R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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Type 'q()' to quit R.
> x <- array(list(1418
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+ ,14)
+ ,dim=c(3
+ ,289)
+ ,dimnames=list(c('pageviews'
+ ,'time'
+ ,'aantal_logins')
+ ,1:289))
> y <- array(NA,dim=c(3,289),dimnames=list(c('pageviews','time','aantal_logins'),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'
> 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
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
pageviews time aantal_logins
1 1418 210907 56
2 869 120982 56
3 1530 176508 54
4 2172 179321 89
5 901 123185 40
6 463 52746 25
7 3201 385534 92
8 371 33170 18
9 1192 101645 63
10 1583 149061 44
11 1439 165446 33
12 1764 237213 84
13 1495 173326 88
14 1373 133131 55
15 2187 258873 60
16 1491 180083 66
17 4041 324799 154
18 1706 230964 53
19 2152 236785 119
20 1036 135473 41
21 1882 202925 61
22 1929 215147 58
23 2242 344297 75
24 1220 153935 33
25 1289 132943 40
26 2515 174724 92
27 2147 174415 100
28 2352 225548 112
29 1638 223632 73
30 1222 124817 40
31 1812 221698 45
32 1677 210767 60
33 1579 170266 62
34 1731 260561 75
35 807 84853 31
36 2452 294424 77
37 829 101011 34
38 1940 215641 46
39 2662 325107 99
40 186 7176 17
41 1499 167542 66
42 865 106408 30
43 1793 96560 76
44 2527 265769 146
45 2747 269651 67
46 1324 149112 56
47 2702 175824 107
48 1383 152871 58
49 1179 111665 34
50 2099 116408 61
51 4308 362301 119
52 918 78800 42
53 1831 183167 66
54 3373 277965 89
55 1713 150629 44
56 1438 168809 66
57 496 24188 24
58 2253 329267 259
59 744 65029 17
60 1161 101097 64
61 2352 218946 41
62 2144 244052 68
63 4691 341570 168
64 1112 103597 43
65 2694 233328 132
66 1973 256462 105
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68 3148 311473 112
69 2474 235800 94
70 2084 177939 82
71 1954 207176 70
72 1226 196553 57
73 1389 174184 53
74 1496 143246 103
75 2269 187559 121
76 1833 187681 62
77 1268 119016 52
78 1943 182192 52
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84 1840 243199 75
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90 1317 145790 63
91 1644 193339 78
92 870 80953 25
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95 937 112611 41
96 3004 286468 144
97 2008 241066 82
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99 1885 204713 71
100 1626 182079 63
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103 1964 243060 63
104 1381 162765 32
105 1369 182613 39
106 1659 232138 62
107 2888 265318 117
108 1290 85574 34
109 2845 310839 92
110 1982 225060 93
111 1904 232317 54
112 1391 144966 144
113 602 43287 14
114 1743 155754 61
115 1559 164709 109
116 2014 201940 38
117 2143 235454 73
118 2146 220801 75
119 874 99466 50
120 1590 92661 61
121 1590 133328 55
122 1210 61361 77
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124 1281 100750 72
125 1401 224549 50
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127 1105 102010 53
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131 761 41566 35
132 1605 152474 65
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134 1988 99923 66
135 1386 132487 41
136 2395 317394 86
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139 620 22648 19
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141 800 46698 45
142 1684 131698 65
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144 2699 244749 95
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147 1204 128423 64
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151 2158 272458 65
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154 2833 328107 65
155 1955 250579 83
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157 1002 158015 29
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160 2186 229242 247
161 3604 351619 139
162 1035 84207 29
163 1417 120445 118
164 3261 324598 110
165 1587 131069 67
166 1424 204271 42
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179 1900 224330 83
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185 2429 271856 103
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226 1803 135458 81
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246 1051 84856 29
247 1656 102538 57
248 705 86678 40
249 945 85709 44
