R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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> x <- array(list(94
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+ ,dim=c(4
+ ,289)
+ ,dimnames=list(c('Writing'
+ ,'Pageviews'
+ ,'TimeRFC'
+ ,'Reviews')
+ ,1:289))
> y <- array(NA,dim=c(4,289),dimnames=list(c('Writing','Pageviews','TimeRFC','Reviews'),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 = '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
Writing Pageviews TimeRFC Reviews
1 94 1418 210907 30
2 103 869 120982 28
3 93 1530 176508 38
4 103 2172 179321 30
5 51 901 123185 22
6 70 463 52746 26
7 91 3201 385534 25
8 22 371 33170 18
9 38 1192 101645 11
10 93 1583 149061 26
11 60 1439 165446 25
12 123 1764 237213 38
13 148 1495 173326 44
14 90 1373 133131 30
15 124 2187 258873 40
16 70 1491 180083 34
17 168 4041 324799 47
18 115 1706 230964 30
19 71 2152 236785 31
20 66 1036 135473 23
21 134 1882 202925 36
22 117 1929 215147 36
23 108 2242 344297 30
24 84 1220 153935 25
25 156 1289 132943 39
26 120 2515 174724 34
27 114 2147 174415 31
28 94 2352 225548 31
29 120 1638 223632 33
30 81 1222 124817 25
31 110 1812 221698 33
32 133 1677 210767 35
33 122 1579 170266 42
34 158 1731 260561 43
35 109 807 84853 30
36 124 2452 294424 33
37 39 829 101011 13
38 92 1940 215641 32
39 126 2662 325107 36
40 0 186 7176 0
41 70 1499 167542 28
42 37 865 106408 14
43 38 1793 96560 17
44 120 2527 265769 32
45 93 2747 269651 30
46 95 1324 149112 35
47 77 2702 175824 20
48 90 1383 152871 28
49 80 1179 111665 28
50 31 2099 116408 39
51 110 4308 362301 34
52 66 918 78800 26
53 138 1831 183167 39
54 133 3373 277965 39
55 113 1713 150629 33
56 100 1438 168809 28
57 7 496 24188 4
58 140 2253 329267 39
59 61 744 65029 18
60 41 1161 101097 14
61 96 2352 218946 29
62 164 2144 244052 44
63 78 4691 341570 21
64 49 1112 103597 16
65 102 2694 233328 28
66 124 1973 256462 35
67 99 1769 206161 28
68 129 3148 311473 38
69 62 2474 235800 23
70 73 2084 177939 36
71 114 1954 207176 32
72 99 1226 196553 29
73 70 1389 174184 25
74 104 1496 143246 27
75 116 2269 187559 36
76 91 1833 187681 28
77 74 1268 119016 23
78 138 1943 182192 40
79 67 893 73566 23
80 151 1762 194979 40
81 72 1403 167488 28
82 120 1425 143756 34
83 115 1857 275541 33
84 105 1840 243199 28
85 104 1502 182999 34
86 108 1441 135649 30
87 98 1420 152299 33
88 69 1416 120221 22
89 111 2970 346485 38
90 99 1317 145790 26
91 71 1644 193339 35
92 27 870 80953 8
93 69 1654 122774 24
94 107 1054 130585 29
95 73 937 112611 20
96 107 3004 286468 29
97 93 2008 241066 45
98 129 2547 148446 37
99 69 1885 204713 33
100 118 1626 182079 33
101 73 1468 140344 25
102 119 2445 220516 32
103 104 1964 243060 29
104 107 1381 162765 28
105 99 1369 182613 28
106 90 1659 232138 31
107 197 2888 265318 52
108 36 1290 85574 21
109 85 2845 310839 24
110 139 1982 225060 41
111 106 1904 232317 33
112 50 1391 144966 32
113 64 602 43287 19
114 31 1743 155754 20
115 63 1559 164709 31
116 92 2014 201940 31
117 106 2143 235454 32
118 63 2146 220801 18
119 69 874 99466 23
120 41 1590 92661 17
121 56 1590 133328 20
122 25 1210 61361 12
123 65 2072 125930 17
124 93 1281 100750 30
125 114 1401 224549 31
126 38 834 82316 10
127 44 1105 102010 13
128 87 1272 101523 22
129 110 1944 243511 42
130 0 391 22938 1
131 27 761 41566 9
132 83 1605 152474 32
133 30 530 61857 11
134 80 1988 99923 25
135 98 1386 132487 36
136 82 2395 317394 31
137 0 387 21054 0
138 60 1742 209641 24
139 28 620 22648 13
140 9 449 31414 8
141 33 800 46698 13
142 59 1684 131698 19
143 49 1050 91735 18
144 115 2699 244749 33
145 140 1606 184510 40
146 49 1502 79863 22
147 120 1204 128423 38
148 66 1138 97839 24
149 21 568 38214 8
150 124 1459 151101 35
151 152 2158 272458 43
152 139 1111 172494 43
153 38 1421 108043 14
154 144 2833 328107 41
155 120 1955 250579 38
156 160 2922 351067 45
157 114 1002 158015 31
158 39 1060 98866 13
159 78 956 85439 28
160 119 2186 229242 31
161 141 3604 351619 40
162 101 1035 84207 30
163 56 1417 120445 16
164 133 3261 324598 37
165 83 1587 131069 30
166 116 1424 204271 35
167 90 1701 165543 32
168 36 1249 141722 27
169 50 946 116048 20
170 61 1926 250047 18
171 97 3352 299775 31
172 98 1641 195838 31
173 78 2035 173260 21
174 117 2312 254488 39
175 148 1369 104389 41
176 41 1577 136084 13
177 105 2201 199476 32
178 55 961 92499 18
179 132 1900 224330 39
180 44 1254 135781 14
181 21 1335 74408 7
182 50 1597 81240 17
183 0 207 14688 0
184 73 1645 181633 30
185 86 2429 271856 37
186 0 151 7199 0
187 13 474 46660 5
188 4 141 17547 1
189 57 1639 133368 16
190 48 872 95227 32
191 46 1318 152601 24
192 48 1018 98146 17
193 32 1383 79619 11
194 68 1314 59194 24
195 87 1335 139942 22
196 43 1403 118612 12
197 67 910 72880 19
198 46 616 65475 13
199 46 1407 99643 17
200 56 771 71965 15
201 48 766 77272 16
202 44 473 49289 24
203 60 1376 135131 15
204 65 1232 108446 17
205 55 1521 89746 18
206 38 572 44296 20
207 52 1059 77648 16
208 60 1544 181528 16
209 54 1230 134019 18
210 86 1206 124064 22
211 24 1205 92630 8
212 52 1255 121848 17
213 49 613 52915 18
214 61 721 81872 16
215 61 1109 58981 23
216 81 740 53515 22
217 43 1126 60812 13
218 40 728 56375 13
219 40 689 65490 16
220 56 592 80949 16
221 68 995 76302 20
222 79 1613 104011 22
223 47 2048 98104 17
224 57 705 67989 18
225 41 301 30989 17
226 29 1803 135458 12
227 3 799 73504 7
228 60 861 63123 17
229 30 1186 61254 14
230 79 1451 74914 23
231 47 628 31774 17
232 40 1161 81437 14
233 48 1463 87186 15
234 36 742 50090 17
235 42 979 65745 21
236 49 675 56653 18
237 57 1241 158399 18
238 12 676 46455 17
239 40 1049 73624 17
240 43 620 38395 16
241 33 1081 91899 15
242 77 1688 139526 21
243 43 736 52164 16
244 45 617 51567 14
245 47 812 70551 15
246 43 1051 84856 17
247 45 1656 102538 15
248 50 705 86678 15
249 35 945 85709 10
250 7 554 34662 6
251 71 1597 150580 22
252 67 982 99611 21
253 0 222 19349 1
254 62 1212 99373 18
255 54 1143 86230 17
256 4 435 30837 4
257 25 532 31706 10
258 40 882 89806 16
259 38 608 62088 16
260 19 459 40151 9
261 17 578 27634 16
262 67 826 76990 17
263 14 509 37460 7
264 30 717 54157 15
265 54 637 49862 14
266 35 857 84337 14
267 59 830 64175 18
268 24 652 59382 12
269 58 707 119308 16
270 42 954 76702 21
271 46 1461 103425 19
272 61 672 70344 16
273 3 778 43410 1
274 52 1141 104838 16
