R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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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
+ ,255
+ ,87.28
+ ,280.2
+ ,87.09
+ ,299.9
+ ,86.92
+ ,339.2
+ ,87.59
+ ,374.2
+ ,90.72
+ ,393.5
+ ,90.69
+ ,389.2
+ ,90.3
+ ,381.7
+ ,89.55
+ ,375.2
+ ,88.94
+ ,369
+ ,88.41
+ ,357.4
+ ,87.82
+ ,352.1
+ ,87.07
+ ,346.5
+ ,86.82
+ ,342.9
+ ,86.4
+ ,340.3
+ ,86.02
+ ,328.3
+ ,85.66
+ ,322.9
+ ,85.32
+ ,314.3
+ ,85
+ ,308.9
+ ,84.67
+ ,294
+ ,83.94
+ ,285.6
+ ,82.83
+ ,281.2
+ ,81.95
+ ,280.3
+ ,81.19
+ ,278.8
+ ,80.48
+ ,274.5
+ ,78.86
+ ,270.4
+ ,69.47
+ ,263.4
+ ,68.77
+ ,259.9
+ ,70.06
+ ,258
+ ,73.95
+ ,262.7
+ ,75.8
+ ,284.7
+ ,77.79
+ ,311.3
+ ,81.57
+ ,322.1
+ ,83.07
+ ,327
+ ,84.34
+ ,331.3
+ ,85.1
+ ,333.3
+ ,85.25
+ ,321.4
+ ,84.26
+ ,327
+ ,83.63
+ ,320
+ ,86.44
+ ,314.7
+ ,85.3
+ ,316.7
+ ,84.1
+ ,314.4
+ ,83.36
+ ,321.3
+ ,82.48
+ ,318.2
+ ,81.58
+ ,307.2
+ ,80.47
+ ,301.3
+ ,79.34
+ ,287.5
+ ,82.13
+ ,277.7
+ ,81.69
+ ,274.4
+ ,80.7
+ ,258.8
+ ,79.88
+ ,253.3
+ ,79.16
+ ,251
+ ,78.38
+ ,248.4
+ ,77.42
+ ,249.5
+ ,76.47
+ ,246.1
+ ,75.46
+ ,244.5
+ ,74.48
+ ,243.6
+ ,78.27
+ ,244
+ ,80.7
+ ,240.8
+ ,79.91
+ ,249.8
+ ,78.75
+ ,248
+ ,77.78
+ ,259.4
+ ,81.14
+ ,260.5
+ ,81.08
+ ,260.8
+ ,80.03
+ ,261.3
+ ,78.91
+ ,259.5
+ ,78.01
+ ,256.6
+ ,76.9
+ ,257.9
+ ,75.97
+ ,256.5
+ ,81.93
+ ,254.2
+ ,80.27
+ ,253.3
+ ,78.67
+ ,253.8
+ ,77.42
+ ,255.5
+ ,76.16
+ ,257.1
+ ,74.7
+ ,257.3
+ ,76.39
+ ,253.2
+ ,76.04
+ ,252.8
+ ,74.65
+ ,252
+ ,73.29
+ ,250.7
+ ,71.79
+ ,252.2
+ ,74.39
+ ,250
+ ,74.91
+ ,251
+ ,74.54
+ ,253.4
+ ,73.08
+ ,251.2
+ ,72.75
+ ,255.6
+ ,71.32
+ ,261.1
+ ,70.38
+ ,258.9
+ ,70.35
+ ,259.9
+ ,70.01
+ ,261.2
+ ,69.36
+ ,264.7
+ ,67.77
+ ,267.1
+ ,69.26
+ ,266.4
+ ,69.8
+ ,267.7
+ ,68.38
+ ,268.6
+ ,67.62
+ ,267.5
+ ,68.39
+ ,268.5
+ ,66.95
+ ,268.5
+ ,65.21
+ ,270.5
+ ,66.64
+ ,270.9
+ ,63.45
+ ,270.1
+ ,60.66
+ ,269.3
+ ,62.34
+ ,269.8
+ ,60.32
+ ,270.1
+ ,58.64
+ ,264.9
+ ,60.46
+ ,263.7
+ ,58.59
+ ,264.8
+ ,61.87
+ ,263.7
+ ,61.85
+ ,255.9
+ ,67.44
+ ,276.2
+ ,77.06
+ ,360.1
+ ,91.74
+ ,380.5
+ ,93.15
+ ,373.7
+ ,94.15
+ ,369.8
+ ,93.11
+ ,366.6
+ ,91.51
+ ,359.3
+ ,89.96
+ ,345.8
+ ,88.16
+ ,326.2
+ ,86.98
+ ,324.5
+ ,88.03
+ ,328.1
+ ,86.24
+ ,327.5
+ ,84.65
+ ,324.4
+ ,83.23
+ ,316.5
+ ,81.7
+ ,310.9
+ ,80.25
+ ,301.5
+ ,78.8
+ ,291.7
+ ,77.51
+ ,290.4
+ ,76.2
+ ,287.4
+ ,75.04
+ ,277.7
+ ,74
+ ,281.6
+ ,75.49
+ ,288
+ ,77.14
+ ,276
+ ,76.15
+ ,272.9
+ ,76.27
+ ,283
+ ,78.19
+ ,283.3
+ ,76.49
+ ,276.8
+ ,77.31
+ ,284.5
+ ,76.65
+ ,282.7
+ ,74.99
+ ,281.2
+ ,73.51
+ ,287.4
+ ,72.07
+ ,283.1
+ ,70.59
+ ,284
+ ,71.96
+ ,285.5
+ ,76.29
+ ,289.2
+ ,74.86
+ ,292.5
+ ,74.93
+ ,296.4
+ ,71.9
+ ,305.2
+ ,71.01
+ ,303.9
+ ,77.47
+ ,311.5
+ ,75.78
+ ,316.3
+ ,76.6
+ ,316.7
+ ,76.07
+ ,322.5
+ ,74.57
+ ,317.1
+ ,73.02
+ ,309.8
+ ,72.65
+ ,303.8
+ ,73.16
+ ,290.3
+ ,71.53
+ ,293.7
+ ,69.78
+ ,291.7
+ ,67.98
+ ,296.5
+ ,69.96
+ ,289.1
+ ,72.16
+ ,288.5
+ ,70.47
+ ,293.8
+ ,68.86
+ ,297.7
+ ,67.37
+ ,305.4
+ ,65.87
+ ,302.7
+ ,72.16
+ ,302.5
+ ,71.34
+ ,303
+ ,69.93
+ ,294.5
+ ,68.44
+ ,294.1
+ ,67.16
+ ,294.5
+ ,66.01
+ ,297.1
+ ,67.25
+ ,289.4
+ ,70.91
+ ,292.4
+ ,69.75
+ ,287.9
+ ,68.59
+ ,286.6
+ ,67.48
+ ,280.5
+ ,66.31
+ ,272.4
+ ,64.81
+ ,269.2
+ ,66.58
+ ,270.6
+ ,65.97
+ ,267.3
+ ,64.7
+ ,262.5
+ ,64.7
+ ,266.8
+ ,60.94
+ ,268.8
+ ,59.08
+ ,263.1
+ ,58.42
+ ,261.2
+ ,57.77
+ ,266
+ ,57.11
+ ,262.5
+ ,53.31
+ ,265.2
+ ,49.96
+ ,261.3
+ ,49.4
+ ,253.7
+ ,48.84
+ ,249.2
+ ,48.3
+ ,239.1
+ ,47.74
+ ,236.4
+ ,47.24
+ ,235.2
+ ,46.76
+ ,245.2
+ ,46.29
+ ,246.2
+ ,48.9
+ ,247.7
+ ,49.23
+ ,251.4
+ ,48.53
+ ,253.3
+ ,48.03
+ ,254.8
+ ,54.34
+ ,250
+ ,53.79
+ ,249.3
+ ,53.24
+ ,241.5
+ ,52.96
+ ,243.3
+ ,52.17
+ ,248
+ ,51.7
+ ,253
+ ,58.55
+ ,252.9
+ ,78.2
+ ,251.5
+ ,77.03
+ ,251.6
+ ,76.19
+ ,253.5
+ ,77.15
+ ,259.8
+ ,75.87
+ ,334.1
+ ,95.47
+ ,448
+ ,109.67
+ ,445.8
+ ,112.28
+ ,445
+ ,112.01
+ ,448.2
+ ,107.93
+ ,438.2
+ ,105.96
+ ,439.8
+ ,105.06
+ ,423.4
+ ,102.98
+ ,410.8
+ ,102.2
+ ,408.4
+ ,105.23
+ ,406.7
+ ,101.85
+ ,405.9
+ ,99.89
+ ,402.7
+ ,96.23
+ ,405.1
+ ,94.76
+ ,399.6
+ ,91.51
+ ,386.5
+ ,91.63
+ ,381.4
+ ,91.54
+ ,375.2
+ ,85.23
+ ,357.7
+ ,87.83
+ ,359
+ ,87.38
+ ,355
+ ,84.44
+ ,352.7
+ ,85.19
+ ,344.4
+ ,84.03
+ ,343.8
+ ,86.73
+ ,338
+ ,102.52
+ ,339
+ ,104.45
+ ,333.3
+ ,106.98
+ ,334.4
+ ,107.02
+ ,328.3
+ ,99.26
+ ,330.7
+ ,94.45
+ ,330
+ ,113.44
+ ,331.6
+ ,157.33
+ ,351.2
+ ,147.38
+ ,389.4
+ ,171.89
+ ,410.9
+ ,171.95
+ ,442.8
+ ,132.71
+ ,462.8
+ ,126.02
+ ,466.9
+ ,121.18
+ ,461.7
+ ,115.45
+ ,439.2
+ ,110.48
+ ,430.3
+ ,117.85
+ ,416.1
+ ,117.63
+ ,402.5
+ ,124.65
+ ,397.3
+ ,109.59
+ ,403.3
+ ,111.27
+ ,395.9
+ ,99.78
+ ,387.8
+ ,98.21
+ ,378.6
+ ,99.2
+ ,377.1
+ ,97.97
+ ,370.4
+ ,89.55
+ ,362
+ ,87.91
+ ,350.3
+ ,93.34
+ ,348.2
+ ,94.42
+ ,344.6
+ ,93.2
+ ,343.5
+ ,90.29
+ ,342.8
+ ,91.46
+ ,347.6
+ ,89.98
+ ,346.6
+ ,88.35
+ ,349.5
+ ,88.41
+ ,342.1
+ ,82.44
+ ,342
+ ,79.89
+ ,342.8
+ ,75.69
+ ,339.3
+ ,75.66
+ ,348.2
+ ,84.5
+ ,333.7
+ ,96.73
+ ,334.7
+ ,87.48
+ ,354
+ ,82.39
+ ,367.7
+ ,83.48
+ ,363.3
+ ,79.31
+ ,358.4
+ ,78.16
+ ,353.1
+ ,72.77
+ ,343.1
+ ,72.45
+ ,344.6
+ ,68.46
+ ,344.4
+ ,67.62
+ ,333.9
+ ,68.76
+ ,331.7
+ ,70.07
+ ,324.3
+ ,68.55
+ ,321.2
+ ,65.3
+ ,322.4
+ ,58.96
+ ,321.7
+ ,59.17
+ ,320.5
+ ,62.37
+ ,312.8
+ ,66.28
+ ,309.7
+ ,55.62
+ ,315.6
+ ,55.23
+ ,309.7
+ ,55.85
+ ,304.6
+ ,56.75
+ ,302.5
+ ,50.89
+ ,301.5
+ ,53.88
+ ,298.8
+ ,52.95
+ ,291.3
+ ,55.08
+ ,293.6
+ ,53.61
+ ,294.6
+ ,58.78
+ ,285.9
+ ,61.85
+ ,297.6
+ ,55.91
+ ,301.1
+ ,53.32
+ ,293.8
+ ,46.41
+ ,297.7
+ ,44.57
+ ,292.9
+ ,50
+ ,292.1
+ ,50
+ ,287.2
+ ,53.36
+ ,288.2
+ ,46.23
+ ,283.8
+ ,50.45
+ ,299.9
+ ,49.07
+ ,292.4
+ ,45.85
+ ,293.3
+ ,48.45
+ ,300.8
+ ,49.96
+ ,293.7
+ ,46.53
+ ,293.1
+ ,50.51
+ ,294.4
+ ,47.58
+ ,292.1
+ ,48.05
+ ,291.9
+ ,46.84
+ ,282.5
+ ,47.67
+ ,277.9
+ ,49.16
+ ,287.5
+ ,55.54
+ ,289.2
+ ,55.82
+ ,285.6
+ ,58.22
+ ,293.2
+ ,56.19
+ ,290.8
+ ,57.77
+ ,283.1
+ ,63.19
+ ,275
+ ,54.76
+ ,287.8
+ ,55.74
+ ,287.8
+ ,62.54
+ ,287.4
+ ,61.39
+ ,284
+ ,69.6
+ ,277.8
+ ,79.23
+ ,277.6
+ ,80
+ ,304.9
+ ,93.68
+ ,294
+ ,107.63
+ ,300.9
+ ,100.18
+ ,324
+ ,97.3
+ ,332.9
+ ,90.45
+ ,341.6
+ ,80.64
+ ,333.4
+ ,80.58
+ ,348.2
+ ,75.82
+ ,344.7
+ ,85.59
+ ,344.7
+ ,89.35
+ ,329.3
+ ,89.42
+ ,323.5
+ ,104.73
+ ,323.2
+ ,95.32
+ ,317.4
+ ,89.27
+ ,330.1
+ ,90.44
+ ,329.2
+ ,86.97
+ ,334.9
+ ,79.98
+ ,315.8
+ ,81.22
+ ,315.4
+ ,87.35
+ ,319.6
+ ,83.64
+ ,317.3
+ ,82.22
+ ,313.8
+ ,94.4
+ ,315.8
+ ,102.18
+ ,311.3)
+ ,dim=c(2
+ ,360)
+ ,dimnames=list(c('Colombia'
+ ,'USA')
+ ,1:360))
> y <- array(NA,dim=c(2,360),dimnames=list(c('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 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Colombia USA
1 87.28 255.0
2 87.28 280.2
3 87.09 299.9
4 86.92 339.2
5 87.59 374.2
6 90.72 393.5
7 90.69 389.2
8 90.30 381.7
9 89.55 375.2
10 88.94 369.0
11 88.41 357.4
12 87.82 352.1
13 87.07 346.5
14 86.82 342.9
15 86.40 340.3
16 86.02 328.3
17 85.66 322.9
18 85.32 314.3
19 85.00 308.9
20 84.67 294.0
21 83.94 285.6
22 82.83 281.2
23 81.95 280.3
24 81.19 278.8
25 80.48 274.5
26 78.86 270.4
27 69.47 263.4
28 68.77 259.9
29 70.06 258.0
30 73.95 262.7
31 75.80 284.7
32 77.79 311.3
33 81.57 322.1
34 83.07 327.0
35 84.34 331.3
36 85.10 333.3
37 85.25 321.4
38 84.26 327.0
39 83.63 320.0
40 86.44 314.7
41 85.30 316.7
42 84.10 314.4
43 83.36 321.3
44 82.48 318.2
45 81.58 307.2
46 80.47 301.3
47 79.34 287.5
48 82.13 277.7
49 81.69 274.4
50 80.70 258.8
51 79.88 253.3
52 79.16 251.0
53 78.38 248.4
54 77.42 249.5
55 76.47 246.1
56 75.46 244.5
57 74.48 243.6
58 78.27 244.0
59 80.70 240.8
60 79.91 249.8
61 78.75 248.0
62 77.78 259.4
63 81.14 260.5
64 81.08 260.8
65 80.03 261.3
66 78.91 259.5
67 78.01 256.6
68 76.90 257.9
69 75.97 256.5
70 81.93 254.2
71 80.27 253.3
72 78.67 253.8
73 77.42 255.5
74 76.16 257.1
75 74.70 257.3
76 76.39 253.2
77 76.04 252.8
78 74.65 252.0
79 73.29 250.7
80 71.79 252.2
81 74.39 250.0
82 74.91 251.0
83 74.54 253.4
84 73.08 251.2
85 72.75 255.6
86 71.32 261.1
87 70.38 258.9
88 70.35 259.9
89 70.01 261.2
90 69.36 264.7
91 67.77 267.1
92 69.26 266.4
93 69.80 267.7
94 68.38 268.6
95 67.62 267.5
96 68.39 268.5
97 66.95 268.5
98 65.21 270.5
99 66.64 270.9
100 63.45 270.1
101 60.66 269.3
102 62.34 269.8
103 60.32 270.1
104 58.64 264.9
105 60.46 263.7
106 58.59 264.8
107 61.87 263.7
108 61.85 255.9
109 67.44 276.2
