R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(1418
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+ ,dim=c(4
+ ,289)
+ ,dimnames=list(c('pageviews'
+ ,'logins'
+ ,'compendium_views_pr'
+ ,'feedback_messages_p120')
+ ,1:289))
> y <- array(NA,dim=c(4,289),dimnames=list(c('pageviews','logins','compendium_views_pr','feedback_messages_p120'),1:289))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '4'
> #'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
feedback_messages_p120 pageviews logins compendium_views_pr
1 94 1418 56 81
2 103 869 56 55
3 93 1530 54 50
4 103 2172 89 125
5 51 901 40 40
6 70 463 25 37
7 91 3201 92 63
8 22 371 18 44
9 38 1192 63 88
10 93 1583 44 66
11 60 1439 33 57
12 123 1764 84 74
13 148 1495 88 49
14 90 1373 55 52
15 124 2187 60 88
16 70 1491 66 36
17 168 4041 154 108
18 115 1706 53 43
19 71 2152 119 75
20 66 1036 41 32
21 134 1882 61 44
22 117 1929 58 85
23 108 2242 75 86
24 84 1220 33 56
25 156 1289 40 50
26 120 2515 92 135
27 114 2147 100 63
28 94 2352 112 81
29 120 1638 73 52
30 81 1222 40 44
31 110 1812 45 113
32 133 1677 60 39
33 122 1579 62 73
34 158 1731 75 48
35 109 807 31 33
36 124 2452 77 59
37 39 829 34 41
38 92 1940 46 69
39 126 2662 99 64
40 0 186 17 1
41 70 1499 66 59
42 37 865 30 32
43 38 1793 76 129
44 120 2527 146 37
45 93 2747 67 31
46 95 1324 56 65
47 77 2702 107 107
48 90 1383 58 74
49 80 1179 34 54
50 31 2099 61 76
51 110 4308 119 715
52 66 918 42 57
53 138 1831 66 66
54 133 3373 89 106
55 113 1713 44 54
56 100 1438 66 32
57 7 496 24 20
58 140 2253 259 71
59 61 744 17 21
60 41 1161 64 70
61 96 2352 41 112
62 164 2144 68 66
63 78 4691 168 190
64 49 1112 43 66
65 102 2694 132 165
66 124 1973 105 56
67 99 1769 71 61
68 129 3148 112 53
69 62 2474 94 127
70 73 2084 82 63
71 114 1954 70 38
72 99 1226 57 50
73 70 1389 53 52
74 104 1496 103 42
75 116 2269 121 76
76 91 1833 62 67
77 74 1268 52 50
78 138 1943 52 53
79 67 893 32 39
80 151 1762 62 50
81 72 1403 45 77
82 120 1425 46 57
83 115 1857 63 73
84 105 1840 75 34
85 104 1502 88 39
86 108 1441 46 46
87 98 1420 53 63
88 69 1416 37 35
89 111 2970 90 106
90 99 1317 63 43
91 71 1644 78 47
92 27 870 25 31
93 69 1654 45 162
94 107 1054 46 57
95 73 937 41 36
96 107 3004 144 263
97 93 2008 82 78
98 129 2547 91 63
99 69 1885 71 54
100 118 1626 63 63
101 73 1468 53 77
102 119 2445 62 79
103 104 1964 63 110
104 107 1381 32 56
105 99 1369 39 56
106 90 1659 62 43
107 197 2888 117 111
108 36 1290 34 71
109 85 2845 92 62
110 139 1982 93 56
111 106 1904 54 74
112 50 1391 144 60
113 64 602 14 43
114 31 1743 61 68
115 63 1559 109 53
116 92 2014 38 87
117 106 2143 73 46
118 63 2146 75 105
119 69 874 50 32
120 41 1590 61 133
121 56 1590 55 79
122 25 1210 77 51
123 65 2072 75 207
124 93 1281 72 67
125 114 1401 50 47
126 38 834 32 34
127 44 1105 53 66
128 87 1272 42 76
129 110 1944 71 65
130 0 391 10 9
131 27 761 35 42
132 83 1605 65 45
133 30 530 25 25
134 80 1988 66 115
135 98 1386 41 97
136 82 2395 86 53
137 0 387 16 2
138 60 1742 42 52
139 28 620 19 44
140 9 449 19 22
141 33 800 45 35
142 59 1684 65 74
143 49 1050 35 103
144 115 2699 95 144
145 140 1606 49 60
146 49 1502 37 134
147 120 1204 64 89
148 66 1138 38 42
149 21 568 34 52
150 124 1459 32 98
151 152 2158 65 99
152 139 1111 52 52
153 38 1421 62 29
154 144 2833 65 125
155 120 1955 83 106
156 160 2922 95 95
157 114 1002 29 40
158 39 1060 18 140
159 78 956 33 43
160 119 2186 247 128
161 141 3604 139 142
162 101 1035 29 73
163 56 1417 118 72
164 133 3261 110 128
165 83 1587 67 61
166 116 1424 42 73
167 90 1701 65 148
168 36 1249 94 64
169 50 946 64 45
170 61 1926 81 58
171 97 3352 95 97
172 98 1641 67 50
173 78 2035 63 37
174 117 2312 83 50
175 148 1369 45 105
176 41 1577 30 69
177 105 2201 70 46
178 55 961 32 57
179 132 1900 83 52
180 44 1254 31 98
181 21 1335 67 61
182 50 1597 66 89
183 0 207 10 0
184 73 1645 70 48
185 86 2429 103 91
186 0 151 5 0
187 13 474 20 7
188 4 141 5 3
189 57 1639 36 54
190 48 872 34 70
191 46 1318 48 36
192 48 1018 40 37
193 32 1383 43 123
194 68 1314 31 247
195 87 1335 42 46
196 43 1403 46 72
197 67 910 33 41
198 46 616 18 24
199 46 1407 55 45
200 56 771 35 33
201 48 766 59 27
202 44 473 19 36
203 60 1376 66 87
204 65 1232 60 90
205 55 1521 36 114
206 38 572 25 31
207 52 1059 47 45
208 60 1544 54 69
209 54 1230 53 51
210 86 1206 40 34
211 24 1205 40 60
212 52 1255 39 45
213 49 613 14 54
214 61 721 45 25
215 61 1109 36 38
216 81 740 28 52
217 43 1126 44 67
218 40 728 30 74
219 40 689 22 38
220 56 592 17 30
221 68 995 31 26
222 79 1613 55 67
223 47 2048 54 132
224 57 705 21 42
225 41 301 14 35
226 29 1803 81 118
227 3 799 35 68
228 60 861 43 43
229 30 1186 46 76
230 79 1451 30 64
231 47 628 23 48
232 40 1161 38 64
233 48 1463 54 56
234 36 742 20 71
235 42 979 53 75
236 49 675 45 39
237 57 1241 39 42
238 12 676 20 39
239 40 1049 24 93
240 43 620 31 38
241 33 1081 35 60
242 77 1688 151 71
243 43 736 52 52
244 45 617 30 27
245 47 812 31 59
246 43 1051 29 40
247 45 1656 57 79
248 50 705 40 44
249 35 945 44 65
250 7 554 25 10
251 71 1597 77 124
252 67 982 35 81
253 0 222 11 15
254 62 1212 63 92
255 54 1143 44 42
256 4 435 19 10
257 25 532 13 24
258 40 882 42 64
259 38 608 38 45
260 19 459 29 22
261 17 578 20 56
262 67 826 27 94
263 14 509 20 19
264 30 717 19 35
265 54 637 37 32
266 35 857 26 35
267 59 830 42 48
268 24 652 49 49
269 58 707 30 48
270 42 954 49 62
271 46 1461 67 96
272 61 672 28 45
273 3 778 19 63
274 52 1141 49 71
275 25 680 27 26
276 40 1090 30 48
277 32 616 22 29
278 4 285 12 19
279 49 1145 31 45
280 63 733 20 45
281 67 888 20 67
282 32 849 39 30
283 23 1182 29 36
284 7 528 16 34
285 54 642 27 36
286 37 947 21 34
287 35 819 19 37
288 51 757 35 46
289 39 894 14 44
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) pageviews logins
22.06492 0.03764 0.08223
compendium_views_pr
-0.12373
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-110.940 -20.151 -2.166 16.906 88.314
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 22.064921 3.673369 6.007 5.76e-09 ***
pageviews 0.037640 0.003909 9.630 < 2e-16 ***
logins 0.082229 0.076170 1.080 0.28125
compendium_views_pr -0.123725 0.038637 -3.202 0.00152 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 28.44 on 285 degrees of freedom
Multiple R-squared: 0.4728, Adjusted R-squared: 0.4672