275 25 680 62215 10
276 40 1090 69304 19
277 32 616 53117 12
278 4 285 19764 2
279 49 1145 86680 14
280 63 733 84105 17
281 67 888 77945 19
282 32 849 89113 14
283 23 1182 91005 11
284 7 528 40248 4
285 54 642 64187 16
286 37 947 50857 20
287 35 819 56613 12
288 51 757 62792 15
289 39 894 72535 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Pageviews TimeRFC Reviews
-6.400e+00 -1.597e-03 9.414e-05 2.896e+00
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-83.145 -6.311 1.796 9.049 39.005
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -6.400e+00 2.294e+00 -2.790 0.005618 **
Pageviews -1.597e-03 2.646e-03 -0.604 0.546523
TimeRFC 9.414e-05 2.708e-05 3.476 0.000588 ***
Reviews 2.896e+00 1.270e-01 22.808 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 14.88 on 285 degrees of freedom
Multiple R-squared: 0.8557, Adjusted R-squared: 0.8542
F-statistic: 563.3 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,] 0.8166382 3.667236e-01 1.833618e-01
[2,] 0.8761036 2.477929e-01 1.238964e-01
[3,] 0.8213928 3.572143e-01 1.786072e-01
[4,] 0.7923519 4.152963e-01 2.076481e-01
[5,] 0.7767772 4.464455e-01 2.232228e-01
[6,] 0.7115711 5.768578e-01 2.884289e-01
[7,] 0.6795391 6.409218e-01 3.204609e-01
[8,] 0.5915861 8.168279e-01 4.084139e-01
[9,] 0.5228765 9.542469e-01 4.771235e-01
[10,] 0.7819222 4.361556e-01 2.180778e-01
[11,] 0.7257561 5.484878e-01 2.742439e-01
[12,] 0.7879901 4.240199e-01 2.120099e-01
[13,] 0.8869372 2.261256e-01 1.130628e-01
[14,] 0.8506569 2.986861e-01 1.493431e-01
[15,] 0.8817142 2.365716e-01 1.182858e-01
[16,] 0.8467365 3.065271e-01 1.532635e-01
[17,] 0.8129725 3.740549e-01 1.870275e-01
[18,] 0.7888142 4.223715e-01 2.111858e-01
[19,] 0.9310774 1.378452e-01 6.892259e-02
[20,] 0.9149011 1.701977e-01 8.509887e-02
[21,] 0.9060643 1.878714e-01 9.393569e-02
[22,] 0.8890368 2.219264e-01 1.109632e-01
[23,] 0.8849126 2.301749e-01 1.150874e-01
[24,] 0.8600295 2.799409e-01 1.399705e-01
[25,] 0.8276422 3.447156e-01 1.723578e-01
[26,] 0.8472915 3.054170e-01 1.527085e-01
[27,] 0.8396960 3.206080e-01 1.603040e-01
[28,] 0.8387910 3.224180e-01 1.612090e-01
[29,] 0.8573710 2.852580e-01 1.426290e-01
[30,] 0.8410544 3.178912e-01 1.589456e-01
[31,] 0.8144737 3.710526e-01 1.855263e-01
[32,] 0.8058320 3.883360e-01 1.941680e-01
[33,] 0.7692499 4.615002e-01 2.307501e-01
[34,] 0.7634139 4.731722e-01 2.365861e-01
[35,] 0.7828848 4.342304e-01 2.171152e-01
[36,] 0.7465268 5.069464e-01 2.534732e-01
[37,] 0.7312302 5.375395e-01 2.687698e-01
[38,] 0.7139585 5.720831e-01 2.860415e-01
[39,] 0.6884290 6.231420e-01 3.115710e-01
[40,] 0.6874875 6.250249e-01 3.125125e-01
[41,] 0.6700500 6.598999e-01 3.299500e-01
[42,] 0.6283163 7.433674e-01 3.716837e-01
[43,] 0.5884163 8.231674e-01 4.115837e-01
[44,] 0.9994418 1.116318e-03 5.581590e-04
[45,] 0.9992662 1.467565e-03 7.337824e-04
[46,] 0.9990100 1.980061e-03 9.900303e-04
[47,] 0.9990813 1.837370e-03 9.186849e-04
[48,] 0.9987811 2.437712e-03 1.218856e-03
[49,] 0.9986584 2.683257e-03 1.341629e-03
[50,] 0.9984293 3.141476e-03 1.570738e-03
[51,] 0.9978771 4.245859e-03 2.122929e-03
[52,] 0.9971643 5.671368e-03 2.835684e-03
[53,] 0.9967600 6.479953e-03 3.239976e-03
[54,] 0.9956260 8.747946e-03 4.373973e-03
[55,] 0.9941733 1.165334e-02 5.826668e-03
[56,] 0.9955202 8.959629e-03 4.479815e-03
[57,] 0.9941036 1.179287e-02 5.896437e-03
[58,] 0.9922716 1.545673e-02 7.728366e-03
[59,] 0.9909142 1.817152e-02 9.085758e-03
[60,] 0.9887322 2.253552e-02 1.126776e-02
[61,] 0.9861986 2.760287e-02 1.380144e-02
[62,] 0.9824241 3.515171e-02 1.757585e-02
[63,] 0.9828488 3.430233e-02 1.715116e-02
[64,] 0.9950855 9.829046e-03 4.914523e-03
[65,] 0.9943619 1.127618e-02 5.638092e-03
[66,] 0.9928043 1.439142e-02 7.195709e-03
[67,] 0.9917270 1.654594e-02 8.272968e-03
[68,] 0.9935745 1.285100e-02 6.425502e-03
[69,] 0.9918676 1.626487e-02 8.132433e-03
[70,] 0.9895533 2.089344e-02 1.044672e-02
[71,] 0.9870459 2.590823e-02 1.295411e-02
[72,] 0.9865977 2.680457e-02 1.340229e-02
[73,] 0.9831439 3.371222e-02 1.685611e-02
[74,] 0.9885517 2.289669e-02 1.144834e-02
[75,] 0.9890098 2.198047e-02 1.099024e-02
[76,] 0.9893731 2.125384e-02 1.062692e-02
[77,] 0.9868151 2.636985e-02 1.318493e-02
[78,] 0.9849346 3.013075e-02 1.506537e-02
[79,] 0.9814816 3.703687e-02 1.851844e-02
[80,] 0.9825345 3.493095e-02 1.746547e-02
[81,] 0.9785611 4.287789e-02 2.143895e-02
[82,] 0.9737508 5.249847e-02 2.624924e-02
[83,] 0.9791051 4.178985e-02 2.089493e-02
[84,] 0.9811611 3.767781e-02 1.883890e-02
[85,] 0.9953567 9.286687e-03 4.643343e-03
[86,] 0.9941542 1.169167e-02 5.845835e-03
[87,] 0.9925570 1.488610e-02 7.443049e-03
[88,] 0.9934480 1.310395e-02 6.551975e-03
[89,] 0.9929063 1.418741e-02 7.093703e-03
[90,] 0.9914467 1.710653e-02 8.553267e-03
[91,] 0.9994347 1.130617e-03 5.653083e-04
[92,] 0.9995114 9.771970e-04 4.885985e-04
[93,] 0.9998936 2.128628e-04 1.064314e-04
[94,] 0.9998893 2.214200e-04 1.107100e-04
[95,] 0.9998482 3.035856e-04 1.517928e-04
[96,] 0.9998522 2.955709e-04 1.477855e-04
[97,] 0.9998078 3.843518e-04 1.921759e-04
[98,] 0.9998433 3.134073e-04 1.567037e-04
[99,] 0.9998096 3.807361e-04 1.903681e-04
[100,] 0.9997874 4.252985e-04 2.126492e-04
[101,] 0.9999403 1.193535e-04 5.967677e-05
[102,] 0.9999661 6.785903e-05 3.392952e-05
[103,] 0.9999519 9.625866e-05 4.812933e-05
[104,] 0.9999409 1.182309e-04 5.911545e-05
[105,] 0.9999172 1.655319e-04 8.276594e-05
[106,] 0.9999970 5.928290e-06 2.964145e-06
[107,] 0.9999967 6.640240e-06 3.320120e-06
[108,] 0.9999993 1.472319e-06 7.361593e-07
[109,] 0.9999999 2.583943e-07 1.291972e-07
[110,] 0.9999998 3.682633e-07 1.841317e-07
[111,] 0.9999997 5.722897e-07 2.861449e-07
[112,] 0.9999996 8.860041e-07 4.430021e-07
[113,] 0.9999993 1.357533e-06 6.787665e-07
[114,] 0.9999991 1.828489e-06 9.142443e-07
[115,] 0.9999987 2.633659e-06 1.316830e-06
[116,] 0.9999982 3.597866e-06 1.798933e-06
[117,] 0.9999981 3.802337e-06 1.901168e-06
[118,] 0.9999973 5.404051e-06 2.702026e-06
[119,] 0.9999971 5.895376e-06 2.947688e-06
[120,] 0.9999963 7.392484e-06 3.696242e-06
[121,] 0.9999948 1.041031e-05 5.205154e-06
[122,] 0.9999969 6.118035e-06 3.059017e-06
[123,] 0.9999985 3.003973e-06 1.501987e-06
[124,] 0.9999978 4.490988e-06 2.245494e-06
[125,] 0.9999968 6.465821e-06 3.232911e-06
[126,] 0.9999968 6.343012e-06 3.171506e-06
[127,] 0.9999953 9.438976e-06 4.719488e-06