110 77.06 360.1
111 91.74 380.5
112 93.15 373.7
113 94.15 369.8
114 93.11 366.6
115 91.51 359.3
116 89.96 345.8
117 88.16 326.2
118 86.98 324.5
119 88.03 328.1
120 86.24 327.5
121 84.65 324.4
122 83.23 316.5
123 81.70 310.9
124 80.25 301.5
125 78.80 291.7
126 77.51 290.4
127 76.20 287.4
128 75.04 277.7
129 74.00 281.6
130 75.49 288.0
131 77.14 276.0
132 76.15 272.9
133 76.27 283.0
134 78.19 283.3
135 76.49 276.8
136 77.31 284.5
137 76.65 282.7
138 74.99 281.2
139 73.51 287.4
140 72.07 283.1
141 70.59 284.0
142 71.96 285.5
143 76.29 289.2
144 74.86 292.5
145 74.93 296.4
146 71.90 305.2
147 71.01 303.9
148 77.47 311.5
149 75.78 316.3
150 76.60 316.7
151 76.07 322.5
152 74.57 317.1
153 73.02 309.8
154 72.65 303.8
155 73.16 290.3
156 71.53 293.7
157 69.78 291.7
158 67.98 296.5
159 69.96 289.1
160 72.16 288.5
161 70.47 293.8
162 68.86 297.7
163 67.37 305.4
164 65.87 302.7
165 72.16 302.5
166 71.34 303.0
167 69.93 294.5
168 68.44 294.1
169 67.16 294.5
170 66.01 297.1
171 67.25 289.4
172 70.91 292.4
173 69.75 287.9
174 68.59 286.6
175 67.48 280.5
176 66.31 272.4
177 64.81 269.2
178 66.58 270.6
179 65.97 267.3
180 64.70 262.5
181 64.70 266.8
182 60.94 268.8
183 59.08 263.1
184 58.42 261.2
185 57.77 266.0
186 57.11 262.5
187 53.31 265.2
188 49.96 261.3
189 49.40 253.7
190 48.84 249.2
191 48.30 239.1
192 47.74 236.4
193 47.24 235.2
194 46.76 245.2
195 46.29 246.2
196 48.90 247.7
197 49.23 251.4
198 48.53 253.3
199 48.03 254.8
200 54.34 250.0
201 53.79 249.3
202 53.24 241.5
203 52.96 243.3
204 52.17 248.0
205 51.70 253.0
206 58.55 252.9
207 78.20 251.5
208 77.03 251.6
209 76.19 253.5
210 77.15 259.8
211 75.87 334.1
212 95.47 448.0
213 109.67 445.8
214 112.28 445.0
215 112.01 448.2
216 107.93 438.2
217 105.96 439.8
218 105.06 423.4
219 102.98 410.8
220 102.20 408.4
221 105.23 406.7
222 101.85 405.9
223 99.89 402.7
224 96.23 405.1
225 94.76 399.6
226 91.51 386.5
227 91.63 381.4
228 91.54 375.2
229 85.23 357.7
230 87.83 359.0
231 87.38 355.0
232 84.44 352.7
233 85.19 344.4
234 84.03 343.8
235 86.73 338.0
236 102.52 339.0
237 104.45 333.3
238 106.98 334.4
239 107.02 328.3
240 99.26 330.7
241 94.45 330.0
242 113.44 331.6
243 157.33 351.2
244 147.38 389.4
245 171.89 410.9
246 171.95 442.8
247 132.71 462.8
248 126.02 466.9
249 121.18 461.7
250 115.45 439.2
251 110.48 430.3
252 117.85 416.1
253 117.63 402.5
254 124.65 397.3
255 109.59 403.3
256 111.27 395.9
257 99.78 387.8
258 98.21 378.6
259 99.20 377.1
260 97.97 370.4
261 89.55 362.0
262 87.91 350.3
263 93.34 348.2
264 94.42 344.6
265 93.20 343.5
266 90.29 342.8
267 91.46 347.6
268 89.98 346.6
269 88.35 349.5
270 88.41 342.1
271 82.44 342.0
272 79.89 342.8
273 75.69 339.3
274 75.66 348.2
275 84.50 333.7
276 96.73 334.7
277 87.48 354.0
278 82.39 367.7
279 83.48 363.3
280 79.31 358.4
281 78.16 353.1
282 72.77 343.1
283 72.45 344.6
284 68.46 344.4
285 67.62 333.9
286 68.76 331.7
287 70.07 324.3
288 68.55 321.2
289 65.30 322.4
290 58.96 321.7
291 59.17 320.5
292 62.37 312.8
293 66.28 309.7
294 55.62 315.6
295 55.23 309.7
296 55.85 304.6
297 56.75 302.5
298 50.89 301.5
299 53.88 298.8
300 52.95 291.3
301 55.08 293.6
302 53.61 294.6
303 58.78 285.9
304 61.85 297.6
305 55.91 301.1
306 53.32 293.8
307 46.41 297.7
308 44.57 292.9
309 50.00 292.1
310 50.00 287.2
311 53.36 288.2
312 46.23 283.8
313 50.45 299.9
314 49.07 292.4
315 45.85 293.3
316 48.45 300.8
317 49.96 293.7
318 46.53 293.1
319 50.51 294.4
320 47.58 292.1
321 48.05 291.9
322 46.84 282.5
323 47.67 277.9
324 49.16 287.5
325 55.54 289.2
326 55.82 285.6
327 58.22 293.2
328 56.19 290.8
329 57.77 283.1
330 63.19 275.0
331 54.76 287.8
332 55.74 287.8
333 62.54 287.4
334 61.39 284.0
335 69.60 277.8
336 79.23 277.6
337 80.00 304.9
338 93.68 294.0
339 107.63 300.9
340 100.18 324.0
341 97.30 332.9
342 90.45 341.6
343 80.64 333.4
344 80.58 348.2
345 75.82 344.7
346 85.59 344.7
347 89.35 329.3
348 89.42 323.5
349 104.73 323.2
350 95.32 317.4
351 89.27 330.1
352 90.44 329.2
353 86.97 334.9
354 79.98 315.8
355 81.22 315.4
356 87.35 319.6
357 83.64 317.3
358 82.22 313.8
359 94.40 315.8
360 102.18 311.3
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) USA
-6.4567 0.2724
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-28.759 -7.333 -0.128 6.677 68.120
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -6.45667 4.47982 -1.441 0.15
USA 0.27240 0.01435 18.984 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 13.33 on 358 degrees of freedom
Multiple R-squared: 0.5017, Adjusted R-squared: 0.5003
F-statistic: 360.4 on 1 and 358 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,] 1.299419e-05 2.598838e-05 0.999987006
[2,] 1.431804e-04 2.863609e-04 0.999856820
[3,] 2.369193e-05 4.738387e-05 0.999976308
[4,] 2.589656e-06 5.179312e-06 0.999997410
[5,] 2.132928e-07 4.265855e-07 0.999999787
[6,] 1.692576e-08 3.385153e-08 0.999999983
[7,] 1.380321e-09 2.760642e-09 0.999999999
[8,] 1.445737e-10 2.891474e-10 1.000000000
[9,] 2.686751e-11 5.373501e-11 1.000000000
[10,] 5.175308e-12 1.035062e-11 1.000000000
[11,] 1.307558e-12 2.615116e-12 1.000000000
[12,] 2.972897e-13 5.945795e-13 1.000000000
[13,] 7.199794e-14 1.439959e-13 1.000000000
[14,] 1.609484e-14 3.218968e-14 1.000000000
[15,] 3.535456e-15 7.070913e-15 1.000000000
[16,] 5.833987e-16 1.166797e-15 1.000000000
[17,] 1.190099e-16 2.380198e-16 1.000000000
[18,] 4.899911e-17 9.799823e-17 1.000000000
[19,] 3.429349e-17 6.858698e-17 1.000000000
[20,] 3.055435e-17 6.110869e-17 1.000000000
[21,] 2.611074e-17 5.222149e-17 1.000000000
[22,] 5.534633e-17 1.106927e-16 1.000000000
[23,] 1.730052e-12 3.460105e-12 1.000000000
[24,] 7.883243e-11 1.576649e-10 1.000000000
[25,] 2.325645e-10 4.651289e-10 1.000000000
[26,] 1.279987e-10 2.559975e-10 1.000000000
[27,] 7.170682e-11 1.434136e-10 1.000000000
[28,] 4.754948e-11 9.509896e-11 1.000000000
[29,] 1.721522e-11 3.443044e-11 1.000000000
[30,] 5.452783e-12 1.090557e-11 1.000000000
[31,] 1.605028e-12 3.210056e-12 1.000000000
[32,] 4.568828e-13 9.137657e-13 1.000000000
[33,] 1.333938e-13 2.667876e-13 1.000000000
[34,] 3.706313e-14 7.412626e-14 1.000000000
[35,] 1.013603e-14 2.027207e-14 1.000000000
[36,] 3.702676e-15 7.405353e-15 1.000000000
[37,] 1.083112e-15 2.166224e-15 1.000000000
[38,] 2.912362e-16 5.824723e-16 1.000000000
[39,] 7.787341e-17 1.557468e-16 1.000000000
[40,] 2.146864e-17 4.293729e-17 1.000000000
[41,] 5.736680e-18 1.147336e-17 1.000000000
[42,] 1.589140e-18 3.178280e-18 1.000000000
[43,] 4.253094e-19 8.506188e-19 1.000000000
[44,] 1.466229e-19 2.932459e-19 1.000000000
[45,] 4.881278e-20 9.762556e-20 1.000000000
[46,] 1.875877e-20 3.751754e-20 1.000000000
[47,] 6.662469e-21 1.332494e-20 1.000000000
[48,] 2.126402e-21 4.252803e-21 1.000000000
[49,] 6.289725e-22 1.257945e-21 1.000000000
[50,] 1.718856e-22 3.437711e-22 1.000000000
[51,] 4.739694e-23 9.479388e-23 1.000000000
[52,] 1.378122e-23 2.756245e-23 1.000000000
[53,] 4.460865e-24 8.921730e-24 1.000000000
[54,] 1.437241e-24 2.874482e-24 1.000000000
[55,] 9.859657e-25 1.971931e-24 1.000000000
[56,] 3.721947e-25 7.443895e-25 1.000000000
[57,] 1.170058e-25 2.340117e-25 1.000000000
[58,] 3.203616e-26 6.407231e-26 1.000000000
[59,] 1.211795e-26 2.423589e-26 1.000000000
[60,] 4.443110e-27 8.886221e-27 1.000000000
[61,] 1.323180e-27 2.646361e-27 1.000000000
[62,] 3.654169e-28 7.308338e-28 1.000000000
[63,] 1.014888e-28 2.029776e-28 1.000000000
[64,] 3.077439e-29 6.154878e-29 1.000000000
[65,] 1.071415e-29 2.142831e-29 1.000000000
[66,] 6.868025e-30 1.373605e-29 1.000000000
[67,] 2.650445e-30 5.300890e-30 1.000000000
[68,] 7.943364e-31 1.588673e-30 1.000000000
[69,] 2.365290e-31 4.730580e-31 1.000000000
[70,] 8.499455e-32 1.699891e-31 1.000000000
[71,] 4.567636e-32 9.135271e-32 1.000000000
[72,] 1.499869e-32 2.999738e-32 1.000000000
[73,] 5.174585e-33 1.034917e-32 1.000000000
[74,] 2.405528e-33 4.811056e-33 1.000000000
[75,] 1.691719e-33 3.383437e-33 1.000000000
[76,] 2.415196e-33 4.830392e-33 1.000000000
[77,] 1.085534e-33 2.171067e-33 1.000000000
[78,] 4.389155e-34 8.778310e-34 1.000000000
[79,] 2.002385e-34 4.004769e-34 1.000000000
[80,] 1.347975e-34 2.695950e-34 1.000000000
[81,] 1.163019e-34 2.326038e-34 1.000000000
[82,] 2.519007e-34 5.038014e-34 1.000000000
[83,] 7.298982e-34 1.459796e-33 1.000000000
[84,] 1.934221e-33 3.868442e-33 1.000000000
[85,] 5.747513e-33 1.149503e-32 1.000000000
[86,] 2.596263e-32 5.192526e-32 1.000000000
[87,] 2.980406e-31 5.960812e-31 1.000000000
[88,] 9.880962e-31 1.976192e-30 1.000000000
