R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(1
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+ ,6
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+ ,11
+ ,94.40
+ ,315.80
+ ,12
+ ,102.18
+ ,311.30)
+ ,dim=c(3
+ ,360)
+ ,dimnames=list(c('Month'
+ ,'Colombia'
+ ,'USA')
+ ,1:360))
> y <- array(NA,dim=c(3,360),dimnames=list(c('Month','Colombia','USA'),1:360))
> 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 = '3'
> #'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
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> 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
USA Month Colombia t
1 255.0 1 87.28 1
2 280.2 2 87.28 2
3 299.9 3 87.09 3
4 339.2 4 86.92 4
5 374.2 5 87.59 5
6 393.5 6 90.72 6
7 389.2 7 90.69 7
8 381.7 8 90.30 8
9 375.2 9 89.55 9
10 369.0 10 88.94 10
11 357.4 11 88.41 11
12 352.1 12 87.82 12
13 346.5 1 87.07 13
14 342.9 2 86.82 14
15 340.3 3 86.40 15
16 328.3 4 86.02 16
17 322.9 5 85.66 17
18 314.3 6 85.32 18
19 308.9 7 85.00 19
20 294.0 8 84.67 20
21 285.6 9 83.94 21
22 281.2 10 82.83 22
23 280.3 11 81.95 23
24 278.8 12 81.19 24
25 274.5 1 80.48 25
26 270.4 2 78.86 26
27 263.4 3 69.47 27
28 259.9 4 68.77 28
29 258.0 5 70.06 29
30 262.7 6 73.95 30
31 284.7 7 75.80 31
32 311.3 8 77.79 32
33 322.1 9 81.57 33
34 327.0 10 83.07 34
35 331.3 11 84.34 35
36 333.3 12 85.10 36
37 321.4 1 85.25 37
38 327.0 2 84.26 38
39 320.0 3 83.63 39
40 314.7 4 86.44 40
41 316.7 5 85.30 41
42 314.4 6 84.10 42
43 321.3 7 83.36 43
44 318.2 8 82.48 44
45 307.2 9 81.58 45
46 301.3 10 80.47 46
47 287.5 11 79.34 47
48 277.7 12 82.13 48
49 274.4 1 81.69 49
50 258.8 2 80.70 50
51 253.3 3 79.88 51
52 251.0 4 79.16 52
53 248.4 5 78.38 53
54 249.5 6 77.42 54
55 246.1 7 76.47 55
56 244.5 8 75.46 56
57 243.6 9 74.48 57
58 244.0 10 78.27 58
59 240.8 11 80.70 59
60 249.8 12 79.91 60
61 248.0 1 78.75 61
62 259.4 2 77.78 62
63 260.5 3 81.14 63
64 260.8 4 81.08 64
65 261.3 5 80.03 65
66 259.5 6 78.91 66
67 256.6 7 78.01 67
68 257.9 8 76.90 68
69 256.5 9 75.97 69
70 254.2 10 81.93 70
71 253.3 11 80.27 71
72 253.8 12 78.67 72
73 255.5 1 77.42 73
74 257.1 2 76.16 74
75 257.3 3 74.70 75
76 253.2 4 76.39 76
77 252.8 5 76.04 77
78 252.0 6 74.65 78
79 250.7 7 73.29 79
80 252.2 8 71.79 80
81 250.0 9 74.39 81
82 251.0 10 74.91 82
83 253.4 11 74.54 83
84 251.2 12 73.08 84
85 255.6 1 72.75 85
86 261.1 2 71.32 86
87 258.9 3 70.38 87
88 259.9 4 70.35 88
89 261.2 5 70.01 89
90 264.7 6 69.36 90
91 267.1 7 67.77 91
92 266.4 8 69.26 92
93 267.7 9 69.80 93
94 268.6 10 68.38 94
95 267.5 11 67.62 95
96 268.5 12 68.39 96
97 268.5 1 66.95 97
98 270.5 2 65.21 98
99 270.9 3 66.64 99
100 270.1 4 63.45 100
101 269.3 5 60.66 101
102 269.8 6 62.34 102
103 270.1 7 60.32 103
104 264.9 8 58.64 104
105 263.7 9 60.46 105
106 264.8 10 58.59 106
107 263.7 11 61.87 107
108 255.9 12 61.85 108
109 276.2 1 67.44 109
110 360.1 2 77.06 110
111 380.5 3 91.74 111
112 373.7 4 93.15 112
113 369.8 5 94.15 113
114 366.6 6 93.11 114
115 359.3 7 91.51 115
116 345.8 8 89.96 116
117 326.2 9 88.16 117
118 324.5 10 86.98 118
119 328.1 11 88.03 119
120 327.5 12 86.24 120
121 324.4 1 84.65 121
122 316.5 2 83.23 122
123 310.9 3 81.70 123
124 301.5 4 80.25 124
125 291.7 5 78.80 125
126 290.4 6 77.51 126
127 287.4 7 76.20 127
128 277.7 8 75.04 128
129 281.6 9 74.00 129
130 288.0 10 75.49 130
131 276.0 11 77.14 131
132 272.9 12 76.15 132
133 283.0 1 76.27 133
134 283.3 2 78.19 134
135 276.8 3 76.49 135
136 284.5 4 77.31 136
137 282.7 5 76.65 137
138 281.2 6 74.99 138
139 287.4 7 73.51 139
140 283.1 8 72.07 140
141 284.0 9 70.59 141
142 285.5 10 71.96 142
143 289.2 11 76.29 143
144 292.5 12 74.86 144
145 296.4 1 74.93 145
146 305.2 2 71.90 146
147 303.9 3 71.01 147
148 311.5 4 77.47 148
149 316.3 5 75.78 149
150 316.7 6 76.60 150
151 322.5 7 76.07 151
152 317.1 8 74.57 152
153 309.8 9 73.02 153
154 303.8 10 72.65 154
155 290.3 11 73.16 155
156 293.7 12 71.53 156
157 291.7 1 69.78 157
158 296.5 2 67.98 158
159 289.1 3 69.96 159
160 288.5 4 72.16 160
161 293.8 5 70.47 161
162 297.7 6 68.86 162
163 305.4 7 67.37 163
164 302.7 8 65.87 164
165 302.5 9 72.16 165
166 303.0 10 71.34 166
167 294.5 11 69.93 167
168 294.1 12 68.44 168
169 294.5 1 67.16 169
170 297.1 2 66.01 170
171 289.4 3 67.25 171
172 292.4 4 70.91 172
173 287.9 5 69.75 173
174 286.6 6 68.59 174
175 280.5 7 67.48 175
176 272.4 8 66.31 176
177 269.2 9 64.81 177
178 270.6 10 66.58 178
179 267.3 11 65.97 179
180 262.5 12 64.70 180
181 266.8 1 64.70 181
182 268.8 2 60.94 182
183 263.1 3 59.08 183
184 261.2 4 58.42 184
185 266.0 5 57.77 185
186 262.5 6 57.11 186
187 265.2 7 53.31 187
188 261.3 8 49.96 188
189 253.7 9 49.40 189
190 249.2 10 48.84 190
191 239.1 11 48.30 191
192 236.4 12 47.74 192
193 235.2 1 47.24 193
194 245.2 2 46.76 194
195 246.2 3 46.29 195
196 247.7 4 48.90 196
197 251.4 5 49.23 197
198 253.3 6 48.53 198
199 254.8 7 48.03 199
200 250.0 8 54.34 200
201 249.3 9 53.79 201
202 241.5 10 53.24 202
203 243.3 11 52.96 203
204 248.0 12 52.17 204
205 253.0 1 51.70 205
206 252.9 2 58.55 206
207 251.5 3 78.20 207
208 251.6 4 77.03 208
209 253.5 5 76.19 209
210 259.8 6 77.15 210
211 334.1 7 75.87 211
212 448.0 8 95.47 212
213 445.8 9 109.67 213
214 445.0 10 112.28 214
215 448.2 11 112.01 215
216 438.2 12 107.93 216
217 439.8 1 105.96 217
218 423.4 2 105.06 218
219 410.8 3 102.98 219
220 408.4 4 102.20 220
221 406.7 5 105.23 221
222 405.9 6 101.85 222
223 402.7 7 99.89 223
224 405.1 8 96.23 224
225 399.6 9 94.76 225
226 386.5 10 91.51 226
227 381.4 11 91.63 227
228 375.2 12 91.54 228
229 357.7 1 85.23 229
230 359.0 2 87.83 230
231 355.0 3 87.38 231
232 352.7 4 84.44 232
233 344.4 5 85.19 233
234 343.8 6 84.03 234
235 338.0 7 86.73 235
236 339.0 8 102.52 236
237 333.3 9 104.45 237
238 334.4 10 106.98 238
239 328.3 11 107.02 239
240 330.7 12 99.26 240
241 330.0 1 94.45 241
242 331.6 2 113.44 242
243 351.2 3 157.33 243
244 389.4 4 147.38 244
245 410.9 5 171.89 245
246 442.8 6 171.95 246
247 462.8 7 132.71 247
248 466.9 8 126.02 248
249 461.7 9 121.18 249
250 439.2 10 115.45 250
251 430.3 11 110.48 251
252 416.1 12 117.85 252
253 402.5 1 117.63 253
254 397.3 2 124.65 254
255 403.3 3 109.59 255
256 395.9 4 111.27 256
257 387.8 5 99.78 257
258 378.6 6 98.21 258
259 377.1 7 99.20 259
260 370.4 8 97.97 260
261 362.0 9 89.55 261
262 350.3 10 87.91 262
263 348.2 11 93.34 263
264 344.6 12 94.42 264
265 343.5 1 93.20 265
266 342.8 2 90.29 266
267 347.6 3 91.46 267
268 346.6 4 89.98 268
269 349.5 5 88.35 269
270 342.1 6 88.41 270
271 342.0 7 82.44 271
272 342.8 8 79.89 272
273 339.3 9 75.69 273
274 348.2 10 75.66 274
275 333.7 11 84.50 275
276 334.7 12 96.73 276
277 354.0 1 87.48 277
278 367.7 2 82.39 278
279 363.3 3 83.48 279
280 358.4 4 79.31 280
281 353.1 5 78.16 281
282 343.1 6 72.77 282
283 344.6 7 72.45 283
284 344.4 8 68.46 284
285 333.9 9 67.62 285
286 331.7 10 68.76 286
287 324.3 11 70.07 287
288 321.2 12 68.55 288
289 322.4 1 65.30 289
290 321.7 2 58.96 290
291 320.5 3 59.17 291
292 312.8 4 62.37 292
293 309.7 5 66.28 293
294 315.6 6 55.62 294
295 309.7 7 55.23 295
296 304.6 8 55.85 296
297 302.5 9 56.75 297
298 301.5 10 50.89 298
299 298.8 11 53.88 299
300 291.3 12 52.95 300
301 293.6 1 55.08 301
302 294.6 2 53.61 302
303 285.9 3 58.78 303
304 297.6 4 61.85 304
305 301.1 5 55.91 305
306 293.8 6 53.32 306
307 297.7 7 46.41 307
308 292.9 8 44.57 308
309 292.1 9 50.00 309
310 287.2 10 50.00 310
311 288.2 11 53.36 311
312 283.8 12 46.23 312
313 299.9 1 50.45 313
314 292.4 2 49.07 314
315 293.3 3 45.85 315
316 300.8 4 48.45 316
317 293.7 5 49.96 317
318 293.1 6 46.53 318
319 294.4 7 50.51 319
320 292.1 8 47.58 320
321 291.9 9 48.05 321
322 282.5 10 46.84 322
323 277.9 11 47.67 323
324 287.5 12 49.16 324
325 289.2 1 55.54 325
326 285.6 2 55.82 326
327 293.2 3 58.22 327
328 290.8 4 56.19 328
329 283.1 5 57.77 329
330 275.0 6 63.19 330