[128,] 0.9999937 1.267977e-05 6.339884e-06
[129,] 0.9999922 1.554570e-05 7.772851e-06
[130,] 0.9999972 5.635455e-06 2.817728e-06
[131,] 0.9999960 8.016447e-06 4.008223e-06
[132,] 0.9999974 5.259591e-06 2.629795e-06
[133,] 0.9999962 7.613943e-06 3.806971e-06
[134,] 0.9999953 9.401024e-06 4.700512e-06
[135,] 0.9999931 1.387939e-05 6.939694e-06
[136,] 0.9999898 2.038749e-05 1.019375e-05
[137,] 0.9999855 2.903083e-05 1.451542e-05
[138,] 0.9999805 3.904483e-05 1.952241e-05
[139,] 0.9999819 3.626434e-05 1.813217e-05
[140,] 0.9999808 3.846726e-05 1.923363e-05
[141,] 0.9999744 5.118033e-05 2.559016e-05
[142,] 0.9999644 7.128629e-05 3.564315e-05
[143,] 0.9999494 1.012933e-04 5.064665e-05
[144,] 0.9999578 8.439203e-05 4.219602e-05
[145,] 0.9999535 9.292089e-05 4.646044e-05
[146,] 0.9999425 1.150258e-04 5.751288e-05
[147,] 0.9999216 1.567018e-04 7.835091e-05
[148,] 0.9998958 2.083975e-04 1.041988e-04
[149,] 0.9998563 2.873958e-04 1.436979e-04
[150,] 0.9998257 3.486702e-04 1.743351e-04
[151,] 0.9998750 2.500690e-04 1.250345e-04
[152,] 0.9998256 3.488347e-04 1.744174e-04
[153,] 0.9997598 4.803783e-04 2.401891e-04
[154,] 0.9998144 3.711124e-04 1.855562e-04
[155,] 0.9997583 4.834931e-04 2.417466e-04
[156,] 0.9997876 4.248305e-04 2.124152e-04
[157,] 0.9997271 5.458482e-04 2.729241e-04
[158,] 0.9996790 6.419613e-04 3.209807e-04
[159,] 0.9995784 8.431151e-04 4.215575e-04
[160,] 0.9995141 9.717668e-04 4.858834e-04
[161,] 0.9993774 1.245230e-03 6.226148e-04
[162,] 0.9999701 5.989004e-05 2.994502e-05
[163,] 0.9999634 7.312557e-05 3.656278e-05
[164,] 0.9999488 1.024060e-04 5.120302e-05
[165,] 0.9999365 1.270349e-04 6.351747e-05
[166,] 0.9999098 1.804047e-04 9.020235e-05
[167,] 0.9998942 2.116631e-04 1.058316e-04
[168,] 0.9998629 2.742263e-04 1.371132e-04
[169,] 0.9999782 4.368027e-05 2.184013e-05
[170,] 0.9999688 6.249595e-05 3.124798e-05
[171,] 0.9999584 8.313357e-05 4.156678e-05
[172,] 0.9999409 1.182516e-04 5.912578e-05
[173,] 0.9999465 1.069989e-04 5.349946e-05
[174,] 0.9999234 1.532869e-04 7.664345e-05
[175,] 0.9998932 2.135564e-04 1.067782e-04
[176,] 0.9998485 3.030627e-04 1.515314e-04
[177,] 0.9997915 4.170890e-04 2.085445e-04
[178,] 0.9998303 3.394564e-04 1.697282e-04
[179,] 0.9999804 3.912051e-05 1.956026e-05
[180,] 0.9999724 5.519997e-05 2.759999e-05
[181,] 0.9999594 8.117293e-05 4.058647e-05
[182,] 0.9999434 1.132021e-04 5.660103e-05
[183,] 0.9999204 1.592101e-04 7.960506e-05
[184,] 0.9999986 2.808110e-06 1.404055e-06
[185,] 0.9999999 1.221308e-07 6.106541e-08
[186,] 0.9999999 1.883474e-07 9.417371e-08
[187,] 0.9999998 3.122770e-07 1.561385e-07
[188,] 0.9999998 4.917234e-07 2.458617e-07
[189,] 0.9999998 4.764092e-07 2.382046e-07
[190,] 0.9999996 7.678260e-07 3.839130e-07
[191,] 0.9999996 7.659432e-07 3.829716e-07
[192,] 0.9999995 9.854916e-07 4.927458e-07
[193,] 0.9999993 1.494902e-06 7.474509e-07
[194,] 0.9999993 1.477629e-06 7.388143e-07
[195,] 0.9999988 2.409241e-06 1.204620e-06
[196,] 0.9999996 8.320033e-07 4.160017e-07
[197,] 0.9999994 1.108020e-06 5.540100e-07
[198,] 0.9999994 1.193230e-06 5.966150e-07
[199,] 0.9999991 1.885787e-06 9.428934e-07
[200,] 0.9999994 1.294261e-06 6.471304e-07
[201,] 0.9999991 1.893262e-06 9.466312e-07
[202,] 0.9999985 3.051485e-06 1.525742e-06
[203,] 0.9999979 4.216965e-06 2.108482e-06
[204,] 0.9999982 3.585091e-06 1.792546e-06
[205,] 0.9999971 5.892100e-06 2.946050e-06
[206,] 0.9999954 9.262357e-06 4.631178e-06
[207,] 0.9999925 1.496516e-05 7.482581e-06
[208,] 0.9999924 1.515804e-05 7.579018e-06
[209,] 0.9999879 2.411546e-05 1.205773e-05
[210,] 0.9999944 1.117139e-05 5.585694e-06
[211,] 0.9999934 1.317250e-05 6.586248e-06
[212,] 0.9999903 1.940238e-05 9.701191e-06
[213,] 0.9999855 2.909609e-05 1.454805e-05
[214,] 0.9999800 3.994304e-05 1.997152e-05
[215,] 0.9999781 4.372883e-05 2.186442e-05
[216,] 0.9999833 3.331649e-05 1.665824e-05
[217,] 0.9999745 5.109734e-05 2.554867e-05
[218,] 0.9999634 7.324910e-05 3.662455e-05
[219,] 0.9999428 1.144924e-04 5.724618e-05
[220,] 0.9999353 1.293490e-04 6.467450e-05
[221,] 0.9999621 7.587840e-05 3.793920e-05
[222,] 0.9999693 6.132807e-05 3.066404e-05
[223,] 0.9999537 9.258896e-05 4.629448e-05
[224,] 0.9999833 3.341773e-05 1.670886e-05
[225,] 0.9999803 3.935876e-05 1.967938e-05
[226,] 0.9999674 6.513882e-05 3.256941e-05
[227,] 0.9999607 7.852801e-05 3.926400e-05
[228,] 0.9999409 1.182179e-04 5.910896e-05
[229,] 0.9999349 1.302837e-04 6.514187e-05
[230,] 0.9998950 2.099461e-04 1.049731e-04
[231,] 0.9999215 1.570983e-04 7.854913e-05
[232,] 0.9999951 9.785368e-06 4.892684e-06
[233,] 0.9999921 1.579953e-05 7.899765e-06
[234,] 0.9999875 2.508521e-05 1.254261e-05
[235,] 0.9999887 2.261747e-05 1.130873e-05
[236,] 0.9999868 2.630469e-05 1.315234e-05
[237,] 0.9999771 4.585021e-05 2.292511e-05
[238,] 0.9999693 6.146345e-05 3.073172e-05
[239,] 0.9999502 9.961989e-05 4.980994e-05
[240,] 0.9999218 1.564427e-04 7.822133e-05
[241,] 0.9998881 2.237163e-04 1.118582e-04
[242,] 0.9998082 3.835659e-04 1.917829e-04
[243,] 0.9996843 6.313731e-04 3.156865e-04
[244,] 0.9995034 9.932215e-04 4.966107e-04
[245,] 0.9991913 1.617344e-03 8.086719e-04
[246,] 0.9986939 2.612242e-03 1.306121e-03
[247,] 0.9978914 4.217197e-03 2.108599e-03
[248,] 0.9975286 4.942714e-03 2.471357e-03
[249,] 0.9968867 6.226571e-03 3.113286e-03
[250,] 0.9953051 9.389742e-03 4.694871e-03
[251,] 0.9929118 1.417644e-02 7.088219e-03
[252,] 0.9917121 1.657581e-02 8.287904e-03
[253,] 0.9896699 2.066022e-02 1.033011e-02
[254,] 0.9854168 2.916637e-02 1.458319e-02
[255,] 0.9931528 1.369442e-02 6.847208e-03
[256,] 0.9956730 8.653923e-03 4.326961e-03
[257,] 0.9933613 1.327738e-02 6.638689e-03
[258,] 0.9928698 1.426031e-02 7.130156e-03
[259,] 0.9947981 1.040376e-02 5.201881e-03
[260,] 0.9930180 1.396405e-02 6.982027e-03
[261,] 0.9925070 1.498604e-02 7.493020e-03
[262,] 0.9922605 1.547900e-02 7.739498e-03
[263,] 0.9913342 1.733158e-02 8.665788e-03
[264,] 0.9951928 9.614450e-03 4.807225e-03
[265,] 0.9909704 1.805917e-02 9.029583e-03
[266,] 0.9888428 2.231435e-02 1.115718e-02
[267,] 0.9865887 2.682258e-02 1.341129e-02
[268,] 0.9754281 4.914385e-02 2.457192e-02
[269,] 0.9609475 7.810508e-02 3.905254e-02
[270,] 0.9395324 1.209353e-01 6.046765e-02
[271,] 0.9008893 1.982215e-01 9.911074e-02
[272,] 0.8376020 3.247960e-01 1.623980e-01
[273,] 0.8780884 2.438231e-01 1.219116e-01