[89,] 2.304477e-30 4.608954e-30 1.000000000
[90,] 1.004085e-29 2.008170e-29 1.000000000
[91,] 5.021394e-29 1.004279e-28 1.000000000
[92,] 1.503716e-28 3.007433e-28 1.000000000
[93,] 7.637001e-28 1.527400e-27 1.000000000
[94,] 8.437595e-27 1.687519e-26 1.000000000
[95,] 3.576130e-26 7.152260e-26 1.000000000
[96,] 5.369938e-25 1.073988e-24 1.000000000
[97,] 2.171176e-23 4.342352e-23 1.000000000
[98,] 2.354065e-22 4.708129e-22 1.000000000
[99,] 4.498091e-21 8.996182e-21 1.000000000
[100,] 8.648076e-20 1.729615e-19 1.000000000
[101,] 5.360194e-19 1.072039e-18 1.000000000
[102,] 5.204911e-18 1.040982e-17 1.000000000
[103,] 1.402555e-17 2.805111e-17 1.000000000
[104,] 2.710476e-17 5.420951e-17 1.000000000
[105,] 2.765128e-17 5.530256e-17 1.000000000
[106,] 4.407369e-17 8.814738e-17 1.000000000
[107,] 2.152942e-17 4.305884e-17 1.000000000
[108,] 1.122411e-17 2.244822e-17 1.000000000
[109,] 6.423385e-18 1.284677e-17 1.000000000
[110,] 3.415347e-18 6.830694e-18 1.000000000
[111,] 1.712436e-18 3.424872e-18 1.000000000
[112,] 8.754680e-19 1.750936e-18 1.000000000
[113,] 5.039500e-19 1.007900e-18 1.000000000
[114,] 2.654307e-19 5.308614e-19 1.000000000
[115,] 1.441186e-19 2.882372e-19 1.000000000
[116,] 6.861904e-20 1.372381e-19 1.000000000
[117,] 3.110597e-20 6.221194e-20 1.000000000
[118,] 1.417404e-20 2.834807e-20 1.000000000
[119,] 6.425781e-21 1.285156e-20 1.000000000
[120,] 2.988911e-21 5.977822e-21 1.000000000
[121,] 1.443698e-21 2.887397e-21 1.000000000
[122,] 6.933342e-22 1.386668e-21 1.000000000
[123,] 3.404844e-22 6.809689e-22 1.000000000
[124,] 1.744761e-22 3.489523e-22 1.000000000
[125,] 9.216473e-23 1.843295e-22 1.000000000
[126,] 4.600787e-23 9.201573e-23 1.000000000
[127,] 2.486372e-23 4.972744e-23 1.000000000
[128,] 1.349444e-23 2.698889e-23 1.000000000
[129,] 6.708117e-24 1.341623e-23 1.000000000
[130,] 3.475711e-24 6.951422e-24 1.000000000
[131,] 1.837300e-24 3.674601e-24 1.000000000
[132,] 9.159586e-25 1.831917e-24 1.000000000
[133,] 4.597424e-25 9.194848e-25 1.000000000
[134,] 2.353209e-25 4.706419e-25 1.000000000
[135,] 1.328581e-25 2.657161e-25 1.000000000
[136,] 8.245861e-26 1.649172e-25 1.000000000
[137,] 6.204535e-26 1.240907e-25 1.000000000
[138,] 3.961122e-26 7.922245e-26 1.000000000
[139,] 1.919059e-26 3.838118e-26 1.000000000
[140,] 9.922052e-27 1.984410e-26 1.000000000
[141,] 5.222476e-27 1.044495e-26 1.000000000
[142,] 4.927359e-27 9.854718e-27 1.000000000
[143,] 5.252630e-27 1.050526e-26 1.000000000
[144,] 2.518216e-27 5.036432e-27 1.000000000
[145,] 1.541085e-27 3.082169e-27 1.000000000
[146,] 8.456539e-28 1.691308e-27 1.000000000
[147,] 5.530526e-28 1.106105e-27 1.000000000
[148,] 4.006033e-28 8.012067e-28 1.000000000
[149,] 3.126504e-28 6.253009e-28 1.000000000
[150,] 2.235634e-28 4.471268e-28 1.000000000
[151,] 1.229629e-28 2.459258e-28 1.000000000
[152,] 8.465998e-29 1.693200e-28 1.000000000
[153,] 7.332669e-29 1.466534e-28 1.000000000
[154,] 1.029216e-28 2.058431e-28 1.000000000
[155,] 7.938332e-29 1.587666e-28 1.000000000
[156,] 4.579134e-29 9.158269e-29 1.000000000
[157,] 3.502281e-29 7.004562e-29 1.000000000
[158,] 3.892753e-29 7.785507e-29 1.000000000
[159,] 7.762452e-29 1.552490e-28 1.000000000
[160,] 1.976911e-28 3.953821e-28 1.000000000
[161,] 1.296106e-28 2.592212e-28 1.000000000
[162,] 9.552728e-29 1.910546e-28 1.000000000
[163,] 7.321301e-29 1.464260e-28 1.000000000
[164,] 7.036942e-29 1.407388e-28 1.000000000
[165,] 8.588184e-29 1.717637e-28 1.000000000
[166,] 1.421019e-28 2.842037e-28 1.000000000
[167,] 1.419612e-28 2.839224e-28 1.000000000
[168,] 8.744972e-29 1.748994e-28 1.000000000
[169,] 5.778001e-29 1.155600e-28 1.000000000
[170,] 4.301977e-29 8.603954e-29 1.000000000
[171,] 3.367676e-29 6.735351e-29 1.000000000
[172,] 2.734261e-29 5.468522e-29 1.000000000
[173,] 2.581109e-29 5.162218e-29 1.000000000
[174,] 1.950425e-29 3.900850e-29 1.000000000
[175,] 1.520412e-29 3.040824e-29 1.000000000
[176,] 1.301763e-29 2.603526e-29 1.000000000
[177,] 1.154927e-29 2.309854e-29 1.000000000
[178,] 1.982345e-29 3.964690e-29 1.000000000
[179,] 4.125739e-29 8.251478e-29 1.000000000
[180,] 8.836009e-29 1.767202e-28 1.000000000
[181,] 2.378653e-28 4.757307e-28 1.000000000
[182,] 6.157330e-28 1.231466e-27 1.000000000
[183,] 4.322167e-27 8.644334e-27 1.000000000
[184,] 5.727742e-26 1.145548e-25 1.000000000
[185,] 4.856378e-25 9.712756e-25 1.000000000
[186,] 3.193997e-24 6.387993e-24 1.000000000
[187,] 1.357655e-23 2.715310e-23 1.000000000
[188,] 5.097776e-23 1.019555e-22 1.000000000
[189,] 1.766465e-22 3.532930e-22 1.000000000
[190,] 8.404869e-22 1.680974e-21 1.000000000
[191,] 3.940752e-21 7.881504e-21 1.000000000
[192,] 1.024568e-20 2.049136e-20 1.000000000
[193,] 2.601638e-20 5.203276e-20 1.000000000
[194,] 7.340304e-20 1.468061e-19 1.000000000
[195,] 2.187145e-19 4.374289e-19 1.000000000
[196,] 2.251017e-19 4.502033e-19 1.000000000
[197,] 2.365605e-19 4.731210e-19 1.000000000
[198,] 2.284180e-19 4.568361e-19 1.000000000
[199,] 2.271717e-19 4.543434e-19 1.000000000
[200,] 2.574577e-19 5.149153e-19 1.000000000
[201,] 3.325502e-19 6.651004e-19 1.000000000
[202,] 2.431480e-19 4.862961e-19 1.000000000
[203,] 6.797203e-19 1.359441e-18 1.000000000
[204,] 1.670699e-18 3.341398e-18 1.000000000
[205,] 3.553709e-18 7.107418e-18 1.000000000
[206,] 7.011402e-18 1.402280e-17 1.000000000
[207,] 4.632806e-18 9.265612e-18 1.000000000
[208,] 1.621865e-17 3.243729e-17 1.000000000
[209,] 1.496725e-17 2.993449e-17 1.000000000
[210,] 1.365307e-17 2.730613e-17 1.000000000
[211,] 1.327257e-17 2.654514e-17 1.000000000
[212,] 1.237378e-17 2.474756e-17 1.000000000
[213,] 1.411709e-17 2.823418e-17 1.000000000
[214,] 1.181212e-17 2.362425e-17 1.000000000
[215,] 8.566423e-18 1.713285e-17 1.000000000
[216,] 6.166027e-18 1.233205e-17 1.000000000
[217,] 4.347671e-18 8.695343e-18 1.000000000
[218,] 3.095571e-18 6.191142e-18 1.000000000
[219,] 2.236462e-18 4.472923e-18 1.000000000
[220,] 2.215016e-18 4.430033e-18 1.000000000
[221,] 2.128974e-18 4.257948e-18 1.000000000
[222,] 1.764927e-18 3.529854e-18 1.000000000
[223,] 1.267760e-18 2.535520e-18 1.000000000
[224,] 7.971636e-19 1.594327e-18 1.000000000
[225,] 4.828265e-19 9.656530e-19 1.000000000
[226,] 2.655128e-19 5.310256e-19 1.000000000
[227,] 1.403180e-19 2.806361e-19 1.000000000
[228,] 7.987500e-20 1.597500e-19 1.000000000
[229,] 4.007925e-20 8.015849e-20 1.000000000
[230,] 2.036998e-20 4.073996e-20 1.000000000
[231,] 1.029411e-20 2.058822e-20 1.000000000
[232,] 3.166506e-20 6.333011e-20 1.000000000
[233,] 2.111487e-19 4.222974e-19 1.000000000
[234,] 2.229845e-18 4.459691e-18 1.000000000
[235,] 3.541822e-17 7.083645e-17 1.000000000
[236,] 8.223277e-17 1.644655e-16 1.000000000
[237,] 9.652813e-17 1.930563e-16 1.000000000
[238,] 5.485528e-15 1.097106e-14 1.000000000
[239,] 1.613084e-07 3.226168e-07 0.999999839
[240,] 2.451702e-05 4.903403e-05 0.999975483
[241,] 1.875730e-02 3.751460e-02 0.981242700
[242,] 2.098359e-01 4.196717e-01 0.790164125
[243,] 1.956638e-01 3.913276e-01 0.804336221
[244,] 1.880189e-01 3.760379e-01 0.811981066
[245,] 1.916886e-01 3.833772e-01 0.808311375
[246,] 1.873475e-01 3.746949e-01 0.812652542
[247,] 1.901462e-01 3.802924e-01 0.809853821
[248,] 1.731677e-01 3.463354e-01 0.826832307
[249,] 1.613291e-01 3.226581e-01 0.838670926
[250,] 1.799103e-01 3.598206e-01 0.820089708
[251,] 1.605555e-01 3.211110e-01 0.839444509
[252,] 1.437734e-01 2.875469e-01 0.856226572
[253,] 1.285693e-01 2.571387e-01 0.871430652
[254,] 1.127845e-01 2.255691e-01 0.887215468
[255,] 9.788822e-02 1.957764e-01 0.902111785
[256,] 8.437215e-02 1.687443e-01 0.915627847
[257,] 7.382507e-02 1.476501e-01 0.926174931
[258,] 6.326481e-02 1.265296e-01 0.936735190
[259,] 5.550960e-02 1.110192e-01 0.944490401
[260,] 5.067433e-02 1.013487e-01 0.949325669
[261,] 4.575367e-02 9.150734e-02 0.954246331
[262,] 3.980183e-02 7.960366e-02 0.960198170
[263,] 3.414391e-02 6.828783e-02 0.965856087
[264,] 2.892900e-02 5.785801e-02 0.971070996
[265,] 2.402310e-02 4.804620e-02 0.975976902
[266,] 2.029827e-02 4.059654e-02 0.979701729
[267,] 1.687758e-02 3.375515e-02 0.983122425
[268,] 1.436227e-02 2.872455e-02 0.985637727
[269,] 1.287114e-02 2.574227e-02 0.987128864
[270,] 1.268919e-02 2.537838e-02 0.987310810
[271,] 1.049101e-02 2.098201e-02 0.989508994
[272,] 1.188913e-02 2.377826e-02 0.988110871
[273,] 9.578823e-03 1.915765e-02 0.990421177
[274,] 9.689243e-03 1.937849e-02 0.990310757
[275,] 9.071360e-03 1.814272e-02 0.990928640
[276,] 9.389046e-03 1.877809e-02 0.990610954