331 287.8 7 54.76 331
332 287.8 8 55.74 332
333 287.4 9 62.54 333
334 284.0 10 61.39 334
335 277.8 11 69.60 335
336 277.6 12 79.23 336
337 304.9 1 80.00 337
338 294.0 2 93.68 338
339 300.9 3 107.63 339
340 324.0 4 100.18 340
341 332.9 5 97.30 341
342 341.6 6 90.45 342
343 333.4 7 80.64 343
344 348.2 8 80.58 344
345 344.7 9 75.82 345
346 344.7 10 85.59 346
347 329.3 11 89.35 347
348 323.5 12 89.42 348
349 323.2 1 104.73 349
350 317.4 2 95.32 350
351 330.1 3 89.27 351
352 329.2 4 90.44 352
353 334.9 5 86.97 353
354 315.8 6 79.98 354
355 315.4 7 81.22 355
356 319.6 8 87.35 356
357 317.3 9 83.64 357
358 313.8 10 82.22 358
359 315.8 11 94.40 359
360 311.3 12 102.18 360
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Month Colombia t
133.2250 0.3657 1.8833 0.1480
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-115.3953 -18.3130 -0.5263 18.3151 100.6663
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 133.22495 8.28147 16.087 <2e-16 ***
Month 0.36574 0.47497 0.770 0.442
Colombia 1.88330 0.08715 21.610 <2e-16 ***
t 0.14804 0.01579 9.377 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 31.08 on 356 degrees of freedom
Multiple R-squared: 0.6014, Adjusted R-squared: 0.598
F-statistic: 179 on 3 and 356 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,] 0.1525180421 3.050361e-01 8.474820e-01
[2,] 0.3812953288 7.625907e-01 6.187047e-01
[3,] 0.5521967958 8.956064e-01 4.478032e-01
[4,] 0.5815042042 8.369916e-01 4.184958e-01
[5,] 0.5659531825 8.680936e-01 4.340468e-01
[6,] 0.4984563891 9.969128e-01 5.015436e-01
[7,] 0.4030642234 8.061284e-01 5.969358e-01
[8,] 0.3176992892 6.353986e-01 6.823007e-01
[9,] 0.2433041422 4.866083e-01 7.566959e-01
[10,] 0.1890914872 3.781830e-01 8.109085e-01
[11,] 0.1449788239 2.899576e-01 8.550212e-01
[12,] 0.1138956618 2.277913e-01 8.861043e-01
[13,] 0.0877637625 1.755275e-01 9.122362e-01
[14,] 0.0771374630 1.542749e-01 9.228625e-01
[15,] 0.0570427205 1.140854e-01 9.429573e-01
[16,] 0.0388882753 7.777655e-02 9.611117e-01
[17,] 0.0305185486 6.103710e-02 9.694815e-01
[18,] 0.0261441152 5.228823e-02 9.738559e-01
[19,] 0.0272349501 5.446990e-02 9.727650e-01
[20,] 0.0427756404 8.555128e-02 9.572244e-01
[21,] 0.6193121303 7.613757e-01 3.806879e-01
[22,] 0.6727272883 6.545454e-01 3.272727e-01
[23,] 0.6402362770 7.195274e-01 3.597637e-01
[24,] 0.5850072553 8.299855e-01 4.149927e-01
[25,] 0.5381881503 9.236237e-01 4.618118e-01
[26,] 0.5251413388 9.497173e-01 4.748587e-01
[27,] 0.4848299823 9.696600e-01 5.151700e-01
[28,] 0.4392786200 8.785572e-01 5.607214e-01
[29,] 0.3945190527 7.890381e-01 6.054809e-01
[30,] 0.3528041570 7.056083e-01 6.471958e-01
[31,] 0.3093029782 6.186060e-01 6.906970e-01
[32,] 0.2752297778 5.504596e-01 7.247702e-01
[33,] 0.2382220913 4.764442e-01 7.617779e-01
[34,] 0.2165279790 4.330560e-01 7.834720e-01
[35,] 0.1869221355 3.738443e-01 8.130779e-01
[36,] 0.1583681051 3.167362e-01 8.416319e-01
[37,] 0.1339035442 2.678071e-01 8.660965e-01
[38,] 0.1120312586 2.240625e-01 8.879687e-01
[39,] 0.0921957392 1.843915e-01 9.078043e-01
[40,] 0.0751743312 1.503487e-01 9.248257e-01
[41,] 0.0634934096 1.269868e-01 9.365066e-01
[42,] 0.0756851469 1.513703e-01 9.243149e-01
[43,] 0.0684129013 1.368258e-01 9.315871e-01
[44,] 0.0701285470 1.402571e-01 9.298715e-01
[45,] 0.0716340053 1.432680e-01 9.283660e-01
[46,] 0.0708271661 1.416543e-01 9.291728e-01
[47,] 0.0686411005 1.372822e-01 9.313589e-01
[48,] 0.0619309696 1.238619e-01 9.380690e-01
[49,] 0.0554975030 1.109950e-01 9.445025e-01
[50,] 0.0483466749 9.669335e-02 9.516533e-01
[51,] 0.0409140636 8.182813e-02 9.590859e-01
[52,] 0.0437734185 8.754684e-02 9.562266e-01
[53,] 0.0620628441 1.241257e-01 9.379372e-01
[54,] 0.0637672581 1.275345e-01 9.362327e-01
[55,] 0.0541677517 1.083355e-01 9.458322e-01
[56,] 0.0456250120 9.125002e-02 9.543750e-01
[57,] 0.0379463006 7.589260e-02 9.620537e-01
[58,] 0.0313948639 6.278973e-02 9.686051e-01
[59,] 0.0255125284 5.102506e-02 9.744875e-01
[60,] 0.0206733721 4.134674e-02 9.793266e-01
[61,] 0.0167655739 3.353115e-02 9.832344e-01
[62,] 0.0137185625 2.743713e-02 9.862814e-01
[63,] 0.0113166113 2.263322e-02 9.886834e-01
[64,] 0.0110112595 2.202252e-02 9.889887e-01
[65,] 0.0097558252 1.951165e-02 9.902442e-01
[66,] 0.0081258995 1.625180e-02 9.918741e-01
[67,] 0.0073140227 1.462805e-02 9.926860e-01
[68,] 0.0070376394 1.407528e-02 9.929624e-01
[69,] 0.0073323248 1.466465e-02 9.926677e-01
[70,] 0.0064222914 1.284458e-02 9.935777e-01
[71,] 0.0056496402 1.129928e-02 9.943504e-01
[72,] 0.0052300283 1.046006e-02 9.947700e-01
[73,] 0.0051078734 1.021575e-02 9.948921e-01
[74,] 0.0055462212 1.109244e-02 9.944538e-01
[75,] 0.0049355896 9.871179e-03 9.950644e-01
[76,] 0.0043254615 8.650923e-03 9.956745e-01
[77,] 0.0038525443 7.705089e-03 9.961475e-01
[78,] 0.0035568570 7.113714e-03 9.964431e-01
[79,] 0.0044063035 8.812607e-03 9.955937e-01
[80,] 0.0065221667 1.304433e-02 9.934778e-01
[81,] 0.0090534750 1.810695e-02 9.909465e-01
[82,] 0.0118054978 2.361100e-02 9.881945e-01
[83,] 0.0151794414 3.035888e-02 9.848206e-01
[84,] 0.0205691515 4.113830e-02 9.794308e-01
[85,] 0.0304528444 6.090569e-02 9.695472e-01
[86,] 0.0367022579 7.340452e-02 9.632977e-01
[87,] 0.0417087219 8.341744e-02 9.582913e-01
[88,] 0.0492086772 9.841735e-02 9.507913e-01
[89,] 0.0560183240 1.120366e-01 9.439817e-01
[90,] 0.0595774957 1.191550e-01 9.404225e-01
[91,] 0.0781421896 1.562844e-01 9.218578e-01
[92,] 0.1033301833 2.066604e-01 8.966698e-01
[93,] 0.1203493009 2.406986e-01 8.796507e-01
[94,] 0.1458369955 2.916740e-01 8.541630e-01
[95,] 0.1769013417 3.538027e-01 8.230987e-01
[96,] 0.1956590896 3.913182e-01 8.043409e-01
[97,] 0.2161298297 4.322597e-01 7.838702e-01
[98,] 0.2252902055 4.505804e-01 7.747098e-01
[99,] 0.2236726000 4.473452e-01 7.763274e-01
[100,] 0.2223819828 4.447640e-01 7.776180e-01
[101,] 0.2130154632 4.260309e-01 7.869845e-01
[102,] 0.1986351917 3.972704e-01 8.013648e-01
[103,] 0.2089463063 4.178926e-01 7.910537e-01
[104,] 0.4776477860 9.552956e-01 5.223522e-01
[105,] 0.6223620404 7.552759e-01 3.776380e-01
[106,] 0.6609538228 6.780924e-01 3.390462e-01
[107,] 0.6648135678 6.703729e-01 3.351864e-01
[108,] 0.6611792309 6.776415e-01 3.388208e-01
[109,] 0.6492062619 7.015875e-01 3.507937e-01
[110,] 0.6247630957 7.504738e-01 3.752369e-01
[111,] 0.5943921254 8.112157e-01 4.056079e-01
[112,] 0.5630257998 8.739484e-01 4.369742e-01
[113,] 0.5314239753 9.371520e-01 4.685760e-01
[114,] 0.4999297879 9.998596e-01 5.000702e-01
[115,] 0.4706103418 9.412207e-01 5.293897e-01
[116,] 0.4394703671 8.789407e-01 5.605296e-01
[117,] 0.4083839695 8.167679e-01 5.916160e-01
[118,] 0.3780627183 7.561254e-01 6.219373e-01
[119,] 0.3510459436 7.020919e-01 6.489541e-01
[120,] 0.3241776857 6.483554e-01 6.758223e-01
[121,] 0.2986058025 5.972116e-01 7.013942e-01
[122,] 0.2783880499 5.567761e-01 7.216120e-01
[123,] 0.2560569632 5.121139e-01 7.439430e-01
[124,] 0.2338462311 4.676925e-01 7.661538e-01
[125,] 0.2248343694 4.496687e-01 7.751656e-01
[126,] 0.2174447382 4.348895e-01 7.825553e-01
[127,] 0.1984739092 3.969478e-01 8.015261e-01
[128,] 0.1837344386 3.674689e-01 8.162656e-01
[129,] 0.1717744068 3.435488e-01 8.282256e-01
[130,] 0.1571566802 3.143134e-01 8.428433e-01
[131,] 0.1439448445 2.878897e-01 8.560552e-01
[132,] 0.1310372617 2.620745e-01 8.689627e-01
[133,] 0.1180627103 2.361254e-01 8.819373e-01
[134,] 0.1067105034 2.134210e-01 8.932895e-01
[135,] 0.0971753369 1.943507e-01 9.028247e-01
[136,] 0.0875748394 1.751497e-01 9.124252e-01
[137,] 0.0786047124 1.572094e-01 9.213953e-01
[138,] 0.0699311546 1.398623e-01 9.300688e-01
[139,] 0.0616128173 1.232256e-01 9.383872e-01
[140,] 0.0594714425 1.189429e-01 9.405286e-01
[141,] 0.0575448380 1.150897e-01 9.424552e-01
[142,] 0.0505774045 1.011548e-01 9.494226e-01
[143,] 0.0467637933 9.352759e-02 9.532362e-01
