R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
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(87.28
+ ,87.28
+ ,87.09
+ ,86.92
+ ,87.59
+ ,90.72
+ ,90.69
+ ,90.3
+ ,89.55
+ ,88.94
+ ,88.41
+ ,87.82
+ ,87.07
+ ,86.82
+ ,86.4
+ ,86.02
+ ,85.66
+ ,85.32
+ ,85
+ ,84.67
+ ,83.94
+ ,82.83
+ ,81.95
+ ,81.19
+ ,80.48
+ ,78.86
+ ,69.47
+ ,68.77
+ ,70.06
+ ,73.95
+ ,75.8
+ ,77.79
+ ,81.57
+ ,83.07
+ ,84.34
+ ,85.1
+ ,85.25
+ ,84.26
+ ,83.63
+ ,86.44
+ ,85.3
+ ,84.1
+ ,83.36
+ ,82.48
+ ,81.58
+ ,80.47
+ ,79.34
+ ,82.13
+ ,81.69
+ ,80.7
+ ,79.88
+ ,79.16
+ ,78.38
+ ,77.42
+ ,76.47
+ ,75.46
+ ,74.48
+ ,78.27
+ ,80.7
+ ,79.91
+ ,78.75
+ ,77.78
+ ,81.14
+ ,81.08
+ ,80.03
+ ,78.91
+ ,78.01
+ ,76.9
+ ,75.97
+ ,81.93
+ ,80.27
+ ,78.67
+ ,77.42
+ ,76.16
+ ,74.7
+ ,76.39
+ ,76.04
+ ,74.65
+ ,73.29
+ ,71.79
+ ,74.39
+ ,74.91
+ ,74.54
+ ,73.08
+ ,72.75
+ ,71.32
+ ,70.38
+ ,70.35
+ ,70.01
+ ,69.36
+ ,67.77
+ ,69.26
+ ,69.8
+ ,68.38
+ ,67.62
+ ,68.39
+ ,66.95
+ ,65.21
+ ,66.64
+ ,63.45
+ ,60.66
+ ,62.34
+ ,60.32
+ ,58.64
+ ,60.46
+ ,58.59
+ ,61.87
+ ,61.85
+ ,67.44
+ ,77.06
+ ,91.74
+ ,93.15
+ ,94.15
+ ,93.11
+ ,91.51
+ ,89.96
+ ,88.16
+ ,86.98
+ ,88.03
+ ,86.24
+ ,84.65
+ ,83.23
+ ,81.7
+ ,80.25
+ ,78.8
+ ,77.51
+ ,76.2
+ ,75.04
+ ,74
+ ,75.49
+ ,77.14
+ ,76.15
+ ,76.27
+ ,78.19
+ ,76.49
+ ,77.31
+ ,76.65
+ ,74.99
+ ,73.51
+ ,72.07
+ ,70.59
+ ,71.96
+ ,76.29
+ ,74.86
+ ,74.93
+ ,71.9
+ ,71.01
+ ,77.47
+ ,75.78
+ ,76.6
+ ,76.07
+ ,74.57
+ ,73.02
+ ,72.65
+ ,73.16
+ ,71.53
+ ,69.78
+ ,67.98
+ ,69.96
+ ,72.16
+ ,70.47
+ ,68.86
+ ,67.37
+ ,65.87
+ ,72.16
+ ,71.34
+ ,69.93
+ ,68.44
+ ,67.16
+ ,66.01
+ ,67.25
+ ,70.91
+ ,69.75
+ ,68.59
+ ,67.48
+ ,66.31
+ ,64.81
+ ,66.58
+ ,65.97
+ ,64.7
+ ,64.7
+ ,60.94
+ ,59.08
+ ,58.42
+ ,57.77
+ ,57.11
+ ,53.31
+ ,49.96
+ ,49.4
+ ,48.84
+ ,48.3
+ ,47.74
+ ,47.24
+ ,46.76
+ ,46.29
+ ,48.9
+ ,49.23
+ ,48.53
+ ,48.03
+ ,54.34
+ ,53.79
+ ,53.24
+ ,52.96
+ ,52.17
+ ,51.7
+ ,58.55
+ ,78.2
+ ,77.03
+ ,76.19
+ ,77.15
+ ,75.87
+ ,95.47
+ ,109.67
+ ,112.28
+ ,112.01
+ ,107.93
+ ,105.96
+ ,105.06
+ ,102.98
+ ,102.2
+ ,105.23
+ ,101.85
+ ,99.89
+ ,96.23
+ ,94.76
+ ,91.51
+ ,91.63
+ ,91.54
+ ,85.23
+ ,87.83
+ ,87.38
+ ,84.44
+ ,85.19
+ ,84.03
+ ,86.73
+ ,102.52
+ ,104.45
+ ,106.98
+ ,107.02
+ ,99.26
+ ,94.45
+ ,113.44
+ ,157.33
+ ,147.38
+ ,171.89
+ ,171.95
+ ,132.71
+ ,126.02
+ ,121.18
+ ,115.45
+ ,110.48
+ ,117.85
+ ,117.63
+ ,124.65
+ ,109.59
+ ,111.27
+ ,99.78
+ ,98.21
+ ,99.2
+ ,97.97
+ ,89.55
+ ,87.91
+ ,93.34
+ ,94.42
+ ,93.2
+ ,90.29
+ ,91.46
+ ,89.98
+ ,88.35
+ ,88.41
+ ,82.44
+ ,79.89
+ ,75.69
+ ,75.66
+ ,84.5
+ ,96.73
+ ,87.48
+ ,82.39
+ ,83.48
+ ,79.31
+ ,78.16
+ ,72.77
+ ,72.45
+ ,68.46
+ ,67.62
+ ,68.76
+ ,70.07
+ ,68.55
+ ,65.3
+ ,58.96
+ ,59.17
+ ,62.37
+ ,66.28
+ ,55.62
+ ,55.23
+ ,55.85
+ ,56.75
+ ,50.89
+ ,53.88
+ ,52.95
+ ,55.08
+ ,53.61
+ ,58.78
+ ,61.85
+ ,55.91
+ ,53.32
+ ,46.41
+ ,44.57
+ ,50
+ ,50
+ ,53.36
+ ,46.23
+ ,50.45
+ ,49.07
+ ,45.85
+ ,48.45
+ ,49.96
+ ,46.53
+ ,50.51
+ ,47.58
+ ,48.05
+ ,46.84
+ ,47.67
+ ,49.16
+ ,55.54
+ ,55.82
+ ,58.22
+ ,56.19
+ ,57.77
+ ,63.19
+ ,54.76
+ ,55.74
+ ,62.54
+ ,61.39
+ ,69.6
+ ,79.23
+ ,80
+ ,93.68
+ ,107.63
+ ,100.18
+ ,97.3
+ ,90.45
+ ,80.64
+ ,80.58
+ ,75.82
+ ,85.59
+ ,89.35
+ ,89.42
+ ,104.73
+ ,95.32
+ ,89.27
+ ,90.44
+ ,86.97
+ ,79.98
+ ,81.22
+ ,87.35
+ ,83.64
+ ,82.22
+ ,94.4
+ ,102.18)
+ ,dim=c(1
+ ,360)
+ ,dimnames=list(c('Columbia')
+ ,1:360))
> y <- array(NA,dim=c(1,360),dimnames=list(c('Columbia'),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 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Columbia t
1 87.28 1
2 87.28 2
3 87.09 3
4 86.92 4
5 87.59 5
6 90.72 6
7 90.69 7
8 90.30 8
9 89.55 9
10 88.94 10
11 88.41 11
12 87.82 12
13 87.07 13
14 86.82 14
15 86.40 15
16 86.02 16
17 85.66 17
18 85.32 18
19 85.00 19
20 84.67 20
21 83.94 21
22 82.83 22
23 81.95 23
24 81.19 24
25 80.48 25
26 78.86 26
27 69.47 27
28 68.77 28
29 70.06 29
30 73.95 30
31 75.80 31
32 77.79 32
33 81.57 33
34 83.07 34
35 84.34 35
36 85.10 36
37 85.25 37
38 84.26 38
39 83.63 39
40 86.44 40
41 85.30 41
42 84.10 42
43 83.36 43
44 82.48 44
45 81.58 45
46 80.47 46
47 79.34 47
48 82.13 48
49 81.69 49
50 80.70 50
51 79.88 51
52 79.16 52
53 78.38 53
54 77.42 54
55 76.47 55
56 75.46 56
57 74.48 57
58 78.27 58
59 80.70 59
60 79.91 60
61 78.75 61
62 77.78 62
63 81.14 63
64 81.08 64
65 80.03 65
66 78.91 66
67 78.01 67
68 76.90 68
69 75.97 69
70 81.93 70
71 80.27 71
72 78.67 72
73 77.42 73
74 76.16 74
75 74.70 75
76 76.39 76
77 76.04 77
78 74.65 78
79 73.29 79
80 71.79 80
81 74.39 81
82 74.91 82
83 74.54 83
84 73.08 84
85 72.75 85
86 71.32 86
87 70.38 87
88 70.35 88
89 70.01 89
90 69.36 90
91 67.77 91
92 69.26 92
93 69.80 93
94 68.38 94
95 67.62 95
96 68.39 96
97 66.95 97
98 65.21 98
99 66.64 99
100 63.45 100
101 60.66 101
102 62.34 102
103 60.32 103
104 58.64 104
105 60.46 105
106 58.59 106
107 61.87 107
108 61.85 108
109 67.44 109
110 77.06 110
111 91.74 111
112 93.15 112
113 94.15 113
114 93.11 114
115 91.51 115
116 89.96 116
117 88.16 117
118 86.98 118
119 88.03 119
120 86.24 120
121 84.65 121
122 83.23 122
123 81.70 123
124 80.25 124
125 78.80 125
126 77.51 126
127 76.20 127
128 75.04 128
129 74.00 129
130 75.49 130
131 77.14 131
132 76.15 132
133 76.27 133
134 78.19 134
135 76.49 135
136 77.31 136
137 76.65 137
138 74.99 138
139 73.51 139
140 72.07 140
141 70.59 141
142 71.96 142
143 76.29 143
144 74.86 144
145 74.93 145
146 71.90 146
147 71.01 147
148 77.47 148
149 75.78 149
150 76.60 150
151 76.07 151
152 74.57 152
153 73.02 153
154 72.65 154
155 73.16 155
156 71.53 156
157 69.78 157
158 67.98 158
159 69.96 159
160 72.16 160
161 70.47 161
162 68.86 162
163 67.37 163
164 65.87 164
165 72.16 165
166 71.34 166
167 69.93 167
168 68.44 168
169 67.16 169
170 66.01 170
171 67.25 171
172 70.91 172
173 69.75 173
174 68.59 174
175 67.48 175
176 66.31 176
177 64.81 177
178 66.58 178
179 65.97 179
180 64.70 180
181 64.70 181
182 60.94 182
183 59.08 183
184 58.42 184
185 57.77 185
186 57.11 186
187 53.31 187
188 49.96 188
189 49.40 189
190 48.84 190
191 48.30 191
192 47.74 192
193 47.24 193
194 46.76 194
195 46.29 195
196 48.90 196
197 49.23 197
198 48.53 198
199 48.03 199
200 54.34 200
201 53.79 201
202 53.24 202
203 52.96 203
204 52.17 204
205 51.70 205
206 58.55 206
207 78.20 207
208 77.03 208
209 76.19 209
210 77.15 210
211 75.87 211
212 95.47 212
213 109.67 213
214 112.28 214