[277,] 9.543262e-03 1.908652e-02 0.990456738
[278,] 1.032729e-02 2.065458e-02 0.989672708
[279,] 1.197064e-02 2.394127e-02 0.988029363
[280,] 1.771957e-02 3.543914e-02 0.982280428
[281,] 2.137385e-02 4.274770e-02 0.978626152
[282,] 2.370038e-02 4.740076e-02 0.976299622
[283,] 2.222571e-02 4.445143e-02 0.977774286
[284,] 2.086823e-02 4.173645e-02 0.979131773
[285,] 2.242024e-02 4.484049e-02 0.977579757
[286,] 3.212345e-02 6.424690e-02 0.967876548
[287,] 4.391365e-02 8.782731e-02 0.956086347
[288,] 4.444711e-02 8.889421e-02 0.955552893
[289,] 3.932313e-02 7.864626e-02 0.960676870
[290,] 5.640787e-02 1.128157e-01 0.943592131
[291,] 6.988253e-02 1.397651e-01 0.930117473
[292,] 7.576546e-02 1.515309e-01 0.924234538
[293,] 7.710898e-02 1.542180e-01 0.922891022
[294,] 9.361149e-02 1.872230e-01 0.906388515
[295,] 9.745646e-02 1.949129e-01 0.902543541
[296,] 9.411259e-02 1.882252e-01 0.905887413
[297,] 8.891808e-02 1.778362e-01 0.911081923
[298,] 8.760421e-02 1.752084e-01 0.912395786
[299,] 7.636471e-02 1.527294e-01 0.923635288
[300,] 6.620864e-02 1.324173e-01 0.933791360
[301,] 6.705154e-02 1.341031e-01 0.932948464
[302,] 6.537240e-02 1.307448e-01 0.934627605
[303,] 8.818732e-02 1.763746e-01 0.911812681
[304,] 1.133890e-01 2.267781e-01 0.886610964
[305,] 1.187480e-01 2.374961e-01 0.881251959
[306,] 1.164187e-01 2.328374e-01 0.883581280
[307,] 1.076325e-01 2.152651e-01 0.892367454
[308,] 1.114327e-01 2.228655e-01 0.888567263
[309,] 1.345895e-01 2.691791e-01 0.865410456
[310,] 1.483753e-01 2.967507e-01 0.851624652
[311,] 1.868506e-01 3.737012e-01 0.813149409
[312,] 2.478726e-01 4.957452e-01 0.752127392
[313,] 2.756358e-01 5.512715e-01 0.724364248
[314,] 3.375132e-01 6.750264e-01 0.662486788
[315,] 3.776036e-01 7.552072e-01 0.622396378
[316,] 4.438485e-01 8.876970e-01 0.556151521
[317,] 5.148805e-01 9.702389e-01 0.485119469
[318,] 5.585642e-01 8.828715e-01 0.441435754
[319,] 5.830638e-01 8.338724e-01 0.416936213
[320,] 6.485810e-01 7.028380e-01 0.351418988
[321,] 6.664382e-01 6.671236e-01 0.333561822
[322,] 6.766311e-01 6.467378e-01 0.323368895
[323,] 6.999623e-01 6.000754e-01 0.300037689
[324,] 7.427531e-01 5.144939e-01 0.257246926
[325,] 7.573460e-01 4.853080e-01 0.242654005
[326,] 7.288787e-01 5.422426e-01 0.271121319
[327,] 8.164488e-01 3.671025e-01 0.183551238
[328,] 9.023168e-01 1.953665e-01 0.097683246
[329,] 9.377658e-01 1.244683e-01 0.062234168
[330,] 9.784963e-01 4.300730e-02 0.021503652
[331,] 9.915241e-01 1.695174e-02 0.008475868
[332,] 9.956503e-01 8.699377e-03 0.004349689
[333,] 9.973965e-01 5.207029e-03 0.002603514
[334,] 9.962318e-01 7.536492e-03 0.003768246
[335,] 9.971349e-01 5.730113e-03 0.002865057
[336,] 9.975531e-01 4.893858e-03 0.002446929
[337,] 9.978010e-01 4.397915e-03 0.002198957
[338,] 9.967960e-01 6.407941e-03 0.003203970
[339,] 9.949117e-01 1.017667e-02 0.005088336
[340,] 9.907456e-01 1.850874e-02 0.009254368
[341,] 9.908400e-01 1.832000e-02 0.009160000
[342,] 9.837565e-01 3.248703e-02 0.016243516
[343,] 9.703902e-01 5.921952e-02 0.029609759
[344,] 9.480540e-01 1.038919e-01 0.051945973
[345,] 9.783286e-01 4.334272e-02 0.021671358
[346,] 9.701519e-01 5.969623e-02 0.029848117
[347,] 9.424525e-01 1.150950e-01 0.057547525
[348,] 9.020695e-01 1.958610e-01 0.097930476
[349,] 8.810963e-01 2.378073e-01 0.118903657
[350,] 8.362123e-01 3.275754e-01 0.163787718
[351,] 7.840126e-01 4.319748e-01 0.215987379
> postscript(file="/var/wessaorg/rcomp/tmp/1s1mo1322154116.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2nhuq1322154116.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3j07k1322154116.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/44xd01322154116.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/53dhv1322154116.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
24.27461187 17.41012642 11.85384216 0.97851366 -7.88549391 -10.01281809
7 8 9 10 11 12
-8.87149716 -7.21849553 -6.19789413 -5.11901279 -2.48917028 -1.63544913
13 14 15 16 17 18
-0.86000792 -0.12936714 0.15887342 3.04767602 4.15863719 6.16127905
19 20 21 22 23 24
7.31224021 11.04100344 12.59916525 12.68772621 12.05288640 11.70148673
25 26 27 28 29 30
12.16280766 11.65964854 4.17645006 4.42985081 6.23741123 8.84713021
31 32 33 34 35 36
4.70432545 -0.55152030 0.28655736 0.45179630 0.55047537 0.76567494
37 38 39 40 41 42
4.15723751 1.64179630 2.91859781 7.17231896 5.48751853 4.91403902
43 44 45 46 47 48
2.29447753 2.25891820 4.35532058 4.85248186 7.48160484 12.94112696
49 50 51 52 53 54
13.40004768 16.65949105 17.33769224 17.24421274 17.17245330 15.91281306
55 56 57 58 59 60
15.88897380 15.31481415 14.57997434 18.26101425 21.56269495 18.32109300
61 62 63 64 65 66
17.65141339 13.57605092 16.63641068 16.49469062 15.30849051 14.67881090
67 68 69 70 71 72
14.56877153 13.10465125 12.55601155 19.14253205 17.72769224 15.99149213
73 74 75 76 77 78
14.27841177 12.58257142 11.06809138 13.87493226 13.63389235 12.46181252
79 80 81 82 83 84
11.45593280 9.54733248 12.74661296 12.99421274 11.97045222 11.10973270
85 86 87 88 89 90
9.58117174 6.65297055 6.31225103 6.00985081 5.31573053 3.71232978
91 92 93 94 95 96
1.46856926 3.14924941 3.33512913 1.66996893 1.20960917 1.70720895
97 98 99 100 101 102
0.26720895 -2.01759148 -0.69655157 -3.66863139 -6.24071122 -4.69691133
103 104 105 106 107 108
-6.79863139 -7.06215027 -4.91527001 -7.08491025 -3.50527001 -1.40054832
109 110 111 112 113 114
-1.34027271 -14.57465086 -5.45161527 -2.18929380 -0.12693296 -0.29525227
115 116 117 118 119 120
0.09326931 2.22067223 5.75971647 5.04279684 5.11215606 3.48559619
121 122 123 124 125 126
2.74003686 3.47199857 3.46743978 4.57800182 5.79752394 4.86164422
127 128 129 130 131 132
4.36884487 5.85112696 3.74876612 3.49540474 8.41420733 8.26864800
133 134 135 136 137 138
5.63740582 7.47568575 7.54628716 6.26880549 6.09912588 4.84772621
139 140 141 142 143 144
1.67884487 1.41016580 -0.31499440 0.64640528 3.96852448 1.63960376
145 146 147 148 149 150
0.64724292 -4.77987899 -5.31575870 -0.92600035 -3.92352139 -3.21248147
151 152 153 154 155 156
-5.32240273 -5.35144156 -4.91291998 -3.64851868 0.53888424 -2.01727650
157 158 159 160 161 162
-3.22247606 -6.32999710 -2.33423550 0.02920463 -3.10451652 -5.77687736
163 164 165 166 167 168
-9.36435903 -10.12887844 -3.78439840 -4.74059851 -3.83519667 -5.21623658
169 170 171 172 173 174
-6.60519667 -8.46343723 -5.12595557 -2.28315622 -2.21735524 -3.02323496
175 176 177 178 179 180
-2.47159364 -1.43515189 -2.06347120 -0.67483150 -0.38591079 -0.34838975
181 182 183 184 185 186
-1.51971068 -5.82451111 -6.13182988 -6.27426947 -8.23179051 -7.93838975
187 188 189 190 191 192
-12.47387033 -14.76150949 -13.25126784 -12.58546687 -10.37422469 -10.19874410
193 194 195 196 197 198
-10.37186384 -13.57586601 -14.31826622 -12.11686655 -12.79474735 -14.01230776
199 200 201 202 203 204
-14.92090808 -7.30338704 -7.66270689 -6.08798521 -6.85830559 -8.92858661
205 206 207 208 209 210
-10.76058769 -3.88334767 16.14801263 14.95077261 13.59321220 12.83709084
211 212 213 214 215 216
-8.68224524 -20.10862988 -5.30934940 -2.48142923 -3.62310992 -4.97910776
217 218 219 220 221 222
-7.38494810 -3.81758455 -2.46534183 -2.59158131 0.90149906 -2.26058077
223 224 225 226 227 228
-3.34890008 -7.66266060 -7.63445941 -7.31601657 -5.80677547 -4.20789413
229 230 231 232 233 234
-5.75089034 -3.50501062 -2.86540976 -5.17888926 -2.16796746 -3.16452734
235 236 237 238 239 240
1.11539392 16.63299370 20.11567494 22.34603470 24.04767602 15.63391550
241 242 243 244 245 246
11.01459565 29.56875530 68.11971106 47.76402280 66.41741815 57.78785125
247 248 249 250 251 252
13.09984692 5.29300604 1.86948716 2.26849203 -0.27714605 10.96093702
253 254 255 256 257 258
14.44557997 22.88206109 6.18765979 9.88342139 0.59986315 1.53594514
259 260 261 262 263 264
2.93454546 3.52962691 -2.60221127 -1.05512874 4.94691171 7.00755249
265 266 267 268 269 270
6.08719273 3.36787288 3.23035184 2.02275206 -0.39720857 1.67855303
271 272 273 274 275 276
-4.26420695 -7.03212712 -10.27872636 -12.73308829 0.05671485 12.01431463
277 278 279 280 281 282
-2.49300954 -11.31489251 -9.02633155 -11.86157049 -11.56784935 -14.23384718
283 284 285 286 287 288
-14.96244751 -18.89796746 -16.87776519 -15.13848472 -11.81272312 -12.48828245
289 290 291 292 293 294
-16.06516271 -22.21448255 -21.67760229 -16.38012063 -11.62567996 -23.89284123
295 296 297 298 299 300
-22.67567996 -20.66643886 -19.19439840 -24.78199818 -21.05651760 -19.94351598