250 554 34662 25
251 1597 150580 77
252 982 99611 35
253 222 19349 11
254 1212 99373 63
255 1143 86230 44
256 435 30837 19
257 532 31706 13
258 882 89806 42
259 608 62088 38
260 459 40151 29
261 578 27634 20
262 826 76990 27
263 509 37460 20
264 717 54157 19
265 637 49862 37
266 857 84337 26
267 830 64175 42
268 652 59382 49
269 707 119308 30
270 954 76702 49
271 1461 103425 67
272 672 70344 28
273 778 43410 19
274 1141 104838 49
275 680 62215 27
276 1090 69304 30
277 616 53117 22
278 285 19764 12
279 1145 86680 31
280 733 84105 20
281 888 77945 20
282 849 89113 39
283 1182 91005 29
284 528 40248 16
285 642 64187 27
286 947 50857 21
287 819 56613 19
288 757 62792 35
289 894 72535 14
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) time aantal_logins
2.387e+02 6.412e-03 5.332e+00
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1478.03 -174.36 -36.54 150.61 1366.29
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.387e+02 3.703e+01 6.445 4.88e-10 ***
time 6.412e-03 3.155e-04 20.324 < 2e-16 ***
aantal_logins 5.332e+00 7.670e-01 6.952 2.45e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 307.8 on 286 degrees of freedom
Multiple R-squared: 0.8264, Adjusted R-squared: 0.8252
F-statistic: 680.9 on 2 and 286 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,] 0.39931751 7.986350e-01 6.006825e-01
[2,] 0.28421609 5.684322e-01 7.157839e-01
[3,] 0.26643135 5.328627e-01 7.335687e-01
[4,] 0.16448722 3.289744e-01 8.355128e-01
[5,] 0.26946054 5.389211e-01 7.305395e-01
[6,] 0.24356389 4.871278e-01 7.564361e-01
[7,] 0.33380930 6.676186e-01 6.661907e-01
[8,] 0.29970924 5.994185e-01 7.002908e-01
[9,] 0.24204323 4.840865e-01 7.579568e-01
[10,] 0.18473908 3.694782e-01 8.152609e-01
[11,] 0.13954568 2.790914e-01 8.604543e-01
[12,] 0.39933595 7.986719e-01 6.006640e-01
[13,] 0.33452576 6.690515e-01 6.654742e-01
[14,] 0.43446537 8.689307e-01 5.655346e-01
[15,] 0.36848470 7.369694e-01 6.315153e-01
[16,] 0.31961735 6.392347e-01 6.803826e-01
[17,] 0.27335537 5.467107e-01 7.266446e-01
[18,] 0.37323090 7.464618e-01 6.267691e-01
[19,] 0.32202297 6.440459e-01 6.779770e-01
[20,] 0.29108159 5.821632e-01 7.089184e-01
[21,] 0.45311856 9.062371e-01 5.468814e-01
[22,] 0.39770160 7.954032e-01 6.022984e-01
[23,] 0.35342217 7.068443e-01 6.465778e-01
[24,] 0.37459041 7.491808e-01 6.254096e-01
[25,] 0.33539646 6.707929e-01 6.646035e-01
[26,] 0.30520682 6.104136e-01 6.947932e-01
[27,] 0.26264620 5.252924e-01 7.373538e-01
[28,] 0.21867551 4.373510e-01 7.813245e-01
[29,] 0.28779342 5.755868e-01 7.122066e-01
[30,] 0.24488888 4.897778e-01 7.551111e-01
[31,] 0.20881249 4.176250e-01 7.911875e-01
[32,] 0.17553906 3.510781e-01 8.244609e-01
[33,] 0.18596945 3.719389e-01 8.140305e-01
[34,] 0.16103806 3.220761e-01 8.389619e-01
[35,] 0.13250141 2.650028e-01 8.674986e-01
[36,] 0.11048903 2.209781e-01 8.895110e-01
[37,] 0.08970312 1.794062e-01 9.102969e-01
[38,] 0.11859534 2.371907e-01 8.814047e-01
[39,] 0.17185172 3.437034e-01 8.281483e-01
[40,] 0.28397019 5.679404e-01 7.160298e-01
[41,] 0.24882400 4.976480e-01 7.511760e-01
[42,] 0.39053160 7.810632e-01 6.094684e-01
[43,] 0.35034696 7.006939e-01 6.496530e-01
[44,] 0.32607383 6.521477e-01 6.739262e-01
[45,] 0.57914605 8.417079e-01 4.208540e-01
[46,] 0.91598411 1.680318e-01 8.401589e-02
[47,] 0.89807073 2.038585e-01 1.019293e-01
[48,] 0.87905542 2.418892e-01 1.209446e-01
[49,] 0.96699080 6.601840e-02 3.300920e-02
[50,] 0.96975316 6.049369e-02 3.024684e-02
[51,] 0.96665034 6.669932e-02 3.334966e-02
[52,] 0.95901158 8.197684e-02 4.098842e-02
[53,] 0.99999617 7.651445e-06 3.825722e-06
[54,] 0.99999399 1.202074e-05 6.010372e-06
[55,] 0.99999072 1.855477e-05 9.277387e-06
[56,] 0.99999423 1.153870e-05 5.769351e-06
[57,] 0.99999106 1.788064e-05 8.940321e-06
[58,] 1.00000000 7.025132e-09 3.512566e-09
[59,] 0.99999999 1.219477e-08 6.097384e-09
[60,] 0.99999999 1.527679e-08 7.638394e-09
[61,] 1.00000000 8.280182e-09 4.140091e-09
[62,] 0.99999999 1.248518e-08 6.242592e-09
[63,] 0.99999999 1.374729e-08 6.873644e-09
[64,] 0.99999999 1.841502e-08 9.207508e-09
[65,] 0.99999999 2.127550e-08 1.063775e-08
[66,] 0.99999998 3.593696e-08 1.796848e-08
[67,] 0.99999999 1.211144e-08 6.055720e-09
[68,] 0.99999999 1.563099e-08 7.815494e-09