215 112.01 215
216 107.93 216
217 105.96 217
218 105.06 218
219 102.98 219
220 102.20 220
221 105.23 221
222 101.85 222
223 99.89 223
224 96.23 224
225 94.76 225
226 91.51 226
227 91.63 227
228 91.54 228
229 85.23 229
230 87.83 230
231 87.38 231
232 84.44 232
233 85.19 233
234 84.03 234
235 86.73 235
236 102.52 236
237 104.45 237
238 106.98 238
239 107.02 239
240 99.26 240
241 94.45 241
242 113.44 242
243 157.33 243
244 147.38 244
245 171.89 245
246 171.95 246
247 132.71 247
248 126.02 248
249 121.18 249
250 115.45 250
251 110.48 251
252 117.85 252
253 117.63 253
254 124.65 254
255 109.59 255
256 111.27 256
257 99.78 257
258 98.21 258
259 99.20 259
260 97.97 260
261 89.55 261
262 87.91 262
263 93.34 263
264 94.42 264
265 93.20 265
266 90.29 266
267 91.46 267
268 89.98 268
269 88.35 269
270 88.41 270
271 82.44 271
272 79.89 272
273 75.69 273
274 75.66 274
275 84.50 275
276 96.73 276
277 87.48 277
278 82.39 278
279 83.48 279
280 79.31 280
281 78.16 281
282 72.77 282
283 72.45 283
284 68.46 284
285 67.62 285
286 68.76 286
287 70.07 287
288 68.55 288
289 65.30 289
290 58.96 290
291 59.17 291
292 62.37 292
293 66.28 293
294 55.62 294
295 55.23 295
296 55.85 296
297 56.75 297
298 50.89 298
299 53.88 299
300 52.95 300
301 55.08 301
302 53.61 302
303 58.78 303
304 61.85 304
305 55.91 305
306 53.32 306
307 46.41 307
308 44.57 308
309 50.00 309
310 50.00 310
311 53.36 311
312 46.23 312
313 50.45 313
314 49.07 314
315 45.85 315
316 48.45 316
317 49.96 317
318 46.53 318
319 50.51 319
320 47.58 320
321 48.05 321
322 46.84 322
323 47.67 323
324 49.16 324
325 55.54 325
326 55.82 326
327 58.22 327
328 56.19 328
329 57.77 329
330 63.19 330
331 54.76 331
332 55.74 332
333 62.54 333
334 61.39 334
335 69.60 335
336 79.23 336
337 80.00 337
338 93.68 338
339 107.63 339
340 100.18 340
341 97.30 341
342 90.45 342
343 80.64 343
344 80.58 344
345 75.82 345
346 85.59 346
347 89.35 347
348 89.42 348
349 104.73 349
350 95.32 350
351 89.27 351
352 90.44 352
353 86.97 353
354 79.98 354
355 81.22 355
356 87.35 356
357 83.64 357
358 82.22 358
359 94.40 359
360 102.18 360
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) t
79.11394 -0.00873
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-31.855 -10.787 -1.078 8.268 94.984
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 79.113944 1.991731 39.721 <2e-16 ***
t -0.008730 0.009563 -0.913 0.362
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 18.86 on 358 degrees of freedom
Multiple R-squared: 0.002323, Adjusted R-squared: -0.0004642
F-statistic: 0.8334 on 1 and 358 DF, p-value: 0.3619
> 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,] 4.696230e-06 9.392461e-06 9.999953e-01
[2,] 3.220571e-05 6.441142e-05 9.999678e-01
[3,] 2.244387e-06 4.488775e-06 9.999978e-01
[4,] 1.235468e-07 2.470935e-07 9.999999e-01
[5,] 1.298929e-08 2.597858e-08 1.000000e+00
[6,] 2.226768e-09 4.453535e-09 1.000000e+00
[7,] 4.372009e-10 8.744018e-10 1.000000e+00
[8,] 9.286346e-11 1.857269e-10 1.000000e+00
[9,] 2.277247e-11 4.554494e-11 1.000000e+00
[10,] 3.941546e-12 7.883091e-12 1.000000e+00
[11,] 6.238101e-13 1.247620e-12 1.000000e+00
[12,] 8.981900e-14 1.796380e-13 1.000000e+00
[13,] 1.188029e-14 2.376057e-14 1.000000e+00
[14,] 1.452732e-15 2.905464e-15 1.000000e+00
[15,] 1.649610e-16 3.299221e-16 1.000000e+00
[16,] 1.770451e-17 3.540901e-17 1.000000e+00
[17,] 2.232967e-18 4.465934e-18 1.000000e+00
[18,] 4.320051e-19 8.640103e-19 1.000000e+00
[19,] 1.021758e-19 2.043516e-19 1.000000e+00
[20,] 2.537234e-20 5.074468e-20 1.000000e+00
[21,] 6.220570e-21 1.244114e-20 1.000000e+00
[22,] 3.264669e-21 6.529338e-21 1.000000e+00
[23,] 4.777341e-17 9.554681e-17 1.000000e+00
[24,] 1.037365e-15 2.074731e-15 1.000000e+00
[25,] 1.219130e-15 2.438261e-15 1.000000e+00
[26,] 2.498137e-16 4.996275e-16 1.000000e+00
[27,] 4.477461e-17 8.954922e-17 1.000000e+00
[28,] 1.107853e-17 2.215705e-17 1.000000e+00
[29,] 1.098050e-17 2.196100e-17 1.000000e+00
[30,] 1.720826e-17 3.441652e-17 1.000000e+00
[31,] 3.351450e-17 6.702899e-17 1.000000e+00
[32,] 5.917745e-17 1.183549e-16 1.000000e+00
[33,] 7.529179e-17 1.505836e-16 1.000000e+00
[34,] 5.222718e-17 1.044544e-16 1.000000e+00
[35,] 2.656304e-17 5.312608e-17 1.000000e+00
[36,] 2.815630e-17 5.631260e-17 1.000000e+00
[37,] 1.707491e-17 3.414981e-17 1.000000e+00
[38,] 7.043673e-18 1.408735e-17 1.000000e+00
[39,] 2.409245e-18 4.818490e-18 1.000000e+00
[40,] 7.029361e-19 1.405872e-18 1.000000e+00
[41,] 1.827891e-19 3.655782e-19 1.000000e+00
[42,] 4.349864e-20 8.699727e-20 1.000000e+00
[43,] 9.926087e-21 1.985217e-20 1.000000e+00
[44,] 2.759878e-21 5.519756e-21 1.000000e+00
[45,] 7.172875e-22 1.434575e-21 1.000000e+00
[46,] 1.684911e-22 3.369821e-22 1.000000e+00
[47,] 3.757572e-23 7.515143e-23 1.000000e+00
[48,] 8.164357e-24 1.632871e-23 1.000000e+00
[49,] 1.758101e-24 3.516202e-24 1.000000e+00
[50,] 3.851502e-25 7.703004e-25 1.000000e+00
[51,] 8.792134e-26 1.758427e-25 1.000000e+00
[52,] 2.150415e-26 4.300831e-26 1.000000e+00
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[344,] 9.968798e-01 6.240448e-03 3.120224e-03
[345,] 9.984803e-01 3.039467e-03 1.519734e-03
[346,] 9.982732e-01 3.453560e-03 1.726780e-03
[347,] 9.965597e-01 6.880622e-03 3.440311e-03
[348,] 9.964566e-01 7.086870e-03 3.543435e-03
[349,] 9.965316e-01 6.936858e-03 3.468429e-03
[350,] 9.877956e-01 2.440879e-02 1.220439e-02
[351,] 9.571723e-01 8.565545e-02 4.282772e-02
> postscript(file="/var/wessaorg/rcomp/tmp/1d6z61321478530.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/20c431321478530.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3vihn1321478530.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4y8pm1321478530.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5138x1321478530.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 = 360
Frequency = 1
1 2 3 4 5 6
8.17478624 8.18351631 8.00224638 7.84097644 8.51970651 11.65843658
7 8 9 10 11 12
11.63716665 11.25589671 10.51462678 9.91335685 9.39208692 8.81081698
13 14 15 16 17 18
8.06954705 7.82827712 7.41700718 7.04573725 6.69446732 6.36319739
19 20 21 22 23 24
6.05192745 5.73065752 5.00938759 3.90811766 3.03684772 2.28557779
25 26 27 28 29 30
1.58430786 -0.02696207 -9.40823201 -10.09950194 -8.80077187 -4.90204180
31 32 33 34 35 36
-3.04331174 -1.04458167 2.74414840 4.25287846 5.53160853 6.30033860
37 38 39 40 41 42
6.45906867 5.47779873 4.85652880 7.67525887 6.54398894 5.35271900