F-statistic: 85.18 on 3 and 285 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.2506667 5.013334e-01 7.493333e-01
[2,] 0.2709302 5.418604e-01 7.290698e-01
[3,] 0.6069783 7.860434e-01 3.930217e-01
[4,] 0.6043234 7.913533e-01 3.956766e-01
[5,] 0.4901791 9.803581e-01 5.098209e-01
[6,] 0.4449860 8.899721e-01 5.550140e-01
[7,] 0.4161571 8.323142e-01 5.838429e-01
[8,] 0.3251986 6.503973e-01 6.748014e-01
[9,] 0.4854091 9.708182e-01 5.145909e-01
[10,] 0.4945905 9.891811e-01 5.054095e-01
[11,] 0.4167342 8.334684e-01 5.832658e-01
[12,] 0.4286647 8.573295e-01 5.713353e-01
[13,] 0.6488726 7.022548e-01 3.511274e-01
[14,] 0.5835182 8.329637e-01 4.164818e-01
[15,] 0.6308852 7.382297e-01 3.691148e-01
[16,] 0.6087679 7.824643e-01 3.912321e-01
[17,] 0.5419248 9.161504e-01 4.580752e-01
[18,] 0.4806939 9.613879e-01 5.193061e-01
[19,] 0.7966835 4.066331e-01 2.033165e-01
[20,] 0.7538170 4.923659e-01 2.461830e-01
[21,] 0.7038248 5.923504e-01 2.961752e-01
[22,] 0.6776365 6.447269e-01 3.223635e-01
[23,] 0.6623980 6.752040e-01 3.376020e-01
[24,] 0.6108844 7.782311e-01 3.891156e-01
[25,] 0.5743063 8.513873e-01 4.256937e-01
[26,] 0.6011921 7.976158e-01 3.988079e-01
[27,] 0.6060588 7.878824e-01 3.939412e-01
[28,] 0.7468618 5.062764e-01 2.531382e-01
[29,] 0.7611111 4.777777e-01 2.388889e-01
[30,] 0.7195537 5.608927e-01 2.804463e-01
[31,] 0.7574755 4.850490e-01 2.425245e-01
[32,] 0.7241770 5.516460e-01 2.758230e-01
[33,] 0.6810660 6.378681e-01 3.189340e-01
[34,] 0.8069150 3.861699e-01 1.930850e-01
[35,] 0.7918368 4.163264e-01 2.081632e-01
[36,] 0.8040909 3.918182e-01 1.959091e-01
[37,] 0.8669499 2.661002e-01 1.330501e-01
[38,] 0.8436121 3.127758e-01 1.563879e-01
[39,] 0.8671775 2.656450e-01 1.328225e-01
[40,] 0.8485687 3.028626e-01 1.514313e-01
[41,] 0.8793554 2.412892e-01 1.206446e-01
[42,] 0.8586205 2.827591e-01 1.413795e-01
[43,] 0.8341767 3.316465e-01 1.658233e-01
[44,] 0.9326969 1.346062e-01 6.730310e-02
[45,] 0.9194208 1.611585e-01 8.057923e-02
[46,] 0.9036018 1.927964e-01 9.639819e-02
[47,] 0.9242746 1.514508e-01 7.572538e-02
[48,] 0.9081258 1.837483e-01 9.187416e-02
[49,] 0.9013532 1.972936e-01 9.864680e-02
[50,] 0.8864955 2.270090e-01 1.135045e-01
[51,] 0.9228739 1.542521e-01 7.712606e-02
[52,] 0.9105108 1.789785e-01 8.948923e-02
[53,] 0.8939716 2.120568e-01 1.060284e-01
[54,] 0.9006557 1.986887e-01 9.934435e-02
[55,] 0.8822387 2.355227e-01 1.177613e-01
[56,] 0.9361396 1.277207e-01 6.386036e-02
[57,] 0.9945629 1.087419e-02 5.437093e-03
[58,] 0.9939944 1.201123e-02 6.005616e-03
[59,] 0.9924774 1.504528e-02 7.522641e-03
[60,] 0.9916350 1.672997e-02 8.364985e-03
[61,] 0.9893449 2.131017e-02 1.065509e-02
[62,] 0.9866302 2.673957e-02 1.336979e-02
[63,] 0.9909427 1.811465e-02 9.057324e-03
[64,] 0.9908618 1.827645e-02 9.138223e-03
[65,] 0.9890068 2.198647e-02 1.099323e-02
[66,] 0.9882388 2.352249e-02 1.176125e-02
[67,] 0.9856170 2.876607e-02 1.438304e-02
[68,] 0.9833029 3.339420e-02 1.669710e-02
[69,] 0.9792346 4.153072e-02 2.076536e-02
[70,] 0.9740971 5.180589e-02 2.590295e-02
[71,] 0.9685192 6.296170e-02 3.148085e-02
[72,] 0.9759309 4.813827e-02 2.406914e-02
[73,] 0.9712166 5.756687e-02 2.878343e-02
[74,] 0.9866784 2.664330e-02 1.332165e-02
[75,] 0.9835532 3.289356e-02 1.644678e-02
[76,] 0.9872842 2.543154e-02 1.271577e-02
[77,] 0.9862413 2.751739e-02 1.375869e-02
[78,] 0.9832496 3.350077e-02 1.675039e-02
[79,] 0.9812417 3.751664e-02 1.875832e-02
[80,] 0.9813201 3.735975e-02 1.867987e-02
[81,] 0.9792942 4.141153e-02 2.070576e-02
[82,] 0.9758166 4.836684e-02 2.418342e-02
[83,] 0.9716668 5.666633e-02 2.833317e-02
[84,] 0.9697430 6.051403e-02 3.025702e-02
[85,] 0.9666733 6.665338e-02 3.332669e-02
[86,] 0.9723796 5.524074e-02 2.762037e-02
[87,] 0.9668191 6.636182e-02 3.318091e-02
[88,] 0.9738766 5.224689e-02 2.612344e-02
[89,] 0.9699500 6.009997e-02 3.004998e-02
[90,] 0.9652314 6.953729e-02 3.476864e-02
[91,] 0.9582141 8.357181e-02 4.178591e-02
[92,] 0.9520851 9.582976e-02 4.791488e-02
[93,] 0.9510683 9.786348e-02 4.893174e-02
[94,] 0.9553436 8.931281e-02 4.465640e-02
[95,] 0.9475983 1.048034e-01 5.240168e-02
[96,] 0.9391942 1.216117e-01 6.080583e-02
[97,] 0.9303295 1.393411e-01 6.967055e-02
[98,] 0.9349881 1.300238e-01 6.501191e-02
[99,] 0.9332061 1.335879e-01 6.679394e-02
[100,] 0.9226901 1.546197e-01 7.730986e-02
[101,] 0.9760150 4.797007e-02 2.398503e-02
[102,] 0.9795963 4.080739e-02 2.040369e-02
[103,] 0.9832401 3.351976e-02 1.675988e-02
[104,] 0.9877348 2.453047e-02 1.226524e-02
[105,] 0.9858973 2.820535e-02 1.410268e-02
[106,] 0.9878653 2.426932e-02 1.213466e-02
[107,] 0.9866685 2.666295e-02 1.333147e-02
[108,] 0.9936336 1.273289e-02 6.366443e-03
[109,] 0.9932127 1.357456e-02 6.787280e-03
[110,] 0.9914551 1.708989e-02 8.544947e-03
[111,] 0.9894712 2.105751e-02 1.052876e-02
[112,] 0.9908137 1.837253e-02 9.186264e-03
[113,] 0.9894346 2.113071e-02 1.056536e-02
[114,] 0.9912276 1.754480e-02 8.772400e-03
[115,] 0.9908630 1.827409e-02 9.137047e-03
[116,] 0.9941206 1.175877e-02 5.879384e-03
[117,] 0.9940157 1.196856e-02 5.984278e-03
[118,] 0.9936533 1.269332e-02 6.346662e-03
[119,] 0.9953547 9.290527e-03 4.645264e-03
[120,] 0.9949353 1.012935e-02 5.064675e-03
[121,] 0.9944748 1.105045e-02 5.525226e-03
[122,] 0.9938626 1.227485e-02 6.137424e-03
[123,] 0.9930961 1.380773e-02 6.903867e-03
[124,] 0.9951784 9.643186e-03 4.821593e-03
[125,] 0.9951485 9.703002e-03 4.851501e-03
[126,] 0.9939789 1.204217e-02 6.021085e-03
[127,] 0.9931750 1.365005e-02 6.825025e-03
[128,] 0.9916887 1.662260e-02 8.311302e-03
[129,] 0.9918625 1.627498e-02 8.137488e-03
[130,] 0.9916838 1.663239e-02 8.316196e-03
[131,] 0.9938130 1.237399e-02 6.186996e-03
[132,] 0.9934598 1.308040e-02 6.540198e-03
[133,] 0.9926037 1.479269e-02 7.396345e-03
[134,] 0.9931966 1.360677e-02 6.803387e-03
[135,] 0.9924793 1.504130e-02 7.520651e-03
[136,] 0.9919047 1.619064e-02 8.095320e-03
[137,] 0.9900250 1.994997e-02 9.974985e-03
[138,] 0.9875695 2.486094e-02 1.243047e-02
[139,] 0.9952993 9.401471e-03 4.700735e-03
[140,] 0.9948838 1.023242e-02 5.116212e-03
[141,] 0.9978017 4.396565e-03 2.198283e-03
[142,] 0.9972294 5.541136e-03 2.770568e-03
[143,] 0.9969659 6.068217e-03 3.034108e-03
[144,] 0.9986633 2.673350e-03 1.336675e-03
[145,] 0.9995283 9.433937e-04 4.716969e-04
[146,] 0.9999682 6.353837e-05 3.176918e-05
[147,] 0.9999756 4.885612e-05 2.442806e-05
[148,] 0.9999778 4.447276e-05 2.223638e-05