[69,] 0.99999999 2.223731e-08 1.111865e-08
[70,] 0.99999998 3.094271e-08 1.547136e-08
[71,] 0.99999997 5.039410e-08 2.519705e-08
[72,] 0.99999996 8.297150e-08 4.148575e-08
[73,] 0.99999995 9.609893e-08 4.804947e-08
[74,] 0.99999992 1.537114e-07 7.685569e-08
[75,] 0.99999988 2.463650e-07 1.231825e-07
[76,] 0.99999982 3.639171e-07 1.819585e-07
[77,] 0.99999971 5.756507e-07 2.878254e-07
[78,] 0.99999985 3.043578e-07 1.521789e-07
[79,] 0.99999986 2.704062e-07 1.352031e-07
[80,] 0.99999988 2.306339e-07 1.153169e-07
[81,] 0.99999983 3.480682e-07 1.740341e-07
[82,] 0.99999973 5.418781e-07 2.709391e-07
[83,] 0.99999967 6.676954e-07 3.338477e-07
[84,] 0.99999948 1.042652e-06 5.213259e-07
[85,] 0.99999929 1.414354e-06 7.071771e-07
[86,] 0.99999915 1.697503e-06 8.487516e-07
[87,] 0.99999871 2.587611e-06 1.293806e-06
[88,] 0.99999903 1.939198e-06 9.695991e-07
[89,] 0.99999887 2.265527e-06 1.132764e-06
[90,] 0.99999860 2.792393e-06 1.396197e-06
[91,] 0.99999809 3.825542e-06 1.912771e-06
[92,] 0.99999760 4.790260e-06 2.395130e-06
[93,] 0.99999989 2.222167e-07 1.111083e-07
[94,] 0.99999983 3.492121e-07 1.746060e-07
[95,] 0.99999974 5.194620e-07 2.597310e-07
[96,] 0.99999960 7.957942e-07 3.978971e-07
[97,] 0.99999977 4.544393e-07 2.272196e-07
[98,] 0.99999969 6.247116e-07 3.123558e-07
[99,] 0.99999953 9.471769e-07 4.735885e-07
[100,] 0.99999944 1.114911e-06 5.574555e-07
[101,] 0.99999958 8.317497e-07 4.158749e-07
[102,] 0.99999961 7.850544e-07 3.925272e-07
[103,] 0.99999964 7.181844e-07 3.590922e-07
[104,] 0.99999948 1.037128e-06 5.185642e-07
[105,] 0.99999932 1.352739e-06 6.763696e-07
[106,] 0.99999903 1.949662e-06 9.748310e-07
[107,] 0.99999958 8.475840e-07 4.237920e-07
[108,] 0.99999936 1.284278e-06 6.421389e-07
[109,] 0.99999916 1.670536e-06 8.352678e-07
[110,] 0.99999916 1.675808e-06 8.379039e-07
[111,] 0.99999910 1.798727e-06 8.993636e-07
[112,] 0.99999863 2.732502e-06 1.366251e-06
[113,] 0.99999802 3.963890e-06 1.981945e-06
[114,] 0.99999777 4.456348e-06 2.228174e-06
[115,] 0.99999862 2.769599e-06 1.384799e-06
[116,] 0.99999829 3.418181e-06 1.709090e-06
[117,] 0.99999779 4.425365e-06 2.212683e-06
[118,] 0.99999947 1.057305e-06 5.286527e-07
[119,] 0.99999919 1.614380e-06 8.071900e-07
[120,] 0.99999970 5.961531e-07 2.980765e-07
[121,] 0.99999956 8.762081e-07 4.381040e-07
[122,] 0.99999934 1.320319e-06 6.601593e-07
[123,] 0.99999911 1.777464e-06 8.887321e-07
[124,] 0.99999897 2.062208e-06 1.031104e-06
[125,] 0.99999846 3.078573e-06 1.539287e-06
[126,] 0.99999775 4.501964e-06 2.250982e-06
[127,] 0.99999667 6.669267e-06 3.334633e-06
[128,] 0.99999614 7.719207e-06 3.859604e-06
[129,] 0.99999963 7.306731e-07 3.653366e-07
[130,] 0.99999945 1.094080e-06 5.470399e-07
[131,] 0.99999955 9.000352e-07 4.500176e-07
[132,] 0.99999933 1.349228e-06 6.746139e-07
[133,] 0.99999902 1.956349e-06 9.781746e-07
[134,] 0.99999864 2.710729e-06 1.355364e-06
[135,] 0.99999803 3.932610e-06 1.966305e-06
[136,] 0.99999707 5.867674e-06 2.933837e-06
[137,] 0.99999678 6.442164e-06 3.221082e-06
[138,] 0.99999523 9.538367e-06 4.769183e-06
[139,] 0.99999639 7.220388e-06 3.610194e-06
[140,] 0.99999485 1.029888e-05 5.149440e-06
[141,] 0.99999817 3.665997e-06 1.832998e-06
[142,] 0.99999768 4.632891e-06 2.316446e-06
[143,] 0.99999659 6.810106e-06 3.405053e-06
[144,] 0.99999511 9.779799e-06 4.889900e-06
[145,] 0.99999291 1.417788e-05 7.088940e-06
[146,] 0.99999139 1.721473e-05 8.607367e-06
[147,] 0.99999654 6.917820e-06 3.458910e-06
[148,] 0.99999549 9.016469e-06 4.508234e-06
[149,] 0.99999365 1.269123e-05 6.345613e-06
[150,] 0.99999491 1.018973e-05 5.094867e-06
[151,] 0.99999337 1.326982e-05 6.634909e-06
[152,] 0.99999655 6.894281e-06 3.447140e-06
[153,] 0.99999496 1.008081e-05 5.040403e-06
[154,] 0.99999252 1.495530e-05 7.477649e-06
[155,] 0.99999950 1.002017e-06 5.010085e-07
[156,] 0.99999949 1.011660e-06 5.058298e-07
[157,] 0.99999925 1.492108e-06 7.460539e-07
[158,] 0.99999923 1.546653e-06 7.733264e-07
[159,] 0.99999925 1.495731e-06 7.478656e-07
[160,] 0.99999894 2.117014e-06 1.058507e-06
[161,] 0.99999920 1.604405e-06 8.022026e-07
[162,] 0.99999877 2.469049e-06 1.234524e-06
[163,] 0.99999936 1.270008e-06 6.350041e-07
[164,] 0.99999963 7.453596e-07 3.726798e-07
[165,] 0.99999980 4.005922e-07 2.002961e-07