301 302 303 304 305 306
-18.44003648 -20.18243669 -12.64255481 -12.75963734 -19.65303810 -20.25451652
307 308 309 310 311 312
-28.22687736 -28.75935632 -23.11143615 -21.77667509 -18.68907531 -24.62051436
313 314 315 316 317 318
-24.78615784 -24.12315622 -27.58831641 -27.03131803 -23.58727650 -26.85383637
319 320 321 322 323 324
-23.22795665 -25.53143615 -25.00695611 -23.65639407 -21.57335308 -22.69839516
325 326 327 328 329 330
-16.78147552 -15.52083475 -15.19107639 -16.56731587 -12.88983420 -5.26339245
331 332 333 334 335 336
-17.18011522 -16.20011522 -9.29115513 -9.51499440 0.38388694 10.06836699
337 338 339 340 341 342
3.40184108 20.05100344 32.12144195 18.37899695 13.07463502 3.85475314
343 344 345 346 347 348
-3.72156509 -7.81308829 -11.61968753 -1.84968753 6.10527580 7.75519706
349 350 351 352 353 354
23.14691712 15.31683838 5.80735563 7.22251582 2.19983459 0.41267872
355 356 357 358 359 360
1.76163881 6.74755790 3.66407840 3.19747915 14.83267872 23.83847970
> postscript(file="/var/wessaorg/rcomp/tmp/67dsn1322154116.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 24.27461187 NA
1 17.41012642 24.27461187
2 11.85384216 17.41012642
3 0.97851366 11.85384216
4 -7.88549391 0.97851366
5 -10.01281809 -7.88549391
6 -8.87149716 -10.01281809
7 -7.21849553 -8.87149716
8 -6.19789413 -7.21849553
9 -5.11901279 -6.19789413
10 -2.48917028 -5.11901279
11 -1.63544913 -2.48917028
12 -0.86000792 -1.63544913
13 -0.12936714 -0.86000792
14 0.15887342 -0.12936714
15 3.04767602 0.15887342
16 4.15863719 3.04767602
17 6.16127905 4.15863719
18 7.31224021 6.16127905
19 11.04100344 7.31224021
20 12.59916525 11.04100344
21 12.68772621 12.59916525
22 12.05288640 12.68772621
23 11.70148673 12.05288640
24 12.16280766 11.70148673
25 11.65964854 12.16280766
26 4.17645006 11.65964854
27 4.42985081 4.17645006
28 6.23741123 4.42985081
29 8.84713021 6.23741123
30 4.70432545 8.84713021
31 -0.55152030 4.70432545
32 0.28655736 -0.55152030
33 0.45179630 0.28655736
34 0.55047537 0.45179630
35 0.76567494 0.55047537
36 4.15723751 0.76567494
37 1.64179630 4.15723751
38 2.91859781 1.64179630
39 7.17231896 2.91859781
40 5.48751853 7.17231896
41 4.91403902 5.48751853
42 2.29447753 4.91403902
43 2.25891820 2.29447753
44 4.35532058 2.25891820
45 4.85248186 4.35532058
46 7.48160484 4.85248186
47 12.94112696 7.48160484
48 13.40004768 12.94112696
49 16.65949105 13.40004768
50 17.33769224 16.65949105
51 17.24421274 17.33769224
52 17.17245330 17.24421274
53 15.91281306 17.17245330
54 15.88897380 15.91281306
55 15.31481415 15.88897380
56 14.57997434 15.31481415
57 18.26101425 14.57997434
58 21.56269495 18.26101425
59 18.32109300 21.56269495
60 17.65141339 18.32109300
61 13.57605092 17.65141339
62 16.63641068 13.57605092
63 16.49469062 16.63641068
64 15.30849051 16.49469062
65 14.67881090 15.30849051
66 14.56877153 14.67881090
67 13.10465125 14.56877153
68 12.55601155 13.10465125
69 19.14253205 12.55601155
70 17.72769224 19.14253205
71 15.99149213 17.72769224
72 14.27841177 15.99149213
73 12.58257142 14.27841177
74 11.06809138 12.58257142
75 13.87493226 11.06809138
76 13.63389235 13.87493226
77 12.46181252 13.63389235
78 11.45593280 12.46181252
79 9.54733248 11.45593280
80 12.74661296 9.54733248
81 12.99421274 12.74661296
82 11.97045222 12.99421274
83 11.10973270 11.97045222
84 9.58117174 11.10973270
85 6.65297055 9.58117174
86 6.31225103 6.65297055
87 6.00985081 6.31225103
88 5.31573053 6.00985081
89 3.71232978 5.31573053
90 1.46856926 3.71232978
91 3.14924941 1.46856926
92 3.33512913 3.14924941
93 1.66996893 3.33512913
94 1.20960917 1.66996893
95 1.70720895 1.20960917
96 0.26720895 1.70720895
97 -2.01759148 0.26720895
98 -0.69655157 -2.01759148
99 -3.66863139 -0.69655157
100 -6.24071122 -3.66863139
101 -4.69691133 -6.24071122
102 -6.79863139 -4.69691133
103 -7.06215027 -6.79863139
104 -4.91527001 -7.06215027
105 -7.08491025 -4.91527001
106 -3.50527001 -7.08491025
107 -1.40054832 -3.50527001
108 -1.34027271 -1.40054832
109 -14.57465086 -1.34027271
110 -5.45161527 -14.57465086
111 -2.18929380 -5.45161527
112 -0.12693296 -2.18929380
113 -0.29525227 -0.12693296
114 0.09326931 -0.29525227
115 2.22067223 0.09326931
116 5.75971647 2.22067223
117 5.04279684 5.75971647
118 5.11215606 5.04279684
119 3.48559619 5.11215606
120 2.74003686 3.48559619
121 3.47199857 2.74003686
122 3.46743978 3.47199857
123 4.57800182 3.46743978
124 5.79752394 4.57800182
125 4.86164422 5.79752394
126 4.36884487 4.86164422
127 5.85112696 4.36884487
128 3.74876612 5.85112696
129 3.49540474 3.74876612
130 8.41420733 3.49540474
131 8.26864800 8.41420733
132 5.63740582 8.26864800
133 7.47568575 5.63740582
134 7.54628716 7.47568575
135 6.26880549 7.54628716
136 6.09912588 6.26880549
137 4.84772621 6.09912588
138 1.67884487 4.84772621
139 1.41016580 1.67884487
140 -0.31499440 1.41016580
141 0.64640528 -0.31499440
142 3.96852448 0.64640528
143 1.63960376 3.96852448
144 0.64724292 1.63960376
145 -4.77987899 0.64724292
146 -5.31575870 -4.77987899
147 -0.92600035 -5.31575870
148 -3.92352139 -0.92600035
149 -3.21248147 -3.92352139
150 -5.32240273 -3.21248147
151 -5.35144156 -5.32240273
152 -4.91291998 -5.35144156
153 -3.64851868 -4.91291998
154 0.53888424 -3.64851868
155 -2.01727650 0.53888424
156 -3.22247606 -2.01727650
157 -6.32999710 -3.22247606
158 -2.33423550 -6.32999710
159 0.02920463 -2.33423550
160 -3.10451652 0.02920463
161 -5.77687736 -3.10451652
162 -9.36435903 -5.77687736
163 -10.12887844 -9.36435903
164 -3.78439840 -10.12887844
165 -4.74059851 -3.78439840
166 -3.83519667 -4.74059851
167 -5.21623658 -3.83519667
168 -6.60519667 -5.21623658
169 -8.46343723 -6.60519667
170 -5.12595557 -8.46343723
171 -2.28315622 -5.12595557
172 -2.21735524 -2.28315622
173 -3.02323496 -2.21735524
174 -2.47159364 -3.02323496
175 -1.43515189 -2.47159364
176 -2.06347120 -1.43515189
177 -0.67483150 -2.06347120
178 -0.38591079 -0.67483150
179 -0.34838975 -0.38591079
180 -1.51971068 -0.34838975
181 -5.82451111 -1.51971068
182 -6.13182988 -5.82451111
183 -6.27426947 -6.13182988
184 -8.23179051 -6.27426947
185 -7.93838975 -8.23179051
186 -12.47387033 -7.93838975
187 -14.76150949 -12.47387033
188 -13.25126784 -14.76150949
189 -12.58546687 -13.25126784
190 -10.37422469 -12.58546687
191 -10.19874410 -10.37422469
192 -10.37186384 -10.19874410
193 -13.57586601 -10.37186384
194 -14.31826622 -13.57586601
195 -12.11686655 -14.31826622
196 -12.79474735 -12.11686655
197 -14.01230776 -12.79474735
198 -14.92090808 -14.01230776
199 -7.30338704 -14.92090808
200 -7.66270689 -7.30338704
201 -6.08798521 -7.66270689
202 -6.85830559 -6.08798521
203 -8.92858661 -6.85830559
204 -10.76058769 -8.92858661
205 -3.88334767 -10.76058769
206 16.14801263 -3.88334767
207 14.95077261 16.14801263
208 13.59321220 14.95077261
209 12.83709084 13.59321220
210 -8.68224524 12.83709084
211 -20.10862988 -8.68224524
212 -5.30934940 -20.10862988
213 -2.48142923 -5.30934940
214 -3.62310992 -2.48142923
215 -4.97910776 -3.62310992
216 -7.38494810 -4.97910776
217 -3.81758455 -7.38494810
218 -2.46534183 -3.81758455
219 -2.59158131 -2.46534183
220 0.90149906 -2.59158131
221 -2.26058077 0.90149906
222 -3.34890008 -2.26058077
223 -7.66266060 -3.34890008
224 -7.63445941 -7.66266060
225 -7.31601657 -7.63445941
226 -5.80677547 -7.31601657
227 -4.20789413 -5.80677547
228 -5.75089034 -4.20789413
229 -3.50501062 -5.75089034
230 -2.86540976 -3.50501062
231 -5.17888926 -2.86540976
232 -2.16796746 -5.17888926
233 -3.16452734 -2.16796746
234 1.11539392 -3.16452734
235 16.63299370 1.11539392
236 20.11567494 16.63299370
237 22.34603470 20.11567494
238 24.04767602 22.34603470
239 15.63391550 24.04767602
240 11.01459565 15.63391550
241 29.56875530 11.01459565
242 68.11971106 29.56875530
243 47.76402280 68.11971106
244 66.41741815 47.76402280
245 57.78785125 66.41741815
246 13.09984692 57.78785125
247 5.29300604 13.09984692
248 1.86948716 5.29300604
249 2.26849203 1.86948716
250 -0.27714605 2.26849203
251 10.96093702 -0.27714605
252 14.44557997 10.96093702
253 22.88206109 14.44557997
254 6.18765979 22.88206109
255 9.88342139 6.18765979
256 0.59986315 9.88342139
257 1.53594514 0.59986315
258 2.93454546 1.53594514
259 3.52962691 2.93454546
260 -2.60221127 3.52962691
261 -1.05512874 -2.60221127
262 4.94691171 -1.05512874
263 7.00755249 4.94691171
264 6.08719273 7.00755249
265 3.36787288 6.08719273
266 3.23035184 3.36787288
267 2.02275206 3.23035184
268 -0.39720857 2.02275206
269 1.67855303 -0.39720857
270 -4.26420695 1.67855303