[144,] 0.0422580457 8.451609e-02 9.577420e-01
[145,] 0.0401030265 8.020605e-02 9.598970e-01
[146,] 0.0376068035 7.521361e-02 9.623932e-01
[147,] 0.0344754114 6.895082e-02 9.655246e-01
[148,] 0.0305610875 6.112218e-02 9.694389e-01
[149,] 0.0264102556 5.282051e-02 9.735897e-01
[150,] 0.0228945542 4.578911e-02 9.771054e-01
[151,] 0.0199220239 3.984405e-02 9.800780e-01
[152,] 0.0184083408 3.681668e-02 9.815917e-01
[153,] 0.0156766895 3.135338e-02 9.843233e-01
[154,] 0.0131943949 2.638879e-02 9.868056e-01
[155,] 0.0112152761 2.243055e-02 9.887847e-01
[156,] 0.0099516728 1.990335e-02 9.900483e-01
[157,] 0.0098617419 1.972348e-02 9.901383e-01
[158,] 0.0099076200 1.981524e-02 9.900924e-01
[159,] 0.0083106136 1.662123e-02 9.916894e-01
[160,] 0.0070270059 1.405401e-02 9.929730e-01
[161,] 0.0058783120 1.175662e-02 9.941217e-01
[162,] 0.0049814688 9.962938e-03 9.950185e-01
[163,] 0.0042948982 8.589796e-03 9.957051e-01
[164,] 0.0038627984 7.725597e-03 9.961372e-01
[165,] 0.0031874713 6.374943e-03 9.968125e-01
[166,] 0.0025635685 5.127137e-03 9.974364e-01
[167,] 0.0020717542 4.143508e-03 9.979282e-01
[168,] 0.0016757372 3.351474e-03 9.983243e-01
[169,] 0.0013744042 2.748808e-03 9.986256e-01
[170,] 0.0011693158 2.338632e-03 9.988307e-01
[171,] 0.0010072557 2.014511e-03 9.989927e-01
[172,] 0.0008923454 1.784691e-03 9.991077e-01
[173,] 0.0008214273 1.642855e-03 9.991786e-01
[174,] 0.0007956820 1.591364e-03 9.992043e-01
[175,] 0.0006775026 1.355005e-03 9.993225e-01
[176,] 0.0005691419 1.138284e-03 9.994309e-01
[177,] 0.0004903694 9.807387e-04 9.995096e-01
[178,] 0.0004293799 8.587597e-04 9.995706e-01
[179,] 0.0003798963 7.597926e-04 9.996201e-01
[180,] 0.0003406750 6.813500e-04 9.996593e-01
[181,] 0.0003355692 6.711385e-04 9.996644e-01
[182,] 0.0003560505 7.121009e-04 9.996439e-01
[183,] 0.0003603604 7.207208e-04 9.996396e-01
[184,] 0.0003656859 7.313719e-04 9.996343e-01
[185,] 0.0003930004 7.860008e-04 9.996070e-01
[186,] 0.0004513598 9.027197e-04 9.995486e-01
[187,] 0.0004555096 9.110191e-04 9.995445e-01
[188,] 0.0004556924 9.113849e-04 9.995443e-01
[189,] 0.0004652339 9.304679e-04 9.995348e-01
[190,] 0.0004758281 9.516562e-04 9.995242e-01
[191,] 0.0004917146 9.834292e-04 9.995083e-01
[192,] 0.0005200393 1.040079e-03 9.994800e-01
[193,] 0.0005640665 1.128133e-03 9.994359e-01
[194,] 0.0007082930 1.416586e-03 9.992917e-01
[195,] 0.0009519474 1.903895e-03 9.990481e-01
[196,] 0.0016142538 3.228508e-03 9.983857e-01
[197,] 0.0029244540 5.848908e-03 9.970755e-01
[198,] 0.0053620513 1.072410e-02 9.946379e-01
[199,] 0.0071764397 1.435288e-02 9.928236e-01
[200,] 0.0125612031 2.512241e-02 9.874388e-01
[201,] 0.0690420632 1.380841e-01 9.309579e-01
[202,] 0.2484058289 4.968117e-01 7.515942e-01
[203,] 0.5720981903 8.558036e-01 4.279018e-01
[204,] 0.8631810006 2.736380e-01 1.368190e-01
[205,] 0.8765263481 2.469473e-01 1.234737e-01
[206,] 0.9502851301 9.942974e-02 4.971487e-02
[207,] 0.9605709242 7.885815e-02 3.942908e-02
[208,] 0.9659643973 6.807121e-02 3.403560e-02
[209,] 0.9732770348 5.344593e-02 2.672297e-02
[210,] 0.9779124151 4.417517e-02 2.208758e-02
[211,] 0.9852185409 2.956292e-02 1.478146e-02
[212,] 0.9865976877 2.680462e-02 1.340231e-02
[213,] 0.9859938811 2.801224e-02 1.400612e-02
[214,] 0.9852287160 2.954257e-02 1.477128e-02
[215,] 0.9838107529 3.237849e-02 1.618925e-02
[216,] 0.9827495859 3.450083e-02 1.725041e-02
[217,] 0.9815343740 3.693125e-02 1.846563e-02
[218,] 0.9823623875 3.527523e-02 1.763761e-02
[219,] 0.9823302471 3.533951e-02 1.766975e-02
[220,] 0.9803465447 3.930691e-02 1.965346e-02
[221,] 0.9771992765 4.560145e-02 2.280072e-02
[222,] 0.9728560257 5.428795e-02 2.714397e-02
[223,] 0.9675143175 6.497137e-02 3.248568e-02
[224,] 0.9613005203 7.739896e-02 3.869948e-02
[225,] 0.9544096502 9.118070e-02 4.559035e-02
[226,] 0.9463437671 1.073125e-01 5.365623e-02
[227,] 0.9395480084 1.209040e-01 6.045199e-02
[228,] 0.9317682898 1.364634e-01 6.823171e-02
[229,] 0.9299355525 1.401289e-01 7.006445e-02
[230,] 0.9580982134 8.380357e-02 4.190179e-02
[231,] 0.9822910168 3.541797e-02 1.770898e-02
[232,] 0.9942035120 1.159298e-02 5.796488e-03
[233,] 0.9988842246 2.231551e-03 1.115775e-03
[234,] 0.9996385332 7.229336e-04 3.614668e-04
[235,] 0.9997951883 4.096233e-04 2.048117e-04
[236,] 0.9999824513 3.509746e-05 1.754873e-05
[237,] 0.9999999988 2.361216e-09 1.180608e-09
[238,] 0.9999999999 1.322277e-10 6.611385e-11
[239,] 1.0000000000 6.678870e-13 3.339435e-13
[240,] 1.0000000000 1.312462e-13 6.562309e-14
[241,] 1.0000000000 5.761823e-14 2.880912e-14
[242,] 1.0000000000 3.421564e-15 1.710782e-15
[243,] 1.0000000000 6.416661e-17 3.208330e-17
[244,] 1.0000000000 6.127587e-18 3.063794e-18
[245,] 1.0000000000 4.378246e-19 2.189123e-19
[246,] 1.0000000000 3.693858e-19 1.846929e-19
[247,] 1.0000000000 7.499070e-19 3.749535e-19
[248,] 1.0000000000 1.625414e-18 8.127068e-19
[249,] 1.0000000000 1.598544e-18 7.992718e-19
[250,] 1.0000000000 2.651348e-18 1.325674e-18
[251,] 1.0000000000 2.896627e-18 1.448314e-18
[252,] 1.0000000000 4.810956e-18 2.405478e-18
[253,] 1.0000000000 8.593373e-18 4.296687e-18
[254,] 1.0000000000 1.815390e-17 9.076952e-18
[255,] 1.0000000000 3.614845e-17 1.807422e-17
[256,] 1.0000000000 8.341318e-17 4.170659e-17
[257,] 1.0000000000 1.652303e-16 8.261517e-17
[258,] 1.0000000000 2.545708e-16 1.272854e-16
[259,] 1.0000000000 3.750321e-16 1.875160e-16
[260,] 1.0000000000 6.082390e-16 3.041195e-16
[261,] 1.0000000000 1.140208e-15 5.701040e-16
[262,] 1.0000000000 2.162598e-15 1.081299e-15
[263,] 1.0000000000 4.643304e-15 2.321652e-15
[264,] 1.0000000000 7.769280e-15 3.884640e-15
[265,] 1.0000000000 1.601674e-14 8.008368e-15
[266,] 1.0000000000 3.437707e-14 1.718853e-14
[267,] 1.0000000000 7.256707e-14 3.628354e-14
[268,] 1.0000000000 1.254100e-13 6.270498e-14
[269,] 1.0000000000 1.871141e-13 9.355703e-14
[270,] 1.0000000000 6.887978e-14 3.443989e-14
[271,] 1.0000000000 1.504290e-13 7.521450e-14
[272,] 1.0000000000 1.408888e-13 7.044439e-14
[273,] 1.0000000000 1.737520e-13 8.687602e-14
[274,] 1.0000000000 1.837108e-13 9.185541e-14
[275,] 1.0000000000 2.261267e-13 1.130633e-13
[276,] 1.0000000000 3.230377e-13 1.615188e-13
[277,] 1.0000000000 3.695049e-13 1.847525e-13
[278,] 1.0000000000 2.482627e-13 1.241314e-13
[279,] 1.0000000000 3.206150e-13 1.603075e-13
[280,] 1.0000000000 4.610507e-13 2.305253e-13
[281,] 1.0000000000 9.282303e-13 4.641151e-13
[282,] 1.0000000000 1.871681e-12 9.358403e-13
[283,] 1.0000000000 3.056576e-12 1.528288e-12
[284,] 1.0000000000 3.229704e-12 1.614852e-12
[285,] 1.0000000000 3.330579e-12 1.665290e-12
[286,] 1.0000000000 6.067641e-12 3.033820e-12
[287,] 1.0000000000 1.307747e-11 6.538735e-12
[288,] 1.0000000000 1.252112e-11 6.260562e-12
[289,] 1.0000000000 1.650878e-11 8.254390e-12
[290,] 1.0000000000 2.824291e-11 1.412145e-11
[291,] 1.0000000000 5.212267e-11 2.606133e-11
[292,] 1.0000000000 7.811194e-11 3.905597e-11
[293,] 0.9999999999 1.380122e-10 6.900608e-11
[294,] 0.9999999999 2.924912e-10 1.462456e-10
[295,] 0.9999999997 6.337765e-10 3.168883e-10
[296,] 0.9999999993 1.307581e-09 6.537907e-10
[297,] 0.9999999987 2.634413e-09 1.317207e-09
[298,] 0.9999999972 5.506007e-09 2.753003e-09
[299,] 0.9999999954 9.220002e-09 4.610001e-09
[300,] 0.9999999909 1.810635e-08 9.053174e-09
[301,] 0.9999999873 2.547316e-08 1.273658e-08
[302,] 0.9999999794 4.124078e-08 2.062039e-08
[303,] 0.9999999631 7.384862e-08 3.692431e-08
[304,] 0.9999999270 1.460299e-07 7.301493e-08
[305,] 0.9999998584 2.831056e-07 1.415528e-07
[306,] 0.9999997251 5.497541e-07 2.748770e-07
[307,] 0.9999995872 8.256473e-07 4.128236e-07
[308,] 0.9999992450 1.509973e-06 7.549863e-07
[309,] 0.9999987398 2.520388e-06 1.260194e-06
[310,] 0.9999984914 3.017270e-06 1.508635e-06
[311,] 0.9999975464 4.907159e-06 2.453579e-06
[312,] 0.9999962288 7.542380e-06 3.771190e-06