[166,] 0.99999997 6.435875e-08 3.217937e-08
[167,] 0.99999996 7.169645e-08 3.584823e-08
[168,] 0.99999997 5.964441e-08 2.982220e-08
[169,] 0.99999995 9.731992e-08 4.865996e-08
[170,] 0.99999994 1.206717e-07 6.033583e-08
[171,] 0.99999995 1.006574e-07 5.032869e-08
[172,] 0.99999996 8.995416e-08 4.497708e-08
[173,] 0.99999993 1.473456e-07 7.367280e-08
[174,] 0.99999992 1.656192e-07 8.280961e-08
[175,] 0.99999986 2.711210e-07 1.355605e-07
[176,] 0.99999984 3.265865e-07 1.632933e-07
[177,] 0.99999993 1.382604e-07 6.913022e-08
[178,] 0.99999991 1.880632e-07 9.403159e-08
[179,] 0.99999987 2.619644e-07 1.309822e-07
[180,] 0.99999983 3.442538e-07 1.721269e-07
[181,] 0.99999975 5.004783e-07 2.502391e-07
[182,] 0.99999966 6.826311e-07 3.413156e-07
[183,] 0.99999960 8.064257e-07 4.032128e-07
[184,] 0.99999971 5.893839e-07 2.946920e-07
[185,] 0.99999960 8.039315e-07 4.019657e-07
[186,] 0.99999946 1.075561e-06 5.377805e-07
[187,] 0.99999917 1.666000e-06 8.329998e-07
[188,] 0.99999951 9.886492e-07 4.943246e-07
[189,] 0.99999989 2.293307e-07 1.146654e-07
[190,] 0.99999981 3.777249e-07 1.888625e-07
[191,] 0.99999973 5.445697e-07 2.722849e-07
[192,] 0.99999955 8.953887e-07 4.476944e-07
[193,] 0.99999935 1.301053e-06 6.505267e-07
[194,] 0.99999923 1.530359e-06 7.651797e-07
[195,] 0.99999887 2.259676e-06 1.129838e-06
[196,] 0.99999903 1.947532e-06 9.737662e-07
[197,] 0.99999873 2.543102e-06 1.271551e-06
[198,] 0.99999811 3.771266e-06 1.885633e-06
[199,] 0.99999702 5.954806e-06 2.977403e-06
[200,] 0.99999919 1.628467e-06 8.142336e-07
[201,] 0.99999872 2.552615e-06 1.276308e-06
[202,] 0.99999795 4.090106e-06 2.045053e-06
[203,] 0.99999730 5.403120e-06 2.701560e-06
[204,] 0.99999659 6.828702e-06 3.414351e-06
[205,] 0.99999471 1.057171e-05 5.285854e-06
[206,] 0.99999253 1.493412e-05 7.467061e-06
[207,] 0.99998813 2.374991e-05 1.187496e-05
[208,] 0.99998135 3.729342e-05 1.864671e-05
[209,] 0.99998382 3.236293e-05 1.618146e-05
[210,] 0.99998547 2.906705e-05 1.453353e-05
[211,] 0.99997700 4.599320e-05 2.299660e-05
[212,] 0.99997632 4.735002e-05 2.367501e-05
[213,] 0.99996294 7.411671e-05 3.705836e-05
[214,] 0.99994486 1.102840e-04 5.514201e-05
[215,] 0.99994585 1.083068e-04 5.415340e-05
[216,] 0.99991971 1.605716e-04 8.028580e-05
[217,] 0.99994979 1.004108e-04 5.020540e-05
[218,] 0.99999984 3.217631e-07 1.608816e-07
[219,] 0.99999973 5.489019e-07 2.744509e-07
[220,] 0.99999966 6.712376e-07 3.356188e-07
[221,] 0.99999971 5.763055e-07 2.881527e-07
[222,] 0.99999952 9.611328e-07 4.805664e-07
[223,] 0.99999913 1.735425e-06 8.677124e-07
[224,] 0.99999946 1.075708e-06 5.378540e-07
[225,] 0.99999998 4.323720e-08 2.161860e-08
[226,] 0.99999996 7.862518e-08 3.931259e-08
[227,] 0.99999996 8.508075e-08 4.254037e-08
[228,] 0.99999999 1.581909e-08 7.909545e-09
[229,] 0.99999999 2.878682e-08 1.439341e-08
[230,] 0.99999997 5.263386e-08 2.631693e-08
[231,] 0.99999996 8.811185e-08 4.405593e-08
[232,] 0.99999996 7.859176e-08 3.929588e-08
[233,] 0.99999992 1.531475e-07 7.657377e-08
[234,] 0.99999992 1.578988e-07 7.894938e-08
[235,] 0.99999984 3.184662e-07 1.592331e-07
[236,] 0.99999970 5.900940e-07 2.950470e-07
[237,] 0.99999960 7.937939e-07 3.968969e-07
[238,] 0.99999928 1.439316e-06 7.196581e-07
[239,] 0.99999869 2.629053e-06 1.314527e-06
[240,] 0.99999743 5.131804e-06 2.565902e-06
[241,] 0.99999614 7.720681e-06 3.860341e-06
[242,] 0.99999970 5.901559e-07 2.950779e-07
[243,] 0.99999980 4.007915e-07 2.003957e-07
[244,] 0.99999958 8.427679e-07 4.213839e-07
[245,] 0.99999910 1.802894e-06 9.014471e-07
[246,] 0.99999810 3.795158e-06 1.897579e-06
[247,] 0.99999622 7.558213e-06 3.779107e-06
[248,] 0.99999492 1.016903e-05 5.084516e-06
[249,] 0.99998996 2.008611e-05 1.004306e-05
[250,] 0.99998617 2.766480e-05 1.383240e-05
[251,] 0.99997484 5.032667e-05 2.516333e-05
[252,] 0.99995038 9.924176e-05 4.962088e-05
[253,] 0.99991647 1.670537e-04 8.352684e-05
[254,] 0.99990314 1.937244e-04 9.686221e-05
[255,] 0.99987896 2.420810e-04 1.210405e-04
[256,] 0.99977014 4.597179e-04 2.298589e-04
[257,] 0.99956159 8.768163e-04 4.384081e-04
[258,] 0.99923090 1.538194e-03 7.690968e-04
[259,] 0.99859925 2.801494e-03 1.400747e-03
[260,] 0.99782969 4.340623e-03 2.170312e-03
[261,] 0.99614790 7.704198e-03 3.852099e-03