271 -7.03212712 -4.26420695
272 -10.27872636 -7.03212712
273 -12.73308829 -10.27872636
274 0.05671485 -12.73308829
275 12.01431463 0.05671485
276 -2.49300954 12.01431463
277 -11.31489251 -2.49300954
278 -9.02633155 -11.31489251
279 -11.86157049 -9.02633155
280 -11.56784935 -11.86157049
281 -14.23384718 -11.56784935
282 -14.96244751 -14.23384718
283 -18.89796746 -14.96244751
284 -16.87776519 -18.89796746
285 -15.13848472 -16.87776519
286 -11.81272312 -15.13848472
287 -12.48828245 -11.81272312
288 -16.06516271 -12.48828245
289 -22.21448255 -16.06516271
290 -21.67760229 -22.21448255
291 -16.38012063 -21.67760229
292 -11.62567996 -16.38012063
293 -23.89284123 -11.62567996
294 -22.67567996 -23.89284123
295 -20.66643886 -22.67567996
296 -19.19439840 -20.66643886
297 -24.78199818 -19.19439840
298 -21.05651760 -24.78199818
299 -19.94351598 -21.05651760
300 -18.44003648 -19.94351598
301 -20.18243669 -18.44003648
302 -12.64255481 -20.18243669
303 -12.75963734 -12.64255481
304 -19.65303810 -12.75963734
305 -20.25451652 -19.65303810
306 -28.22687736 -20.25451652
307 -28.75935632 -28.22687736
308 -23.11143615 -28.75935632
309 -21.77667509 -23.11143615
310 -18.68907531 -21.77667509
311 -24.62051436 -18.68907531
312 -24.78615784 -24.62051436
313 -24.12315622 -24.78615784
314 -27.58831641 -24.12315622
315 -27.03131803 -27.58831641
316 -23.58727650 -27.03131803
317 -26.85383637 -23.58727650
318 -23.22795665 -26.85383637
319 -25.53143615 -23.22795665
320 -25.00695611 -25.53143615
321 -23.65639407 -25.00695611
322 -21.57335308 -23.65639407
323 -22.69839516 -21.57335308
324 -16.78147552 -22.69839516
325 -15.52083475 -16.78147552
326 -15.19107639 -15.52083475
327 -16.56731587 -15.19107639
328 -12.88983420 -16.56731587
329 -5.26339245 -12.88983420
330 -17.18011522 -5.26339245
331 -16.20011522 -17.18011522
332 -9.29115513 -16.20011522
333 -9.51499440 -9.29115513
334 0.38388694 -9.51499440
335 10.06836699 0.38388694
336 3.40184108 10.06836699
337 20.05100344 3.40184108
338 32.12144195 20.05100344
339 18.37899695 32.12144195
340 13.07463502 18.37899695
341 3.85475314 13.07463502
342 -3.72156509 3.85475314
343 -7.81308829 -3.72156509
344 -11.61968753 -7.81308829
345 -1.84968753 -11.61968753
346 6.10527580 -1.84968753
347 7.75519706 6.10527580
348 23.14691712 7.75519706
349 15.31683838 23.14691712
350 5.80735563 15.31683838
351 7.22251582 5.80735563
352 2.19983459 7.22251582
353 0.41267872 2.19983459
354 1.76163881 0.41267872
355 6.74755790 1.76163881
356 3.66407840 6.74755790
357 3.19747915 3.66407840
358 14.83267872 3.19747915
359 23.83847970 14.83267872
360 NA 23.83847970
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 17.41012642 24.27461187
[2,] 11.85384216 17.41012642
[3,] 0.97851366 11.85384216
[4,] -7.88549391 0.97851366
[5,] -10.01281809 -7.88549391
[6,] -8.87149716 -10.01281809
[7,] -7.21849553 -8.87149716
[8,] -6.19789413 -7.21849553
[9,] -5.11901279 -6.19789413
[10,] -2.48917028 -5.11901279
[11,] -1.63544913 -2.48917028
[12,] -0.86000792 -1.63544913
[13,] -0.12936714 -0.86000792
[14,] 0.15887342 -0.12936714
[15,] 3.04767602 0.15887342
[16,] 4.15863719 3.04767602
[17,] 6.16127905 4.15863719
[18,] 7.31224021 6.16127905
[19,] 11.04100344 7.31224021
[20,] 12.59916525 11.04100344
[21,] 12.68772621 12.59916525
[22,] 12.05288640 12.68772621
[23,] 11.70148673 12.05288640
[24,] 12.16280766 11.70148673
[25,] 11.65964854 12.16280766
[26,] 4.17645006 11.65964854
[27,] 4.42985081 4.17645006
[28,] 6.23741123 4.42985081
[29,] 8.84713021 6.23741123
[30,] 4.70432545 8.84713021
[31,] -0.55152030 4.70432545
[32,] 0.28655736 -0.55152030
[33,] 0.45179630 0.28655736
[34,] 0.55047537 0.45179630
[35,] 0.76567494 0.55047537
[36,] 4.15723751 0.76567494
[37,] 1.64179630 4.15723751
[38,] 2.91859781 1.64179630
[39,] 7.17231896 2.91859781
[40,] 5.48751853 7.17231896
[41,] 4.91403902 5.48751853
[42,] 2.29447753 4.91403902
[43,] 2.25891820 2.29447753
[44,] 4.35532058 2.25891820
[45,] 4.85248186 4.35532058
[46,] 7.48160484 4.85248186
[47,] 12.94112696 7.48160484
[48,] 13.40004768 12.94112696
[49,] 16.65949105 13.40004768
[50,] 17.33769224 16.65949105
[51,] 17.24421274 17.33769224
[52,] 17.17245330 17.24421274
[53,] 15.91281306 17.17245330
[54,] 15.88897380 15.91281306
[55,] 15.31481415 15.88897380
[56,] 14.57997434 15.31481415
[57,] 18.26101425 14.57997434
[58,] 21.56269495 18.26101425
[59,] 18.32109300 21.56269495
[60,] 17.65141339 18.32109300
[61,] 13.57605092 17.65141339
[62,] 16.63641068 13.57605092
[63,] 16.49469062 16.63641068
[64,] 15.30849051 16.49469062
[65,] 14.67881090 15.30849051
[66,] 14.56877153 14.67881090
[67,] 13.10465125 14.56877153
[68,] 12.55601155 13.10465125
[69,] 19.14253205 12.55601155
[70,] 17.72769224 19.14253205
[71,] 15.99149213 17.72769224
[72,] 14.27841177 15.99149213
[73,] 12.58257142 14.27841177
[74,] 11.06809138 12.58257142
[75,] 13.87493226 11.06809138
[76,] 13.63389235 13.87493226
[77,] 12.46181252 13.63389235
[78,] 11.45593280 12.46181252
[79,] 9.54733248 11.45593280
[80,] 12.74661296 9.54733248
[81,] 12.99421274 12.74661296
[82,] 11.97045222 12.99421274
[83,] 11.10973270 11.97045222
[84,] 9.58117174 11.10973270
[85,] 6.65297055 9.58117174
[86,] 6.31225103 6.65297055
[87,] 6.00985081 6.31225103
[88,] 5.31573053 6.00985081
[89,] 3.71232978 5.31573053
[90,] 1.46856926 3.71232978
[91,] 3.14924941 1.46856926
[92,] 3.33512913 3.14924941
[93,] 1.66996893 3.33512913
[94,] 1.20960917 1.66996893
[95,] 1.70720895 1.20960917
[96,] 0.26720895 1.70720895
[97,] -2.01759148 0.26720895
[98,] -0.69655157 -2.01759148
[99,] -3.66863139 -0.69655157
[100,] -6.24071122 -3.66863139
[101,] -4.69691133 -6.24071122
[102,] -6.79863139 -4.69691133
[103,] -7.06215027 -6.79863139
[104,] -4.91527001 -7.06215027
[105,] -7.08491025 -4.91527001
[106,] -3.50527001 -7.08491025
[107,] -1.40054832 -3.50527001
[108,] -1.34027271 -1.40054832
[109,] -14.57465086 -1.34027271
[110,] -5.45161527 -14.57465086
[111,] -2.18929380 -5.45161527
[112,] -0.12693296 -2.18929380
[113,] -0.29525227 -0.12693296
[114,] 0.09326931 -0.29525227
[115,] 2.22067223 0.09326931
[116,] 5.75971647 2.22067223
[117,] 5.04279684 5.75971647
[118,] 5.11215606 5.04279684
[119,] 3.48559619 5.11215606
[120,] 2.74003686 3.48559619
[121,] 3.47199857 2.74003686
[122,] 3.46743978 3.47199857
[123,] 4.57800182 3.46743978
[124,] 5.79752394 4.57800182
[125,] 4.86164422 5.79752394
[126,] 4.36884487 4.86164422
[127,] 5.85112696 4.36884487
[128,] 3.74876612 5.85112696
[129,] 3.49540474 3.74876612
[130,] 8.41420733 3.49540474
[131,] 8.26864800 8.41420733
[132,] 5.63740582 8.26864800
[133,] 7.47568575 5.63740582
[134,] 7.54628716 7.47568575
[135,] 6.26880549 7.54628716
[136,] 6.09912588 6.26880549
[137,] 4.84772621 6.09912588
[138,] 1.67884487 4.84772621
[139,] 1.41016580 1.67884487
[140,] -0.31499440 1.41016580
[141,] 0.64640528 -0.31499440
[142,] 3.96852448 0.64640528
[143,] 1.63960376 3.96852448
[144,] 0.64724292 1.63960376
[145,] -4.77987899 0.64724292
[146,] -5.31575870 -4.77987899
[147,] -0.92600035 -5.31575870
[148,] -3.92352139 -0.92600035
[149,] -3.21248147 -3.92352139
[150,] -5.32240273 -3.21248147
[151,] -5.35144156 -5.32240273
[152,] -4.91291998 -5.35144156
[153,] -3.64851868 -4.91291998
[154,] 0.53888424 -3.64851868
[155,] -2.01727650 0.53888424
[156,] -3.22247606 -2.01727650
[157,] -6.32999710 -3.22247606
[158,] -2.33423550 -6.32999710
[159,] 0.02920463 -2.33423550
[160,] -3.10451652 0.02920463
[161,] -5.77687736 -3.10451652
[162,] -9.36435903 -5.77687736
[163,] -10.12887844 -9.36435903
[164,] -3.78439840 -10.12887844
[165,] -4.74059851 -3.78439840
[166,] -3.83519667 -4.74059851
[167,] -5.21623658 -3.83519667
[168,] -6.60519667 -5.21623658
[169,] -8.46343723 -6.60519667
[170,] -5.12595557 -8.46343723
[171,] -2.28315622 -5.12595557
[172,] -2.21735524 -2.28315622
[173,] -3.02323496 -2.21735524
[174,] -2.47159364 -3.02323496
[175,] -1.43515189 -2.47159364
[176,] -2.06347120 -1.43515189
[177,] -0.67483150 -2.06347120
[178,] -0.38591079 -0.67483150
[179,] -0.34838975 -0.38591079
[180,] -1.51971068 -0.34838975
[181,] -5.82451111 -1.51971068
[182,] -6.13182988 -5.82451111
[183,] -6.27426947 -6.13182988
[184,] -8.23179051 -6.27426947
[185,] -7.93838975 -8.23179051
[186,] -12.47387033 -7.93838975
[187,] -14.76150949 -12.47387033
[188,] -13.25126784 -14.76150949
[189,] -12.58546687 -13.25126784
[190,] -10.37422469 -12.58546687
[191,] -10.19874410 -10.37422469
[192,] -10.37186384 -10.19874410
[193,] -13.57586601 -10.37186384
[194,] -14.31826622 -13.57586601