[313,] 0.9999943020 1.139601e-05 5.698005e-06
[314,] 0.9999912730 1.745400e-05 8.727000e-06
[315,] 0.9999869063 2.618745e-05 1.309372e-05
[316,] 0.9999756771 4.864572e-05 2.432286e-05
[317,] 0.9999539638 9.207233e-05 4.603616e-05
[318,] 0.9999234492 1.531016e-04 7.655078e-05
[319,] 0.9998599059 2.801882e-04 1.400941e-04
[320,] 0.9997476311 5.047378e-04 2.523689e-04
[321,] 0.9995616605 8.766791e-04 4.383395e-04
[322,] 0.9992401548 1.519690e-03 7.598452e-04
[323,] 0.9987409735 2.518053e-03 1.259027e-03
[324,] 0.9985247828 2.950434e-03 1.475217e-03
[325,] 0.9975452585 4.909483e-03 2.454742e-03
[326,] 0.9960837842 7.832432e-03 3.916216e-03
[327,] 0.9944044999 1.119100e-02 5.595500e-03
[328,] 0.9937920895 1.241582e-02 6.207911e-03
[329,] 0.9975024235 4.995153e-03 2.497576e-03
[330,] 0.9999382188 1.235624e-04 6.178120e-05
[331,] 0.9999748336 5.033283e-05 2.516641e-05
[332,] 0.9999994984 1.003241e-06 5.016206e-07
[333,] 0.9999999847 3.052384e-08 1.526192e-08
[334,] 0.9999999870 2.605408e-08 1.302704e-08
[335,] 0.9999999638 7.239429e-08 3.619715e-08
[336,] 0.9999998368 3.263368e-07 1.631684e-07
[337,] 0.9999996888 6.223962e-07 3.111981e-07
[338,] 0.9999990731 1.853748e-06 9.268742e-07
[339,] 0.9999969127 6.174531e-06 3.087266e-06
[340,] 0.9999975973 4.805492e-06 2.402746e-06
[341,] 0.9999891977 2.160454e-05 1.080227e-05
[342,] 0.9999474473 1.051053e-04 5.255266e-05
[343,] 0.9998012678 3.974643e-04 1.987322e-04
[344,] 0.9999303899 1.392202e-04 6.961012e-05
[345,] 0.9995958153 8.083694e-04 4.041847e-04
[346,] 0.9978692366 4.261527e-03 2.130763e-03
[347,] 0.9986222253 2.755549e-03 1.377775e-03
> postscript(file="/var/www/html/freestat/rcomp/tmp/1j9g41289489981.ps",horizontal=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2u1xp1289489981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/freestat/rcomp/tmp/3u1xp1289489981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4u1xp1289489981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5u1xp1289489981.ps",horizontal=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 = 360
Frequency = 1
1 2 3 4 5 6
-43.1134414 -18.4272177 1.1168335 40.2232187 73.4476291 86.3391134
7 8 9 10 11 12
81.5818361 74.3025480 68.7012492 63.1362878 52.0206622 47.3180348
13 14 15 16 17 18
47.0056076 43.3626570 41.0398681 29.2417470 24.0059598 15.5325066
19 20 21 22 23 24
10.2213873 -4.5708990 -12.1098639 -14.9331736 -14.6896431 -15.2721089
25 26 27 28 29 30
-14.3598683 -15.9226933 -5.7522514 -8.4477155 -13.2909531 -16.4307794
31 32 33 34 35 36
1.5713331 23.9097831 27.0771202 28.6383888 30.0328172 30.0877303
37 38 39 40 41 42
21.7803301 28.7310240 22.4037287 11.2978700 14.9310595 14.3772471
43 44 45 46 47 48
22.1571152 20.2006457 10.3818424 6.0585327 -6.1271109 -21.6953035
49 50 51 52 53 54
-20.2915549 -34.5408609 -39.0103286 -40.4681265 -42.1129263 -39.7187315
55 56 57 58 59 60
-41.8433697 -42.0550097 -41.6231488 -48.8746447 -57.1648482 -47.1908149
61 62 63 64 65 66
-42.9310878 -30.2180600 -35.9597355 -36.0605137 -34.0968215 -34.3012982
67 68 69 70 71 72
-36.0201016 -33.1434112 -33.3057155 -47.3439797 -45.6314725 -42.6319636
73 74 75 76 77 78
-34.7027392 -31.2435534 -28.8077069 -36.6042658 -36.8588860 -35.5548708
79 80 81 82 83 84
-34.8073546 -30.9961760 -38.6065410 -39.0996351 -36.5165892 -36.4807427
85 86 87 88 89 90
-27.5841574 -19.9048100 -20.8482813 -20.3055585 -18.8790118 -14.6686410
91 92 93 94 95 96
-9.7879650 -13.8078634 -14.0386235 -10.9781092 -11.1605750 -12.1244949
97 98 99 100 101 102
-5.5374429 -0.7742715 -3.5811716 1.1127896 5.0534295 1.8757036
103 104 105 106 107 108
5.4662000 2.9163732 -2.2250152 1.8829856 -5.9080256 -14.1841359
109 110 111 112 113 114
-0.5367063 64.7321394 56.9714702 47.0022362 40.7051565 38.9500156
115 116 117 118 119 120
34.1495245 23.0548683 6.3310379 6.3395595 7.4483146 9.7056512
121 122 123 124 125 126
13.4751987 7.7357131 4.5033908 -2.6795957 -10.2625823 -9.6468973
127 128 129 130 131 132
-10.6935464 -18.7226909 -13.3778318 -10.2977301 -25.9189569 -27.6682630
133 134 135 136 137 138
-13.9191642 -17.7488829 -21.5610436 -15.9191287 -16.9899249 -15.8774177
139 140 141 142 143 144
-7.4039052 -9.5057248 -6.3322122 -7.9261141 -12.8945939 -7.4152465
145 146 147 148 149 150
0.2280175 14.2206502 14.0830138 9.0030980 16.4721042 14.8140192
151 152 153 154 155 156
21.0983936 18.0095722 13.1149160 7.2979618 -7.6762992 -1.7202912
157 158 159 160 161 162
3.4505849 11.1267545 -0.5159624 -5.7730061 2.1960001 8.6143421
163 164 165 166 167 168
18.6066877 18.2178663 5.6581121 7.1886444 0.8303257 2.7226713
169 170 171 172 173 174
9.4083948 13.6604173 3.1113448 -1.2953217 -4.1244662 -3.7536107
175 176 177 178 179 180
-8.2769204 -14.6872319 -15.5760533 -18.0232765 -20.6882379 -23.6102190
181 182 183 184 185 186
-15.4351238 -6.8676796 -9.5785118 -10.7493080 -5.2389372 -8.0097333
187 188 189 190 191 192
1.3330429 3.2283327 -3.8307938 -7.7899203 -17.3867129 -19.5458394
193 194 195 196 197 198
-15.9290925 -5.5388833 -4.1675071 -8.0967051 -5.5319716 -2.8274356
199 200 201 202 203 204
-0.8995603 -18.0969806 -18.2749402 -25.5528997 -23.7393511 -18.0653179
205 206 207 208 209 210
-8.3050701 -21.8194742 -60.7401609 -58.9504724 -55.9822739 -52.0040215
211 212 213 214 215 216
24.1928304 100.6663089 71.2096253 64.9804273 68.1751428 65.3452440
217 218 219 220 221 222
74.5304468 59.3116434 50.1151380 48.6703382 40.7501528 45.8019417
223 224 225 226 227 228
45.7794398 54.5585536 51.3132331 43.8201926 37.9804198 31.4361407
229 230 231 232 233 234
29.6948799 25.5845149 21.9182251 24.6413605 14.4151066 15.4859621
235 236 237 238 239 240
4.0872668 -25.1638691 -35.0124208 -39.1909546 -45.8800631 -29.3794057
241 242 243 244 245 246
-17.1456215 -51.8233279 -115.3952872 -58.9701955 -84.1437363 -52.8705109
247 248 249 250 251 252
40.5165352 56.7020581 60.1034698 47.8810215 47.8272626 19.2335408
253 254 255 256 257 258
9.9229627 -9.0116030 24.8371687 13.7594428 26.7848216 20.0278315
259 260 261 262 263 264
16.1495848 11.2522715 18.1959092 9.0707503 -3.7693632 -9.9171071
265 266 267 268 269 270
-4.8443818 -0.5777455 1.5050132 2.7785258 8.2345338 0.2077593
271 272 273 274 275 276
10.8373038 15.9259509 19.8220485 28.2647712 -3.3974065 -25.9439826
277 278 279 280 281 282
14.6516684 37.4239060 30.4573290 32.8969275 29.2489499 28.8861785
283 284 285 286 287 288
30.4750592 37.2756631 27.8438615 22.9831194 12.6022157 11.8510604
289 290 291 292 293 294
23.0468914 33.7732581 31.6639880 17.4236410 6.4461487 31.9083857
295 296 297 298 299 300
26.2290977 19.4476733 15.1389239 24.6613050 15.8164517 9.5541474
301 302 303 304 305 306
11.7178066 14.9724861 -3.9779684 1.4265140 15.5995594 12.6635386
307 308 309 310 311 312
29.0633882 27.2148900 15.6747766 10.2610002 4.4193247 12.9335010
313 314 315 316 317 318
24.9610562 19.5462384 25.9966988 28.0863338 17.6287694 22.9747234
319 320 321 322 323 324
16.2653998 18.9697022 17.3707733 9.7357940 3.0588758 9.3389775
325 326 327 328 329 330
2.8985975 -1.7425038 0.8237919 1.7331213 -9.4562743 -28.2775547
331 332 333 334 335 336
-0.1150840 -2.4744977 -16.1947366 -17.9427142 -40.1184108 -58.9683982
337 338 339 340 341 342
-29.2434465 -66.4208124 -86.3066701 -49.6898367 -35.8796995 -14.7928481
343 344 345 346 347 348
-5.0314188 9.3678030 14.3185505 -4.5950994 -27.5900962 -34.0357038
349 350 351 352 353 354
-59.2939825 -47.8858746 -24.3056658 -27.9229071 -16.2016209 -22.6511070
355 356 357 358 359 360
-25.9001795 -33.7586053 -29.5853263 -30.9248119 -52.3772228 -72.0430990
> postscript(file="/var/www/html/freestat/rcomp/tmp/64sea1289489981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 360
Frequency = 1
lag(myerror, k = 1) myerror
0 -43.1134414 NA
1 -18.4272177 -43.1134414
2 1.1168335 -18.4272177
3 40.2232187 1.1168335
4 73.4476291 40.2232187
5 86.3391134 73.4476291
6 81.5818361 86.3391134
7 74.3025480 81.5818361