43 44 45 46 47 48
4.62144907 3.75017914 2.85890921 1.75763927 0.63636934 3.43509941
49 50 51 52 53 54
3.00382948 2.02255954 1.21128961 0.50001968 -0.27125026 -1.22252019
55 56 57 58 59 60
-2.16379012 -3.16506005 -4.13632999 -0.33759992 2.10113015 1.31986022
61 62 63 64 65 66
0.16859028 -0.79267965 2.57605042 2.52478049 1.48351055 0.37224062
67 68 69 70 71 72
-0.51902931 -1.62029924 -2.54156918 3.42716089 1.77589096 0.18462102
73 74 75 76 77 78
-1.05664891 -2.30791884 -3.75918877 -2.06045871 -2.40172864 -3.78299857
79 80 81 82 83 84
-5.13426850 -6.62553844 -4.01680837 -3.48807830 -3.84934823 -5.30061817
85 86 87 88 89 90
-5.62188810 -7.04315803 -7.97442796 -7.99569790 -8.32696783 -8.96823776
91 92 93 94 95 96
-10.54950770 -9.05077763 -8.50204756 -9.91331749 -10.66458743 -9.88585736
97 98 99 100 101 102
-11.31712729 -13.04839722 -11.60966716 -14.79093709 -17.57220702 -15.88347695
103 104 105 106 107 108
-17.89474689 -19.56601682 -17.73728675 -19.59855669 -16.30982662 -16.32109655
109 110 111 112 113 114
-10.72236648 -1.09363642 13.59509365 15.01382372 16.02255379 14.99128385
115 116 117 118 119 120
13.40001392 11.85874399 10.06747406 8.89620412 9.95493419 8.17366426
121 122 123 124 125 126
6.59239433 5.18112439 3.65985446 2.21858453 0.77731459 -0.50395534
127 128 129 130 131 132
-1.80522527 -2.95649520 -3.98776514 -2.48903507 -0.83030500 -1.81157493
133 134 135 136 137 138
-1.68284487 0.24588520 -1.44538473 -0.61665466 -1.26792460 -2.91919453
139 140 141 142 143 144
-4.39046446 -5.82173439 -7.29300433 -5.91427426 -1.57554419 -2.99681413
145 146 147 148 149 150
-2.91808406 -5.93935399 -6.82062392 -0.35189386 -2.03316379 -1.20443372
151 152 153 154 155 156
-1.72570365 -3.21697359 -4.75824352 -5.11951345 -4.60078338 -6.22205332
157 158 159 160 161 162
-7.96332325 -9.75459318 -7.76586311 -5.55713305 -7.23840298 -8.83967291
163 164 165 166 167 168
-10.32094285 -11.81221278 -5.51348271 -6.32475264 -7.72602258 -9.20729251
169 170 171 172 173 174
-10.47856244 -11.61983237 -10.37110231 -6.70237224 -7.85364217 -9.00491210
175 176 177 178 179 180
-10.10618204 -11.26745197 -12.75872190 -10.97999184 -11.58126177 -12.84253170
181 182 183 184 185 186
-12.83380163 -16.58507157 -18.43634150 -19.08761143 -19.72888136 -20.38015130
187 188 189 190 191 192
-24.17142123 -27.51269116 -28.06396109 -28.61523103 -29.14650096 -29.69777089
193 194 195 196 197 198
-30.18904082 -30.66031076 -31.12158069 -28.50285062 -28.16412056 -28.85539049
199 200 201 202 203 204
-29.34666042 -23.02793035 -23.56920029 -24.11047022 -24.38174015 -25.16301008
205 206 207 208 209 210
-25.62428002 -18.76554995 0.89318012 -0.26808981 -1.09935975 -0.13062968
211 212 213 214 215 216
-1.40189961 18.20683046 32.41556052 35.03429059 34.77302066 30.70175072
217 218 219 220 221 222
28.74048079 27.84921086 25.77794093 25.00667099 28.04540106 24.67413113
223 224 225 226 227 228
22.72286120 19.07159126 17.61032133 14.36905140 14.49778147 14.41651153
229 230 231 232 233 234
8.11524160 10.72397167 10.28270174 7.35143180 8.11016187 6.95889194
235 236 237 238 239 240
9.66762200 25.46635207 27.40508214 29.94381221 29.99254227 22.24127234
241 242 243 244 245 246
17.44000241 36.43873248 80.33746254 70.39619261 94.91492268 94.98365275
247 248 249 250 251 252
55.75238281 49.07111288 44.23984295 38.51857301 33.55730308 40.93603315
253 254 255 256 257 258
40.72476322 47.75349328 32.70222335 34.39095342 22.90968349 21.34841355
259 260 261 262 263 264
22.34714362 21.12587369 12.71460376 11.08333382 16.52206389 17.61079396
265 266 267 268 269 270
16.39952403 13.49825409 14.67698416 13.20571423 11.58444429 11.65317436
271 272 273 274 275 276
5.69190443 3.15063450 -1.04063544 -1.06190537 7.78682470 20.02555477
277 278 279 280 281 282
10.78428483 5.70301490 6.80174497 2.64047504 1.49920510 -3.88206483
283 284 285 286 287 288
-4.19333476 -8.17460469 -9.00587463 -7.85714456 -6.53841449 -8.04968443
289 290 291 292 293 294
-11.29095436 -17.62222429 -17.40349422 -14.19476416 -10.27603409 -20.92730402
295 296 297 298 299 300
-21.30857395 -20.67984389 -19.77111382 -25.62238375 -22.62365368 -23.54492362
301 302 303 304 305 306
-21.40619355 -22.86746348 -17.68873341 -14.61000335 -20.54127328 -23.12254321
307 308 309 310 311 312
-30.02381315 -31.85508308 -26.41635301 -26.40762294 -23.03889288 -30.16016281
313 314 315 316 317 318
-25.93143274 -27.30270267 -30.51397261 -27.90524254 -26.38651247 -29.80778240
319 320 321 322 323 324
-25.81905234 -28.74032227 -28.26159220 -29.46286213 -28.62413207 -27.12540200
325 326 327 328 329 330
-20.73667193 -20.44794187 -18.03921180 -20.06048173 -18.47175166 -13.04302160
331 332 333 334 335 336
-21.46429153 -20.47556146 -13.66683139 -14.80810133 -6.58937126 3.04935881
337 338 339 340 341 342
3.82808888 17.51681894 31.47554901 24.03427908 21.16300914 14.32173921
343 344 345 346 347 348
4.52046928 4.46919935 -0.28207059 9.49665948 13.26538955 13.34411962
349 350 351 352 353 354
28.66284968 19.26157975 13.22030982 14.39903989 10.93776995 3.95650002
355 356 357 358 359 360
5.20523009 11.34396016 7.64269022 6.23142029 18.42015036 26.20888042
> postscript(file="/var/wessaorg/rcomp/tmp/6bcyl1321478530.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 = 360
Frequency = 1
lag(myerror, k = 1) myerror
0 8.17478624 NA
1 8.18351631 8.17478624
2 8.00224638 8.18351631
3 7.84097644 8.00224638
4 8.51970651 7.84097644
5 11.65843658 8.51970651
6 11.63716665 11.65843658
7 11.25589671 11.63716665
8 10.51462678 11.25589671
9 9.91335685 10.51462678
10 9.39208692 9.91335685
11 8.81081698 9.39208692
12 8.06954705 8.81081698
13 7.82827712 8.06954705
14 7.41700718 7.82827712
15 7.04573725 7.41700718
16 6.69446732 7.04573725
17 6.36319739 6.69446732
18 6.05192745 6.36319739
19 5.73065752 6.05192745
20 5.00938759 5.73065752
21 3.90811766 5.00938759
22 3.03684772 3.90811766
23 2.28557779 3.03684772
24 1.58430786 2.28557779
25 -0.02696207 1.58430786
26 -9.40823201 -0.02696207
27 -10.09950194 -9.40823201
28 -8.80077187 -10.09950194
29 -4.90204180 -8.80077187
30 -3.04331174 -4.90204180
31 -1.04458167 -3.04331174
32 2.74414840 -1.04458167
33 4.25287846 2.74414840
34 5.53160853 4.25287846
35 6.30033860 5.53160853
36 6.45906867 6.30033860
37 5.47779873 6.45906867
38 4.85652880 5.47779873
39 7.67525887 4.85652880
40 6.54398894 7.67525887
41 5.35271900 6.54398894
42 4.62144907 5.35271900
43 3.75017914 4.62144907