[195,] -12.11686655 -14.31826622
[196,] -12.79474735 -12.11686655
[197,] -14.01230776 -12.79474735
[198,] -14.92090808 -14.01230776
[199,] -7.30338704 -14.92090808
[200,] -7.66270689 -7.30338704
[201,] -6.08798521 -7.66270689
[202,] -6.85830559 -6.08798521
[203,] -8.92858661 -6.85830559
[204,] -10.76058769 -8.92858661
[205,] -3.88334767 -10.76058769
[206,] 16.14801263 -3.88334767
[207,] 14.95077261 16.14801263
[208,] 13.59321220 14.95077261
[209,] 12.83709084 13.59321220
[210,] -8.68224524 12.83709084
[211,] -20.10862988 -8.68224524
[212,] -5.30934940 -20.10862988
[213,] -2.48142923 -5.30934940
[214,] -3.62310992 -2.48142923
[215,] -4.97910776 -3.62310992
[216,] -7.38494810 -4.97910776
[217,] -3.81758455 -7.38494810
[218,] -2.46534183 -3.81758455
[219,] -2.59158131 -2.46534183
[220,] 0.90149906 -2.59158131
[221,] -2.26058077 0.90149906
[222,] -3.34890008 -2.26058077
[223,] -7.66266060 -3.34890008
[224,] -7.63445941 -7.66266060
[225,] -7.31601657 -7.63445941
[226,] -5.80677547 -7.31601657
[227,] -4.20789413 -5.80677547
[228,] -5.75089034 -4.20789413
[229,] -3.50501062 -5.75089034
[230,] -2.86540976 -3.50501062
[231,] -5.17888926 -2.86540976
[232,] -2.16796746 -5.17888926
[233,] -3.16452734 -2.16796746
[234,] 1.11539392 -3.16452734
[235,] 16.63299370 1.11539392
[236,] 20.11567494 16.63299370
[237,] 22.34603470 20.11567494
[238,] 24.04767602 22.34603470
[239,] 15.63391550 24.04767602
[240,] 11.01459565 15.63391550
[241,] 29.56875530 11.01459565
[242,] 68.11971106 29.56875530
[243,] 47.76402280 68.11971106
[244,] 66.41741815 47.76402280
[245,] 57.78785125 66.41741815
[246,] 13.09984692 57.78785125
[247,] 5.29300604 13.09984692
[248,] 1.86948716 5.29300604
[249,] 2.26849203 1.86948716
[250,] -0.27714605 2.26849203
[251,] 10.96093702 -0.27714605
[252,] 14.44557997 10.96093702
[253,] 22.88206109 14.44557997
[254,] 6.18765979 22.88206109
[255,] 9.88342139 6.18765979
[256,] 0.59986315 9.88342139
[257,] 1.53594514 0.59986315
[258,] 2.93454546 1.53594514
[259,] 3.52962691 2.93454546
[260,] -2.60221127 3.52962691
[261,] -1.05512874 -2.60221127
[262,] 4.94691171 -1.05512874
[263,] 7.00755249 4.94691171
[264,] 6.08719273 7.00755249
[265,] 3.36787288 6.08719273
[266,] 3.23035184 3.36787288
[267,] 2.02275206 3.23035184
[268,] -0.39720857 2.02275206
[269,] 1.67855303 -0.39720857
[270,] -4.26420695 1.67855303
[271,] -7.03212712 -4.26420695
[272,] -10.27872636 -7.03212712
[273,] -12.73308829 -10.27872636
[274,] 0.05671485 -12.73308829
[275,] 12.01431463 0.05671485
[276,] -2.49300954 12.01431463
[277,] -11.31489251 -2.49300954
[278,] -9.02633155 -11.31489251
[279,] -11.86157049 -9.02633155
[280,] -11.56784935 -11.86157049
[281,] -14.23384718 -11.56784935
[282,] -14.96244751 -14.23384718
[283,] -18.89796746 -14.96244751
[284,] -16.87776519 -18.89796746
[285,] -15.13848472 -16.87776519
[286,] -11.81272312 -15.13848472
[287,] -12.48828245 -11.81272312
[288,] -16.06516271 -12.48828245
[289,] -22.21448255 -16.06516271
[290,] -21.67760229 -22.21448255
[291,] -16.38012063 -21.67760229
[292,] -11.62567996 -16.38012063
[293,] -23.89284123 -11.62567996
[294,] -22.67567996 -23.89284123
[295,] -20.66643886 -22.67567996
[296,] -19.19439840 -20.66643886
[297,] -24.78199818 -19.19439840
[298,] -21.05651760 -24.78199818
[299,] -19.94351598 -21.05651760
[300,] -18.44003648 -19.94351598
[301,] -20.18243669 -18.44003648
[302,] -12.64255481 -20.18243669
[303,] -12.75963734 -12.64255481
[304,] -19.65303810 -12.75963734
[305,] -20.25451652 -19.65303810
[306,] -28.22687736 -20.25451652
[307,] -28.75935632 -28.22687736
[308,] -23.11143615 -28.75935632
[309,] -21.77667509 -23.11143615
[310,] -18.68907531 -21.77667509
[311,] -24.62051436 -18.68907531
[312,] -24.78615784 -24.62051436
[313,] -24.12315622 -24.78615784
[314,] -27.58831641 -24.12315622
[315,] -27.03131803 -27.58831641
[316,] -23.58727650 -27.03131803
[317,] -26.85383637 -23.58727650
[318,] -23.22795665 -26.85383637
[319,] -25.53143615 -23.22795665
[320,] -25.00695611 -25.53143615
[321,] -23.65639407 -25.00695611
[322,] -21.57335308 -23.65639407
[323,] -22.69839516 -21.57335308
[324,] -16.78147552 -22.69839516
[325,] -15.52083475 -16.78147552
[326,] -15.19107639 -15.52083475
[327,] -16.56731587 -15.19107639
[328,] -12.88983420 -16.56731587
[329,] -5.26339245 -12.88983420
[330,] -17.18011522 -5.26339245
[331,] -16.20011522 -17.18011522
[332,] -9.29115513 -16.20011522
[333,] -9.51499440 -9.29115513
[334,] 0.38388694 -9.51499440
[335,] 10.06836699 0.38388694
[336,] 3.40184108 10.06836699
[337,] 20.05100344 3.40184108
[338,] 32.12144195 20.05100344
[339,] 18.37899695 32.12144195
[340,] 13.07463502 18.37899695
[341,] 3.85475314 13.07463502
[342,] -3.72156509 3.85475314
[343,] -7.81308829 -3.72156509
[344,] -11.61968753 -7.81308829
[345,] -1.84968753 -11.61968753
[346,] 6.10527580 -1.84968753
[347,] 7.75519706 6.10527580
[348,] 23.14691712 7.75519706
[349,] 15.31683838 23.14691712
[350,] 5.80735563 15.31683838
[351,] 7.22251582 5.80735563
[352,] 2.19983459 7.22251582
[353,] 0.41267872 2.19983459
[354,] 1.76163881 0.41267872
[355,] 6.74755790 1.76163881
[356,] 3.66407840 6.74755790
[357,] 3.19747915 3.66407840
[358,] 14.83267872 3.19747915
[359,] 23.83847970 14.83267872
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 17.41012642 24.27461187
2 11.85384216 17.41012642
3 0.97851366 11.85384216
4 -7.88549391 0.97851366
5 -10.01281809 -7.88549391
6 -8.87149716 -10.01281809
7 -7.21849553 -8.87149716
8 -6.19789413 -7.21849553
9 -5.11901279 -6.19789413
10 -2.48917028 -5.11901279
11 -1.63544913 -2.48917028
12 -0.86000792 -1.63544913
13 -0.12936714 -0.86000792
14 0.15887342 -0.12936714
15 3.04767602 0.15887342
16 4.15863719 3.04767602
17 6.16127905 4.15863719
18 7.31224021 6.16127905
19 11.04100344 7.31224021
20 12.59916525 11.04100344
21 12.68772621 12.59916525
22 12.05288640 12.68772621
23 11.70148673 12.05288640
24 12.16280766 11.70148673
25 11.65964854 12.16280766
26 4.17645006 11.65964854
27 4.42985081 4.17645006
28 6.23741123 4.42985081
29 8.84713021 6.23741123
30 4.70432545 8.84713021
31 -0.55152030 4.70432545
32 0.28655736 -0.55152030
33 0.45179630 0.28655736
34 0.55047537 0.45179630
35 0.76567494 0.55047537
36 4.15723751 0.76567494
37 1.64179630 4.15723751
38 2.91859781 1.64179630
39 7.17231896 2.91859781
40 5.48751853 7.17231896
41 4.91403902 5.48751853
42 2.29447753 4.91403902
43 2.25891820 2.29447753
44 4.35532058 2.25891820
45 4.85248186 4.35532058
46 7.48160484 4.85248186
47 12.94112696 7.48160484
48 13.40004768 12.94112696
49 16.65949105 13.40004768
50 17.33769224 16.65949105
51 17.24421274 17.33769224
52 17.17245330 17.24421274
53 15.91281306 17.17245330
54 15.88897380 15.91281306
55 15.31481415 15.88897380
56 14.57997434 15.31481415
57 18.26101425 14.57997434
58 21.56269495 18.26101425
59 18.32109300 21.56269495
60 17.65141339 18.32109300
61 13.57605092 17.65141339
62 16.63641068 13.57605092
63 16.49469062 16.63641068
64 15.30849051 16.49469062
65 14.67881090 15.30849051
66 14.56877153 14.67881090
67 13.10465125 14.56877153
68 12.55601155 13.10465125
69 19.14253205 12.55601155
70 17.72769224 19.14253205
71 15.99149213 17.72769224
72 14.27841177 15.99149213
73 12.58257142 14.27841177
74 11.06809138 12.58257142
75 13.87493226 11.06809138
76 13.63389235 13.87493226
77 12.46181252 13.63389235
78 11.45593280 12.46181252
79 9.54733248 11.45593280
80 12.74661296 9.54733248
81 12.99421274 12.74661296
82 11.97045222 12.99421274
83 11.10973270 11.97045222
84 9.58117174 11.10973270
85 6.65297055 9.58117174
86 6.31225103 6.65297055
87 6.00985081 6.31225103
88 5.31573053 6.00985081
89 3.71232978 5.31573053
90 1.46856926 3.71232978
91 3.14924941 1.46856926
92 3.33512913 3.14924941
93 1.66996893 3.33512913
94 1.20960917 1.66996893
95 1.70720895 1.20960917
96 0.26720895 1.70720895
97 -2.01759148 0.26720895
98 -0.69655157 -2.01759148
99 -3.66863139 -0.69655157
100 -6.24071122 -3.66863139
101 -4.69691133 -6.24071122
102 -6.79863139 -4.69691133
103 -7.06215027 -6.79863139
104 -4.91527001 -7.06215027
105 -7.08491025 -4.91527001
106 -3.50527001 -7.08491025
107 -1.40054832 -3.50527001
108 -1.34027271 -1.40054832
109 -14.57465086 -1.34027271
110 -5.45161527 -14.57465086
111 -2.18929380 -5.45161527
112 -0.12693296 -2.18929380
113 -0.29525227 -0.12693296
114 0.09326931 -0.29525227
115 2.22067223 0.09326931
116 5.75971647 2.22067223
117 5.04279684 5.75971647
118 5.11215606 5.04279684
119 3.48559619 5.11215606
120 2.74003686 3.48559619
121 3.47199857 2.74003686