[274,] 0.7966258 4.067483e-01 2.033742e-01
[275,] 0.8072468 3.855064e-01 1.927532e-01
[276,] 0.8652661 2.694679e-01 1.347339e-01
> postscript(file="/var/www/rcomp/tmp/10ywl1324573861.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/20in81324573861.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/382iu1324573861.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4i7mh1324573861.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5qbj61324573861.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 6
-4.06553933 18.31446600 -24.81560109 9.11232356 -16.46641982 -3.11881700
7 8 9 10 11 12
-6.17655931 -26.25579802 4.88099313 12.60357985 -19.27297945 -0.15634501
13 14 15 16 17 18
13.05265186 -0.81587722 -6.31141182 -36.63085325 14.17294317 15.50643222
19 20 21 22 23 24
-31.22497169 -5.30340846 20.05169259 1.97623825 -1.30609030 5.46078358
25 26 27 28 29 30
39.00456766 15.50940604 17.63832390 -6.84767295 12.40032443 5.20504008
31 32 33 34 35 36
2.86033936 20.88189585 -6.73331291 18.11356242 21.82468312 11.03654492
37 38 39 40 41 42
-0.43098939 -11.46910768 1.79593405 6.02178946 -18.06213170 -5.77743155
43 44 45 46 47 48
-11.05563806 12.74972610 -8.47248067 -11.87802656 13.24712748 3.13363886
49 50 51 52 53 54
-3.31325817 -83.14495847 -9.28418688 -8.84460786 17.14247937 5.68180242
55 56 57 58 59 60
12.39236713 11.72115348 0.33196436 6.06328316 10.34095932 -0.80463007
61 62 63 64 65 66
1.56560785 23.43150708 -1.07417259 1.08996158 9.65396143 8.05317976
67 68 69 70 71 72
7.73372732 1.06395380 -16.45069935 -38.27353341 11.35012056 4.87488066
73 74 75 76 77 78
-10.17541489 21.11610859 4.11640226 1.57560309 4.61640012 14.51727964
79 80 81 82 83 84
1.29585473 26.02442103 -16.21040297 16.68340585 2.86364200 10.36052451
85 86 87 88 89 90
-2.88778290 17.05571370 -3.23289165 2.63528394 -20.51629238 18.48657966
91 92 93 94 95 96
-39.53021187 4.00217421 -3.01664719 18.81010560 12.37827847 7.25086820
97 98 99 100 101 102
-50.40055062 18.34654954 -36.42414169 14.29280196 -3.86364346 15.87868697
103 104 105 106 107 108
6.67579614 19.19905914 9.31147196 -12.57506009 32.45093122 -24.40855625
109 110 111 112 113 114
-2.81783995 8.64824744 -1.99232946 -47.69301944 12.26493794 -32.39550525
115 116 117 118 119 120
-33.38728599 -7.16523860 0.99005039 -0.08322829 0.82737238 -8.01288166
121 122 123 124 125 126
-5.52881288 -7.19396140 13.62526486 5.08538638 11.72719995 9.02456564
127 128 129 130 131 132
4.91586297 22.16541307 -25.04526121 1.96959229 4.63990400 -15.05794197
133 134 135 136 137 138
-0.43101859 7.77211199 -10.10986495 -27.42502809 5.03645174 -20.05341256
139 140 141 142 143 144
-4.38805008 -10.00693016 -1.36448886 0.67068546 -3.68422759 7.10733572
145 146 147 148 149 150
15.76073299 -13.42818192 6.19017750 -4.49363896 1.54303865 17.15039123
151 152 153 154 155 156
11.67573113 6.41345115 -4.04316556 5.30720608 -4.10945937 7.70442296
157 158 159 160 161 162
17.35308625 0.13994261 -3.20066884 17.53941174 4.22139847 14.24971243
163 164 165 166 167 168
6.99117315 6.90482205 -7.27991508 4.08925210 -9.13485502 -47.13499633
169 170 171 172 173 174
-10.93089109 -5.18777705 -9.23768616 -1.18666535 10.52710146 -9.80304713
175 176 177 178 179 180
28.02853914 -0.53774469 3.46953897 2.10167973 7.37776932 -0.92109220
181 182 183 184 185 186
2.25700435 2.07343146 5.34818368 -21.94717265 -36.45931316 5.96371378
187 188 189 190 191 192
1.28549263 6.07772023 7.12928196 -45.83984606 -29.36119266 -2.44295742
193 194 195 196 197 198
1.25955172 1.42540961 18.64942844 5.72494636 12.97117433 9.57398360
199 200 201 202 203 204
-3.96247377 13.41884989 2.01538479 -22.98562051 12.43908821 13.92929142
205 206 207 208 209 210
3.25540572 -16.77386532 6.44804063 5.44391919 -2.37714818 18.93805478
211 212 213 214 215 216
0.43808806 -0.29558244 -0.72793837 14.51047269 -2.98611900 19.83486970
217 218 219 220 221 222
7.82763776 4.60953792 -4.99850418 9.39129024 10.88892618 14.47593031
223 224 225 226 227 228
-1.79363632 6.00001547 -4.26641139 -9.22189661 -16.51412642 12.60318050
229 230 231 232 233 234
-8.01402023 14.06033274 2.18205580 0.04609014 5.09143211 -10.36003657
235 236 237 238 239 240
-17.03873209 -0.98077843 -1.65461998 -34.12328232 -8.08502560 0.44189600
241 242 243 244 245 246
-10.96245603 12.14838329 -0.66896360 6.98893271 4.61745386 -6.13916996
247 248 249 250 251 252
0.95455790 5.92839078 5.88247737 -6.35316056 2.06653652 4.77803934
253 254 255 256 257 258
2.03747953 8.85554507 4.87845158 -3.39139218 0.30637713 -6.97921645
259 260 261 262 263 264
-6.80764536 -3.70932120 -24.61219562 18.24188149 -2.58433537 -10.99103235
265 266 267 268 269 270
16.18138404 -5.71252820 8.55873193 -8.89903938 7.96402088 -18.11011994
271 272 273 274 275 276
-10.02402815 15.51740153 3.66064422 4.01946427 -2.32920640 -13.40465423
277 278 279 280 281 282
-0.36678327 3.20315555 8.52697427 13.42353922 12.45923006 -9.17490286
283 284 285 286 287 288
-9.13337077 -1.12874687 9.04907558 -17.79245226 2.62839727 9.25999821
289
-6.33421859
> postscript(file="/var/www/rcomp/tmp/6kr511324573861.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 -4.06553933 NA
1 18.31446600 -4.06553933
2 -24.81560109 18.31446600
3 9.11232356 -24.81560109
4 -16.46641982 9.11232356
5 -3.11881700 -16.46641982
6 -6.17655931 -3.11881700
7 -26.25579802 -6.17655931
8 4.88099313 -26.25579802
9 12.60357985 4.88099313
10 -19.27297945 12.60357985
11 -0.15634501 -19.27297945
12 13.05265186 -0.15634501
13 -0.81587722 13.05265186
14 -6.31141182 -0.81587722
15 -36.63085325 -6.31141182
16 14.17294317 -36.63085325
17 15.50643222 14.17294317
18 -31.22497169 15.50643222
19 -5.30340846 -31.22497169
20 20.05169259 -5.30340846
21 1.97623825 20.05169259
22 -1.30609030 1.97623825
23 5.46078358 -1.30609030
24 39.00456766 5.46078358
25 15.50940604 39.00456766
26 17.63832390 15.50940604
27 -6.84767295 17.63832390
28 12.40032443 -6.84767295
29 5.20504008 12.40032443
30 2.86033936 5.20504008
31 20.88189585 2.86033936
32 -6.73331291 20.88189585
33 18.11356242 -6.73331291
34 21.82468312 18.11356242
35 11.03654492 21.82468312
36 -0.43098939 11.03654492
37 -11.46910768 -0.43098939
38 1.79593405 -11.46910768
39 6.02178946 1.79593405
40 -18.06213170 6.02178946
41 -5.77743155 -18.06213170
42 -11.05563806 -5.77743155
43 12.74972610 -11.05563806
44 -8.47248067 12.74972610