8 68.7012492 74.3025480
9 63.1362878 68.7012492
10 52.0206622 63.1362878
11 47.3180348 52.0206622
12 47.0056076 47.3180348
13 43.3626570 47.0056076
14 41.0398681 43.3626570
15 29.2417470 41.0398681
16 24.0059598 29.2417470
17 15.5325066 24.0059598
18 10.2213873 15.5325066
19 -4.5708990 10.2213873
20 -12.1098639 -4.5708990
21 -14.9331736 -12.1098639
22 -14.6896431 -14.9331736
23 -15.2721089 -14.6896431
24 -14.3598683 -15.2721089
25 -15.9226933 -14.3598683
26 -5.7522514 -15.9226933
27 -8.4477155 -5.7522514
28 -13.2909531 -8.4477155
29 -16.4307794 -13.2909531
30 1.5713331 -16.4307794
31 23.9097831 1.5713331
32 27.0771202 23.9097831
33 28.6383888 27.0771202
34 30.0328172 28.6383888
35 30.0877303 30.0328172
36 21.7803301 30.0877303
37 28.7310240 21.7803301
38 22.4037287 28.7310240
39 11.2978700 22.4037287
40 14.9310595 11.2978700
41 14.3772471 14.9310595
42 22.1571152 14.3772471
43 20.2006457 22.1571152
44 10.3818424 20.2006457
45 6.0585327 10.3818424
46 -6.1271109 6.0585327
47 -21.6953035 -6.1271109
48 -20.2915549 -21.6953035
49 -34.5408609 -20.2915549
50 -39.0103286 -34.5408609
51 -40.4681265 -39.0103286
52 -42.1129263 -40.4681265
53 -39.7187315 -42.1129263
54 -41.8433697 -39.7187315
55 -42.0550097 -41.8433697
56 -41.6231488 -42.0550097
57 -48.8746447 -41.6231488
58 -57.1648482 -48.8746447
59 -47.1908149 -57.1648482
60 -42.9310878 -47.1908149
61 -30.2180600 -42.9310878
62 -35.9597355 -30.2180600
63 -36.0605137 -35.9597355
64 -34.0968215 -36.0605137
65 -34.3012982 -34.0968215
66 -36.0201016 -34.3012982
67 -33.1434112 -36.0201016
68 -33.3057155 -33.1434112
69 -47.3439797 -33.3057155
70 -45.6314725 -47.3439797
71 -42.6319636 -45.6314725
72 -34.7027392 -42.6319636
73 -31.2435534 -34.7027392
74 -28.8077069 -31.2435534
75 -36.6042658 -28.8077069
76 -36.8588860 -36.6042658
77 -35.5548708 -36.8588860
78 -34.8073546 -35.5548708
79 -30.9961760 -34.8073546
80 -38.6065410 -30.9961760
81 -39.0996351 -38.6065410
82 -36.5165892 -39.0996351
83 -36.4807427 -36.5165892
84 -27.5841574 -36.4807427
85 -19.9048100 -27.5841574
86 -20.8482813 -19.9048100
87 -20.3055585 -20.8482813
88 -18.8790118 -20.3055585
89 -14.6686410 -18.8790118
90 -9.7879650 -14.6686410
91 -13.8078634 -9.7879650
92 -14.0386235 -13.8078634
93 -10.9781092 -14.0386235
94 -11.1605750 -10.9781092
95 -12.1244949 -11.1605750
96 -5.5374429 -12.1244949
97 -0.7742715 -5.5374429
98 -3.5811716 -0.7742715
99 1.1127896 -3.5811716
100 5.0534295 1.1127896
101 1.8757036 5.0534295
102 5.4662000 1.8757036
103 2.9163732 5.4662000
104 -2.2250152 2.9163732
105 1.8829856 -2.2250152
106 -5.9080256 1.8829856
107 -14.1841359 -5.9080256
108 -0.5367063 -14.1841359
109 64.7321394 -0.5367063
110 56.9714702 64.7321394
111 47.0022362 56.9714702
112 40.7051565 47.0022362
113 38.9500156 40.7051565
114 34.1495245 38.9500156
115 23.0548683 34.1495245
116 6.3310379 23.0548683
117 6.3395595 6.3310379
118 7.4483146 6.3395595
119 9.7056512 7.4483146
120 13.4751987 9.7056512
121 7.7357131 13.4751987
122 4.5033908 7.7357131
123 -2.6795957 4.5033908
124 -10.2625823 -2.6795957
125 -9.6468973 -10.2625823
126 -10.6935464 -9.6468973
127 -18.7226909 -10.6935464
128 -13.3778318 -18.7226909
129 -10.2977301 -13.3778318
130 -25.9189569 -10.2977301
131 -27.6682630 -25.9189569
132 -13.9191642 -27.6682630
133 -17.7488829 -13.9191642
134 -21.5610436 -17.7488829
135 -15.9191287 -21.5610436
136 -16.9899249 -15.9191287
137 -15.8774177 -16.9899249
138 -7.4039052 -15.8774177
139 -9.5057248 -7.4039052
140 -6.3322122 -9.5057248
141 -7.9261141 -6.3322122
142 -12.8945939 -7.9261141
143 -7.4152465 -12.8945939
144 0.2280175 -7.4152465
145 14.2206502 0.2280175
146 14.0830138 14.2206502
147 9.0030980 14.0830138
148 16.4721042 9.0030980
149 14.8140192 16.4721042
150 21.0983936 14.8140192
151 18.0095722 21.0983936
152 13.1149160 18.0095722
153 7.2979618 13.1149160
154 -7.6762992 7.2979618
155 -1.7202912 -7.6762992
156 3.4505849 -1.7202912
157 11.1267545 3.4505849
158 -0.5159624 11.1267545
159 -5.7730061 -0.5159624
160 2.1960001 -5.7730061
161 8.6143421 2.1960001
162 18.6066877 8.6143421
163 18.2178663 18.6066877
164 5.6581121 18.2178663
165 7.1886444 5.6581121
166 0.8303257 7.1886444
167 2.7226713 0.8303257
168 9.4083948 2.7226713
169 13.6604173 9.4083948
170 3.1113448 13.6604173
171 -1.2953217 3.1113448
172 -4.1244662 -1.2953217
173 -3.7536107 -4.1244662
174 -8.2769204 -3.7536107
175 -14.6872319 -8.2769204
176 -15.5760533 -14.6872319
177 -18.0232765 -15.5760533
178 -20.6882379 -18.0232765
179 -23.6102190 -20.6882379
180 -15.4351238 -23.6102190
181 -6.8676796 -15.4351238
182 -9.5785118 -6.8676796
183 -10.7493080 -9.5785118
184 -5.2389372 -10.7493080
185 -8.0097333 -5.2389372
186 1.3330429 -8.0097333
187 3.2283327 1.3330429
188 -3.8307938 3.2283327
189 -7.7899203 -3.8307938
190 -17.3867129 -7.7899203
191 -19.5458394 -17.3867129
192 -15.9290925 -19.5458394
193 -5.5388833 -15.9290925
194 -4.1675071 -5.5388833
195 -8.0967051 -4.1675071
196 -5.5319716 -8.0967051
197 -2.8274356 -5.5319716
198 -0.8995603 -2.8274356
199 -18.0969806 -0.8995603
200 -18.2749402 -18.0969806
201 -25.5528997 -18.2749402
202 -23.7393511 -25.5528997
203 -18.0653179 -23.7393511
204 -8.3050701 -18.0653179
205 -21.8194742 -8.3050701
206 -60.7401609 -21.8194742
207 -58.9504724 -60.7401609
208 -55.9822739 -58.9504724
209 -52.0040215 -55.9822739
210 24.1928304 -52.0040215
211 100.6663089 24.1928304
212 71.2096253 100.6663089
213 64.9804273 71.2096253
214 68.1751428 64.9804273
215 65.3452440 68.1751428
216 74.5304468 65.3452440
217 59.3116434 74.5304468
218 50.1151380 59.3116434
219 48.6703382 50.1151380
220 40.7501528 48.6703382
221 45.8019417 40.7501528
222 45.7794398 45.8019417
223 54.5585536 45.7794398
224 51.3132331 54.5585536
225 43.8201926 51.3132331
226 37.9804198 43.8201926
227 31.4361407 37.9804198
228 29.6948799 31.4361407
229 25.5845149 29.6948799
230 21.9182251 25.5845149
231 24.6413605 21.9182251
232 14.4151066 24.6413605
233 15.4859621 14.4151066
234 4.0872668 15.4859621
235 -25.1638691 4.0872668
236 -35.0124208 -25.1638691
237 -39.1909546 -35.0124208
238 -45.8800631 -39.1909546
239 -29.3794057 -45.8800631
240 -17.1456215 -29.3794057
241 -51.8233279 -17.1456215
242 -115.3952872 -51.8233279
243 -58.9701955 -115.3952872
244 -84.1437363 -58.9701955
245 -52.8705109 -84.1437363
246 40.5165352 -52.8705109
247 56.7020581 40.5165352
248 60.1034698 56.7020581
249 47.8810215 60.1034698
250 47.8272626 47.8810215
251 19.2335408 47.8272626
252 9.9229627 19.2335408
253 -9.0116030 9.9229627
254 24.8371687 -9.0116030
255 13.7594428 24.8371687
256 26.7848216 13.7594428
257 20.0278315 26.7848216
258 16.1495848 20.0278315
259 11.2522715 16.1495848
260 18.1959092 11.2522715
261 9.0707503 18.1959092
262 -3.7693632 9.0707503
263 -9.9171071 -3.7693632
264 -4.8443818 -9.9171071
265 -0.5777455 -4.8443818
266 1.5050132 -0.5777455
267 2.7785258 1.5050132
268 8.2345338 2.7785258
269 0.2077593 8.2345338
270 10.8373038 0.2077593
271 15.9259509 10.8373038
272 19.8220485 15.9259509
273 28.2647712 19.8220485
274 -3.3974065 28.2647712
275 -25.9439826 -3.3974065
276 14.6516684 -25.9439826
277 37.4239060 14.6516684
278 30.4573290 37.4239060
279 32.8969275 30.4573290
280 29.2489499 32.8969275
281 28.8861785 29.2489499
282 30.4750592 28.8861785
283 37.2756631 30.4750592
284 27.8438615 37.2756631
285 22.9831194 27.8438615
286 12.6022157 22.9831194
287 11.8510604 12.6022157
288 23.0468914 11.8510604
289 33.7732581 23.0468914
290 31.6639880 33.7732581
291 17.4236410 31.6639880
292 6.4461487 17.4236410
293 31.9083857 6.4461487
294 26.2290977 31.9083857
295 19.4476733 26.2290977
296 15.1389239 19.4476733
297 24.6613050 15.1389239
298 15.8164517 24.6613050
299 9.5541474 15.8164517
300 11.7178066 9.5541474
301 14.9724861 11.7178066
302 -3.9779684 14.9724861
303 1.4265140 -3.9779684
304 15.5995594 1.4265140