[262,] 0.99339456 1.321089e-02 6.605443e-03
[263,] 0.99466681 1.066638e-02 5.333191e-03
[264,] 0.99893804 2.123927e-03 1.061964e-03
[265,] 0.99796499 4.070021e-03 2.035011e-03
[266,] 0.99778078 4.438448e-03 2.219224e-03
[267,] 0.99717500 5.650003e-03 2.825002e-03
[268,] 0.99614331 7.713375e-03 3.856687e-03
[269,] 0.99224521 1.550957e-02 7.754785e-03
[270,] 0.98659381 2.681237e-02 1.340619e-02
[271,] 0.98872236 2.255527e-02 1.127764e-02
[272,] 0.97817581 4.364838e-02 2.182419e-02
[273,] 0.96681285 6.637430e-02 3.318715e-02
[274,] 0.96074168 7.851664e-02 3.925832e-02
[275,] 0.96415066 7.169869e-02 3.584934e-02
[276,] 0.92807363 1.438527e-01 7.192637e-02
[277,] 0.88389145 2.322171e-01 1.161086e-01
[278,] 0.80497912 3.900418e-01 1.950209e-01
> postscript(file="/var/wessaorg/rcomp/tmp/1c9e91355868156.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2lir01355868156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3adeb1355868156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4dtm31355868156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5eefc1355868156.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
-471.6874076 -444.0627384 -128.4473462 308.8967806 -340.8778615
6 7 8 9 10
-247.2237718 -0.3954483 -176.3732701 -34.3920197 153.8700842
11 12 13 14 15
-36.5437864 -443.6634533 -324.3296286 -12.6336347 -31.5868230
16 17 18 19 20
-254.3546172 898.4739760 -296.3027559 -239.5371129 -290.0039576
21 22 23 24 25
16.8357150 1.4606144 -604.3289934 -181.7319814 -15.4489320
26 27 28 29 30
665.3782131 256.7040392 69.8413497 -423.9268113 -30.3427095
31 32 33 34 35
-88.2309595 -233.1174726 -82.0774370 -578.3899521 -141.0946623
36 37 38 39 40
-85.1930291 -238.7001913 73.2763005 -189.2439660 -189.3604048
41 42 43 44 45
-165.9381593 -215.9795050 529.8991455 -194.3533099 421.9779530
46 47 48 49 50
-169.4402969 765.3455071 -145.2079661 42.9833314 788.6073191
51 52 53 54 55
1111.6186061 -49.9325135 65.8698979 877.3634043 273.8156223
56 57 58 59 60
-235.0625236 -25.7698095 -1478.0304626 -2.3302906 -67.2100341
61 62 63 64 65
490.7434318 -22.2059265 1366.2863084 -20.2698745 255.3148533
66 67 68 69 70
-470.0643849 -170.2338992 314.8658179 222.0776424 267.0821810
71 72 73 74 75
13.5895784 -576.9774244 -249.2132512 -210.4273088 182.4501035
76 77 78 79 80
60.2526312 -11.1284026 258.7691221 11.9488448 -57.5442199
81 82 83 84 85
-149.6210256 19.2233602 -484.4626169 -358.0598714 -379.3556550
86 87 88 89 90
87.2077493 -77.8804084 209.1239879 29.6617353 -192.4623118
91 92 93 94 95
-250.3392129 -21.0950761 388.0978563 -267.3204428 -242.4063131
96 97 98 99 100
160.5827090 -213.7060924 871.2121671 -44.9489115 -116.1576981
101 102 103 104 105
46.7784508 461.7052750 -169.1852094 -72.0205059 -248.6151489
106 107 108 109 110
-398.8182936 324.1650705 321.2862420 122.5701304 -195.7224776
111 112 113 114 115
-112.3105228 -545.0662325 11.0814341 180.3095795 -317.0458449
116 117 118 119 120
277.7865779 5.2671632 91.5624732 -269.1043514 431.8798353
121 122 123 124 125
203.1031453 167.2731957 625.9023007 12.3594589 -544.1721132
126 127 128 129 130
-103.1586432 -70.4130413 158.3611494 -234.7327193 -48.1072071
131 132 133 134 135
69.1461050 42.0140873 -238.6460944 756.6540953 79.1431234
136 137 138 139 140
-337.4707162 -72.0181407 -64.9222086 134.7648395 -92.4452450
141 142 143 144 145
21.9187997 254.2357067 36.4482120 384.3621637 -77.0987144
146 147 148 149 150
553.9109593 -199.4321159 69.3117898 -97.0279717 80.7723786
151 152 153 154 155
-174.3574368 -511.0445444 158.9141314 143.8053521 -333.0380995
156 157 158 159 160
-74.3790826 -404.5663166 91.3652980 -6.5161534 -839.6583671
161 162 163 164 165
369.4757032 101.7115658 -223.2000068 354.3684784 150.6051411
166 167 168 169 170
-348.4882417 54.2119433 -399.6674716 -378.0800972 -347.9628718
171 172 173 174 175
684.5198057 -210.7121032 349.3922375 -1.1037190 220.9877039
176 177 178 179 180
305.7295450 309.9641678 -41.4549346 -219.7220479 -20.6594791
181 182 183 184 185
261.9315840 485.4548036 -179.2058613 -131.6214428 -102.1111976
186 187 188 189 190
-160.5245328 -170.5388783 -236.8788512 353.1536320 -158.6115387
191 192 193 194 195
-155.1571872 -63.3206739 404.4838794 530.4381415 -24.9924025
196 197 198 199 200
