234.64495004
124 -120.91398932 -186.98932886
125 -141.44978343 -120.91398932
126 306.87487003 -141.44978343
127 -222.50324075 306.87487003
128 167.15782654 -222.50324075
129 -95.92311727 167.15782654
130 -379.91288461 -95.92311727
131 -72.15376754 -379.91288461
132 -26.61484708 -72.15376754
133 33.30602989 -26.61484708
134 264.56234151 33.30602989
135 71.95498480 264.56234151
136 284.94931393 71.95498480
137 -206.17003512 284.94931393
138 -184.10218504 -206.17003512
139 66.25765291 -184.10218504
140 -144.29799474 66.25765291
141 -184.71360037 -144.29799474
142 9.78788396 -184.71360037
143 38.38047379 9.78788396
144 -172.33229881 38.38047379
145 -377.02958607 -172.33229881
146 463.20955698 -377.02958607
147 -248.56350964 463.20955698
148 -128.61843353 -248.56350964
149 -99.29504247 -128.61843353
150 56.69599712 -99.29504247
151 -8.56234599 56.69599712
152 -322.54074264 -8.56234599
153 216.96831001 -322.54074264
154 -244.00266596 216.96831001
155 -261.36586660 -244.00266596
156 -207.94055553 -261.36586660
157 -167.79848047 -207.94055553
158 -162.73294075 -167.79848047
159 -325.88460556 -162.73294075
160 -187.67265111 -325.88460556
161 -115.68392187 -187.67265111
162 -116.02362742 -115.68392187
163 -212.32457569 -116.02362742
164 33.40490222 -212.32457569
165 -200.41587988 33.40490222
166 -284.81972735 -200.41587988
167 -232.06080241 -284.81972735
168 -277.35972356 -232.06080241
169 320.34003220 -277.35972356
170 -39.63927483 320.34003220
171 64.50937930 -39.63927483
172 292.80444819 64.50937930
173 530.78176315 292.80444819
174 552.18126876 530.78176315
175 -377.45859163 552.18126876
176 42.94719139 -377.45859163
177 607.24926014 42.94719139
178 438.15172297 607.24926014
179 418.55451811 438.15172297
180 -1.49186836 418.55451811
181 -184.04975759 -1.49186836
182 138.09245504 -184.04975759
183 -325.55163508 138.09245504
184 -101.22291598 -325.55163508
185 -77.26615048 -101.22291598
186 -132.37898924 -77.26615048
187 -376.96219490 -132.37898924
188 -123.61719775 -376.96219490
189 -90.11647618 -123.61719775
190 162.59342332 -90.11647618
191 -119.60616331 162.59342332
192 275.71764855 -119.60616331
193 -381.67131438 275.71764855
194 3.55569214 -381.67131438
195 -58.60444130 3.55569214
196 -68.37288719 -58.60444130
197 575.12041370 -68.37288719
198 -135.69189977 575.12041370
199 -103.81453835 -135.69189977
200 -63.04490320 -103.81453835
201 -6.38705667 -63.04490320
202 71.15949082 -6.38705667
203 -190.62806514 71.15949082
204 -213.40875879 -190.62806514
205 -96.71383821 -213.40875879
206 40.42753282 -96.71383821
207 -175.53420169 40.42753282
208 -90.03619005 -175.53420169
209 -162.44628580 -90.03619005
210 -324.01257488 -162.44628580
211 71.06927495 -324.01257488
212 121.95258828 71.06927495
213 -14.98200957 121.95258828
214 -257.62532359 -14.98200957
215 93.87490840 -257.62532359
216 201.24769815 93.87490840
217 -380.37012629 201.24769815
218 -379.24410672 -380.37012629
219 24.22025046 -379.24410672
220 236.28125946 24.22025046
221 -21.64712447 236.28125946
222 210.19701080 -21.64712447
223 121.15251389 210.19701080
224 -18.63406290 121.15251389
225 62.18559810 -18.63406290
226 183.90723453 62.18559810
227 176.64175398 183.90723453
228 2.52205291 176.64175398
229 185.09807678 2.52205291
230 411.24781830 185.09807678
231 209.86774917 411.24781830
232 -6.24704793 209.86774917
233 283.44647267 -6.24704793
234 -58.44831996 283.44647267
235 256.43184140 -58.44831996
236 112.68878017 256.43184140
237 238.04854934 112.68878017
238 -138.77188075 238.04854934
239 -225.30060620 -138.77188075
240 281.24587252 -225.30060620
241 -200.94552872 281.24587252
242 -135.50461158 -200.94552872
243 -295.03270177 -135.50461158
244 526.99716387 -295.03270177