44 2.85890921 3.75017914
45 1.75763927 2.85890921
46 0.63636934 1.75763927
47 3.43509941 0.63636934
48 3.00382948 3.43509941
49 2.02255954 3.00382948
50 1.21128961 2.02255954
51 0.50001968 1.21128961
52 -0.27125026 0.50001968
53 -1.22252019 -0.27125026
54 -2.16379012 -1.22252019
55 -3.16506005 -2.16379012
56 -4.13632999 -3.16506005
57 -0.33759992 -4.13632999
58 2.10113015 -0.33759992
59 1.31986022 2.10113015
60 0.16859028 1.31986022
61 -0.79267965 0.16859028
62 2.57605042 -0.79267965
63 2.52478049 2.57605042
64 1.48351055 2.52478049
65 0.37224062 1.48351055
66 -0.51902931 0.37224062
67 -1.62029924 -0.51902931
68 -2.54156918 -1.62029924
69 3.42716089 -2.54156918
70 1.77589096 3.42716089
71 0.18462102 1.77589096
72 -1.05664891 0.18462102
73 -2.30791884 -1.05664891
74 -3.75918877 -2.30791884
75 -2.06045871 -3.75918877
76 -2.40172864 -2.06045871
77 -3.78299857 -2.40172864
78 -5.13426850 -3.78299857
79 -6.62553844 -5.13426850
80 -4.01680837 -6.62553844
81 -3.48807830 -4.01680837
82 -3.84934823 -3.48807830
83 -5.30061817 -3.84934823
84 -5.62188810 -5.30061817
85 -7.04315803 -5.62188810
86 -7.97442796 -7.04315803
87 -7.99569790 -7.97442796
88 -8.32696783 -7.99569790
89 -8.96823776 -8.32696783
90 -10.54950770 -8.96823776
91 -9.05077763 -10.54950770
92 -8.50204756 -9.05077763
93 -9.91331749 -8.50204756
94 -10.66458743 -9.91331749
95 -9.88585736 -10.66458743
96 -11.31712729 -9.88585736
97 -13.04839722 -11.31712729
98 -11.60966716 -13.04839722
99 -14.79093709 -11.60966716
100 -17.57220702 -14.79093709
101 -15.88347695 -17.57220702
102 -17.89474689 -15.88347695
103 -19.56601682 -17.89474689
104 -17.73728675 -19.56601682
105 -19.59855669 -17.73728675
106 -16.30982662 -19.59855669
107 -16.32109655 -16.30982662
108 -10.72236648 -16.32109655
109 -1.09363642 -10.72236648
110 13.59509365 -1.09363642
111 15.01382372 13.59509365
112 16.02255379 15.01382372
113 14.99128385 16.02255379
114 13.40001392 14.99128385
115 11.85874399 13.40001392
116 10.06747406 11.85874399
117 8.89620412 10.06747406
118 9.95493419 8.89620412
119 8.17366426 9.95493419
120 6.59239433 8.17366426
121 5.18112439 6.59239433
122 3.65985446 5.18112439
123 2.21858453 3.65985446
124 0.77731459 2.21858453
125 -0.50395534 0.77731459
126 -1.80522527 -0.50395534
127 -2.95649520 -1.80522527
128 -3.98776514 -2.95649520
129 -2.48903507 -3.98776514
130 -0.83030500 -2.48903507
131 -1.81157493 -0.83030500
132 -1.68284487 -1.81157493
133 0.24588520 -1.68284487
134 -1.44538473 0.24588520
135 -0.61665466 -1.44538473
136 -1.26792460 -0.61665466
137 -2.91919453 -1.26792460
138 -4.39046446 -2.91919453
139 -5.82173439 -4.39046446
140 -7.29300433 -5.82173439
141 -5.91427426 -7.29300433
142 -1.57554419 -5.91427426
143 -2.99681413 -1.57554419
144 -2.91808406 -2.99681413
145 -5.93935399 -2.91808406
146 -6.82062392 -5.93935399
147 -0.35189386 -6.82062392
148 -2.03316379 -0.35189386
149 -1.20443372 -2.03316379
150 -1.72570365 -1.20443372
151 -3.21697359 -1.72570365
152 -4.75824352 -3.21697359
153 -5.11951345 -4.75824352
154 -4.60078338 -5.11951345
155 -6.22205332 -4.60078338
156 -7.96332325 -6.22205332
157 -9.75459318 -7.96332325
158 -7.76586311 -9.75459318
159 -5.55713305 -7.76586311
160 -7.23840298 -5.55713305
161 -8.83967291 -7.23840298
162 -10.32094285 -8.83967291
163 -11.81221278 -10.32094285
164 -5.51348271 -11.81221278
165 -6.32475264 -5.51348271
166 -7.72602258 -6.32475264
167 -9.20729251 -7.72602258
168 -10.47856244 -9.20729251
169 -11.61983237 -10.47856244
170 -10.37110231 -11.61983237
171 -6.70237224 -10.37110231
172 -7.85364217 -6.70237224
173 -9.00491210 -7.85364217
174 -10.10618204 -9.00491210
175 -11.26745197 -10.10618204
176 -12.75872190 -11.26745197
177 -10.97999184 -12.75872190
178 -11.58126177 -10.97999184
179 -12.84253170 -11.58126177
180 -12.83380163 -12.84253170
181 -16.58507157 -12.83380163
182 -18.43634150 -16.58507157
183 -19.08761143 -18.43634150
184 -19.72888136 -19.08761143
185 -20.38015130 -19.72888136
186 -24.17142123 -20.38015130
187 -27.51269116 -24.17142123
188 -28.06396109 -27.51269116
189 -28.61523103 -28.06396109
190 -29.14650096 -28.61523103
191 -29.69777089 -29.14650096
192 -30.18904082 -29.69777089
193 -30.66031076 -30.18904082
194 -31.12158069 -30.66031076
195 -28.50285062 -31.12158069
196 -28.16412056 -28.50285062
197 -28.85539049 -28.16412056
198 -29.34666042 -28.85539049
199 -23.02793035 -29.34666042
200 -23.56920029 -23.02793035
201 -24.11047022 -23.56920029
202 -24.38174015 -24.11047022
203 -25.16301008 -24.38174015
204 -25.62428002 -25.16301008
205 -18.76554995 -25.62428002
206 0.89318012 -18.76554995
207 -0.26808981 0.89318012
208 -1.09935975 -0.26808981
209 -0.13062968 -1.09935975
210 -1.40189961 -0.13062968
211 18.20683046 -1.40189961
212 32.41556052 18.20683046
213 35.03429059 32.41556052
214 34.77302066 35.03429059
215 30.70175072 34.77302066
216 28.74048079 30.70175072
217 27.84921086 28.74048079
218 25.77794093 27.84921086
219 25.00667099 25.77794093
220 28.04540106 25.00667099
221 24.67413113 28.04540106
222 22.72286120 24.67413113
223 19.07159126 22.72286120
224 17.61032133 19.07159126
225 14.36905140 17.61032133
226 14.49778147 14.36905140
227 14.41651153 14.49778147
228 8.11524160 14.41651153
229 10.72397167 8.11524160
230 10.28270174 10.72397167
231 7.35143180 10.28270174
232 8.11016187 7.35143180
233 6.95889194 8.11016187
234 9.66762200 6.95889194
235 25.46635207 9.66762200
236 27.40508214 25.46635207
237 29.94381221 27.40508214
238 29.99254227 29.94381221
239 22.24127234 29.99254227
240 17.44000241 22.24127234
241 36.43873248 17.44000241
242 80.33746254 36.43873248
243 70.39619261 80.33746254
244 94.91492268 70.39619261
245 94.98365275 94.91492268
246 55.75238281 94.98365275
247 49.07111288 55.75238281
248 44.23984295 49.07111288
249 38.51857301 44.23984295
250 33.55730308 38.51857301
251 40.93603315 33.55730308
252 40.72476322 40.93603315
253 47.75349328 40.72476322
254 32.70222335 47.75349328
255 34.39095342 32.70222335
256 22.90968349 34.39095342
257 21.34841355 22.90968349
258 22.34714362 21.34841355
259 21.12587369 22.34714362
260 12.71460376 21.12587369
261 11.08333382 12.71460376
262 16.52206389 11.08333382
263 17.61079396 16.52206389
264 16.39952403 17.61079396
265 13.49825409 16.39952403
266 14.67698416 13.49825409
267 13.20571423 14.67698416
268 11.58444429 13.20571423
269 11.65317436 11.58444429
270 5.69190443 11.65317436