305 12.6635386 15.5995594
306 29.0633882 12.6635386
307 27.2148900 29.0633882
308 15.6747766 27.2148900
309 10.2610002 15.6747766
310 4.4193247 10.2610002
311 12.9335010 4.4193247
312 24.9610562 12.9335010
313 19.5462384 24.9610562
314 25.9966988 19.5462384
315 28.0863338 25.9966988
316 17.6287694 28.0863338
317 22.9747234 17.6287694
318 16.2653998 22.9747234
319 18.9697022 16.2653998
320 17.3707733 18.9697022
321 9.7357940 17.3707733
322 3.0588758 9.7357940
323 9.3389775 3.0588758
324 2.8985975 9.3389775
325 -1.7425038 2.8985975
326 0.8237919 -1.7425038
327 1.7331213 0.8237919
328 -9.4562743 1.7331213
329 -28.2775547 -9.4562743
330 -0.1150840 -28.2775547
331 -2.4744977 -0.1150840
332 -16.1947366 -2.4744977
333 -17.9427142 -16.1947366
334 -40.1184108 -17.9427142
335 -58.9683982 -40.1184108
336 -29.2434465 -58.9683982
337 -66.4208124 -29.2434465
338 -86.3066701 -66.4208124
339 -49.6898367 -86.3066701
340 -35.8796995 -49.6898367
341 -14.7928481 -35.8796995
342 -5.0314188 -14.7928481
343 9.3678030 -5.0314188
344 14.3185505 9.3678030
345 -4.5950994 14.3185505
346 -27.5900962 -4.5950994
347 -34.0357038 -27.5900962
348 -59.2939825 -34.0357038
349 -47.8858746 -59.2939825
350 -24.3056658 -47.8858746
351 -27.9229071 -24.3056658
352 -16.2016209 -27.9229071
353 -22.6511070 -16.2016209
354 -25.9001795 -22.6511070
355 -33.7586053 -25.9001795
356 -29.5853263 -33.7586053
357 -30.9248119 -29.5853263
358 -52.3772228 -30.9248119
359 -72.0430990 -52.3772228
360 NA -72.0430990
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -18.4272177 -43.1134414
[2,] 1.1168335 -18.4272177
[3,] 40.2232187 1.1168335
[4,] 73.4476291 40.2232187
[5,] 86.3391134 73.4476291
[6,] 81.5818361 86.3391134
[7,] 74.3025480 81.5818361
[8,] 68.7012492 74.3025480
[9,] 63.1362878 68.7012492
[10,] 52.0206622 63.1362878
[11,] 47.3180348 52.0206622
[12,] 47.0056076 47.3180348
[13,] 43.3626570 47.0056076
[14,] 41.0398681 43.3626570
[15,] 29.2417470 41.0398681
[16,] 24.0059598 29.2417470
[17,] 15.5325066 24.0059598
[18,] 10.2213873 15.5325066
[19,] -4.5708990 10.2213873
[20,] -12.1098639 -4.5708990
[21,] -14.9331736 -12.1098639
[22,] -14.6896431 -14.9331736
[23,] -15.2721089 -14.6896431
[24,] -14.3598683 -15.2721089
[25,] -15.9226933 -14.3598683
[26,] -5.7522514 -15.9226933
[27,] -8.4477155 -5.7522514
[28,] -13.2909531 -8.4477155
[29,] -16.4307794 -13.2909531
[30,] 1.5713331 -16.4307794
[31,] 23.9097831 1.5713331
[32,] 27.0771202 23.9097831
[33,] 28.6383888 27.0771202
[34,] 30.0328172 28.6383888
[35,] 30.0877303 30.0328172
[36,] 21.7803301 30.0877303
[37,] 28.7310240 21.7803301
[38,] 22.4037287 28.7310240
[39,] 11.2978700 22.4037287
[40,] 14.9310595 11.2978700
[41,] 14.3772471 14.9310595
[42,] 22.1571152 14.3772471
[43,] 20.2006457 22.1571152
[44,] 10.3818424 20.2006457
[45,] 6.0585327 10.3818424
[46,] -6.1271109 6.0585327
[47,] -21.6953035 -6.1271109
[48,] -20.2915549 -21.6953035
[49,] -34.5408609 -20.2915549
[50,] -39.0103286 -34.5408609
[51,] -40.4681265 -39.0103286
[52,] -42.1129263 -40.4681265
[53,] -39.7187315 -42.1129263
[54,] -41.8433697 -39.7187315
[55,] -42.0550097 -41.8433697
[56,] -41.6231488 -42.0550097
[57,] -48.8746447 -41.6231488
[58,] -57.1648482 -48.8746447
[59,] -47.1908149 -57.1648482
[60,] -42.9310878 -47.1908149
[61,] -30.2180600 -42.9310878
[62,] -35.9597355 -30.2180600
[63,] -36.0605137 -35.9597355
[64,] -34.0968215 -36.0605137
[65,] -34.3012982 -34.0968215
[66,] -36.0201016 -34.3012982
[67,] -33.1434112 -36.0201016
[68,] -33.3057155 -33.1434112
[69,] -47.3439797 -33.3057155
[70,] -45.6314725 -47.3439797
[71,] -42.6319636 -45.6314725
[72,] -34.7027392 -42.6319636
[73,] -31.2435534 -34.7027392
[74,] -28.8077069 -31.2435534
[75,] -36.6042658 -28.8077069
[76,] -36.8588860 -36.6042658
[77,] -35.5548708 -36.8588860
[78,] -34.8073546 -35.5548708
[79,] -30.9961760 -34.8073546
[80,] -38.6065410 -30.9961760
[81,] -39.0996351 -38.6065410
[82,] -36.5165892 -39.0996351
[83,] -36.4807427 -36.5165892
[84,] -27.5841574 -36.4807427
[85,] -19.9048100 -27.5841574
[86,] -20.8482813 -19.9048100
[87,] -20.3055585 -20.8482813
[88,] -18.8790118 -20.3055585
[89,] -14.6686410 -18.8790118
[90,] -9.7879650 -14.6686410
[91,] -13.8078634 -9.7879650
[92,] -14.0386235 -13.8078634
[93,] -10.9781092 -14.0386235
[94,] -11.1605750 -10.9781092
[95,] -12.1244949 -11.1605750
[96,] -5.5374429 -12.1244949
[97,] -0.7742715 -5.5374429
[98,] -3.5811716 -0.7742715
[99,] 1.1127896 -3.5811716
[100,] 5.0534295 1.1127896
[101,] 1.8757036 5.0534295
[102,] 5.4662000 1.8757036
[103,] 2.9163732 5.4662000
[104,] -2.2250152 2.9163732
[105,] 1.8829856 -2.2250152
[106,] -5.9080256 1.8829856
[107,] -14.1841359 -5.9080256
[108,] -0.5367063 -14.1841359
[109,] 64.7321394 -0.5367063
[110,] 56.9714702 64.7321394
[111,] 47.0022362 56.9714702
[112,] 40.7051565 47.0022362
[113,] 38.9500156 40.7051565
[114,] 34.1495245 38.9500156
[115,] 23.0548683 34.1495245
[116,] 6.3310379 23.0548683
[117,] 6.3395595 6.3310379
[118,] 7.4483146 6.3395595
[119,] 9.7056512 7.4483146
[120,] 13.4751987 9.7056512
[121,] 7.7357131 13.4751987
[122,] 4.5033908 7.7357131
[123,] -2.6795957 4.5033908
[124,] -10.2625823 -2.6795957
[125,] -9.6468973 -10.2625823
[126,] -10.6935464 -9.6468973
[127,] -18.7226909 -10.6935464
[128,] -13.3778318 -18.7226909
[129,] -10.2977301 -13.3778318
[130,] -25.9189569 -10.2977301
[131,] -27.6682630 -25.9189569
[132,] -13.9191642 -27.6682630
[133,] -17.7488829 -13.9191642
[134,] -21.5610436 -17.7488829
[135,] -15.9191287 -21.5610436
[136,] -16.9899249 -15.9191287
[137,] -15.8774177 -16.9899249
[138,] -7.4039052 -15.8774177
[139,] -9.5057248 -7.4039052
[140,] -6.3322122 -9.5057248
[141,] -7.9261141 -6.3322122
[142,] -12.8945939 -7.9261141
[143,] -7.4152465 -12.8945939
[144,] 0.2280175 -7.4152465
[145,] 14.2206502 0.2280175
[146,] 14.0830138 14.2206502
[147,] 9.0030980 14.0830138
[148,] 16.4721042 9.0030980
[149,] 14.8140192 16.4721042
[150,] 21.0983936 14.8140192
[151,] 18.0095722 21.0983936
[152,] 13.1149160 18.0095722
[153,] 7.2979618 13.1149160
[154,] -7.6762992 7.2979618
[155,] -1.7202912 -7.6762992
[156,] 3.4505849 -1.7202912
[157,] 11.1267545 3.4505849
[158,] -0.5159624 11.1267545
[159,] -5.7730061 -0.5159624
[160,] 2.1960001 -5.7730061
[161,] 8.6143421 2.1960001
[162,] 18.6066877 8.6143421
[163,] 18.2178663 18.6066877
[164,] 5.6581121 18.2178663
[165,] 7.1886444 5.6581121
[166,] 0.8303257 7.1886444
[167,] 2.7226713 0.8303257
[168,] 9.4083948 2.7226713
[169,] 13.6604173 9.4083948
[170,] 3.1113448 13.6604173
[171,] -1.2953217 3.1113448
[172,] -4.1244662 -1.2953217
[173,] -3.7536107 -4.1244662
[174,] -8.2769204 -3.7536107
[175,] -14.6872319 -8.2769204
[176,] -15.5760533 -14.6872319
[177,] -18.0232765 -15.5760533
[178,] -20.6882379 -18.0232765
[179,] -23.6102190 -20.6882379
[180,] -15.4351238 -23.6102190
[181,] -6.8676796 -15.4351238
[182,] -9.5785118 -6.8676796
[183,] -10.7493080 -9.5785118
[184,] -5.2389372 -10.7493080
[185,] -8.0097333 -5.2389372
[186,] 1.3330429 -8.0097333
[187,] 3.2283327 1.3330429
[188,] -3.8307938 3.2283327
[189,] -7.7899203 -3.8307938
[190,] -17.3867129 -7.7899203
[191,] -19.5458394 -17.3867129
[192,] -15.9290925 -19.5458394
[193,] -5.5388833 -15.9290925
[194,] -4.1675071 -5.5388833
[195,] -8.0967051 -4.1675071
[196,] -5.5319716 -8.0967051
[197,] -2.8274356 -5.5319716
[198,] -0.8995603 -2.8274356
[199,] -18.0969806 -0.8995603
[200,] -18.2749402 -18.0969806
[201,] -25.5528997 -18.2749402
[202,] -23.7393511 -25.5528997
[203,] -18.0653179 -23.7393511
[204,] -8.3050701 -18.0653179
[205,] -21.8194742 -8.3050701
[206,] -60.7401609 -21.8194742
[207,] -58.9504724 -60.7401609
[208,] -55.9822739 -58.9504724
[209,] -52.0040215 -55.9822739
[210,] 24.1928304 -52.0040215
[211,] 100.6663089 24.1928304
[212,] 71.2096253 100.6663089
[213,] 64.9804273 71.2096253
[214,] 68.1751428 64.9804273
[215,] 65.3452440 68.1751428