122 3.46743978 3.47199857
123 4.57800182 3.46743978
124 5.79752394 4.57800182
125 4.86164422 5.79752394
126 4.36884487 4.86164422
127 5.85112696 4.36884487
128 3.74876612 5.85112696
129 3.49540474 3.74876612
130 8.41420733 3.49540474
131 8.26864800 8.41420733
132 5.63740582 8.26864800
133 7.47568575 5.63740582
134 7.54628716 7.47568575
135 6.26880549 7.54628716
136 6.09912588 6.26880549
137 4.84772621 6.09912588
138 1.67884487 4.84772621
139 1.41016580 1.67884487
140 -0.31499440 1.41016580
141 0.64640528 -0.31499440
142 3.96852448 0.64640528
143 1.63960376 3.96852448
144 0.64724292 1.63960376
145 -4.77987899 0.64724292
146 -5.31575870 -4.77987899
147 -0.92600035 -5.31575870
148 -3.92352139 -0.92600035
149 -3.21248147 -3.92352139
150 -5.32240273 -3.21248147
151 -5.35144156 -5.32240273
152 -4.91291998 -5.35144156
153 -3.64851868 -4.91291998
154 0.53888424 -3.64851868
155 -2.01727650 0.53888424
156 -3.22247606 -2.01727650
157 -6.32999710 -3.22247606
158 -2.33423550 -6.32999710
159 0.02920463 -2.33423550
160 -3.10451652 0.02920463
161 -5.77687736 -3.10451652
162 -9.36435903 -5.77687736
163 -10.12887844 -9.36435903
164 -3.78439840 -10.12887844
165 -4.74059851 -3.78439840
166 -3.83519667 -4.74059851
167 -5.21623658 -3.83519667
168 -6.60519667 -5.21623658
169 -8.46343723 -6.60519667
170 -5.12595557 -8.46343723
171 -2.28315622 -5.12595557
172 -2.21735524 -2.28315622
173 -3.02323496 -2.21735524
174 -2.47159364 -3.02323496
175 -1.43515189 -2.47159364
176 -2.06347120 -1.43515189
177 -0.67483150 -2.06347120
178 -0.38591079 -0.67483150
179 -0.34838975 -0.38591079
180 -1.51971068 -0.34838975
181 -5.82451111 -1.51971068
182 -6.13182988 -5.82451111
183 -6.27426947 -6.13182988
184 -8.23179051 -6.27426947
185 -7.93838975 -8.23179051
186 -12.47387033 -7.93838975
187 -14.76150949 -12.47387033
188 -13.25126784 -14.76150949
189 -12.58546687 -13.25126784
190 -10.37422469 -12.58546687
191 -10.19874410 -10.37422469
192 -10.37186384 -10.19874410
193 -13.57586601 -10.37186384
194 -14.31826622 -13.57586601
195 -12.11686655 -14.31826622
196 -12.79474735 -12.11686655
197 -14.01230776 -12.79474735
198 -14.92090808 -14.01230776
199 -7.30338704 -14.92090808
200 -7.66270689 -7.30338704
201 -6.08798521 -7.66270689
202 -6.85830559 -6.08798521
203 -8.92858661 -6.85830559
204 -10.76058769 -8.92858661
205 -3.88334767 -10.76058769
206 16.14801263 -3.88334767
207 14.95077261 16.14801263
208 13.59321220 14.95077261
209 12.83709084 13.59321220
210 -8.68224524 12.83709084
211 -20.10862988 -8.68224524
212 -5.30934940 -20.10862988
213 -2.48142923 -5.30934940
214 -3.62310992 -2.48142923
215 -4.97910776 -3.62310992
216 -7.38494810 -4.97910776
217 -3.81758455 -7.38494810
218 -2.46534183 -3.81758455
219 -2.59158131 -2.46534183
220 0.90149906 -2.59158131
221 -2.26058077 0.90149906
222 -3.34890008 -2.26058077
223 -7.66266060 -3.34890008
224 -7.63445941 -7.66266060
225 -7.31601657 -7.63445941
226 -5.80677547 -7.31601657
227 -4.20789413 -5.80677547
228 -5.75089034 -4.20789413
229 -3.50501062 -5.75089034
230 -2.86540976 -3.50501062
231 -5.17888926 -2.86540976
232 -2.16796746 -5.17888926
233 -3.16452734 -2.16796746
234 1.11539392 -3.16452734
235 16.63299370 1.11539392
236 20.11567494 16.63299370
237 22.34603470 20.11567494
238 24.04767602 22.34603470
239 15.63391550 24.04767602
240 11.01459565 15.63391550
241 29.56875530 11.01459565
242 68.11971106 29.56875530
243 47.76402280 68.11971106
244 66.41741815 47.76402280
245 57.78785125 66.41741815
246 13.09984692 57.78785125
247 5.29300604 13.09984692
248 1.86948716 5.29300604
249 2.26849203 1.86948716
250 -0.27714605 2.26849203
251 10.96093702 -0.27714605
252 14.44557997 10.96093702
253 22.88206109 14.44557997
254 6.18765979 22.88206109
255 9.88342139 6.18765979
256 0.59986315 9.88342139
257 1.53594514 0.59986315
258 2.93454546 1.53594514
259 3.52962691 2.93454546
260 -2.60221127 3.52962691
261 -1.05512874 -2.60221127
262 4.94691171 -1.05512874
263 7.00755249 4.94691171
264 6.08719273 7.00755249
265 3.36787288 6.08719273
266 3.23035184 3.36787288
267 2.02275206 3.23035184
268 -0.39720857 2.02275206
269 1.67855303 -0.39720857
270 -4.26420695 1.67855303
271 -7.03212712 -4.26420695
272 -10.27872636 -7.03212712
273 -12.73308829 -10.27872636
274 0.05671485 -12.73308829
275 12.01431463 0.05671485
276 -2.49300954 12.01431463
277 -11.31489251 -2.49300954
278 -9.02633155 -11.31489251
279 -11.86157049 -9.02633155
280 -11.56784935 -11.86157049
281 -14.23384718 -11.56784935
282 -14.96244751 -14.23384718
283 -18.89796746 -14.96244751
284 -16.87776519 -18.89796746
285 -15.13848472 -16.87776519
286 -11.81272312 -15.13848472
287 -12.48828245 -11.81272312
288 -16.06516271 -12.48828245
289 -22.21448255 -16.06516271
290 -21.67760229 -22.21448255
291 -16.38012063 -21.67760229
292 -11.62567996 -16.38012063
293 -23.89284123 -11.62567996
294 -22.67567996 -23.89284123
295 -20.66643886 -22.67567996
296 -19.19439840 -20.66643886
297 -24.78199818 -19.19439840
298 -21.05651760 -24.78199818
299 -19.94351598 -21.05651760
300 -18.44003648 -19.94351598
301 -20.18243669 -18.44003648
302 -12.64255481 -20.18243669
303 -12.75963734 -12.64255481
304 -19.65303810 -12.75963734
305 -20.25451652 -19.65303810
306 -28.22687736 -20.25451652
307 -28.75935632 -28.22687736
308 -23.11143615 -28.75935632
309 -21.77667509 -23.11143615
310 -18.68907531 -21.77667509
311 -24.62051436 -18.68907531
312 -24.78615784 -24.62051436
313 -24.12315622 -24.78615784
314 -27.58831641 -24.12315622
315 -27.03131803 -27.58831641
316 -23.58727650 -27.03131803
317 -26.85383637 -23.58727650
318 -23.22795665 -26.85383637
319 -25.53143615 -23.22795665
320 -25.00695611 -25.53143615
321 -23.65639407 -25.00695611
322 -21.57335308 -23.65639407
323 -22.69839516 -21.57335308
324 -16.78147552 -22.69839516
325 -15.52083475 -16.78147552
326 -15.19107639 -15.52083475
327 -16.56731587 -15.19107639
328 -12.88983420 -16.56731587
329 -5.26339245 -12.88983420
330 -17.18011522 -5.26339245
331 -16.20011522 -17.18011522
332 -9.29115513 -16.20011522
333 -9.51499440 -9.29115513
334 0.38388694 -9.51499440
335 10.06836699 0.38388694
336 3.40184108 10.06836699
337 20.05100344 3.40184108
338 32.12144195 20.05100344
339 18.37899695 32.12144195
340 13.07463502 18.37899695
341 3.85475314 13.07463502
342 -3.72156509 3.85475314
343 -7.81308829 -3.72156509
344 -11.61968753 -7.81308829
345 -1.84968753 -11.61968753
346 6.10527580 -1.84968753
347 7.75519706 6.10527580
348 23.14691712 7.75519706
349 15.31683838 23.14691712
350 5.80735563 15.31683838
351 7.22251582 5.80735563
352 2.19983459 7.22251582
353 0.41267872 2.19983459
354 1.76163881 0.41267872
355 6.74755790 1.76163881
356 3.66407840 6.74755790
357 3.19747915 3.66407840
358 14.83267872 3.19747915
359 23.83847970 14.83267872
> 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/7sz0f1322154116.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/84ymx1322154116.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9z8lm1322154116.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10qgda1322154116.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11hlul1322154116.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/12i8ll1322154116.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/13m2ht1322154116.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/14gag91322154116.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/15ahof1322154116.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/16fbcf1322154116.tab")
+ }
>
> try(system("convert tmp/1s1mo1322154116.ps tmp/1s1mo1322154116.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nhuq1322154116.ps tmp/2nhuq1322154116.png",intern=TRUE))
character(0)
> try(system("convert tmp/3j07k1322154116.ps tmp/3j07k1322154116.png",intern=TRUE))
character(0)
> try(system("convert tmp/44xd01322154116.ps tmp/44xd01322154116.png",intern=TRUE))
character(0)
> try(system("convert tmp/53dhv1322154116.ps tmp/53dhv1322154116.png",intern=TRUE))
character(0)
> try(system("convert tmp/67dsn1322154116.ps tmp/67dsn1322154116.png",intern=TRUE))
character(0)
> try(system("convert tmp/7sz0f1322154116.ps tmp/7sz0f1322154116.png",intern=TRUE))
character(0)
> try(system("convert tmp/84ymx1322154116.ps tmp/84ymx1322154116.png",intern=TRUE))
character(0)
> try(system("convert tmp/9z8lm1322154116.ps tmp/9z8lm1322154116.png",intern=TRUE))
character(0)
> try(system("convert tmp/10qgda1322154116.ps tmp/10qgda1322154116.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
9.003 0.538 9.683