[149,] 0.9999824 3.514446e-05 1.757223e-05
[150,] 0.9999907 1.853734e-05 9.268671e-06
[151,] 0.9999987 2.642385e-06 1.321193e-06
[152,] 0.9999982 3.612180e-06 1.806090e-06
[153,] 0.9999984 3.279223e-06 1.639611e-06
[154,] 0.9999978 4.361811e-06 2.180905e-06
[155,] 0.9999968 6.472426e-06 3.236213e-06
[156,] 0.9999990 2.033755e-06 1.016878e-06
[157,] 0.9999987 2.601080e-06 1.300540e-06
[158,] 0.9999981 3.721451e-06 1.860725e-06
[159,] 0.9999975 4.979265e-06 2.489633e-06
[160,] 0.9999994 1.124338e-06 5.621688e-07
[161,] 0.9999993 1.369567e-06 6.847836e-07
[162,] 0.9999994 1.130612e-06 5.653062e-07
[163,] 0.9999992 1.679897e-06 8.399484e-07
[164,] 0.9999991 1.747633e-06 8.738163e-07
[165,] 0.9999993 1.435608e-06 7.178040e-07
[166,] 0.9999993 1.410815e-06 7.054073e-07
[167,] 0.9999990 1.981319e-06 9.906594e-07
[168,] 0.9999990 1.982256e-06 9.911281e-07
[169,] 1.0000000 3.667064e-09 1.833532e-09
[170,] 1.0000000 3.420701e-09 1.710351e-09
[171,] 1.0000000 3.772045e-09 1.886023e-09
[172,] 1.0000000 5.793921e-09 2.896961e-09
[173,] 1.0000000 3.078601e-10 1.539301e-10
[174,] 1.0000000 4.737386e-10 2.368693e-10
[175,] 1.0000000 1.362054e-10 6.810269e-11
[176,] 1.0000000 1.743174e-10 8.715872e-11
[177,] 1.0000000 1.231478e-10 6.157388e-11
[178,] 1.0000000 1.983889e-10 9.919445e-11
[179,] 1.0000000 3.295412e-10 1.647706e-10
[180,] 1.0000000 2.540865e-10 1.270432e-10
[181,] 1.0000000 2.436463e-10 1.218231e-10
[182,] 1.0000000 2.268616e-10 1.134308e-10
[183,] 1.0000000 3.708661e-10 1.854331e-10
[184,] 1.0000000 6.637683e-10 3.318841e-10
[185,] 1.0000000 1.001839e-09 5.009193e-10
[186,] 1.0000000 1.742330e-09 8.711651e-10
[187,] 1.0000000 1.527388e-09 7.636939e-10
[188,] 1.0000000 1.941746e-09 9.708732e-10
[189,] 1.0000000 1.066891e-09 5.334456e-10
[190,] 1.0000000 1.491002e-09 7.455010e-10
[191,] 1.0000000 1.528653e-09 7.643267e-10
[192,] 1.0000000 2.522481e-09 1.261240e-09
[193,] 1.0000000 3.589602e-09 1.794801e-09
[194,] 1.0000000 5.244094e-09 2.622047e-09
[195,] 1.0000000 9.328747e-09 4.664373e-09
[196,] 1.0000000 1.485781e-08 7.428906e-09
[197,] 1.0000000 2.582110e-08 1.291055e-08
[198,] 1.0000000 3.939784e-08 1.969892e-08
[199,] 1.0000000 6.688790e-08 3.344395e-08
[200,] 0.9999999 1.154086e-07 5.770432e-08
[201,] 0.9999999 1.943200e-07 9.716002e-08
[202,] 0.9999998 3.200994e-07 1.600497e-07
[203,] 0.9999997 5.310190e-07 2.655095e-07
[204,] 0.9999999 2.405185e-07 1.202592e-07
[205,] 0.9999999 1.880776e-07 9.403881e-08
[206,] 0.9999998 3.139181e-07 1.569590e-07
[207,] 0.9999998 4.480342e-07 2.240171e-07
[208,] 0.9999997 5.107969e-07 2.553984e-07
[209,] 0.9999997 6.914670e-07 3.457335e-07
[210,] 0.9999999 1.661687e-07 8.308436e-08
[211,] 0.9999999 2.785659e-07 1.392830e-07
[212,] 0.9999998 4.913933e-07 2.456966e-07
[213,] 0.9999996 8.376880e-07 4.188440e-07
[214,] 0.9999996 8.187878e-07 4.093939e-07
[215,] 0.9999997 6.278543e-07 3.139272e-07
[216,] 0.9999997 5.670116e-07 2.835058e-07
[217,] 0.9999997 5.448198e-07 2.724099e-07
[218,] 0.9999997 5.441757e-07 2.720878e-07
[219,] 0.9999996 7.602261e-07 3.801130e-07
[220,] 1.0000000 9.636983e-08 4.818492e-08
[221,] 1.0000000 1.545672e-08 7.728360e-09
[222,] 1.0000000 1.653323e-08 8.266613e-09
[223,] 1.0000000 1.249123e-08 6.245615e-09
[224,] 1.0000000 6.604564e-09 3.302282e-09
[225,] 1.0000000 1.051320e-08 5.256601e-09
[226,] 1.0000000 1.885620e-08 9.428099e-09
[227,] 1.0000000 3.493812e-08 1.746906e-08
[228,] 1.0000000 6.781542e-08 3.390771e-08
[229,] 0.9999999 1.150035e-07 5.750175e-08
[230,] 0.9999999 1.836561e-07 9.182805e-08
[231,] 0.9999999 2.552474e-07 1.276237e-07
[232,] 0.9999999 2.445531e-07 1.222766e-07
[233,] 0.9999998 3.560350e-07 1.780175e-07
[234,] 0.9999997 6.183722e-07 3.091861e-07
[235,] 0.9999996 8.974517e-07 4.487258e-07
[236,] 0.9999992 1.670681e-06 8.353405e-07
[237,] 0.9999984 3.257736e-06 1.628868e-06
[238,] 0.9999979 4.173863e-06 2.086931e-06
[239,] 0.9999961 7.891886e-06 3.945943e-06
[240,] 0.9999929 1.420152e-05 7.100762e-06
[241,] 0.9999920 1.594446e-05 7.972232e-06
[242,] 0.9999888 2.234953e-05 1.117477e-05
[243,] 0.9999832 3.365809e-05 1.682905e-05
[244,] 0.9999771 4.587370e-05 2.293685e-05
[245,] 0.9999649 7.027535e-05 3.513767e-05
[246,] 0.9999474 1.052068e-04 5.260338e-05
[247,] 0.9999331 1.337410e-04 6.687049e-05
[248,] 0.9998756 2.488002e-04 1.244001e-04
[249,] 0.9998065 3.870788e-04 1.935394e-04
[250,] 0.9997616 4.768219e-04 2.384110e-04
[251,] 0.9995734 8.531299e-04 4.265650e-04
[252,] 0.9992784 1.443153e-03 7.215767e-04
[253,] 0.9987328 2.534476e-03 1.267238e-03
[254,] 0.9979995 4.000907e-03 2.000453e-03
[255,] 0.9981083 3.783407e-03 1.891704e-03
[256,] 0.9971526 5.694824e-03 2.847412e-03
[257,] 0.9962196 7.560746e-03 3.780373e-03
[258,] 0.9937730 1.245398e-02 6.226991e-03
[259,] 0.9925685 1.486296e-02 7.431479e-03
[260,] 0.9877301 2.453990e-02 1.226995e-02
[261,] 0.9858171 2.836582e-02 1.418291e-02
[262,] 0.9811607 3.767857e-02 1.883928e-02
[263,] 0.9781226 4.375484e-02 2.187742e-02
[264,] 0.9649072 7.018555e-02 3.509277e-02
[265,] 0.9670768 6.584644e-02 3.292322e-02
[266,] 0.9666402 6.671959e-02 3.335980e-02
[267,] 0.9974174 5.165226e-03 2.582613e-03
[268,] 0.9988377 2.324688e-03 1.162344e-03
[269,] 0.9971106 5.778798e-03 2.889399e-03
[270,] 0.9949560 1.008803e-02 5.044015e-03
[271,] 0.9893172 2.136554e-02 1.068277e-02
[272,] 0.9762738 4.745241e-02 2.372621e-02
[273,] 0.9484874 1.030251e-01 5.151257e-02
[274,] 0.9458626 1.082748e-01 5.413739e-02
[275,] 0.8826363 2.347273e-01 1.173637e-01
[276,] 0.7620443 4.759115e-01 2.379557e-01
> postscript(file="/var/wessaorg/rcomp/tmp/13i6y1324456697.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2vmzj1324456697.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wcfm1324456697.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/417du1324456697.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5t1l61324456697.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 289
Frequency = 1
1 2 3 4 5
23.97863777 50.42606999 15.09195156 7.32851388 -3.31861189
6 7 8 9 10
33.02991584 -51.32055698 -10.06553412 -23.22428253 15.89893587
11 12 13 14 15
-11.88992586 36.78674313 68.48982017 18.16663142 25.57073904
16 17 18 19 20
-9.15899946 -5.46863845 29.68348842 -32.57183077 5.52797540
21 22 23 24 25
41.52476149 28.07510792 6.01965421 20.22947965 88.31437170
26 27 28 29 30