45 -11.87802656 -8.47248067
46 13.24712748 -11.87802656
47 3.13363886 13.24712748
48 -3.31325817 3.13363886
49 -83.14495847 -3.31325817
50 -9.28418688 -83.14495847
51 -8.84460786 -9.28418688
52 17.14247937 -8.84460786
53 5.68180242 17.14247937
54 12.39236713 5.68180242
55 11.72115348 12.39236713
56 0.33196436 11.72115348
57 6.06328316 0.33196436
58 10.34095932 6.06328316
59 -0.80463007 10.34095932
60 1.56560785 -0.80463007
61 23.43150708 1.56560785
62 -1.07417259 23.43150708
63 1.08996158 -1.07417259
64 9.65396143 1.08996158
65 8.05317976 9.65396143
66 7.73372732 8.05317976
67 1.06395380 7.73372732
68 -16.45069935 1.06395380
69 -38.27353341 -16.45069935
70 11.35012056 -38.27353341
71 4.87488066 11.35012056
72 -10.17541489 4.87488066
73 21.11610859 -10.17541489
74 4.11640226 21.11610859
75 1.57560309 4.11640226
76 4.61640012 1.57560309
77 14.51727964 4.61640012
78 1.29585473 14.51727964
79 26.02442103 1.29585473
80 -16.21040297 26.02442103
81 16.68340585 -16.21040297
82 2.86364200 16.68340585
83 10.36052451 2.86364200
84 -2.88778290 10.36052451
85 17.05571370 -2.88778290
86 -3.23289165 17.05571370
87 2.63528394 -3.23289165
88 -20.51629238 2.63528394
89 18.48657966 -20.51629238
90 -39.53021187 18.48657966
91 4.00217421 -39.53021187
92 -3.01664719 4.00217421
93 18.81010560 -3.01664719
94 12.37827847 18.81010560
95 7.25086820 12.37827847
96 -50.40055062 7.25086820
97 18.34654954 -50.40055062
98 -36.42414169 18.34654954
99 14.29280196 -36.42414169
100 -3.86364346 14.29280196
101 15.87868697 -3.86364346
102 6.67579614 15.87868697
103 19.19905914 6.67579614
104 9.31147196 19.19905914
105 -12.57506009 9.31147196
106 32.45093122 -12.57506009
107 -24.40855625 32.45093122
108 -2.81783995 -24.40855625
109 8.64824744 -2.81783995
110 -1.99232946 8.64824744
111 -47.69301944 -1.99232946
112 12.26493794 -47.69301944
113 -32.39550525 12.26493794
114 -33.38728599 -32.39550525
115 -7.16523860 -33.38728599
116 0.99005039 -7.16523860
117 -0.08322829 0.99005039
118 0.82737238 -0.08322829
119 -8.01288166 0.82737238
120 -5.52881288 -8.01288166
121 -7.19396140 -5.52881288
122 13.62526486 -7.19396140
123 5.08538638 13.62526486
124 11.72719995 5.08538638
125 9.02456564 11.72719995
126 4.91586297 9.02456564
127 22.16541307 4.91586297
128 -25.04526121 22.16541307
129 1.96959229 -25.04526121
130 4.63990400 1.96959229
131 -15.05794197 4.63990400
132 -0.43101859 -15.05794197
133 7.77211199 -0.43101859
134 -10.10986495 7.77211199
135 -27.42502809 -10.10986495
136 5.03645174 -27.42502809
137 -20.05341256 5.03645174
138 -4.38805008 -20.05341256
139 -10.00693016 -4.38805008
140 -1.36448886 -10.00693016
141 0.67068546 -1.36448886
142 -3.68422759 0.67068546
143 7.10733572 -3.68422759
144 15.76073299 7.10733572
145 -13.42818192 15.76073299
146 6.19017750 -13.42818192
147 -4.49363896 6.19017750
148 1.54303865 -4.49363896
149 17.15039123 1.54303865
150 11.67573113 17.15039123
151 6.41345115 11.67573113
152 -4.04316556 6.41345115
153 5.30720608 -4.04316556
154 -4.10945937 5.30720608
155 7.70442296 -4.10945937
156 17.35308625 7.70442296
157 0.13994261 17.35308625
158 -3.20066884 0.13994261
159 17.53941174 -3.20066884
160 4.22139847 17.53941174
161 14.24971243 4.22139847
162 6.99117315 14.24971243
163 6.90482205 6.99117315
164 -7.27991508 6.90482205
165 4.08925210 -7.27991508
166 -9.13485502 4.08925210
167 -47.13499633 -9.13485502
168 -10.93089109 -47.13499633
169 -5.18777705 -10.93089109
170 -9.23768616 -5.18777705
171 -1.18666535 -9.23768616
172 10.52710146 -1.18666535
173 -9.80304713 10.52710146
174 28.02853914 -9.80304713
175 -0.53774469 28.02853914
176 3.46953897 -0.53774469
177 2.10167973 3.46953897
178 7.37776932 2.10167973
179 -0.92109220 7.37776932
180 2.25700435 -0.92109220
181 2.07343146 2.25700435
182 5.34818368 2.07343146
183 -21.94717265 5.34818368
184 -36.45931316 -21.94717265
185 5.96371378 -36.45931316
186 1.28549263 5.96371378
187 6.07772023 1.28549263
188 7.12928196 6.07772023
189 -45.83984606 7.12928196
190 -29.36119266 -45.83984606
191 -2.44295742 -29.36119266
192 1.25955172 -2.44295742
193 1.42540961 1.25955172
194 18.64942844 1.42540961
195 5.72494636 18.64942844
196 12.97117433 5.72494636
197 9.57398360 12.97117433
198 -3.96247377 9.57398360
199 13.41884989 -3.96247377
200 2.01538479 13.41884989
201 -22.98562051 2.01538479
202 12.43908821 -22.98562051
203 13.92929142 12.43908821
204 3.25540572 13.92929142
205 -16.77386532 3.25540572
206 6.44804063 -16.77386532
207 5.44391919 6.44804063
208 -2.37714818 5.44391919
209 18.93805478 -2.37714818
210 0.43808806 18.93805478
211 -0.29558244 0.43808806
212 -0.72793837 -0.29558244
213 14.51047269 -0.72793837
214 -2.98611900 14.51047269
215 19.83486970 -2.98611900
216 7.82763776 19.83486970
217 4.60953792 7.82763776
218 -4.99850418 4.60953792
219 9.39129024 -4.99850418
220 10.88892618 9.39129024
221 14.47593031 10.88892618
222 -1.79363632 14.47593031
223 6.00001547 -1.79363632
224 -4.26641139 6.00001547
225 -9.22189661 -4.26641139
226 -16.51412642 -9.22189661
227 12.60318050 -16.51412642
228 -8.01402023 12.60318050
229 14.06033274 -8.01402023
230 2.18205580 14.06033274
231 0.04609014 2.18205580
232 5.09143211 0.04609014
233 -10.36003657 5.09143211
234 -17.03873209 -10.36003657
235 -0.98077843 -17.03873209
236 -1.65461998 -0.98077843
237 -34.12328232 -1.65461998
238 -8.08502560 -34.12328232
239 0.44189600 -8.08502560
240 -10.96245603 0.44189600
241 12.14838329 -10.96245603
242 -0.66896360 12.14838329
243 6.98893271 -0.66896360
244 4.61745386 6.98893271
245 -6.13916996 4.61745386
246 0.95455790 -6.13916996
247 5.92839078 0.95455790
248 5.88247737 5.92839078
249 -6.35316056 5.88247737
250 2.06653652 -6.35316056
251 4.77803934 2.06653652
252 2.03747953 4.77803934
253 8.85554507 2.03747953
254 4.87845158 8.85554507
255 -3.39139218 4.87845158
256 0.30637713 -3.39139218
257 -6.97921645 0.30637713
258 -6.80764536 -6.97921645
259 -3.70932120 -6.80764536
260 -24.61219562 -3.70932120
261 18.24188149 -24.61219562
262 -2.58433537 18.24188149
263 -10.99103235 -2.58433537
264 16.18138404 -10.99103235
265 -5.71252820 16.18138404
266 8.55873193 -5.71252820
267 -8.89903938 8.55873193
268 7.96402088 -8.89903938
269 -18.11011994 7.96402088
270 -10.02402815 -18.11011994
271 15.51740153 -10.02402815
272 3.66064422 15.51740153
273 4.01946427 3.66064422