245 199.36192704 526.99716387
246 -146.53225969 199.36192704
247 13.24100891 -146.53225969
248 186.41351017 13.24100891
249 281.14760881 186.41351017
250 57.76949803 281.14760881
251 21.58558625 57.76949803
252 -383.80354260 21.58558625
253 -156.40023326 -383.80354260
254 -27.51887827 -156.40023326
255 101.36037271 -27.51887827
256 323.98037236 101.36037271
257 262.95372311 323.98037236
258 -216.76969093 262.95372311
259 -68.37410201 -216.76969093
260 -154.22902065 -68.37410201
261 -74.90800874 -154.22902065
262 199.05442544 -74.90800874
263 -21.99784418 199.05442544
264 -175.51788653 -21.99784418
265 -173.38085300 -175.51788653
266 82.24488412 -173.38085300
267 -99.73371887 82.24488412
268 -205.10476099 -99.73371887
269 47.73405761 -205.10476099
270 344.13832151 47.73405761
271 -85.86643897 344.13832151
272 -126.68568353 -85.86643897
273 -174.99887957 -126.68568353
274 -231.41238929 -174.99887957
275 -198.33144174 -231.41238929
276 -136.94523996 -198.33144174
277 -76.19426127 -136.94523996
278 -148.00087007 -76.19426127
279 113.37038214 -148.00087007
280 -78.34820483 113.37038214
281 90.86759753 -78.34820483
282 199.45801260 90.86759753
283 -49.85273550 199.45801260
284 470.88185273 -49.85273550
285 -1.49317486 470.88185273
286 322.27449384 -1.49317486
287 -41.91760333 322.27449384
288 63.11093111 -41.91760333
289 -34.85962405 63.11093111
290 159.94897471 -34.85962405
291 55.68447333 159.94897471
292 347.63668688 55.68447333
293 -239.91245047 347.63668688
294 -128.07272959 -239.91245047
295 326.50277534 -128.07272959
296 -101.61377376 326.50277534
297 275.30199289 -101.61377376
298 -121.37286406 275.30199289
299 -89.38175568 -121.37286406
300 13.87182477 -89.38175568
301 -20.20918782 13.87182477
302 -44.73476130 -20.20918782
303 145.12932565 -44.73476130
304 -167.18926394 145.12932565
305 -66.66670113 -167.18926394
306 206.16721351 -66.66670113
307 -96.32511258 206.16721351
308 -174.25455258 -96.32511258
309 -148.73934167 -174.25455258
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/79ws21321634523.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/82zeo1321634523.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9xa8a1321634523.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10mj341321634523.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/1176qr1321634523.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/12j2vg1321634523.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/1370np1321634523.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/14282b1321634523.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/155ue71321634523.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/16tswr1321634523.tab")
+ }
>
> try(system("convert tmp/1mxvj1321634523.ps tmp/1mxvj1321634523.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dcbs1321634523.ps tmp/2dcbs1321634523.png",intern=TRUE))
character(0)
> try(system("convert tmp/3io2l1321634523.ps tmp/3io2l1321634523.png",intern=TRUE))
character(0)
> try(system("convert tmp/4kdc41321634523.ps tmp/4kdc41321634523.png",intern=TRUE))
character(0)
> try(system("convert tmp/5x4471321634523.ps tmp/5x4471321634523.png",intern=TRUE))
character(0)
> try(system("convert tmp/6h2lc1321634523.ps tmp/6h2lc1321634523.png",intern=TRUE))
character(0)
> try(system("convert tmp/79ws21321634523.ps tmp/79ws21321634523.png",intern=TRUE))
character(0)
> try(system("convert tmp/82zeo1321634523.ps tmp/82zeo1321634523.png",intern=TRUE))
character(0)
> try(system("convert tmp/9xa8a1321634523.ps tmp/9xa8a1321634523.png",intern=TRUE))
character(0)
> try(system("convert tmp/10mj341321634523.ps tmp/10mj341321634523.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.868 0.628 11.486