12.40860307 10.69402627 -15.78184680 36.71193666 15.09389174
31 32 33 34 35
30.01225983 47.70453768 44.43544126 70.55206954 58.09352449
36 37 38 39 40
10.61024395 -11.99143962 1.66822024 3.51544983 -30.34011152
41 42 43 44 45
-6.61443959 -16.13108346 -41.84209325 -4.60853219 -34.13552661
46 47 48 49 50
26.53718255 -42.32779837 20.26549802 17.44303438 -65.68388418
51 52 53 54 55
4.46072350 12.98037928 49.75520101 -10.22774349 29.52105129
56 57 58 59 60
22.34101279 -33.23329809 20.61951808 12.13134647 -21.36672911
61 62 63 64 65
-4.10807523 63.80946399 -110.94030031 -10.29045772 -11.90635630
66 67 68 69 70
25.96613954 12.05909960 -14.20748487 -45.20242265 -26.45453193
71 72 73 74 75
17.33227502 32.28778249 -2.27114753 22.35266229 7.98357114
76 77 78 79 80
3.13256427 6.11805540 45.08232126 13.51661753 63.70166696
81 82 83 84 85
2.95285913 47.56804932 26.88932902 11.71717182 22.98908945
86 87 88 89 90
33.60483464 25.92299344 -5.07508040 -17.14110689 27.50310178
91 92 93 94 95
-13.54367565 -26.03186067 1.02189176 48.53243965 16.74922281
96 97 98 99 100
-7.43640211 -1.73802463 11.37814493 -23.17320103 37.34688644
101 102 103 104 105
0.84843218 9.58166817 16.43969445 37.25169066 29.12776286
106 107 108 109 110
5.71249702 70.34379261 -28.63166296 -44.04448980 41.61413423
111 112 113 114 115
16.98404559 -28.83950654 23.44484947 -53.27389316 -20.15104921
116 117 118 119 120
1.76775877 2.96145327 -33.01614050 13.88556860 -29.47285791
121 122 123 124 125
-20.66064008 -42.63084363 -15.61082357 25.08747581 40.90523663
126 127 128 129 130
-13.88125619 -15.84927323 23.00664480 16.96702368 -36.49087656
131 132 133 134 135
-21.39043301 0.74581175 -10.97665717 -8.09172489 32.39615799
136 137 138 139 140
-30.72669978 -37.69977000 -24.65349624 -13.52009024 -28.80562677
141 142 143 144 145
-18.54675852 -22.63970789 -2.72111926 1.34970582 60.87972067
146 147 148 149 150
-16.06331755 58.36553479 3.17264908 -18.80645774 56.51223804
151 152 153 154 155
55.61212469 77.27496472 -39.06136716 25.42206934 30.63896344
156 157 158 159 160
31.89348258 56.78428566 -7.12178604 22.55797717 10.18047701
161 162 163 164 165
-10.57991948 46.62510053 -20.19547519 -5.01694345 3.23847306
166 167 168 169 170
45.91420965 16.87607660 -32.88827203 -7.36728701 -33.04382945
171 172 173 174 175
-47.04420953 14.84494348 -21.26467310 7.27292198 83.69691920
176 177 178 179 180
-34.35283704 0.02502941 1.18415961 38.02799716 -15.68935995
181 182 183 184 185
-49.27628067 -26.59139152 -30.67866768 -10.79975469 -24.70279973
186 187 188 189 190
-28.15968789 -27.68473035 -23.41211373 -23.03576296 -1.02192408
191 192 193 194 195
-25.16717239 -11.09365172 -30.43852704 24.48729768 16.92357828
196 197 198 199 200
-26.74799615 13.04196068 2.23819538 -27.97920019 6.11964184
201 202 203 204 205
-4.40801679 7.02316876 -8.52043143 2.76426153 -13.17074885
206 207 208 209 210
-3.81518056 -8.22269111 -16.08422843 -12.41013398 19.45887795
211 212 213 214 215
-39.28662789 -14.94226922 9.39178776 11.18953925 -1.06623655
216 217 218 219 220
35.21286203 -16.77592014 -2.77796486 -5.10628037 13.96613261
221 222 223 224 225
9.15115350 -0.01105898 -40.26003556 11.86861189 10.78464785
226 227 228 229 230
-52.99061601 -43.60389363 7.31146988 -31.08524454 7.77116027
231 232 233 234 235
5.34477366 -20.97111421 -26.64382642 -6.85380391 -11.99312361
236 237 238 239 240
2.65312541 -9.78648659 -32.32877803 -12.01620701 -0.24919472
241 242 243 244 245
-25.20813721 -12.23317617 -4.61008548 0.58497752 -0.87782055
246 247 248 249 250
-16.06006778 -34.30933016 3.55370253 -18.21055470 -36.73589143
251 252 253 254 255
-2.16553477 15.11643801 -29.46961765 0.51782081 -9.50892699
256 257 258 259 260
-34.76337062 -15.18890858 -10.79850939 -4.50704637 -20.00432000
261 262 263 264 265
-21.53674334 23.25451993 -26.51742369 -16.28468374 8.87519982
266 267 268 269 270
-17.12987120 8.17916101 -20.57282385 12.79561803 -12.33163628
271 272 273 274 275
-24.68852303 16.90629677 -42.11641096 -8.25676476 -21.66337084
276 277 278 279 280
-19.62045070 -11.47209663 -27.42825801 -13.14404829 17.26810059
281 282 283 284 285
18.15587497 -21.51636104 -41.48579091 -32.04778584 10.00419572
286 287 288 289
-18.23003704 -14.87649976 3.25502711 -12.42226628
> postscript(file="/var/wessaorg/rcomp/tmp/6qeza1324456697.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 289
Frequency = 1
lag(myerror, k = 1) myerror
0 23.97863777 NA
1 50.42606999 23.97863777
2 15.09195156 50.42606999
3 7.32851388 15.09195156
4 -3.31861189 7.32851388
5 33.02991584 -3.31861189
6 -51.32055698 33.02991584
7 -10.06553412 -51.32055698
8 -23.22428253 -10.06553412
9 15.89893587 -23.22428253
10 -11.88992586 15.89893587
11 36.78674313 -11.88992586
12 68.48982017 36.78674313
13 18.16663142 68.48982017
14 25.57073904 18.16663142
15 -9.15899946 25.57073904
16 -5.46863845 -9.15899946
17 29.68348842 -5.46863845
18 -32.57183077 29.68348842
19 5.52797540 -32.57183077
20 41.52476149 5.52797540
21 28.07510792 41.52476149
22 6.01965421 28.07510792
23 20.22947965 6.01965421
24 88.31437170 20.22947965
25 12.40860307 88.31437170
26 10.69402627 12.40860307
27 -15.78184680 10.69402627
28 36.71193666 -15.78184680
29 15.09389174 36.71193666
30 30.01225983 15.09389174
31 47.70453768 30.01225983
32 44.43544126 47.70453768
33 70.55206954 44.43544126
34 58.09352449 70.55206954
35 10.61024395 58.09352449
36 -11.99143962 10.61024395
37 1.66822024 -11.99143962
38 3.51544983 1.66822024
39 -30.34011152 3.51544983
40 -6.61443959 -30.34011152
41 -16.13108346 -6.61443959
42 -41.84209325 -16.13108346
43 -4.60853219 -41.84209325
44 -34.13552661 -4.60853219
45 26.53718255 -34.13552661
46 -42.32779837 26.53718255
47 20.26549802 -42.32779837
48 17.44303438 20.26549802
49 -65.68388418 17.44303438
50 4.46072350 -65.68388418
51 12.98037928 4.46072350
52 49.75520101 12.98037928
53 -10.22774349 49.75520101
54 29.52105129 -10.22774349
55 22.34101279 29.52105129
56 -33.23329809 22.34101279
57 20.61951808 -33.23329809
58 12.13134647 20.61951808
59 -21.36672911 12.13134647
60 -4.10807523 -21.36672911
61 63.80946399 -4.10807523
62 -110.94030031 63.80946399
63 -10.29045772 -110.94030031
64 -11.90635630 -10.29045772
65 25.96613954 -11.90635630
66 12.05909960 25.96613954
67 -14.20748487 12.05909960
68 -45.20242265 -14.20748487
69 -26.45453193 -45.20242265