274 -2.32920640 4.01946427
275 -13.40465423 -2.32920640
276 -0.36678327 -13.40465423
277 3.20315555 -0.36678327
278 8.52697427 3.20315555
279 13.42353922 8.52697427
280 12.45923006 13.42353922
281 -9.17490286 12.45923006
282 -9.13337077 -9.17490286
283 -1.12874687 -9.13337077
284 9.04907558 -1.12874687
285 -17.79245226 9.04907558
286 2.62839727 -17.79245226
287 9.25999821 2.62839727
288 -6.33421859 9.25999821
289 NA -6.33421859
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 18.31446600 -4.06553933
[2,] -24.81560109 18.31446600
[3,] 9.11232356 -24.81560109
[4,] -16.46641982 9.11232356
[5,] -3.11881700 -16.46641982
[6,] -6.17655931 -3.11881700
[7,] -26.25579802 -6.17655931
[8,] 4.88099313 -26.25579802
[9,] 12.60357985 4.88099313
[10,] -19.27297945 12.60357985
[11,] -0.15634501 -19.27297945
[12,] 13.05265186 -0.15634501
[13,] -0.81587722 13.05265186
[14,] -6.31141182 -0.81587722
[15,] -36.63085325 -6.31141182
[16,] 14.17294317 -36.63085325
[17,] 15.50643222 14.17294317
[18,] -31.22497169 15.50643222
[19,] -5.30340846 -31.22497169
[20,] 20.05169259 -5.30340846
[21,] 1.97623825 20.05169259
[22,] -1.30609030 1.97623825
[23,] 5.46078358 -1.30609030
[24,] 39.00456766 5.46078358
[25,] 15.50940604 39.00456766
[26,] 17.63832390 15.50940604
[27,] -6.84767295 17.63832390
[28,] 12.40032443 -6.84767295
[29,] 5.20504008 12.40032443
[30,] 2.86033936 5.20504008
[31,] 20.88189585 2.86033936
[32,] -6.73331291 20.88189585
[33,] 18.11356242 -6.73331291
[34,] 21.82468312 18.11356242
[35,] 11.03654492 21.82468312
[36,] -0.43098939 11.03654492
[37,] -11.46910768 -0.43098939
[38,] 1.79593405 -11.46910768
[39,] 6.02178946 1.79593405
[40,] -18.06213170 6.02178946
[41,] -5.77743155 -18.06213170
[42,] -11.05563806 -5.77743155
[43,] 12.74972610 -11.05563806
[44,] -8.47248067 12.74972610
[45,] -11.87802656 -8.47248067
[46,] 13.24712748 -11.87802656
[47,] 3.13363886 13.24712748
[48,] -3.31325817 3.13363886
[49,] -83.14495847 -3.31325817
[50,] -9.28418688 -83.14495847
[51,] -8.84460786 -9.28418688
[52,] 17.14247937 -8.84460786
[53,] 5.68180242 17.14247937
[54,] 12.39236713 5.68180242
[55,] 11.72115348 12.39236713
[56,] 0.33196436 11.72115348
[57,] 6.06328316 0.33196436
[58,] 10.34095932 6.06328316
[59,] -0.80463007 10.34095932
[60,] 1.56560785 -0.80463007
[61,] 23.43150708 1.56560785
[62,] -1.07417259 23.43150708
[63,] 1.08996158 -1.07417259
[64,] 9.65396143 1.08996158
[65,] 8.05317976 9.65396143
[66,] 7.73372732 8.05317976
[67,] 1.06395380 7.73372732
[68,] -16.45069935 1.06395380
[69,] -38.27353341 -16.45069935
[70,] 11.35012056 -38.27353341
[71,] 4.87488066 11.35012056
[72,] -10.17541489 4.87488066
[73,] 21.11610859 -10.17541489
[74,] 4.11640226 21.11610859
[75,] 1.57560309 4.11640226
[76,] 4.61640012 1.57560309
[77,] 14.51727964 4.61640012
[78,] 1.29585473 14.51727964
[79,] 26.02442103 1.29585473
[80,] -16.21040297 26.02442103
[81,] 16.68340585 -16.21040297
[82,] 2.86364200 16.68340585
[83,] 10.36052451 2.86364200
[84,] -2.88778290 10.36052451
[85,] 17.05571370 -2.88778290
[86,] -3.23289165 17.05571370
[87,] 2.63528394 -3.23289165
[88,] -20.51629238 2.63528394
[89,] 18.48657966 -20.51629238
[90,] -39.53021187 18.48657966
[91,] 4.00217421 -39.53021187
[92,] -3.01664719 4.00217421
[93,] 18.81010560 -3.01664719
[94,] 12.37827847 18.81010560
[95,] 7.25086820 12.37827847
[96,] -50.40055062 7.25086820
[97,] 18.34654954 -50.40055062
[98,] -36.42414169 18.34654954
[99,] 14.29280196 -36.42414169
[100,] -3.86364346 14.29280196
[101,] 15.87868697 -3.86364346
[102,] 6.67579614 15.87868697
[103,] 19.19905914 6.67579614
[104,] 9.31147196 19.19905914
[105,] -12.57506009 9.31147196
[106,] 32.45093122 -12.57506009
[107,] -24.40855625 32.45093122
[108,] -2.81783995 -24.40855625
[109,] 8.64824744 -2.81783995
[110,] -1.99232946 8.64824744
[111,] -47.69301944 -1.99232946
[112,] 12.26493794 -47.69301944
[113,] -32.39550525 12.26493794
[114,] -33.38728599 -32.39550525
[115,] -7.16523860 -33.38728599
[116,] 0.99005039 -7.16523860
[117,] -0.08322829 0.99005039
[118,] 0.82737238 -0.08322829
[119,] -8.01288166 0.82737238
[120,] -5.52881288 -8.01288166
[121,] -7.19396140 -5.52881288
[122,] 13.62526486 -7.19396140
[123,] 5.08538638 13.62526486
[124,] 11.72719995 5.08538638
[125,] 9.02456564 11.72719995
[126,] 4.91586297 9.02456564
[127,] 22.16541307 4.91586297
[128,] -25.04526121 22.16541307
[129,] 1.96959229 -25.04526121
[130,] 4.63990400 1.96959229
[131,] -15.05794197 4.63990400
[132,] -0.43101859 -15.05794197
[133,] 7.77211199 -0.43101859
[134,] -10.10986495 7.77211199
[135,] -27.42502809 -10.10986495
[136,] 5.03645174 -27.42502809
[137,] -20.05341256 5.03645174
[138,] -4.38805008 -20.05341256
[139,] -10.00693016 -4.38805008
[140,] -1.36448886 -10.00693016
[141,] 0.67068546 -1.36448886
[142,] -3.68422759 0.67068546
[143,] 7.10733572 -3.68422759
[144,] 15.76073299 7.10733572
[145,] -13.42818192 15.76073299
[146,] 6.19017750 -13.42818192
[147,] -4.49363896 6.19017750
[148,] 1.54303865 -4.49363896
[149,] 17.15039123 1.54303865
[150,] 11.67573113 17.15039123
[151,] 6.41345115 11.67573113
[152,] -4.04316556 6.41345115
[153,] 5.30720608 -4.04316556
[154,] -4.10945937 5.30720608
[155,] 7.70442296 -4.10945937
[156,] 17.35308625 7.70442296
[157,] 0.13994261 17.35308625
[158,] -3.20066884 0.13994261
[159,] 17.53941174 -3.20066884
[160,] 4.22139847 17.53941174
[161,] 14.24971243 4.22139847
[162,] 6.99117315 14.24971243
[163,] 6.90482205 6.99117315
[164,] -7.27991508 6.90482205
[165,] 4.08925210 -7.27991508
[166,] -9.13485502 4.08925210
[167,] -47.13499633 -9.13485502
[168,] -10.93089109 -47.13499633
[169,] -5.18777705 -10.93089109
[170,] -9.23768616 -5.18777705
[171,] -1.18666535 -9.23768616
[172,] 10.52710146 -1.18666535
[173,] -9.80304713 10.52710146
[174,] 28.02853914 -9.80304713
[175,] -0.53774469 28.02853914
[176,] 3.46953897 -0.53774469
[177,] 2.10167973 3.46953897
[178,] 7.37776932 2.10167973
[179,] -0.92109220 7.37776932
[180,] 2.25700435 -0.92109220
[181,] 2.07343146 2.25700435
[182,] 5.34818368 2.07343146
[183,] -21.94717265 5.34818368
[184,] -36.45931316 -21.94717265
[185,] 5.96371378 -36.45931316
[186,] 1.28549263 5.96371378
[187,] 6.07772023 1.28549263
[188,] 7.12928196 6.07772023
[189,] -45.83984606 7.12928196
[190,] -29.36119266 -45.83984606
[191,] -2.44295742 -29.36119266
[192,] 1.25955172 -2.44295742