158.4538376 28.0157256 -138.5221157 236.1009433 -115.7809266
201 202 203 204 205
-282.7776286 -183.0648276 -81.1096116 -22.0061268 514.8702994
206 207 208 209 210
-84.0399691 71.7947070 -146.6370136 -150.6638507 -41.5142594
211 212 213 214 215
159.0494865 27.0273089 -39.6560395 -282.6268897 300.1442270
216 217 218 219 220
8.8493429 262.7477647 -32.1536827 -86.9460848 -256.4138573
221 222 223 224 225
101.7367811 414.0920853 892.3013951 -81.6384371 -211.0602931
226 227 228 229 230
263.8143782 -97.6494322 -11.7390782 309.2496426 571.9689779
231 232 233 234 235
62.9185478 197.4860775 377.3107155 75.4669865 36.1284502
236 237 238 239 240
-166.9154909 -221.3480959 32.7756400 210.2325020 -30.1927565
241 242 243 244 245
66.3965974 -250.5070292 -114.4543700 -112.3234196 -44.3861717
246 247 248 249 250
113.5499933 455.8734877 -302.7845971 -77.8988784 -40.2640218
251 252 253 254 255
-17.8244007 -82.0549394 -199.4254648 0.1766904 116.7603214
256 257 258 259 260
-102.7453570 20.6740452 -156.5061150 -231.4426328 -191.7888354
261 262 263 264 265
55.4612436 -50.3470857 -76.5458624 29.7201723 -118.7140983
266 267 268 269 270
-61.1261925 -44.1528551 -228.7423997 -456.6979730 -37.8031645
271 272 273 274 275
201.8663294 -167.0629902 159.6329920 -31.2191966 -101.6055846
276 277 278 279 280
246.9418931 -80.6068907 -144.4185090 185.1900942 -151.6468653
281 282 283 284 285
42.8528062 -169.0665633 205.1208569 -54.0955262 -152.2506093
286 287 288 289
270.2168182 115.9716019 -70.9610424 115.5349417
> postscript(file="/var/wessaorg/rcomp/tmp/6elnt1355868156.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 -471.6874076 NA
1 -444.0627384 -471.6874076
2 -128.4473462 -444.0627384
3 308.8967806 -128.4473462
4 -340.8778615 308.8967806
5 -247.2237718 -340.8778615
6 -0.3954483 -247.2237718
7 -176.3732701 -0.3954483
8 -34.3920197 -176.3732701
9 153.8700842 -34.3920197
10 -36.5437864 153.8700842
11 -443.6634533 -36.5437864
12 -324.3296286 -443.6634533
13 -12.6336347 -324.3296286
14 -31.5868230 -12.6336347
15 -254.3546172 -31.5868230
16 898.4739760 -254.3546172
17 -296.3027559 898.4739760
18 -239.5371129 -296.3027559
19 -290.0039576 -239.5371129
20 16.8357150 -290.0039576
21 1.4606144 16.8357150
22 -604.3289934 1.4606144
23 -181.7319814 -604.3289934
24 -15.4489320 -181.7319814
25 665.3782131 -15.4489320
26 256.7040392 665.3782131
27 69.8413497 256.7040392
28 -423.9268113 69.8413497
29 -30.3427095 -423.9268113
30 -88.2309595 -30.3427095
31 -233.1174726 -88.2309595
32 -82.0774370 -233.1174726
33 -578.3899521 -82.0774370
34 -141.0946623 -578.3899521
35 -85.1930291 -141.0946623
36 -238.7001913 -85.1930291
37 73.2763005 -238.7001913
38 -189.2439660 73.2763005
39 -189.3604048 -189.2439660
40 -165.9381593 -189.3604048
41 -215.9795050 -165.9381593
42 529.8991455 -215.9795050
43 -194.3533099 529.8991455
44 421.9779530 -194.3533099
45 -169.4402969 421.9779530
46 765.3455071 -169.4402969
47 -145.2079661 765.3455071
48 42.9833314 -145.2079661
49 788.6073191 42.9833314
50 1111.6186061 788.6073191
51 -49.9325135 1111.6186061
52 65.8698979 -49.9325135
53 877.3634043 65.8698979
54 273.8156223 877.3634043
55 -235.0625236 273.8156223
56 -25.7698095 -235.0625236
57 -1478.0304626 -25.7698095
58 -2.3302906 -1478.0304626
59 -67.2100341 -2.3302906
60 490.7434318 -67.2100341
61 -22.2059265 490.7434318
62 1366.2863084 -22.2059265
63 -20.2698745 1366.2863084
64 255.3148533 -20.2698745
65 -470.0643849 255.3148533
66 -170.2338992 -470.0643849
67 314.8658179 -170.2338992
68 222.0776424 314.8658179
69 267.0821810 222.0776424
70 13.5895784 267.0821810
71 -576.9774244 13.5895784
72 -249.2132512 -576.9774244
73 -210.4273088 -249.2132512
74 182.4501035 -210.4273088
75 60.2526312 182.4501035
76 -11.1284026 60.2526312
77 258.7691221 -11.1284026
78 11.9488448 258.7691221
79 -57.5442199 11.9488448
80 -149.6210256 -57.5442199
81 19.2233602 -149.6210256
82 -484.4626169 19.2233602
83 -358.0598714 -484.4626169
84 -379.3556550 -358.0598714
85 87.2077493 -379.3556550
86 -77.8804084 87.2077493
87 209.1239879 -77.8804084
88 29.6617353 209.1239879
89 -192.4623118 29.6617353
90 -250.3392129 -192.4623118
91 -21.0950761 -250.3392129
92 388.0978563 -21.0950761
93 -267.3204428 388.0978563
94 -242.4063131 -267.3204428
95 160.5827090 -242.4063131