70 17.33227502 -26.45453193
71 32.28778249 17.33227502
72 -2.27114753 32.28778249
73 22.35266229 -2.27114753
74 7.98357114 22.35266229
75 3.13256427 7.98357114
76 6.11805540 3.13256427
77 45.08232126 6.11805540
78 13.51661753 45.08232126
79 63.70166696 13.51661753
80 2.95285913 63.70166696
81 47.56804932 2.95285913
82 26.88932902 47.56804932
83 11.71717182 26.88932902
84 22.98908945 11.71717182
85 33.60483464 22.98908945
86 25.92299344 33.60483464
87 -5.07508040 25.92299344
88 -17.14110689 -5.07508040
89 27.50310178 -17.14110689
90 -13.54367565 27.50310178
91 -26.03186067 -13.54367565
92 1.02189176 -26.03186067
93 48.53243965 1.02189176
94 16.74922281 48.53243965
95 -7.43640211 16.74922281
96 -1.73802463 -7.43640211
97 11.37814493 -1.73802463
98 -23.17320103 11.37814493
99 37.34688644 -23.17320103
100 0.84843218 37.34688644
101 9.58166817 0.84843218
102 16.43969445 9.58166817
103 37.25169066 16.43969445
104 29.12776286 37.25169066
105 5.71249702 29.12776286
106 70.34379261 5.71249702
107 -28.63166296 70.34379261
108 -44.04448980 -28.63166296
109 41.61413423 -44.04448980
110 16.98404559 41.61413423
111 -28.83950654 16.98404559
112 23.44484947 -28.83950654
113 -53.27389316 23.44484947
114 -20.15104921 -53.27389316
115 1.76775877 -20.15104921
116 2.96145327 1.76775877
117 -33.01614050 2.96145327
118 13.88556860 -33.01614050
119 -29.47285791 13.88556860
120 -20.66064008 -29.47285791
121 -42.63084363 -20.66064008
122 -15.61082357 -42.63084363
123 25.08747581 -15.61082357
124 40.90523663 25.08747581
125 -13.88125619 40.90523663
126 -15.84927323 -13.88125619
127 23.00664480 -15.84927323
128 16.96702368 23.00664480
129 -36.49087656 16.96702368
130 -21.39043301 -36.49087656
131 0.74581175 -21.39043301
132 -10.97665717 0.74581175
133 -8.09172489 -10.97665717
134 32.39615799 -8.09172489
135 -30.72669978 32.39615799
136 -37.69977000 -30.72669978
137 -24.65349624 -37.69977000
138 -13.52009024 -24.65349624
139 -28.80562677 -13.52009024
140 -18.54675852 -28.80562677
141 -22.63970789 -18.54675852
142 -2.72111926 -22.63970789
143 1.34970582 -2.72111926
144 60.87972067 1.34970582
145 -16.06331755 60.87972067
146 58.36553479 -16.06331755
147 3.17264908 58.36553479
148 -18.80645774 3.17264908
149 56.51223804 -18.80645774
150 55.61212469 56.51223804
151 77.27496472 55.61212469
152 -39.06136716 77.27496472
153 25.42206934 -39.06136716
154 30.63896344 25.42206934
155 31.89348258 30.63896344
156 56.78428566 31.89348258
157 -7.12178604 56.78428566
158 22.55797717 -7.12178604
159 10.18047701 22.55797717
160 -10.57991948 10.18047701
161 46.62510053 -10.57991948
162 -20.19547519 46.62510053
163 -5.01694345 -20.19547519
164 3.23847306 -5.01694345
165 45.91420965 3.23847306
166 16.87607660 45.91420965
167 -32.88827203 16.87607660
168 -7.36728701 -32.88827203
169 -33.04382945 -7.36728701
170 -47.04420953 -33.04382945
171 14.84494348 -47.04420953
172 -21.26467310 14.84494348
173 7.27292198 -21.26467310
174 83.69691920 7.27292198
175 -34.35283704 83.69691920
176 0.02502941 -34.35283704
177 1.18415961 0.02502941
178 38.02799716 1.18415961
179 -15.68935995 38.02799716
180 -49.27628067 -15.68935995
181 -26.59139152 -49.27628067
182 -30.67866768 -26.59139152
183 -10.79975469 -30.67866768
184 -24.70279973 -10.79975469
185 -28.15968789 -24.70279973
186 -27.68473035 -28.15968789
187 -23.41211373 -27.68473035
188 -23.03576296 -23.41211373
189 -1.02192408 -23.03576296
190 -25.16717239 -1.02192408
191 -11.09365172 -25.16717239
192 -30.43852704 -11.09365172
193 24.48729768 -30.43852704
194 16.92357828 24.48729768
195 -26.74799615 16.92357828
196 13.04196068 -26.74799615
197 2.23819538 13.04196068
198 -27.97920019 2.23819538
199 6.11964184 -27.97920019
200 -4.40801679 6.11964184
201 7.02316876 -4.40801679
202 -8.52043143 7.02316876
203 2.76426153 -8.52043143
204 -13.17074885 2.76426153
205 -3.81518056 -13.17074885
206 -8.22269111 -3.81518056
207 -16.08422843 -8.22269111
208 -12.41013398 -16.08422843
209 19.45887795 -12.41013398
210 -39.28662789 19.45887795
211 -14.94226922 -39.28662789
212 9.39178776 -14.94226922
213 11.18953925 9.39178776
214 -1.06623655 11.18953925
215 35.21286203 -1.06623655
216 -16.77592014 35.21286203
217 -2.77796486 -16.77592014
218 -5.10628037 -2.77796486
219 13.96613261 -5.10628037
220 9.15115350 13.96613261
221 -0.01105898 9.15115350
222 -40.26003556 -0.01105898
223 11.86861189 -40.26003556
224 10.78464785 11.86861189
225 -52.99061601 10.78464785
226 -43.60389363 -52.99061601
227 7.31146988 -43.60389363
228 -31.08524454 7.31146988
229 7.77116027 -31.08524454
230 5.34477366 7.77116027
231 -20.97111421 5.34477366
232 -26.64382642 -20.97111421
233 -6.85380391 -26.64382642
234 -11.99312361 -6.85380391
235 2.65312541 -11.99312361
236 -9.78648659 2.65312541
237 -32.32877803 -9.78648659
238 -12.01620701 -32.32877803
239 -0.24919472 -12.01620701
240 -25.20813721 -0.24919472
241 -12.23317617 -25.20813721
242 -4.61008548 -12.23317617
243 0.58497752 -4.61008548
244 -0.87782055 0.58497752
245 -16.06006778 -0.87782055
246 -34.30933016 -16.06006778
247 3.55370253 -34.30933016
248 -18.21055470 3.55370253
249 -36.73589143 -18.21055470
250 -2.16553477 -36.73589143
251 15.11643801 -2.16553477
252 -29.46961765 15.11643801
253 0.51782081 -29.46961765
254 -9.50892699 0.51782081
255 -34.76337062 -9.50892699
256 -15.18890858 -34.76337062
257 -10.79850939 -15.18890858
258 -4.50704637 -10.79850939
259 -20.00432000 -4.50704637
260 -21.53674334 -20.00432000
261 23.25451993 -21.53674334
262 -26.51742369 23.25451993
263 -16.28468374 -26.51742369
264 8.87519982 -16.28468374
265 -17.12987120 8.87519982
266 8.17916101 -17.12987120
267 -20.57282385 8.17916101
268 12.79561803 -20.57282385
269 -12.33163628 12.79561803
270 -24.68852303 -12.33163628
271 16.90629677 -24.68852303
272 -42.11641096 16.90629677
273 -8.25676476 -42.11641096
274 -21.66337084 -8.25676476
275 -19.62045070 -21.66337084
276 -11.47209663 -19.62045070
277 -27.42825801 -11.47209663
278 -13.14404829 -27.42825801
279 17.26810059 -13.14404829
280 18.15587497 17.26810059
281 -21.51636104 18.15587497
282 -41.48579091 -21.51636104
283 -32.04778584 -41.48579091
284 10.00419572 -32.04778584
285 -18.23003704 10.00419572
286 -14.87649976 -18.23003704
287 3.25502711 -14.87649976
288 -12.42226628 3.25502711
289 NA -12.42226628
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 50.42606999 23.97863777