[193,] 1.42540961 1.25955172
[194,] 18.64942844 1.42540961
[195,] 5.72494636 18.64942844
[196,] 12.97117433 5.72494636
[197,] 9.57398360 12.97117433
[198,] -3.96247377 9.57398360
[199,] 13.41884989 -3.96247377
[200,] 2.01538479 13.41884989
[201,] -22.98562051 2.01538479
[202,] 12.43908821 -22.98562051
[203,] 13.92929142 12.43908821
[204,] 3.25540572 13.92929142
[205,] -16.77386532 3.25540572
[206,] 6.44804063 -16.77386532
[207,] 5.44391919 6.44804063
[208,] -2.37714818 5.44391919
[209,] 18.93805478 -2.37714818
[210,] 0.43808806 18.93805478
[211,] -0.29558244 0.43808806
[212,] -0.72793837 -0.29558244
[213,] 14.51047269 -0.72793837
[214,] -2.98611900 14.51047269
[215,] 19.83486970 -2.98611900
[216,] 7.82763776 19.83486970
[217,] 4.60953792 7.82763776
[218,] -4.99850418 4.60953792
[219,] 9.39129024 -4.99850418
[220,] 10.88892618 9.39129024
[221,] 14.47593031 10.88892618
[222,] -1.79363632 14.47593031
[223,] 6.00001547 -1.79363632
[224,] -4.26641139 6.00001547
[225,] -9.22189661 -4.26641139
[226,] -16.51412642 -9.22189661
[227,] 12.60318050 -16.51412642
[228,] -8.01402023 12.60318050
[229,] 14.06033274 -8.01402023
[230,] 2.18205580 14.06033274
[231,] 0.04609014 2.18205580
[232,] 5.09143211 0.04609014
[233,] -10.36003657 5.09143211
[234,] -17.03873209 -10.36003657
[235,] -0.98077843 -17.03873209
[236,] -1.65461998 -0.98077843
[237,] -34.12328232 -1.65461998
[238,] -8.08502560 -34.12328232
[239,] 0.44189600 -8.08502560
[240,] -10.96245603 0.44189600
[241,] 12.14838329 -10.96245603
[242,] -0.66896360 12.14838329
[243,] 6.98893271 -0.66896360
[244,] 4.61745386 6.98893271
[245,] -6.13916996 4.61745386
[246,] 0.95455790 -6.13916996
[247,] 5.92839078 0.95455790
[248,] 5.88247737 5.92839078
[249,] -6.35316056 5.88247737
[250,] 2.06653652 -6.35316056
[251,] 4.77803934 2.06653652
[252,] 2.03747953 4.77803934
[253,] 8.85554507 2.03747953
[254,] 4.87845158 8.85554507
[255,] -3.39139218 4.87845158
[256,] 0.30637713 -3.39139218
[257,] -6.97921645 0.30637713
[258,] -6.80764536 -6.97921645
[259,] -3.70932120 -6.80764536
[260,] -24.61219562 -3.70932120
[261,] 18.24188149 -24.61219562
[262,] -2.58433537 18.24188149
[263,] -10.99103235 -2.58433537
[264,] 16.18138404 -10.99103235
[265,] -5.71252820 16.18138404
[266,] 8.55873193 -5.71252820
[267,] -8.89903938 8.55873193
[268,] 7.96402088 -8.89903938
[269,] -18.11011994 7.96402088
[270,] -10.02402815 -18.11011994
[271,] 15.51740153 -10.02402815
[272,] 3.66064422 15.51740153
[273,] 4.01946427 3.66064422
[274,] -2.32920640 4.01946427
[275,] -13.40465423 -2.32920640
[276,] -0.36678327 -13.40465423
[277,] 3.20315555 -0.36678327
[278,] 8.52697427 3.20315555
[279,] 13.42353922 8.52697427
[280,] 12.45923006 13.42353922
[281,] -9.17490286 12.45923006
[282,] -9.13337077 -9.17490286
[283,] -1.12874687 -9.13337077
[284,] 9.04907558 -1.12874687
[285,] -17.79245226 9.04907558
[286,] 2.62839727 -17.79245226
[287,] 9.25999821 2.62839727
[288,] -6.33421859 9.25999821
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 18.31446600 -4.06553933
2 -24.81560109 18.31446600
3 9.11232356 -24.81560109
4 -16.46641982 9.11232356
5 -3.11881700 -16.46641982
6 -6.17655931 -3.11881700
7 -26.25579802 -6.17655931
8 4.88099313 -26.25579802
9 12.60357985 4.88099313
10 -19.27297945 12.60357985
11 -0.15634501 -19.27297945
12 13.05265186 -0.15634501
13 -0.81587722 13.05265186
14 -6.31141182 -0.81587722
15 -36.63085325 -6.31141182
16 14.17294317 -36.63085325
17 15.50643222 14.17294317
18 -31.22497169 15.50643222
19 -5.30340846 -31.22497169
20 20.05169259 -5.30340846
21 1.97623825 20.05169259
22 -1.30609030 1.97623825
23 5.46078358 -1.30609030
24 39.00456766 5.46078358
25 15.50940604 39.00456766
26 17.63832390 15.50940604
27 -6.84767295 17.63832390
28 12.40032443 -6.84767295
29 5.20504008 12.40032443
30 2.86033936 5.20504008
31 20.88189585 2.86033936
32 -6.73331291 20.88189585
33 18.11356242 -6.73331291
34 21.82468312 18.11356242
35 11.03654492 21.82468312
36 -0.43098939 11.03654492
37 -11.46910768 -0.43098939
38 1.79593405 -11.46910768
39 6.02178946 1.79593405
40 -18.06213170 6.02178946
41 -5.77743155 -18.06213170
42 -11.05563806 -5.77743155
43 12.74972610 -11.05563806
44 -8.47248067 12.74972610
45 -11.87802656 -8.47248067
46 13.24712748 -11.87802656
47 3.13363886 13.24712748
48 -3.31325817 3.13363886
49 -83.14495847 -3.31325817
50 -9.28418688 -83.14495847
51 -8.84460786 -9.28418688
52 17.14247937 -8.84460786
53 5.68180242 17.14247937
54 12.39236713 5.68180242
55 11.72115348 12.39236713
56 0.33196436 11.72115348
57 6.06328316 0.33196436
58 10.34095932 6.06328316
59 -0.80463007 10.34095932
60 1.56560785 -0.80463007
61 23.43150708 1.56560785
62 -1.07417259 23.43150708
63 1.08996158 -1.07417259
64 9.65396143 1.08996158
65 8.05317976 9.65396143
66 7.73372732 8.05317976
67 1.06395380 7.73372732
68 -16.45069935 1.06395380
69 -38.27353341 -16.45069935
70 11.35012056 -38.27353341
71 4.87488066 11.35012056
72 -10.17541489 4.87488066
73 21.11610859 -10.17541489
74 4.11640226 21.11610859
75 1.57560309 4.11640226
76 4.61640012 1.57560309
77 14.51727964 4.61640012
78 1.29585473 14.51727964
79 26.02442103 1.29585473
80 -16.21040297 26.02442103
81 16.68340585 -16.21040297
82 2.86364200 16.68340585
83 10.36052451 2.86364200
84 -2.88778290 10.36052451
85 17.05571370 -2.88778290
86 -3.23289165 17.05571370
87 2.63528394 -3.23289165
88 -20.51629238 2.63528394
89 18.48657966 -20.51629238
90 -39.53021187 18.48657966
91 4.00217421 -39.53021187
92 -3.01664719 4.00217421
93 18.81010560 -3.01664719
94 12.37827847 18.81010560
95 7.25086820 12.37827847
96 -50.40055062 7.25086820
97 18.34654954 -50.40055062
98 -36.42414169 18.34654954
99 14.29280196 -36.42414169
100 -3.86364346 14.29280196
101 15.87868697 -3.86364346
102 6.67579614 15.87868697
103 19.19905914 6.67579614
104 9.31147196 19.19905914
105 -12.57506009 9.31147196
106 32.45093122 -12.57506009
107 -24.40855625 32.45093122
108 -2.81783995 -24.40855625
109 8.64824744 -2.81783995
110 -1.99232946 8.64824744
111 -47.69301944 -1.99232946
112 12.26493794 -47.69301944
113 -32.39550525 12.26493794
114 -33.38728599 -32.39550525
115 -7.16523860 -33.38728599
116 0.99005039 -7.16523860
117 -0.08322829 0.99005039
118 0.82737238 -0.08322829
119 -8.01288166 0.82737238
120 -5.52881288 -8.01288166
121 -7.19396140 -5.52881288
122 13.62526486 -7.19396140
123 5.08538638 13.62526486