96 -213.7060924 160.5827090
97 871.2121671 -213.7060924
98 -44.9489115 871.2121671
99 -116.1576981 -44.9489115
100 46.7784508 -116.1576981
101 461.7052750 46.7784508
102 -169.1852094 461.7052750
103 -72.0205059 -169.1852094
104 -248.6151489 -72.0205059
105 -398.8182936 -248.6151489
106 324.1650705 -398.8182936
107 321.2862420 324.1650705
108 122.5701304 321.2862420
109 -195.7224776 122.5701304
110 -112.3105228 -195.7224776
111 -545.0662325 -112.3105228
112 11.0814341 -545.0662325
113 180.3095795 11.0814341
114 -317.0458449 180.3095795
115 277.7865779 -317.0458449
116 5.2671632 277.7865779
117 91.5624732 5.2671632
118 -269.1043514 91.5624732
119 431.8798353 -269.1043514
120 203.1031453 431.8798353
121 167.2731957 203.1031453
122 625.9023007 167.2731957
123 12.3594589 625.9023007
124 -544.1721132 12.3594589
125 -103.1586432 -544.1721132
126 -70.4130413 -103.1586432
127 158.3611494 -70.4130413
128 -234.7327193 158.3611494
129 -48.1072071 -234.7327193
130 69.1461050 -48.1072071
131 42.0140873 69.1461050
132 -238.6460944 42.0140873
133 756.6540953 -238.6460944
134 79.1431234 756.6540953
135 -337.4707162 79.1431234
136 -72.0181407 -337.4707162
137 -64.9222086 -72.0181407
138 134.7648395 -64.9222086
139 -92.4452450 134.7648395
140 21.9187997 -92.4452450
141 254.2357067 21.9187997
142 36.4482120 254.2357067
143 384.3621637 36.4482120
144 -77.0987144 384.3621637
145 553.9109593 -77.0987144
146 -199.4321159 553.9109593
147 69.3117898 -199.4321159
148 -97.0279717 69.3117898
149 80.7723786 -97.0279717
150 -174.3574368 80.7723786
151 -511.0445444 -174.3574368
152 158.9141314 -511.0445444
153 143.8053521 158.9141314
154 -333.0380995 143.8053521
155 -74.3790826 -333.0380995
156 -404.5663166 -74.3790826
157 91.3652980 -404.5663166
158 -6.5161534 91.3652980
159 -839.6583671 -6.5161534
160 369.4757032 -839.6583671
161 101.7115658 369.4757032
162 -223.2000068 101.7115658
163 354.3684784 -223.2000068
164 150.6051411 354.3684784
165 -348.4882417 150.6051411
166 54.2119433 -348.4882417
167 -399.6674716 54.2119433
168 -378.0800972 -399.6674716
169 -347.9628718 -378.0800972
170 684.5198057 -347.9628718
171 -210.7121032 684.5198057
172 349.3922375 -210.7121032
173 -1.1037190 349.3922375
174 220.9877039 -1.1037190
175 305.7295450 220.9877039
176 309.9641678 305.7295450
177 -41.4549346 309.9641678
178 -219.7220479 -41.4549346
179 -20.6594791 -219.7220479
180 261.9315840 -20.6594791
181 485.4548036 261.9315840
182 -179.2058613 485.4548036
183 -131.6214428 -179.2058613
184 -102.1111976 -131.6214428
185 -160.5245328 -102.1111976
186 -170.5388783 -160.5245328
187 -236.8788512 -170.5388783
188 353.1536320 -236.8788512
189 -158.6115387 353.1536320
190 -155.1571872 -158.6115387
191 -63.3206739 -155.1571872
192 404.4838794 -63.3206739
193 530.4381415 404.4838794
194 -24.9924025 530.4381415
195 158.4538376 -24.9924025
196 28.0157256 158.4538376
197 -138.5221157 28.0157256
198 236.1009433 -138.5221157
199 -115.7809266 236.1009433
200 -282.7776286 -115.7809266
201 -183.0648276 -282.7776286
202 -81.1096116 -183.0648276
203 -22.0061268 -81.1096116
204 514.8702994 -22.0061268
205 -84.0399691 514.8702994
206 71.7947070 -84.0399691
207 -146.6370136 71.7947070
208 -150.6638507 -146.6370136
209 -41.5142594 -150.6638507
210 159.0494865 -41.5142594
211 27.0273089 159.0494865
212 -39.6560395 27.0273089
213 -282.6268897 -39.6560395
214 300.1442270 -282.6268897
215 8.8493429 300.1442270
216 262.7477647 8.8493429
217 -32.1536827 262.7477647
218 -86.9460848 -32.1536827
219 -256.4138573 -86.9460848
220 101.7367811 -256.4138573
221 414.0920853 101.7367811
222 892.3013951 414.0920853
223 -81.6384371 892.3013951
224 -211.0602931 -81.6384371
225 263.8143782 -211.0602931
226 -97.6494322 263.8143782
227 -11.7390782 -97.6494322
228 309.2496426 -11.7390782
229 571.9689779 309.2496426
230 62.9185478 571.9689779
231 197.4860775 62.9185478
232 377.3107155 197.4860775
233 75.4669865 377.3107155
234 36.1284502 75.4669865
235 -166.9154909 36.1284502
236 -221.3480959 -166.9154909
237 32.7756400 -221.3480959
238 210.2325020 32.7756400
239 -30.1927565 210.2325020
240 66.3965974 -30.1927565
241 -250.5070292 66.3965974
242 -114.4543700 -250.5070292
243 -112.3234196 -114.4543700
244 -44.3861717 -112.3234196
245 113.5499933 -44.3861717