271 3.15063450 5.69190443
272 -1.04063544 3.15063450
273 -1.06190537 -1.04063544
274 7.78682470 -1.06190537
275 20.02555477 7.78682470
276 10.78428483 20.02555477
277 5.70301490 10.78428483
278 6.80174497 5.70301490
279 2.64047504 6.80174497
280 1.49920510 2.64047504
281 -3.88206483 1.49920510
282 -4.19333476 -3.88206483
283 -8.17460469 -4.19333476
284 -9.00587463 -8.17460469
285 -7.85714456 -9.00587463
286 -6.53841449 -7.85714456
287 -8.04968443 -6.53841449
288 -11.29095436 -8.04968443
289 -17.62222429 -11.29095436
290 -17.40349422 -17.62222429
291 -14.19476416 -17.40349422
292 -10.27603409 -14.19476416
293 -20.92730402 -10.27603409
294 -21.30857395 -20.92730402
295 -20.67984389 -21.30857395
296 -19.77111382 -20.67984389
297 -25.62238375 -19.77111382
298 -22.62365368 -25.62238375
299 -23.54492362 -22.62365368
300 -21.40619355 -23.54492362
301 -22.86746348 -21.40619355
302 -17.68873341 -22.86746348
303 -14.61000335 -17.68873341
304 -20.54127328 -14.61000335
305 -23.12254321 -20.54127328
306 -30.02381315 -23.12254321
307 -31.85508308 -30.02381315
308 -26.41635301 -31.85508308
309 -26.40762294 -26.41635301
310 -23.03889288 -26.40762294
311 -30.16016281 -23.03889288
312 -25.93143274 -30.16016281
313 -27.30270267 -25.93143274
314 -30.51397261 -27.30270267
315 -27.90524254 -30.51397261
316 -26.38651247 -27.90524254
317 -29.80778240 -26.38651247
318 -25.81905234 -29.80778240
319 -28.74032227 -25.81905234
320 -28.26159220 -28.74032227
321 -29.46286213 -28.26159220
322 -28.62413207 -29.46286213
323 -27.12540200 -28.62413207
324 -20.73667193 -27.12540200
325 -20.44794187 -20.73667193
326 -18.03921180 -20.44794187
327 -20.06048173 -18.03921180
328 -18.47175166 -20.06048173
329 -13.04302160 -18.47175166
330 -21.46429153 -13.04302160
331 -20.47556146 -21.46429153
332 -13.66683139 -20.47556146
333 -14.80810133 -13.66683139
334 -6.58937126 -14.80810133
335 3.04935881 -6.58937126
336 3.82808888 3.04935881
337 17.51681894 3.82808888
338 31.47554901 17.51681894
339 24.03427908 31.47554901
340 21.16300914 24.03427908
341 14.32173921 21.16300914
342 4.52046928 14.32173921
343 4.46919935 4.52046928
344 -0.28207059 4.46919935
345 9.49665948 -0.28207059
346 13.26538955 9.49665948
347 13.34411962 13.26538955
348 28.66284968 13.34411962
349 19.26157975 28.66284968
350 13.22030982 19.26157975
351 14.39903989 13.22030982
352 10.93776995 14.39903989
353 3.95650002 10.93776995
354 5.20523009 3.95650002
355 11.34396016 5.20523009
356 7.64269022 11.34396016
357 6.23142029 7.64269022
358 18.42015036 6.23142029
359 26.20888042 18.42015036
360 NA 26.20888042
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 8.18351631 8.17478624
[2,] 8.00224638 8.18351631
[3,] 7.84097644 8.00224638
[4,] 8.51970651 7.84097644
[5,] 11.65843658 8.51970651
[6,] 11.63716665 11.65843658
[7,] 11.25589671 11.63716665
[8,] 10.51462678 11.25589671
[9,] 9.91335685 10.51462678
[10,] 9.39208692 9.91335685
[11,] 8.81081698 9.39208692
[12,] 8.06954705 8.81081698
[13,] 7.82827712 8.06954705
[14,] 7.41700718 7.82827712
[15,] 7.04573725 7.41700718
[16,] 6.69446732 7.04573725
[17,] 6.36319739 6.69446732
[18,] 6.05192745 6.36319739
[19,] 5.73065752 6.05192745
[20,] 5.00938759 5.73065752
[21,] 3.90811766 5.00938759
[22,] 3.03684772 3.90811766
[23,] 2.28557779 3.03684772
[24,] 1.58430786 2.28557779
[25,] -0.02696207 1.58430786
[26,] -9.40823201 -0.02696207
[27,] -10.09950194 -9.40823201
[28,] -8.80077187 -10.09950194
[29,] -4.90204180 -8.80077187
[30,] -3.04331174 -4.90204180
[31,] -1.04458167 -3.04331174
[32,] 2.74414840 -1.04458167
[33,] 4.25287846 2.74414840
[34,] 5.53160853 4.25287846
[35,] 6.30033860 5.53160853
[36,] 6.45906867 6.30033860
[37,] 5.47779873 6.45906867
[38,] 4.85652880 5.47779873
[39,] 7.67525887 4.85652880
[40,] 6.54398894 7.67525887
[41,] 5.35271900 6.54398894
[42,] 4.62144907 5.35271900
[43,] 3.75017914 4.62144907
[44,] 2.85890921 3.75017914
[45,] 1.75763927 2.85890921
[46,] 0.63636934 1.75763927
[47,] 3.43509941 0.63636934
[48,] 3.00382948 3.43509941
[49,] 2.02255954 3.00382948
[50,] 1.21128961 2.02255954
[51,] 0.50001968 1.21128961
[52,] -0.27125026 0.50001968
[53,] -1.22252019 -0.27125026
[54,] -2.16379012 -1.22252019
[55,] -3.16506005 -2.16379012
[56,] -4.13632999 -3.16506005
[57,] -0.33759992 -4.13632999
[58,] 2.10113015 -0.33759992
[59,] 1.31986022 2.10113015
[60,] 0.16859028 1.31986022
[61,] -0.79267965 0.16859028
[62,] 2.57605042 -0.79267965
[63,] 2.52478049 2.57605042
[64,] 1.48351055 2.52478049
[65,] 0.37224062 1.48351055
[66,] -0.51902931 0.37224062
[67,] -1.62029924 -0.51902931
[68,] -2.54156918 -1.62029924
[69,] 3.42716089 -2.54156918
[70,] 1.77589096 3.42716089
[71,] 0.18462102 1.77589096
[72,] -1.05664891 0.18462102
[73,] -2.30791884 -1.05664891
[74,] -3.75918877 -2.30791884
[75,] -2.06045871 -3.75918877
[76,] -2.40172864 -2.06045871
[77,] -3.78299857 -2.40172864
[78,] -5.13426850 -3.78299857
[79,] -6.62553844 -5.13426850
[80,] -4.01680837 -6.62553844
[81,] -3.48807830 -4.01680837
[82,] -3.84934823 -3.48807830
[83,] -5.30061817 -3.84934823
[84,] -5.62188810 -5.30061817
[85,] -7.04315803 -5.62188810
[86,] -7.97442796 -7.04315803
[87,] -7.99569790 -7.97442796
[88,] -8.32696783 -7.99569790
[89,] -8.96823776 -8.32696783
[90,] -10.54950770 -8.96823776
[91,] -9.05077763 -10.54950770
[92,] -8.50204756 -9.05077763
[93,] -9.91331749 -8.50204756
[94,] -10.66458743 -9.91331749
[95,] -9.88585736 -10.66458743
[96,] -11.31712729 -9.88585736
[97,] -13.04839722 -11.31712729
[98,] -11.60966716 -13.04839722
[99,] -14.79093709 -11.60966716
[100,] -17.57220702 -14.79093709
[101,] -15.88347695 -17.57220702
[102,] -17.89474689 -15.88347695
[103,] -19.56601682 -17.89474689
[104,] -17.73728675 -19.56601682
[105,] -19.59855669 -17.73728675
[106,] -16.30982662 -19.59855669
[107,] -16.32109655 -16.30982662
[108,] -10.72236648 -16.32109655
[109,] -1.09363642 -10.72236648
[110,] 13.59509365 -1.09363642
[111,] 15.01382372 13.59509365
[112,] 16.02255379 15.01382372
[113,] 14.99128385 16.02255379
[114,] 13.40001392 14.99128385
[115,] 11.85874399 13.40001392
[116,] 10.06747406 11.85874399
[117,] 8.89620412 10.06747406
[118,] 9.95493419 8.89620412
[119,] 8.17366426 9.95493419
[120,] 6.59239433 8.17366426
[121,] 5.18112439 6.59239433
[122,] 3.65985446 5.18112439
[123,] 2.21858453 3.65985446
[124,] 0.77731459 2.21858453
[125,] -0.50395534 0.77731459
[126,] -1.80522527 -0.50395534
[127,] -2.95649520 -1.80522527