[216,] 74.5304468 65.3452440
[217,] 59.3116434 74.5304468
[218,] 50.1151380 59.3116434
[219,] 48.6703382 50.1151380
[220,] 40.7501528 48.6703382
[221,] 45.8019417 40.7501528
[222,] 45.7794398 45.8019417
[223,] 54.5585536 45.7794398
[224,] 51.3132331 54.5585536
[225,] 43.8201926 51.3132331
[226,] 37.9804198 43.8201926
[227,] 31.4361407 37.9804198
[228,] 29.6948799 31.4361407
[229,] 25.5845149 29.6948799
[230,] 21.9182251 25.5845149
[231,] 24.6413605 21.9182251
[232,] 14.4151066 24.6413605
[233,] 15.4859621 14.4151066
[234,] 4.0872668 15.4859621
[235,] -25.1638691 4.0872668
[236,] -35.0124208 -25.1638691
[237,] -39.1909546 -35.0124208
[238,] -45.8800631 -39.1909546
[239,] -29.3794057 -45.8800631
[240,] -17.1456215 -29.3794057
[241,] -51.8233279 -17.1456215
[242,] -115.3952872 -51.8233279
[243,] -58.9701955 -115.3952872
[244,] -84.1437363 -58.9701955
[245,] -52.8705109 -84.1437363
[246,] 40.5165352 -52.8705109
[247,] 56.7020581 40.5165352
[248,] 60.1034698 56.7020581
[249,] 47.8810215 60.1034698
[250,] 47.8272626 47.8810215
[251,] 19.2335408 47.8272626
[252,] 9.9229627 19.2335408
[253,] -9.0116030 9.9229627
[254,] 24.8371687 -9.0116030
[255,] 13.7594428 24.8371687
[256,] 26.7848216 13.7594428
[257,] 20.0278315 26.7848216
[258,] 16.1495848 20.0278315
[259,] 11.2522715 16.1495848
[260,] 18.1959092 11.2522715
[261,] 9.0707503 18.1959092
[262,] -3.7693632 9.0707503
[263,] -9.9171071 -3.7693632
[264,] -4.8443818 -9.9171071
[265,] -0.5777455 -4.8443818
[266,] 1.5050132 -0.5777455
[267,] 2.7785258 1.5050132
[268,] 8.2345338 2.7785258
[269,] 0.2077593 8.2345338
[270,] 10.8373038 0.2077593
[271,] 15.9259509 10.8373038
[272,] 19.8220485 15.9259509
[273,] 28.2647712 19.8220485
[274,] -3.3974065 28.2647712
[275,] -25.9439826 -3.3974065
[276,] 14.6516684 -25.9439826
[277,] 37.4239060 14.6516684
[278,] 30.4573290 37.4239060
[279,] 32.8969275 30.4573290
[280,] 29.2489499 32.8969275
[281,] 28.8861785 29.2489499
[282,] 30.4750592 28.8861785
[283,] 37.2756631 30.4750592
[284,] 27.8438615 37.2756631
[285,] 22.9831194 27.8438615
[286,] 12.6022157 22.9831194
[287,] 11.8510604 12.6022157
[288,] 23.0468914 11.8510604
[289,] 33.7732581 23.0468914
[290,] 31.6639880 33.7732581
[291,] 17.4236410 31.6639880
[292,] 6.4461487 17.4236410
[293,] 31.9083857 6.4461487
[294,] 26.2290977 31.9083857
[295,] 19.4476733 26.2290977
[296,] 15.1389239 19.4476733
[297,] 24.6613050 15.1389239
[298,] 15.8164517 24.6613050
[299,] 9.5541474 15.8164517
[300,] 11.7178066 9.5541474
[301,] 14.9724861 11.7178066
[302,] -3.9779684 14.9724861
[303,] 1.4265140 -3.9779684
[304,] 15.5995594 1.4265140
[305,] 12.6635386 15.5995594
[306,] 29.0633882 12.6635386
[307,] 27.2148900 29.0633882
[308,] 15.6747766 27.2148900
[309,] 10.2610002 15.6747766
[310,] 4.4193247 10.2610002
[311,] 12.9335010 4.4193247
[312,] 24.9610562 12.9335010
[313,] 19.5462384 24.9610562
[314,] 25.9966988 19.5462384
[315,] 28.0863338 25.9966988
[316,] 17.6287694 28.0863338
[317,] 22.9747234 17.6287694
[318,] 16.2653998 22.9747234
[319,] 18.9697022 16.2653998
[320,] 17.3707733 18.9697022
[321,] 9.7357940 17.3707733
[322,] 3.0588758 9.7357940
[323,] 9.3389775 3.0588758
[324,] 2.8985975 9.3389775
[325,] -1.7425038 2.8985975
[326,] 0.8237919 -1.7425038
[327,] 1.7331213 0.8237919
[328,] -9.4562743 1.7331213
[329,] -28.2775547 -9.4562743
[330,] -0.1150840 -28.2775547
[331,] -2.4744977 -0.1150840
[332,] -16.1947366 -2.4744977
[333,] -17.9427142 -16.1947366
[334,] -40.1184108 -17.9427142
[335,] -58.9683982 -40.1184108
[336,] -29.2434465 -58.9683982
[337,] -66.4208124 -29.2434465
[338,] -86.3066701 -66.4208124
[339,] -49.6898367 -86.3066701
[340,] -35.8796995 -49.6898367
[341,] -14.7928481 -35.8796995
[342,] -5.0314188 -14.7928481
[343,] 9.3678030 -5.0314188
[344,] 14.3185505 9.3678030
[345,] -4.5950994 14.3185505
[346,] -27.5900962 -4.5950994
[347,] -34.0357038 -27.5900962
[348,] -59.2939825 -34.0357038
[349,] -47.8858746 -59.2939825
[350,] -24.3056658 -47.8858746
[351,] -27.9229071 -24.3056658
[352,] -16.2016209 -27.9229071
[353,] -22.6511070 -16.2016209
[354,] -25.9001795 -22.6511070
[355,] -33.7586053 -25.9001795
[356,] -29.5853263 -33.7586053
[357,] -30.9248119 -29.5853263
[358,] -52.3772228 -30.9248119
[359,] -72.0430990 -52.3772228
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -18.4272177 -43.1134414
2 1.1168335 -18.4272177
3 40.2232187 1.1168335
4 73.4476291 40.2232187
5 86.3391134 73.4476291
6 81.5818361 86.3391134
7 74.3025480 81.5818361
8 68.7012492 74.3025480
9 63.1362878 68.7012492
10 52.0206622 63.1362878
11 47.3180348 52.0206622
12 47.0056076 47.3180348
13 43.3626570 47.0056076
14 41.0398681 43.3626570
15 29.2417470 41.0398681
16 24.0059598 29.2417470
17 15.5325066 24.0059598
18 10.2213873 15.5325066
19 -4.5708990 10.2213873
20 -12.1098639 -4.5708990
21 -14.9331736 -12.1098639
22 -14.6896431 -14.9331736
23 -15.2721089 -14.6896431
24 -14.3598683 -15.2721089
25 -15.9226933 -14.3598683
26 -5.7522514 -15.9226933
27 -8.4477155 -5.7522514
28 -13.2909531 -8.4477155
29 -16.4307794 -13.2909531
30 1.5713331 -16.4307794
31 23.9097831 1.5713331
32 27.0771202 23.9097831
33 28.6383888 27.0771202
34 30.0328172 28.6383888
35 30.0877303 30.0328172
36 21.7803301 30.0877303
37 28.7310240 21.7803301
38 22.4037287 28.7310240
39 11.2978700 22.4037287
40 14.9310595 11.2978700
41 14.3772471 14.9310595
42 22.1571152 14.3772471
43 20.2006457 22.1571152
44 10.3818424 20.2006457
45 6.0585327 10.3818424
46 -6.1271109 6.0585327
47 -21.6953035 -6.1271109
48 -20.2915549 -21.6953035
49 -34.5408609 -20.2915549
50 -39.0103286 -34.5408609
51 -40.4681265 -39.0103286
52 -42.1129263 -40.4681265
53 -39.7187315 -42.1129263
54 -41.8433697 -39.7187315
55 -42.0550097 -41.8433697
56 -41.6231488 -42.0550097
57 -48.8746447 -41.6231488
58 -57.1648482 -48.8746447
59 -47.1908149 -57.1648482
60 -42.9310878 -47.1908149
61 -30.2180600 -42.9310878
62 -35.9597355 -30.2180600
63 -36.0605137 -35.9597355
64 -34.0968215 -36.0605137
65 -34.3012982 -34.0968215
66 -36.0201016 -34.3012982
67 -33.1434112 -36.0201016
68 -33.3057155 -33.1434112
69 -47.3439797 -33.3057155
70 -45.6314725 -47.3439797
71 -42.6319636 -45.6314725
72 -34.7027392 -42.6319636
73 -31.2435534 -34.7027392
74 -28.8077069 -31.2435534
75 -36.6042658 -28.8077069
76 -36.8588860 -36.6042658
77 -35.5548708 -36.8588860
78 -34.8073546 -35.5548708
79 -30.9961760 -34.8073546
80 -38.6065410 -30.9961760
81 -39.0996351 -38.6065410
82 -36.5165892 -39.0996351
83 -36.4807427 -36.5165892
84 -27.5841574 -36.4807427
85 -19.9048100 -27.5841574
86 -20.8482813 -19.9048100
87 -20.3055585 -20.8482813
88 -18.8790118 -20.3055585
89 -14.6686410 -18.8790118
90 -9.7879650 -14.6686410
91 -13.8078634 -9.7879650
92 -14.0386235 -13.8078634
93 -10.9781092 -14.0386235
94 -11.1605750 -10.9781092
95 -12.1244949 -11.1605750
96 -5.5374429 -12.1244949
97 -0.7742715 -5.5374429
98 -3.5811716 -0.7742715
99 1.1127896 -3.5811716
100 5.0534295 1.1127896
101 1.8757036 5.0534295
102 5.4662000 1.8757036
103 2.9163732 5.4662000
104 -2.2250152 2.9163732
105 1.8829856 -2.2250152
106 -5.9080256 1.8829856
107 -14.1841359 -5.9080256
108 -0.5367063 -14.1841359
109 64.7321394 -0.5367063
110 56.9714702 64.7321394
111 47.0022362 56.9714702
112 40.7051565 47.0022362
113 38.9500156 40.7051565
114 34.1495245 38.9500156
115 23.0548683 34.1495245
116 6.3310379 23.0548683
117 6.3395595 6.3310379
118 7.4483146 6.3395595
119 9.7056512 7.4483146
120 13.4751987 9.7056512
121 7.7357131 13.4751987
122 4.5033908 7.7357131
123 -2.6795957 4.5033908
124 -10.2625823 -2.6795957
125 -9.6468973 -10.2625823
126 -10.6935464 -9.6468973
127 -18.7226909 -10.6935464
128 -13.3778318 -18.7226909
129 -10.2977301 -13.3778318
130 -25.9189569 -10.2977301
131 -27.6682630 -25.9189569
132 -13.9191642 -27.6682630
133 -17.7488829 -13.9191642
134 -21.5610436 -17.7488829
135 -15.9191287 -21.5610436