[2,] 15.09195156 50.42606999
[3,] 7.32851388 15.09195156
[4,] -3.31861189 7.32851388
[5,] 33.02991584 -3.31861189
[6,] -51.32055698 33.02991584
[7,] -10.06553412 -51.32055698
[8,] -23.22428253 -10.06553412
[9,] 15.89893587 -23.22428253
[10,] -11.88992586 15.89893587
[11,] 36.78674313 -11.88992586
[12,] 68.48982017 36.78674313
[13,] 18.16663142 68.48982017
[14,] 25.57073904 18.16663142
[15,] -9.15899946 25.57073904
[16,] -5.46863845 -9.15899946
[17,] 29.68348842 -5.46863845
[18,] -32.57183077 29.68348842
[19,] 5.52797540 -32.57183077
[20,] 41.52476149 5.52797540
[21,] 28.07510792 41.52476149
[22,] 6.01965421 28.07510792
[23,] 20.22947965 6.01965421
[24,] 88.31437170 20.22947965
[25,] 12.40860307 88.31437170
[26,] 10.69402627 12.40860307
[27,] -15.78184680 10.69402627
[28,] 36.71193666 -15.78184680
[29,] 15.09389174 36.71193666
[30,] 30.01225983 15.09389174
[31,] 47.70453768 30.01225983
[32,] 44.43544126 47.70453768
[33,] 70.55206954 44.43544126
[34,] 58.09352449 70.55206954
[35,] 10.61024395 58.09352449
[36,] -11.99143962 10.61024395
[37,] 1.66822024 -11.99143962
[38,] 3.51544983 1.66822024
[39,] -30.34011152 3.51544983
[40,] -6.61443959 -30.34011152
[41,] -16.13108346 -6.61443959
[42,] -41.84209325 -16.13108346
[43,] -4.60853219 -41.84209325
[44,] -34.13552661 -4.60853219
[45,] 26.53718255 -34.13552661
[46,] -42.32779837 26.53718255
[47,] 20.26549802 -42.32779837
[48,] 17.44303438 20.26549802
[49,] -65.68388418 17.44303438
[50,] 4.46072350 -65.68388418
[51,] 12.98037928 4.46072350
[52,] 49.75520101 12.98037928
[53,] -10.22774349 49.75520101
[54,] 29.52105129 -10.22774349
[55,] 22.34101279 29.52105129
[56,] -33.23329809 22.34101279
[57,] 20.61951808 -33.23329809
[58,] 12.13134647 20.61951808
[59,] -21.36672911 12.13134647
[60,] -4.10807523 -21.36672911
[61,] 63.80946399 -4.10807523
[62,] -110.94030031 63.80946399
[63,] -10.29045772 -110.94030031
[64,] -11.90635630 -10.29045772
[65,] 25.96613954 -11.90635630
[66,] 12.05909960 25.96613954
[67,] -14.20748487 12.05909960
[68,] -45.20242265 -14.20748487
[69,] -26.45453193 -45.20242265
[70,] 17.33227502 -26.45453193
[71,] 32.28778249 17.33227502
[72,] -2.27114753 32.28778249
[73,] 22.35266229 -2.27114753
[74,] 7.98357114 22.35266229
[75,] 3.13256427 7.98357114
[76,] 6.11805540 3.13256427
[77,] 45.08232126 6.11805540
[78,] 13.51661753 45.08232126
[79,] 63.70166696 13.51661753
[80,] 2.95285913 63.70166696
[81,] 47.56804932 2.95285913
[82,] 26.88932902 47.56804932
[83,] 11.71717182 26.88932902
[84,] 22.98908945 11.71717182
[85,] 33.60483464 22.98908945
[86,] 25.92299344 33.60483464
[87,] -5.07508040 25.92299344
[88,] -17.14110689 -5.07508040
[89,] 27.50310178 -17.14110689
[90,] -13.54367565 27.50310178
[91,] -26.03186067 -13.54367565
[92,] 1.02189176 -26.03186067
[93,] 48.53243965 1.02189176
[94,] 16.74922281 48.53243965
[95,] -7.43640211 16.74922281
[96,] -1.73802463 -7.43640211
[97,] 11.37814493 -1.73802463
[98,] -23.17320103 11.37814493
[99,] 37.34688644 -23.17320103
[100,] 0.84843218 37.34688644
[101,] 9.58166817 0.84843218
[102,] 16.43969445 9.58166817
[103,] 37.25169066 16.43969445
[104,] 29.12776286 37.25169066
[105,] 5.71249702 29.12776286
[106,] 70.34379261 5.71249702
[107,] -28.63166296 70.34379261
[108,] -44.04448980 -28.63166296
[109,] 41.61413423 -44.04448980
[110,] 16.98404559 41.61413423
[111,] -28.83950654 16.98404559
[112,] 23.44484947 -28.83950654
[113,] -53.27389316 23.44484947
[114,] -20.15104921 -53.27389316
[115,] 1.76775877 -20.15104921
[116,] 2.96145327 1.76775877
[117,] -33.01614050 2.96145327
[118,] 13.88556860 -33.01614050
[119,] -29.47285791 13.88556860
[120,] -20.66064008 -29.47285791
[121,] -42.63084363 -20.66064008
[122,] -15.61082357 -42.63084363
[123,] 25.08747581 -15.61082357
[124,] 40.90523663 25.08747581
[125,] -13.88125619 40.90523663
[126,] -15.84927323 -13.88125619
[127,] 23.00664480 -15.84927323
[128,] 16.96702368 23.00664480
[129,] -36.49087656 16.96702368
[130,] -21.39043301 -36.49087656
[131,] 0.74581175 -21.39043301
[132,] -10.97665717 0.74581175
[133,] -8.09172489 -10.97665717
[134,] 32.39615799 -8.09172489
[135,] -30.72669978 32.39615799
[136,] -37.69977000 -30.72669978
[137,] -24.65349624 -37.69977000
[138,] -13.52009024 -24.65349624
[139,] -28.80562677 -13.52009024
[140,] -18.54675852 -28.80562677
[141,] -22.63970789 -18.54675852
[142,] -2.72111926 -22.63970789
[143,] 1.34970582 -2.72111926
[144,] 60.87972067 1.34970582
[145,] -16.06331755 60.87972067
[146,] 58.36553479 -16.06331755
[147,] 3.17264908 58.36553479
[148,] -18.80645774 3.17264908
[149,] 56.51223804 -18.80645774
[150,] 55.61212469 56.51223804
[151,] 77.27496472 55.61212469
[152,] -39.06136716 77.27496472
[153,] 25.42206934 -39.06136716
[154,] 30.63896344 25.42206934
[155,] 31.89348258 30.63896344
[156,] 56.78428566 31.89348258
[157,] -7.12178604 56.78428566
[158,] 22.55797717 -7.12178604
[159,] 10.18047701 22.55797717
[160,] -10.57991948 10.18047701
[161,] 46.62510053 -10.57991948
[162,] -20.19547519 46.62510053
[163,] -5.01694345 -20.19547519
[164,] 3.23847306 -5.01694345
[165,] 45.91420965 3.23847306
[166,] 16.87607660 45.91420965
[167,] -32.88827203 16.87607660
[168,] -7.36728701 -32.88827203
[169,] -33.04382945 -7.36728701
[170,] -47.04420953 -33.04382945
[171,] 14.84494348 -47.04420953
[172,] -21.26467310 14.84494348
[173,] 7.27292198 -21.26467310
[174,] 83.69691920 7.27292198
[175,] -34.35283704 83.69691920
[176,] 0.02502941 -34.35283704
[177,] 1.18415961 0.02502941
[178,] 38.02799716 1.18415961
[179,] -15.68935995 38.02799716
[180,] -49.27628067 -15.68935995
[181,] -26.59139152 -49.27628067
[182,] -30.67866768 -26.59139152
[183,] -10.79975469 -30.67866768
[184,] -24.70279973 -10.79975469
[185,] -28.15968789 -24.70279973
[186,] -27.68473035 -28.15968789
[187,] -23.41211373 -27.68473035
[188,] -23.03576296 -23.41211373
[189,] -1.02192408 -23.03576296
[190,] -25.16717239 -1.02192408
[191,] -11.09365172 -25.16717239
[192,] -30.43852704 -11.09365172
[193,] 24.48729768 -30.43852704
[194,] 16.92357828 24.48729768
[195,] -26.74799615 16.92357828
[196,] 13.04196068 -26.74799615
[197,] 2.23819538 13.04196068
[198,] -27.97920019 2.23819538
[199,] 6.11964184 -27.97920019
[200,] -4.40801679 6.11964184
[201,] 7.02316876 -4.40801679
[202,] -8.52043143 7.02316876
[203,] 2.76426153 -8.52043143