[128,] -3.98776514 -2.95649520
[129,] -2.48903507 -3.98776514
[130,] -0.83030500 -2.48903507
[131,] -1.81157493 -0.83030500
[132,] -1.68284487 -1.81157493
[133,] 0.24588520 -1.68284487
[134,] -1.44538473 0.24588520
[135,] -0.61665466 -1.44538473
[136,] -1.26792460 -0.61665466
[137,] -2.91919453 -1.26792460
[138,] -4.39046446 -2.91919453
[139,] -5.82173439 -4.39046446
[140,] -7.29300433 -5.82173439
[141,] -5.91427426 -7.29300433
[142,] -1.57554419 -5.91427426
[143,] -2.99681413 -1.57554419
[144,] -2.91808406 -2.99681413
[145,] -5.93935399 -2.91808406
[146,] -6.82062392 -5.93935399
[147,] -0.35189386 -6.82062392
[148,] -2.03316379 -0.35189386
[149,] -1.20443372 -2.03316379
[150,] -1.72570365 -1.20443372
[151,] -3.21697359 -1.72570365
[152,] -4.75824352 -3.21697359
[153,] -5.11951345 -4.75824352
[154,] -4.60078338 -5.11951345
[155,] -6.22205332 -4.60078338
[156,] -7.96332325 -6.22205332
[157,] -9.75459318 -7.96332325
[158,] -7.76586311 -9.75459318
[159,] -5.55713305 -7.76586311
[160,] -7.23840298 -5.55713305
[161,] -8.83967291 -7.23840298
[162,] -10.32094285 -8.83967291
[163,] -11.81221278 -10.32094285
[164,] -5.51348271 -11.81221278
[165,] -6.32475264 -5.51348271
[166,] -7.72602258 -6.32475264
[167,] -9.20729251 -7.72602258
[168,] -10.47856244 -9.20729251
[169,] -11.61983237 -10.47856244
[170,] -10.37110231 -11.61983237
[171,] -6.70237224 -10.37110231
[172,] -7.85364217 -6.70237224
[173,] -9.00491210 -7.85364217
[174,] -10.10618204 -9.00491210
[175,] -11.26745197 -10.10618204
[176,] -12.75872190 -11.26745197
[177,] -10.97999184 -12.75872190
[178,] -11.58126177 -10.97999184
[179,] -12.84253170 -11.58126177
[180,] -12.83380163 -12.84253170
[181,] -16.58507157 -12.83380163
[182,] -18.43634150 -16.58507157
[183,] -19.08761143 -18.43634150
[184,] -19.72888136 -19.08761143
[185,] -20.38015130 -19.72888136
[186,] -24.17142123 -20.38015130
[187,] -27.51269116 -24.17142123
[188,] -28.06396109 -27.51269116
[189,] -28.61523103 -28.06396109
[190,] -29.14650096 -28.61523103
[191,] -29.69777089 -29.14650096
[192,] -30.18904082 -29.69777089
[193,] -30.66031076 -30.18904082
[194,] -31.12158069 -30.66031076
[195,] -28.50285062 -31.12158069
[196,] -28.16412056 -28.50285062
[197,] -28.85539049 -28.16412056
[198,] -29.34666042 -28.85539049
[199,] -23.02793035 -29.34666042
[200,] -23.56920029 -23.02793035
[201,] -24.11047022 -23.56920029
[202,] -24.38174015 -24.11047022
[203,] -25.16301008 -24.38174015
[204,] -25.62428002 -25.16301008
[205,] -18.76554995 -25.62428002
[206,] 0.89318012 -18.76554995
[207,] -0.26808981 0.89318012
[208,] -1.09935975 -0.26808981
[209,] -0.13062968 -1.09935975
[210,] -1.40189961 -0.13062968
[211,] 18.20683046 -1.40189961
[212,] 32.41556052 18.20683046
[213,] 35.03429059 32.41556052
[214,] 34.77302066 35.03429059
[215,] 30.70175072 34.77302066
[216,] 28.74048079 30.70175072
[217,] 27.84921086 28.74048079
[218,] 25.77794093 27.84921086
[219,] 25.00667099 25.77794093
[220,] 28.04540106 25.00667099
[221,] 24.67413113 28.04540106
[222,] 22.72286120 24.67413113
[223,] 19.07159126 22.72286120
[224,] 17.61032133 19.07159126
[225,] 14.36905140 17.61032133
[226,] 14.49778147 14.36905140
[227,] 14.41651153 14.49778147
[228,] 8.11524160 14.41651153
[229,] 10.72397167 8.11524160
[230,] 10.28270174 10.72397167
[231,] 7.35143180 10.28270174
[232,] 8.11016187 7.35143180
[233,] 6.95889194 8.11016187
[234,] 9.66762200 6.95889194
[235,] 25.46635207 9.66762200
[236,] 27.40508214 25.46635207
[237,] 29.94381221 27.40508214
[238,] 29.99254227 29.94381221
[239,] 22.24127234 29.99254227
[240,] 17.44000241 22.24127234
[241,] 36.43873248 17.44000241
[242,] 80.33746254 36.43873248
[243,] 70.39619261 80.33746254
[244,] 94.91492268 70.39619261
[245,] 94.98365275 94.91492268
[246,] 55.75238281 94.98365275
[247,] 49.07111288 55.75238281
[248,] 44.23984295 49.07111288
[249,] 38.51857301 44.23984295
[250,] 33.55730308 38.51857301
[251,] 40.93603315 33.55730308
[252,] 40.72476322 40.93603315
[253,] 47.75349328 40.72476322
[254,] 32.70222335 47.75349328
[255,] 34.39095342 32.70222335
[256,] 22.90968349 34.39095342
[257,] 21.34841355 22.90968349
[258,] 22.34714362 21.34841355
[259,] 21.12587369 22.34714362
[260,] 12.71460376 21.12587369
[261,] 11.08333382 12.71460376
[262,] 16.52206389 11.08333382
[263,] 17.61079396 16.52206389
[264,] 16.39952403 17.61079396
[265,] 13.49825409 16.39952403
[266,] 14.67698416 13.49825409
[267,] 13.20571423 14.67698416
[268,] 11.58444429 13.20571423
[269,] 11.65317436 11.58444429
[270,] 5.69190443 11.65317436
[271,] 3.15063450 5.69190443
[272,] -1.04063544 3.15063450
[273,] -1.06190537 -1.04063544
[274,] 7.78682470 -1.06190537
[275,] 20.02555477 7.78682470
[276,] 10.78428483 20.02555477
[277,] 5.70301490 10.78428483
[278,] 6.80174497 5.70301490
[279,] 2.64047504 6.80174497
[280,] 1.49920510 2.64047504
[281,] -3.88206483 1.49920510
[282,] -4.19333476 -3.88206483
[283,] -8.17460469 -4.19333476
[284,] -9.00587463 -8.17460469
[285,] -7.85714456 -9.00587463
[286,] -6.53841449 -7.85714456
[287,] -8.04968443 -6.53841449
[288,] -11.29095436 -8.04968443
[289,] -17.62222429 -11.29095436
[290,] -17.40349422 -17.62222429
[291,] -14.19476416 -17.40349422
[292,] -10.27603409 -14.19476416
[293,] -20.92730402 -10.27603409
[294,] -21.30857395 -20.92730402
[295,] -20.67984389 -21.30857395
[296,] -19.77111382 -20.67984389
[297,] -25.62238375 -19.77111382
[298,] -22.62365368 -25.62238375
[299,] -23.54492362 -22.62365368
[300,] -21.40619355 -23.54492362
[301,] -22.86746348 -21.40619355
[302,] -17.68873341 -22.86746348
[303,] -14.61000335 -17.68873341
[304,] -20.54127328 -14.61000335
[305,] -23.12254321 -20.54127328
[306,] -30.02381315 -23.12254321
[307,] -31.85508308 -30.02381315
[308,] -26.41635301 -31.85508308
[309,] -26.40762294 -26.41635301
[310,] -23.03889288 -26.40762294
[311,] -30.16016281 -23.03889288
[312,] -25.93143274 -30.16016281
[313,] -27.30270267 -25.93143274
[314,] -30.51397261 -27.30270267
[315,] -27.90524254 -30.51397261
[316,] -26.38651247 -27.90524254
[317,] -29.80778240 -26.38651247
[318,] -25.81905234 -29.80778240
[319,] -28.74032227 -25.81905234
[320,] -28.26159220 -28.74032227
[321,] -29.46286213 -28.26159220
[322,] -28.62413207 -29.46286213
[323,] -27.12540200 -28.62413207
[324,] -20.73667193 -27.12540200
[325,] -20.44794187 -20.73667193
[326,] -18.03921180 -20.44794187
[327,] -20.06048173 -18.03921180
[328,] -18.47175166 -20.06048173