124 11.72719995 5.08538638
125 9.02456564 11.72719995
126 4.91586297 9.02456564
127 22.16541307 4.91586297
128 -25.04526121 22.16541307
129 1.96959229 -25.04526121
130 4.63990400 1.96959229
131 -15.05794197 4.63990400
132 -0.43101859 -15.05794197
133 7.77211199 -0.43101859
134 -10.10986495 7.77211199
135 -27.42502809 -10.10986495
136 5.03645174 -27.42502809
137 -20.05341256 5.03645174
138 -4.38805008 -20.05341256
139 -10.00693016 -4.38805008
140 -1.36448886 -10.00693016
141 0.67068546 -1.36448886
142 -3.68422759 0.67068546
143 7.10733572 -3.68422759
144 15.76073299 7.10733572
145 -13.42818192 15.76073299
146 6.19017750 -13.42818192
147 -4.49363896 6.19017750
148 1.54303865 -4.49363896
149 17.15039123 1.54303865
150 11.67573113 17.15039123
151 6.41345115 11.67573113
152 -4.04316556 6.41345115
153 5.30720608 -4.04316556
154 -4.10945937 5.30720608
155 7.70442296 -4.10945937
156 17.35308625 7.70442296
157 0.13994261 17.35308625
158 -3.20066884 0.13994261
159 17.53941174 -3.20066884
160 4.22139847 17.53941174
161 14.24971243 4.22139847
162 6.99117315 14.24971243
163 6.90482205 6.99117315
164 -7.27991508 6.90482205
165 4.08925210 -7.27991508
166 -9.13485502 4.08925210
167 -47.13499633 -9.13485502
168 -10.93089109 -47.13499633
169 -5.18777705 -10.93089109
170 -9.23768616 -5.18777705
171 -1.18666535 -9.23768616
172 10.52710146 -1.18666535
173 -9.80304713 10.52710146
174 28.02853914 -9.80304713
175 -0.53774469 28.02853914
176 3.46953897 -0.53774469
177 2.10167973 3.46953897
178 7.37776932 2.10167973
179 -0.92109220 7.37776932
180 2.25700435 -0.92109220
181 2.07343146 2.25700435
182 5.34818368 2.07343146
183 -21.94717265 5.34818368
184 -36.45931316 -21.94717265
185 5.96371378 -36.45931316
186 1.28549263 5.96371378
187 6.07772023 1.28549263
188 7.12928196 6.07772023
189 -45.83984606 7.12928196
190 -29.36119266 -45.83984606
191 -2.44295742 -29.36119266
192 1.25955172 -2.44295742
193 1.42540961 1.25955172
194 18.64942844 1.42540961
195 5.72494636 18.64942844
196 12.97117433 5.72494636
197 9.57398360 12.97117433
198 -3.96247377 9.57398360
199 13.41884989 -3.96247377
200 2.01538479 13.41884989
201 -22.98562051 2.01538479
202 12.43908821 -22.98562051
203 13.92929142 12.43908821
204 3.25540572 13.92929142
205 -16.77386532 3.25540572
206 6.44804063 -16.77386532
207 5.44391919 6.44804063
208 -2.37714818 5.44391919
209 18.93805478 -2.37714818
210 0.43808806 18.93805478
211 -0.29558244 0.43808806
212 -0.72793837 -0.29558244
213 14.51047269 -0.72793837
214 -2.98611900 14.51047269
215 19.83486970 -2.98611900
216 7.82763776 19.83486970
217 4.60953792 7.82763776
218 -4.99850418 4.60953792
219 9.39129024 -4.99850418
220 10.88892618 9.39129024
221 14.47593031 10.88892618
222 -1.79363632 14.47593031
223 6.00001547 -1.79363632
224 -4.26641139 6.00001547
225 -9.22189661 -4.26641139
226 -16.51412642 -9.22189661
227 12.60318050 -16.51412642
228 -8.01402023 12.60318050
229 14.06033274 -8.01402023
230 2.18205580 14.06033274
231 0.04609014 2.18205580
232 5.09143211 0.04609014
233 -10.36003657 5.09143211
234 -17.03873209 -10.36003657
235 -0.98077843 -17.03873209
236 -1.65461998 -0.98077843
237 -34.12328232 -1.65461998
238 -8.08502560 -34.12328232
239 0.44189600 -8.08502560
240 -10.96245603 0.44189600
241 12.14838329 -10.96245603
242 -0.66896360 12.14838329
243 6.98893271 -0.66896360
244 4.61745386 6.98893271
245 -6.13916996 4.61745386
246 0.95455790 -6.13916996
247 5.92839078 0.95455790
248 5.88247737 5.92839078
249 -6.35316056 5.88247737
250 2.06653652 -6.35316056
251 4.77803934 2.06653652
252 2.03747953 4.77803934
253 8.85554507 2.03747953
254 4.87845158 8.85554507
255 -3.39139218 4.87845158
256 0.30637713 -3.39139218
257 -6.97921645 0.30637713
258 -6.80764536 -6.97921645
259 -3.70932120 -6.80764536
260 -24.61219562 -3.70932120
261 18.24188149 -24.61219562
262 -2.58433537 18.24188149
263 -10.99103235 -2.58433537
264 16.18138404 -10.99103235
265 -5.71252820 16.18138404
266 8.55873193 -5.71252820
267 -8.89903938 8.55873193
268 7.96402088 -8.89903938
269 -18.11011994 7.96402088
270 -10.02402815 -18.11011994
271 15.51740153 -10.02402815
272 3.66064422 15.51740153
273 4.01946427 3.66064422
274 -2.32920640 4.01946427
275 -13.40465423 -2.32920640
276 -0.36678327 -13.40465423
277 3.20315555 -0.36678327
278 8.52697427 3.20315555
279 13.42353922 8.52697427
280 12.45923006 13.42353922
281 -9.17490286 12.45923006
282 -9.13337077 -9.17490286
283 -1.12874687 -9.13337077
284 9.04907558 -1.12874687
285 -17.79245226 9.04907558
286 2.62839727 -17.79245226
287 9.25999821 2.62839727
288 -6.33421859 9.25999821
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/7ya7y1324573861.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/80nq11324573861.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9lmnm1324573861.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/105aue1324573861.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/11dd9w1324573861.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/12lvec1324573861.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/137xir1324573861.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/14pnsn1324573861.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/15x0ly1324573861.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/rcomp/tmp/16nc081324573861.tab")
+ }
>
> try(system("convert tmp/10ywl1324573861.ps tmp/10ywl1324573861.png",intern=TRUE))
character(0)
> try(system("convert tmp/20in81324573861.ps tmp/20in81324573861.png",intern=TRUE))
character(0)
> try(system("convert tmp/382iu1324573861.ps tmp/382iu1324573861.png",intern=TRUE))
character(0)
> try(system("convert tmp/4i7mh1324573861.ps tmp/4i7mh1324573861.png",intern=TRUE))
character(0)
> try(system("convert tmp/5qbj61324573861.ps tmp/5qbj61324573861.png",intern=TRUE))
character(0)
> try(system("convert tmp/6kr511324573861.ps tmp/6kr511324573861.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ya7y1324573861.ps tmp/7ya7y1324573861.png",intern=TRUE))
character(0)
> try(system("convert tmp/80nq11324573861.ps tmp/80nq11324573861.png",intern=TRUE))
character(0)
> try(system("convert tmp/9lmnm1324573861.ps tmp/9lmnm1324573861.png",intern=TRUE))
character(0)
> try(system("convert tmp/105aue1324573861.ps tmp/105aue1324573861.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.750 0.320 7.044