136 -16.9899249 -15.9191287
137 -15.8774177 -16.9899249
138 -7.4039052 -15.8774177
139 -9.5057248 -7.4039052
140 -6.3322122 -9.5057248
141 -7.9261141 -6.3322122
142 -12.8945939 -7.9261141
143 -7.4152465 -12.8945939
144 0.2280175 -7.4152465
145 14.2206502 0.2280175
146 14.0830138 14.2206502
147 9.0030980 14.0830138
148 16.4721042 9.0030980
149 14.8140192 16.4721042
150 21.0983936 14.8140192
151 18.0095722 21.0983936
152 13.1149160 18.0095722
153 7.2979618 13.1149160
154 -7.6762992 7.2979618
155 -1.7202912 -7.6762992
156 3.4505849 -1.7202912
157 11.1267545 3.4505849
158 -0.5159624 11.1267545
159 -5.7730061 -0.5159624
160 2.1960001 -5.7730061
161 8.6143421 2.1960001
162 18.6066877 8.6143421
163 18.2178663 18.6066877
164 5.6581121 18.2178663
165 7.1886444 5.6581121
166 0.8303257 7.1886444
167 2.7226713 0.8303257
168 9.4083948 2.7226713
169 13.6604173 9.4083948
170 3.1113448 13.6604173
171 -1.2953217 3.1113448
172 -4.1244662 -1.2953217
173 -3.7536107 -4.1244662
174 -8.2769204 -3.7536107
175 -14.6872319 -8.2769204
176 -15.5760533 -14.6872319
177 -18.0232765 -15.5760533
178 -20.6882379 -18.0232765
179 -23.6102190 -20.6882379
180 -15.4351238 -23.6102190
181 -6.8676796 -15.4351238
182 -9.5785118 -6.8676796
183 -10.7493080 -9.5785118
184 -5.2389372 -10.7493080
185 -8.0097333 -5.2389372
186 1.3330429 -8.0097333
187 3.2283327 1.3330429
188 -3.8307938 3.2283327
189 -7.7899203 -3.8307938
190 -17.3867129 -7.7899203
191 -19.5458394 -17.3867129
192 -15.9290925 -19.5458394
193 -5.5388833 -15.9290925
194 -4.1675071 -5.5388833
195 -8.0967051 -4.1675071
196 -5.5319716 -8.0967051
197 -2.8274356 -5.5319716
198 -0.8995603 -2.8274356
199 -18.0969806 -0.8995603
200 -18.2749402 -18.0969806
201 -25.5528997 -18.2749402
202 -23.7393511 -25.5528997
203 -18.0653179 -23.7393511
204 -8.3050701 -18.0653179
205 -21.8194742 -8.3050701
206 -60.7401609 -21.8194742
207 -58.9504724 -60.7401609
208 -55.9822739 -58.9504724
209 -52.0040215 -55.9822739
210 24.1928304 -52.0040215
211 100.6663089 24.1928304
212 71.2096253 100.6663089
213 64.9804273 71.2096253
214 68.1751428 64.9804273
215 65.3452440 68.1751428
216 74.5304468 65.3452440
217 59.3116434 74.5304468
218 50.1151380 59.3116434
219 48.6703382 50.1151380
220 40.7501528 48.6703382
221 45.8019417 40.7501528
222 45.7794398 45.8019417
223 54.5585536 45.7794398
224 51.3132331 54.5585536
225 43.8201926 51.3132331
226 37.9804198 43.8201926
227 31.4361407 37.9804198
228 29.6948799 31.4361407
229 25.5845149 29.6948799
230 21.9182251 25.5845149
231 24.6413605 21.9182251
232 14.4151066 24.6413605
233 15.4859621 14.4151066
234 4.0872668 15.4859621
235 -25.1638691 4.0872668
236 -35.0124208 -25.1638691
237 -39.1909546 -35.0124208
238 -45.8800631 -39.1909546
239 -29.3794057 -45.8800631
240 -17.1456215 -29.3794057
241 -51.8233279 -17.1456215
242 -115.3952872 -51.8233279
243 -58.9701955 -115.3952872
244 -84.1437363 -58.9701955
245 -52.8705109 -84.1437363
246 40.5165352 -52.8705109
247 56.7020581 40.5165352
248 60.1034698 56.7020581
249 47.8810215 60.1034698
250 47.8272626 47.8810215
251 19.2335408 47.8272626
252 9.9229627 19.2335408
253 -9.0116030 9.9229627
254 24.8371687 -9.0116030
255 13.7594428 24.8371687
256 26.7848216 13.7594428
257 20.0278315 26.7848216
258 16.1495848 20.0278315
259 11.2522715 16.1495848
260 18.1959092 11.2522715
261 9.0707503 18.1959092
262 -3.7693632 9.0707503
263 -9.9171071 -3.7693632
264 -4.8443818 -9.9171071
265 -0.5777455 -4.8443818
266 1.5050132 -0.5777455
267 2.7785258 1.5050132
268 8.2345338 2.7785258
269 0.2077593 8.2345338
270 10.8373038 0.2077593
271 15.9259509 10.8373038
272 19.8220485 15.9259509
273 28.2647712 19.8220485
274 -3.3974065 28.2647712
275 -25.9439826 -3.3974065
276 14.6516684 -25.9439826
277 37.4239060 14.6516684
278 30.4573290 37.4239060
279 32.8969275 30.4573290
280 29.2489499 32.8969275
281 28.8861785 29.2489499
282 30.4750592 28.8861785
283 37.2756631 30.4750592
284 27.8438615 37.2756631
285 22.9831194 27.8438615
286 12.6022157 22.9831194
287 11.8510604 12.6022157
288 23.0468914 11.8510604
289 33.7732581 23.0468914
290 31.6639880 33.7732581
291 17.4236410 31.6639880
292 6.4461487 17.4236410
293 31.9083857 6.4461487
294 26.2290977 31.9083857
295 19.4476733 26.2290977
296 15.1389239 19.4476733
297 24.6613050 15.1389239
298 15.8164517 24.6613050
299 9.5541474 15.8164517
300 11.7178066 9.5541474
301 14.9724861 11.7178066
302 -3.9779684 14.9724861
303 1.4265140 -3.9779684
304 15.5995594 1.4265140
305 12.6635386 15.5995594
306 29.0633882 12.6635386
307 27.2148900 29.0633882
308 15.6747766 27.2148900
309 10.2610002 15.6747766
310 4.4193247 10.2610002
311 12.9335010 4.4193247
312 24.9610562 12.9335010
313 19.5462384 24.9610562
314 25.9966988 19.5462384
315 28.0863338 25.9966988
316 17.6287694 28.0863338
317 22.9747234 17.6287694
318 16.2653998 22.9747234
319 18.9697022 16.2653998
320 17.3707733 18.9697022
321 9.7357940 17.3707733
322 3.0588758 9.7357940
323 9.3389775 3.0588758
324 2.8985975 9.3389775
325 -1.7425038 2.8985975
326 0.8237919 -1.7425038
327 1.7331213 0.8237919
328 -9.4562743 1.7331213
329 -28.2775547 -9.4562743
330 -0.1150840 -28.2775547
331 -2.4744977 -0.1150840
332 -16.1947366 -2.4744977
333 -17.9427142 -16.1947366
334 -40.1184108 -17.9427142
335 -58.9683982 -40.1184108
336 -29.2434465 -58.9683982
337 -66.4208124 -29.2434465
338 -86.3066701 -66.4208124
339 -49.6898367 -86.3066701
340 -35.8796995 -49.6898367
341 -14.7928481 -35.8796995
342 -5.0314188 -14.7928481
343 9.3678030 -5.0314188
344 14.3185505 9.3678030
345 -4.5950994 14.3185505
346 -27.5900962 -4.5950994
347 -34.0357038 -27.5900962
348 -59.2939825 -34.0357038
349 -47.8858746 -59.2939825
350 -24.3056658 -47.8858746
351 -27.9229071 -24.3056658
352 -16.2016209 -27.9229071
353 -22.6511070 -16.2016209
354 -25.9001795 -22.6511070
355 -33.7586053 -25.9001795
356 -29.5853263 -33.7586053
357 -30.9248119 -29.5853263
358 -52.3772228 -30.9248119
359 -72.0430990 -52.3772228
> 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/html/freestat/rcomp/tmp/7x1vv1289489981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8x1vv1289489981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9x1vv1289489981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/108tdg1289489981.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/html/freestat/rcomp/tmp/11tbb41289489981.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/html/freestat/rcomp/tmp/12pmun1289489982.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/html/freestat/rcomp/tmp/13lvae1289489982.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/html/freestat/rcomp/tmp/14bhyq1289489982.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/html/freestat/rcomp/tmp/15ae7p1289489982.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/html/freestat/rcomp/tmp/16o6ny1289489982.tab")
+ }
>
> try(system("convert tmp/1j9g41289489981.ps tmp/1j9g41289489981.png",intern=TRUE))
character(0)
> try(system("convert tmp/2u1xp1289489981.ps tmp/2u1xp1289489981.png",intern=TRUE))
character(0)
> try(system("convert tmp/3u1xp1289489981.ps tmp/3u1xp1289489981.png",intern=TRUE))
character(0)
> try(system("convert tmp/4u1xp1289489981.ps tmp/4u1xp1289489981.png",intern=TRUE))
character(0)
> try(system("convert tmp/5u1xp1289489981.ps tmp/5u1xp1289489981.png",intern=TRUE))
character(0)
> try(system("convert tmp/64sea1289489981.ps tmp/64sea1289489981.png",intern=TRUE))
character(0)
> try(system("convert tmp/7x1vv1289489981.ps tmp/7x1vv1289489981.png",intern=TRUE))
character(0)
> try(system("convert tmp/8x1vv1289489981.ps tmp/8x1vv1289489981.png",intern=TRUE))
character(0)
> try(system("convert tmp/9x1vv1289489981.ps tmp/9x1vv1289489981.png",intern=TRUE))
character(0)
> try(system("convert tmp/108tdg1289489981.ps tmp/108tdg1289489981.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
10.659 3.140 11.091