[329,] -13.04302160 -18.47175166
[330,] -21.46429153 -13.04302160
[331,] -20.47556146 -21.46429153
[332,] -13.66683139 -20.47556146
[333,] -14.80810133 -13.66683139
[334,] -6.58937126 -14.80810133
[335,] 3.04935881 -6.58937126
[336,] 3.82808888 3.04935881
[337,] 17.51681894 3.82808888
[338,] 31.47554901 17.51681894
[339,] 24.03427908 31.47554901
[340,] 21.16300914 24.03427908
[341,] 14.32173921 21.16300914
[342,] 4.52046928 14.32173921
[343,] 4.46919935 4.52046928
[344,] -0.28207059 4.46919935
[345,] 9.49665948 -0.28207059
[346,] 13.26538955 9.49665948
[347,] 13.34411962 13.26538955
[348,] 28.66284968 13.34411962
[349,] 19.26157975 28.66284968
[350,] 13.22030982 19.26157975
[351,] 14.39903989 13.22030982
[352,] 10.93776995 14.39903989
[353,] 3.95650002 10.93776995
[354,] 5.20523009 3.95650002
[355,] 11.34396016 5.20523009
[356,] 7.64269022 11.34396016
[357,] 6.23142029 7.64269022
[358,] 18.42015036 6.23142029
[359,] 26.20888042 18.42015036
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 8.18351631 8.17478624
2 8.00224638 8.18351631
3 7.84097644 8.00224638
4 8.51970651 7.84097644
5 11.65843658 8.51970651
6 11.63716665 11.65843658
7 11.25589671 11.63716665
8 10.51462678 11.25589671
9 9.91335685 10.51462678
10 9.39208692 9.91335685
11 8.81081698 9.39208692
12 8.06954705 8.81081698
13 7.82827712 8.06954705
14 7.41700718 7.82827712
15 7.04573725 7.41700718
16 6.69446732 7.04573725
17 6.36319739 6.69446732
18 6.05192745 6.36319739
19 5.73065752 6.05192745
20 5.00938759 5.73065752
21 3.90811766 5.00938759
22 3.03684772 3.90811766
23 2.28557779 3.03684772
24 1.58430786 2.28557779
25 -0.02696207 1.58430786
26 -9.40823201 -0.02696207
27 -10.09950194 -9.40823201
28 -8.80077187 -10.09950194
29 -4.90204180 -8.80077187
30 -3.04331174 -4.90204180
31 -1.04458167 -3.04331174
32 2.74414840 -1.04458167
33 4.25287846 2.74414840
34 5.53160853 4.25287846
35 6.30033860 5.53160853
36 6.45906867 6.30033860
37 5.47779873 6.45906867
38 4.85652880 5.47779873
39 7.67525887 4.85652880
40 6.54398894 7.67525887
41 5.35271900 6.54398894
42 4.62144907 5.35271900
43 3.75017914 4.62144907
44 2.85890921 3.75017914
45 1.75763927 2.85890921
46 0.63636934 1.75763927
47 3.43509941 0.63636934
48 3.00382948 3.43509941
49 2.02255954 3.00382948
50 1.21128961 2.02255954
51 0.50001968 1.21128961
52 -0.27125026 0.50001968
53 -1.22252019 -0.27125026
54 -2.16379012 -1.22252019
55 -3.16506005 -2.16379012
56 -4.13632999 -3.16506005
57 -0.33759992 -4.13632999
58 2.10113015 -0.33759992
59 1.31986022 2.10113015
60 0.16859028 1.31986022
61 -0.79267965 0.16859028
62 2.57605042 -0.79267965
63 2.52478049 2.57605042
64 1.48351055 2.52478049
65 0.37224062 1.48351055
66 -0.51902931 0.37224062
67 -1.62029924 -0.51902931
68 -2.54156918 -1.62029924
69 3.42716089 -2.54156918
70 1.77589096 3.42716089
71 0.18462102 1.77589096
72 -1.05664891 0.18462102
73 -2.30791884 -1.05664891
74 -3.75918877 -2.30791884
75 -2.06045871 -3.75918877
76 -2.40172864 -2.06045871
77 -3.78299857 -2.40172864
78 -5.13426850 -3.78299857
79 -6.62553844 -5.13426850
80 -4.01680837 -6.62553844
81 -3.48807830 -4.01680837
82 -3.84934823 -3.48807830
83 -5.30061817 -3.84934823
84 -5.62188810 -5.30061817
85 -7.04315803 -5.62188810
86 -7.97442796 -7.04315803
87 -7.99569790 -7.97442796
88 -8.32696783 -7.99569790
89 -8.96823776 -8.32696783
90 -10.54950770 -8.96823776
91 -9.05077763 -10.54950770
92 -8.50204756 -9.05077763
93 -9.91331749 -8.50204756
94 -10.66458743 -9.91331749
95 -9.88585736 -10.66458743
96 -11.31712729 -9.88585736
97 -13.04839722 -11.31712729
98 -11.60966716 -13.04839722
99 -14.79093709 -11.60966716
100 -17.57220702 -14.79093709
101 -15.88347695 -17.57220702
102 -17.89474689 -15.88347695
103 -19.56601682 -17.89474689
104 -17.73728675 -19.56601682
105 -19.59855669 -17.73728675
106 -16.30982662 -19.59855669
107 -16.32109655 -16.30982662
108 -10.72236648 -16.32109655
109 -1.09363642 -10.72236648
110 13.59509365 -1.09363642
111 15.01382372 13.59509365
112 16.02255379 15.01382372
113 14.99128385 16.02255379
114 13.40001392 14.99128385
115 11.85874399 13.40001392
116 10.06747406 11.85874399
117 8.89620412 10.06747406
118 9.95493419 8.89620412
119 8.17366426 9.95493419
120 6.59239433 8.17366426
121 5.18112439 6.59239433
122 3.65985446 5.18112439
123 2.21858453 3.65985446
124 0.77731459 2.21858453
125 -0.50395534 0.77731459
126 -1.80522527 -0.50395534
127 -2.95649520 -1.80522527
128 -3.98776514 -2.95649520
129 -2.48903507 -3.98776514
130 -0.83030500 -2.48903507
131 -1.81157493 -0.83030500
132 -1.68284487 -1.81157493
133 0.24588520 -1.68284487
134 -1.44538473 0.24588520
135 -0.61665466 -1.44538473
136 -1.26792460 -0.61665466
137 -2.91919453 -1.26792460
138 -4.39046446 -2.91919453
139 -5.82173439 -4.39046446
140 -7.29300433 -5.82173439
141 -5.91427426 -7.29300433
142 -1.57554419 -5.91427426
143 -2.99681413 -1.57554419
144 -2.91808406 -2.99681413
145 -5.93935399 -2.91808406
146 -6.82062392 -5.93935399
147 -0.35189386 -6.82062392
148 -2.03316379 -0.35189386
149 -1.20443372 -2.03316379
150 -1.72570365 -1.20443372
151 -3.21697359 -1.72570365
152 -4.75824352 -3.21697359
153 -5.11951345 -4.75824352
154 -4.60078338 -5.11951345
155 -6.22205332 -4.60078338
156 -7.96332325 -6.22205332
157 -9.75459318 -7.96332325
158 -7.76586311 -9.75459318
159 -5.55713305 -7.76586311
160 -7.23840298 -5.55713305
161 -8.83967291 -7.23840298
162 -10.32094285 -8.83967291
163 -11.81221278 -10.32094285
164 -5.51348271 -11.81221278
165 -6.32475264 -5.51348271
166 -7.72602258 -6.32475264
167 -9.20729251 -7.72602258
168 -10.47856244 -9.20729251
169 -11.61983237 -10.47856244
170 -10.37110231 -11.61983237
171 -6.70237224 -10.37110231
172 -7.85364217 -6.70237224
173 -9.00491210 -7.85364217
174 -10.10618204 -9.00491210
175 -11.26745197 -10.10618204
176 -12.75872190 -11.26745197
177 -10.97999184 -12.75872190
178 -11.58126177 -10.97999184
179 -12.84253170 -11.58126177
180 -12.83380163 -12.84253170
181 -16.58507157 -12.83380163
182 -18.43634150 -16.58507157
183 -19.08761143 -18.43634150
184 -19.72888136 -19.08761143
185 -20.38015130 -19.72888136
186 -24.17142123 -20.38015130
187 -27.51269116 -24.17142123
188 -28.06396109 -27.51269116
189 -28.61523103 -28.06396109
190 -29.14650096 -28.61523103
191 -29.69777089 -29.14650096
192 -30.18904082 -29.69777089
193 -30.66031076 -30.18904082
194 -31.12158069 -30.66031076
195 -28.50285062 -31.12158069
196 -28.16412056 -28.50285062