[204,] -13.17074885 2.76426153
[205,] -3.81518056 -13.17074885
[206,] -8.22269111 -3.81518056
[207,] -16.08422843 -8.22269111
[208,] -12.41013398 -16.08422843
[209,] 19.45887795 -12.41013398
[210,] -39.28662789 19.45887795
[211,] -14.94226922 -39.28662789
[212,] 9.39178776 -14.94226922
[213,] 11.18953925 9.39178776
[214,] -1.06623655 11.18953925
[215,] 35.21286203 -1.06623655
[216,] -16.77592014 35.21286203
[217,] -2.77796486 -16.77592014
[218,] -5.10628037 -2.77796486
[219,] 13.96613261 -5.10628037
[220,] 9.15115350 13.96613261
[221,] -0.01105898 9.15115350
[222,] -40.26003556 -0.01105898
[223,] 11.86861189 -40.26003556
[224,] 10.78464785 11.86861189
[225,] -52.99061601 10.78464785
[226,] -43.60389363 -52.99061601
[227,] 7.31146988 -43.60389363
[228,] -31.08524454 7.31146988
[229,] 7.77116027 -31.08524454
[230,] 5.34477366 7.77116027
[231,] -20.97111421 5.34477366
[232,] -26.64382642 -20.97111421
[233,] -6.85380391 -26.64382642
[234,] -11.99312361 -6.85380391
[235,] 2.65312541 -11.99312361
[236,] -9.78648659 2.65312541
[237,] -32.32877803 -9.78648659
[238,] -12.01620701 -32.32877803
[239,] -0.24919472 -12.01620701
[240,] -25.20813721 -0.24919472
[241,] -12.23317617 -25.20813721
[242,] -4.61008548 -12.23317617
[243,] 0.58497752 -4.61008548
[244,] -0.87782055 0.58497752
[245,] -16.06006778 -0.87782055
[246,] -34.30933016 -16.06006778
[247,] 3.55370253 -34.30933016
[248,] -18.21055470 3.55370253
[249,] -36.73589143 -18.21055470
[250,] -2.16553477 -36.73589143
[251,] 15.11643801 -2.16553477
[252,] -29.46961765 15.11643801
[253,] 0.51782081 -29.46961765
[254,] -9.50892699 0.51782081
[255,] -34.76337062 -9.50892699
[256,] -15.18890858 -34.76337062
[257,] -10.79850939 -15.18890858
[258,] -4.50704637 -10.79850939
[259,] -20.00432000 -4.50704637
[260,] -21.53674334 -20.00432000
[261,] 23.25451993 -21.53674334
[262,] -26.51742369 23.25451993
[263,] -16.28468374 -26.51742369
[264,] 8.87519982 -16.28468374
[265,] -17.12987120 8.87519982
[266,] 8.17916101 -17.12987120
[267,] -20.57282385 8.17916101
[268,] 12.79561803 -20.57282385
[269,] -12.33163628 12.79561803
[270,] -24.68852303 -12.33163628
[271,] 16.90629677 -24.68852303
[272,] -42.11641096 16.90629677
[273,] -8.25676476 -42.11641096
[274,] -21.66337084 -8.25676476
[275,] -19.62045070 -21.66337084
[276,] -11.47209663 -19.62045070
[277,] -27.42825801 -11.47209663
[278,] -13.14404829 -27.42825801
[279,] 17.26810059 -13.14404829
[280,] 18.15587497 17.26810059
[281,] -21.51636104 18.15587497
[282,] -41.48579091 -21.51636104
[283,] -32.04778584 -41.48579091
[284,] 10.00419572 -32.04778584
[285,] -18.23003704 10.00419572
[286,] -14.87649976 -18.23003704
[287,] 3.25502711 -14.87649976
[288,] -12.42226628 3.25502711
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 50.42606999 23.97863777
2 15.09195156 50.42606999
3 7.32851388 15.09195156
4 -3.31861189 7.32851388
5 33.02991584 -3.31861189
6 -51.32055698 33.02991584
7 -10.06553412 -51.32055698
8 -23.22428253 -10.06553412
9 15.89893587 -23.22428253
10 -11.88992586 15.89893587
11 36.78674313 -11.88992586
12 68.48982017 36.78674313
13 18.16663142 68.48982017
14 25.57073904 18.16663142
15 -9.15899946 25.57073904
16 -5.46863845 -9.15899946
17 29.68348842 -5.46863845
18 -32.57183077 29.68348842
19 5.52797540 -32.57183077
20 41.52476149 5.52797540
21 28.07510792 41.52476149
22 6.01965421 28.07510792
23 20.22947965 6.01965421
24 88.31437170 20.22947965
25 12.40860307 88.31437170
26 10.69402627 12.40860307
27 -15.78184680 10.69402627
28 36.71193666 -15.78184680
29 15.09389174 36.71193666
30 30.01225983 15.09389174
31 47.70453768 30.01225983
32 44.43544126 47.70453768
33 70.55206954 44.43544126
34 58.09352449 70.55206954
35 10.61024395 58.09352449
36 -11.99143962 10.61024395
37 1.66822024 -11.99143962
38 3.51544983 1.66822024
39 -30.34011152 3.51544983
40 -6.61443959 -30.34011152
41 -16.13108346 -6.61443959
42 -41.84209325 -16.13108346
43 -4.60853219 -41.84209325
44 -34.13552661 -4.60853219
45 26.53718255 -34.13552661
46 -42.32779837 26.53718255
47 20.26549802 -42.32779837
48 17.44303438 20.26549802
49 -65.68388418 17.44303438
50 4.46072350 -65.68388418
51 12.98037928 4.46072350
52 49.75520101 12.98037928
53 -10.22774349 49.75520101
54 29.52105129 -10.22774349
55 22.34101279 29.52105129
56 -33.23329809 22.34101279
57 20.61951808 -33.23329809
58 12.13134647 20.61951808
59 -21.36672911 12.13134647
60 -4.10807523 -21.36672911
61 63.80946399 -4.10807523
62 -110.94030031 63.80946399
63 -10.29045772 -110.94030031
64 -11.90635630 -10.29045772
65 25.96613954 -11.90635630
66 12.05909960 25.96613954
67 -14.20748487 12.05909960
68 -45.20242265 -14.20748487
69 -26.45453193 -45.20242265
70 17.33227502 -26.45453193
71 32.28778249 17.33227502
72 -2.27114753 32.28778249
73 22.35266229 -2.27114753
74 7.98357114 22.35266229
75 3.13256427 7.98357114
76 6.11805540 3.13256427
77 45.08232126 6.11805540
78 13.51661753 45.08232126
79 63.70166696 13.51661753
80 2.95285913 63.70166696
81 47.56804932 2.95285913
82 26.88932902 47.56804932
83 11.71717182 26.88932902
84 22.98908945 11.71717182
85 33.60483464 22.98908945
86 25.92299344 33.60483464
87 -5.07508040 25.92299344
88 -17.14110689 -5.07508040
89 27.50310178 -17.14110689
90 -13.54367565 27.50310178
91 -26.03186067 -13.54367565
92 1.02189176 -26.03186067
93 48.53243965 1.02189176
94 16.74922281 48.53243965
95 -7.43640211 16.74922281
96 -1.73802463 -7.43640211
97 11.37814493 -1.73802463
98 -23.17320103 11.37814493
99 37.34688644 -23.17320103
100 0.84843218 37.34688644
101 9.58166817 0.84843218
102 16.43969445 9.58166817
103 37.25169066 16.43969445
104 29.12776286 37.25169066
105 5.71249702 29.12776286
106 70.34379261 5.71249702
107 -28.63166296 70.34379261
108 -44.04448980 -28.63166296
109 41.61413423 -44.04448980
110 16.98404559 41.61413423
111 -28.83950654 16.98404559
112 23.44484947 -28.83950654
113 -53.27389316 23.44484947
114 -20.15104921 -53.27389316
115 1.76775877 -20.15104921
116 2.96145327 1.76775877
117 -33.01614050 2.96145327
118 13.88556860 -33.01614050
119 -29.47285791 13.88556860
120 -20.66064008 -29.47285791
121 -42.63084363 -20.66064008
122 -15.61082357 -42.63084363
123 25.08747581 -15.61082357
124 40.90523663 25.08747581
125 -13.88125619 40.90523663
126 -15.84927323 -13.88125619
127 23.00664480 -15.84927323
128 16.96702368 23.00664480
129 -36.49087656 16.96702368
130 -21.39043301 -36.49087656
131 0.74581175 -21.39043301
132 -10.97665717 0.74581175
133 -8.09172489 -10.97665717
134 32.39615799 -8.09172489
135 -30.72669978 32.39615799
136 -37.69977000 -30.72669978
137 -24.65349624 -37.69977000
138 -13.52009024 -24.65349624
139 -28.80562677 -13.52009024
140 -18.54675852 -28.80562677
141 -22.63970789 -18.54675852
142 -2.72111926 -22.63970789
143 1.34970582 -2.72111926
144 60.87972067 1.34970582
145 -16.06331755 60.87972067
146 58.36553479 -16.06331755
147 3.17264908 58.36553479
148 -18.80645774 3.17264908
149 56.51223804 -18.80645774
150 55.61212469 56.51223804
151 77.27496472 55.61212469
152 -39.06136716 77.27496472
153 25.42206934 -39.06136716
154 30.63896344 25.42206934
155 31.89348258 30.63896344
156 56.78428566 31.89348258
157 -7.12178604 56.78428566
158 22.55797717 -7.12178604
159 10.18047701 22.55797717
160 -10.57991948 10.18047701
161 46.62510053 -10.57991948
162 -20.19547519 46.62510053
163 -5.01694345 -20.19547519
164 3.23847306 -5.01694345
165 45.91420965 3.23847306
166 16.87607660 45.91420965
167 -32.88827203 16.87607660
168 -7.36728701 -32.88827203
169 -33.04382945 -7.36728701
170 -47.04420953 -33.04382945
171 14.84494348 -47.04420953
172 -21.26467310 14.84494348
173 7.27292198 -21.26467310
174 83.69691920 7.27292198
175 -34.35283704 83.69691920
176 0.02502941 -34.35283704
177 1.18415961 0.02502941
178 38.02799716 1.18415961
179 -15.68935995 38.02799716
180 -49.27628067 -15.68935995
181 -26.59139152 -49.27628067
182 -30.67866768 -26.59139152
183 -10.79975469 -30.67866768
184 -24.70279973 -10.79975469
185 -28.15968789 -24.70279973
186 -27.68473035 -28.15968789
187 -23.41211373 -27.68473035
188 -23.03576296 -23.41211373
189 -1.02192408 -23.03576296
190 -25.16717239 -1.02192408
191 -11.09365172 -25.16717239
192 -30.43852704 -11.09365172
193 24.48729768 -30.43852704
194 16.92357828 24.48729768
195 -26.74799615 16.92357828
196 13.04196068 -26.74799615
197 2.23819538 13.04196068
198 -27.97920019 2.23819538
199 6.11964184 -27.97920019
200 -4.40801679 6.11964184
201 7.02316876 -4.40801679
202 -8.52043143 7.02316876
203 2.76426153 -8.52043143
204 -13.17074885 2.76426153
205 -3.81518056 -13.17074885
206 -8.22269111 -3.81518056
207 -16.08422843 -8.22269111
208 -12.41013398 -16.08422843
209 19.45887795 -12.41013398
210 -39.28662789 19.45887795
211 -14.94226922 -39.28662789
212 9.39178776 -14.94226922
213 11.18953925 9.39178776
214 -1.06623655 11.18953925
215 35.21286203 -1.06623655
216 -16.77592014 35.21286203
217 -2.77796486 -16.77592014
218 -5.10628037 -2.77796486
219 13.96613261 -5.10628037
220 9.15115350 13.96613261
221 -0.01105898 9.15115350
222 -40.26003556 -0.01105898
223 11.86861189 -40.26003556
224 10.78464785 11.86861189
225 -52.99061601 10.78464785
226 -43.60389363 -52.99061601
227 7.31146988 -43.60389363
228 -31.08524454 7.31146988
229 7.77116027 -31.08524454
230 5.34477366 7.77116027
231 -20.97111421 5.34477366
232 -26.64382642 -20.97111421
233 -6.85380391 -26.64382642
234 -11.99312361 -6.85380391
235 2.65312541 -11.99312361
236 -9.78648659 2.65312541
237 -32.32877803 -9.78648659
238 -12.01620701 -32.32877803
239 -0.24919472 -12.01620701
240 -25.20813721 -0.24919472
241 -12.23317617 -25.20813721
242 -4.61008548 -12.23317617
243 0.58497752 -4.61008548
244 -0.87782055 0.58497752
245 -16.06006778 -0.87782055
246 -34.30933016 -16.06006778
247 3.55370253 -34.30933016
248 -18.21055470 3.55370253
249 -36.73589143 -18.21055470
250 -2.16553477 -36.73589143
251 15.11643801 -2.16553477
252 -29.46961765 15.11643801
253 0.51782081 -29.46961765
254 -9.50892699 0.51782081
255 -34.76337062 -9.50892699
256 -15.18890858 -34.76337062
257 -10.79850939 -15.18890858
258 -4.50704637 -10.79850939
259 -20.00432000 -4.50704637
260 -21.53674334 -20.00432000
261 23.25451993 -21.53674334
262 -26.51742369 23.25451993
263 -16.28468374 -26.51742369
264 8.87519982 -16.28468374
265 -17.12987120 8.87519982
266 8.17916101 -17.12987120
267 -20.57282385 8.17916101
268 12.79561803 -20.57282385
269 -12.33163628 12.79561803
270 -24.68852303 -12.33163628
271 16.90629677 -24.68852303
272 -42.11641096 16.90629677
273 -8.25676476 -42.11641096
274 -21.66337084 -8.25676476
275 -19.62045070 -21.66337084
276 -11.47209663 -19.62045070
277 -27.42825801 -11.47209663
278 -13.14404829 -27.42825801
279 17.26810059 -13.14404829
280 18.15587497 17.26810059
281 -21.51636104 18.15587497
282 -41.48579091 -21.51636104
283 -32.04778584 -41.48579091
284 10.00419572 -32.04778584
285 -18.23003704 10.00419572
286 -14.87649976 -18.23003704
287 3.25502711 -14.87649976
288 -12.42226628 3.25502711
> 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/7jhh81324456697.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/852l91324456697.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9kr8f1324456697.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10e7zb1324456697.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11jexl1324456697.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/12lbff1324456697.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/13c1l31324456697.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/14gkdz1324456697.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/151u771324456697.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/16wthh1324456697.tab")
+ }
>
> try(system("convert tmp/13i6y1324456697.ps tmp/13i6y1324456697.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vmzj1324456697.ps tmp/2vmzj1324456697.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wcfm1324456697.ps tmp/3wcfm1324456697.png",intern=TRUE))
character(0)
> try(system("convert tmp/417du1324456697.ps tmp/417du1324456697.png",intern=TRUE))
character(0)
> try(system("convert tmp/5t1l61324456697.ps tmp/5t1l61324456697.png",intern=TRUE))
character(0)
> try(system("convert tmp/6qeza1324456697.ps tmp/6qeza1324456697.png",intern=TRUE))
character(0)
> try(system("convert tmp/7jhh81324456697.ps tmp/7jhh81324456697.png",intern=TRUE))
character(0)
> try(system("convert tmp/852l91324456697.ps tmp/852l91324456697.png",intern=TRUE))
character(0)
> try(system("convert tmp/9kr8f1324456697.ps tmp/9kr8f1324456697.png",intern=TRUE))
character(0)
> try(system("convert tmp/10e7zb1324456697.ps tmp/10e7zb1324456697.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
8.105 1.015 9.129