197 -28.85539049 -28.16412056
198 -29.34666042 -28.85539049
199 -23.02793035 -29.34666042
200 -23.56920029 -23.02793035
201 -24.11047022 -23.56920029
202 -24.38174015 -24.11047022
203 -25.16301008 -24.38174015
204 -25.62428002 -25.16301008
205 -18.76554995 -25.62428002
206 0.89318012 -18.76554995
207 -0.26808981 0.89318012
208 -1.09935975 -0.26808981
209 -0.13062968 -1.09935975
210 -1.40189961 -0.13062968
211 18.20683046 -1.40189961
212 32.41556052 18.20683046
213 35.03429059 32.41556052
214 34.77302066 35.03429059
215 30.70175072 34.77302066
216 28.74048079 30.70175072
217 27.84921086 28.74048079
218 25.77794093 27.84921086
219 25.00667099 25.77794093
220 28.04540106 25.00667099
221 24.67413113 28.04540106
222 22.72286120 24.67413113
223 19.07159126 22.72286120
224 17.61032133 19.07159126
225 14.36905140 17.61032133
226 14.49778147 14.36905140
227 14.41651153 14.49778147
228 8.11524160 14.41651153
229 10.72397167 8.11524160
230 10.28270174 10.72397167
231 7.35143180 10.28270174
232 8.11016187 7.35143180
233 6.95889194 8.11016187
234 9.66762200 6.95889194
235 25.46635207 9.66762200
236 27.40508214 25.46635207
237 29.94381221 27.40508214
238 29.99254227 29.94381221
239 22.24127234 29.99254227
240 17.44000241 22.24127234
241 36.43873248 17.44000241
242 80.33746254 36.43873248
243 70.39619261 80.33746254
244 94.91492268 70.39619261
245 94.98365275 94.91492268
246 55.75238281 94.98365275
247 49.07111288 55.75238281
248 44.23984295 49.07111288
249 38.51857301 44.23984295
250 33.55730308 38.51857301
251 40.93603315 33.55730308
252 40.72476322 40.93603315
253 47.75349328 40.72476322
254 32.70222335 47.75349328
255 34.39095342 32.70222335
256 22.90968349 34.39095342
257 21.34841355 22.90968349
258 22.34714362 21.34841355
259 21.12587369 22.34714362
260 12.71460376 21.12587369
261 11.08333382 12.71460376
262 16.52206389 11.08333382
263 17.61079396 16.52206389
264 16.39952403 17.61079396
265 13.49825409 16.39952403
266 14.67698416 13.49825409
267 13.20571423 14.67698416
268 11.58444429 13.20571423
269 11.65317436 11.58444429
270 5.69190443 11.65317436
271 3.15063450 5.69190443
272 -1.04063544 3.15063450
273 -1.06190537 -1.04063544
274 7.78682470 -1.06190537
275 20.02555477 7.78682470
276 10.78428483 20.02555477
277 5.70301490 10.78428483
278 6.80174497 5.70301490
279 2.64047504 6.80174497
280 1.49920510 2.64047504
281 -3.88206483 1.49920510
282 -4.19333476 -3.88206483
283 -8.17460469 -4.19333476
284 -9.00587463 -8.17460469
285 -7.85714456 -9.00587463
286 -6.53841449 -7.85714456
287 -8.04968443 -6.53841449
288 -11.29095436 -8.04968443
289 -17.62222429 -11.29095436
290 -17.40349422 -17.62222429
291 -14.19476416 -17.40349422
292 -10.27603409 -14.19476416
293 -20.92730402 -10.27603409
294 -21.30857395 -20.92730402
295 -20.67984389 -21.30857395
296 -19.77111382 -20.67984389
297 -25.62238375 -19.77111382
298 -22.62365368 -25.62238375
299 -23.54492362 -22.62365368
300 -21.40619355 -23.54492362
301 -22.86746348 -21.40619355
302 -17.68873341 -22.86746348
303 -14.61000335 -17.68873341
304 -20.54127328 -14.61000335
305 -23.12254321 -20.54127328
306 -30.02381315 -23.12254321
307 -31.85508308 -30.02381315
308 -26.41635301 -31.85508308
309 -26.40762294 -26.41635301
310 -23.03889288 -26.40762294
311 -30.16016281 -23.03889288
312 -25.93143274 -30.16016281
313 -27.30270267 -25.93143274
314 -30.51397261 -27.30270267
315 -27.90524254 -30.51397261
316 -26.38651247 -27.90524254
317 -29.80778240 -26.38651247
318 -25.81905234 -29.80778240
319 -28.74032227 -25.81905234
320 -28.26159220 -28.74032227
321 -29.46286213 -28.26159220
322 -28.62413207 -29.46286213
323 -27.12540200 -28.62413207
324 -20.73667193 -27.12540200
325 -20.44794187 -20.73667193
326 -18.03921180 -20.44794187
327 -20.06048173 -18.03921180
328 -18.47175166 -20.06048173
329 -13.04302160 -18.47175166
330 -21.46429153 -13.04302160
331 -20.47556146 -21.46429153
332 -13.66683139 -20.47556146
333 -14.80810133 -13.66683139
334 -6.58937126 -14.80810133
335 3.04935881 -6.58937126
336 3.82808888 3.04935881
337 17.51681894 3.82808888
338 31.47554901 17.51681894
339 24.03427908 31.47554901
340 21.16300914 24.03427908
341 14.32173921 21.16300914
342 4.52046928 14.32173921
343 4.46919935 4.52046928
344 -0.28207059 4.46919935
345 9.49665948 -0.28207059
346 13.26538955 9.49665948
347 13.34411962 13.26538955
348 28.66284968 13.34411962
349 19.26157975 28.66284968
350 13.22030982 19.26157975
351 14.39903989 13.22030982
352 10.93776995 14.39903989
353 3.95650002 10.93776995
354 5.20523009 3.95650002
355 11.34396016 5.20523009
356 7.64269022 11.34396016
357 6.23142029 7.64269022
358 18.42015036 6.23142029
359 26.20888042 18.42015036
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7drl41321478530.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/83esg1321478530.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9lsnl1321478530.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/104rpz1321478530.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/1196n71321478530.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12fctg1321478530.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13g2dr1321478530.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14ecdr1321478530.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/154zw71321478530.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/16donz1321478530.tab")
+ }
>
> try(system("convert tmp/1d6z61321478530.ps tmp/1d6z61321478530.png",intern=TRUE))
character(0)
> try(system("convert tmp/20c431321478530.ps tmp/20c431321478530.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vihn1321478530.ps tmp/3vihn1321478530.png",intern=TRUE))
character(0)
> try(system("convert tmp/4y8pm1321478530.ps tmp/4y8pm1321478530.png",intern=TRUE))
character(0)
> try(system("convert tmp/5138x1321478530.ps tmp/5138x1321478530.png",intern=TRUE))
character(0)
> try(system("convert tmp/6bcyl1321478530.ps tmp/6bcyl1321478530.png",intern=TRUE))
character(0)
> try(system("convert tmp/7drl41321478530.ps tmp/7drl41321478530.png",intern=TRUE))
character(0)
> try(system("convert tmp/83esg1321478530.ps tmp/83esg1321478530.png",intern=TRUE))
character(0)
> try(system("convert tmp/9lsnl1321478530.ps tmp/9lsnl1321478530.png",intern=TRUE))
character(0)
> try(system("convert tmp/104rpz1321478530.ps tmp/104rpz1321478530.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
9.219 0.552 16.423