246 455.8734877 113.5499933
247 -302.7845971 455.8734877
248 -77.8988784 -302.7845971
249 -40.2640218 -77.8988784
250 -17.8244007 -40.2640218
251 -82.0549394 -17.8244007
252 -199.4254648 -82.0549394
253 0.1766904 -199.4254648
254 116.7603214 0.1766904
255 -102.7453570 116.7603214
256 20.6740452 -102.7453570
257 -156.5061150 20.6740452
258 -231.4426328 -156.5061150
259 -191.7888354 -231.4426328
260 55.4612436 -191.7888354
261 -50.3470857 55.4612436
262 -76.5458624 -50.3470857
263 29.7201723 -76.5458624
264 -118.7140983 29.7201723
265 -61.1261925 -118.7140983
266 -44.1528551 -61.1261925
267 -228.7423997 -44.1528551
268 -456.6979730 -228.7423997
269 -37.8031645 -456.6979730
270 201.8663294 -37.8031645
271 -167.0629902 201.8663294
272 159.6329920 -167.0629902
273 -31.2191966 159.6329920
274 -101.6055846 -31.2191966
275 246.9418931 -101.6055846
276 -80.6068907 246.9418931
277 -144.4185090 -80.6068907
278 185.1900942 -144.4185090
279 -151.6468653 185.1900942
280 42.8528062 -151.6468653
281 -169.0665633 42.8528062
282 205.1208569 -169.0665633
283 -54.0955262 205.1208569
284 -152.2506093 -54.0955262
285 270.2168182 -152.2506093
286 115.9716019 270.2168182
287 -70.9610424 115.9716019
288 115.5349417 -70.9610424
289 NA 115.5349417
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -444.0627384 -471.6874076
[2,] -128.4473462 -444.0627384
[3,] 308.8967806 -128.4473462
[4,] -340.8778615 308.8967806
[5,] -247.2237718 -340.8778615
[6,] -0.3954483 -247.2237718
[7,] -176.3732701 -0.3954483
[8,] -34.3920197 -176.3732701
[9,] 153.8700842 -34.3920197
[10,] -36.5437864 153.8700842
[11,] -443.6634533 -36.5437864
[12,] -324.3296286 -443.6634533
[13,] -12.6336347 -324.3296286
[14,] -31.5868230 -12.6336347
[15,] -254.3546172 -31.5868230
[16,] 898.4739760 -254.3546172
[17,] -296.3027559 898.4739760
[18,] -239.5371129 -296.3027559
[19,] -290.0039576 -239.5371129
[20,] 16.8357150 -290.0039576
[21,] 1.4606144 16.8357150
[22,] -604.3289934 1.4606144
[23,] -181.7319814 -604.3289934
[24,] -15.4489320 -181.7319814
[25,] 665.3782131 -15.4489320
[26,] 256.7040392 665.3782131
[27,] 69.8413497 256.7040392
[28,] -423.9268113 69.8413497
[29,] -30.3427095 -423.9268113
[30,] -88.2309595 -30.3427095
[31,] -233.1174726 -88.2309595
[32,] -82.0774370 -233.1174726
[33,] -578.3899521 -82.0774370
[34,] -141.0946623 -578.3899521
[35,] -85.1930291 -141.0946623
[36,] -238.7001913 -85.1930291
[37,] 73.2763005 -238.7001913
[38,] -189.2439660 73.2763005
[39,] -189.3604048 -189.2439660
[40,] -165.9381593 -189.3604048
[41,] -215.9795050 -165.9381593
[42,] 529.8991455 -215.9795050
[43,] -194.3533099 529.8991455
[44,] 421.9779530 -194.3533099
[45,] -169.4402969 421.9779530
[46,] 765.3455071 -169.4402969
[47,] -145.2079661 765.3455071
[48,] 42.9833314 -145.2079661
[49,] 788.6073191 42.9833314
[50,] 1111.6186061 788.6073191
[51,] -49.9325135 1111.6186061
[52,] 65.8698979 -49.9325135
[53,] 877.3634043 65.8698979
[54,] 273.8156223 877.3634043
[55,] -235.0625236 273.8156223
[56,] -25.7698095 -235.0625236
[57,] -1478.0304626 -25.7698095
[58,] -2.3302906 -1478.0304626
[59,] -67.2100341 -2.3302906
[60,] 490.7434318 -67.2100341
[61,] -22.2059265 490.7434318
[62,] 1366.2863084 -22.2059265
[63,] -20.2698745 1366.2863084
[64,] 255.3148533 -20.2698745
[65,] -470.0643849 255.3148533
[66,] -170.2338992 -470.0643849
[67,] 314.8658179 -170.2338992
[68,] 222.0776424 314.8658179
[69,] 267.0821810 222.0776424
[70,] 13.5895784 267.0821810
[71,] -576.9774244 13.5895784
[72,] -249.2132512 -576.9774244
[73,] -210.4273088 -249.2132512
[74,] 182.4501035 -210.4273088
[75,] 60.2526312 182.4501035
[76,] -11.1284026 60.2526312
[77,] 258.7691221 -11.1284026
[78,] 11.9488448 258.7691221
[79,] -57.5442199 11.9488448
[80,] -149.6210256 -57.5442199
[81,] 19.2233602 -149.6210256
[82,] -484.4626169 19.2233602
[83,] -358.0598714 -484.4626169
[84,] -379.3556550 -358.0598714
[85,] 87.2077493 -379.3556550
[86,] -77.8804084 87.2077493
[87,] 209.1239879 -77.8804084
[88,] 29.6617353 209.1239879
[89,] -192.4623118 29.6617353
[90,] -250.3392129 -192.4623118
[91,] -21.0950761 -250.3392129
[92,] 388.0978563 -21.0950761
[93,] -267.3204428 388.0978563
[94,] -242.4063131 -267.3204428
[95,] 160.5827090 -242.4063131
[96,] -213.7060924 160.5827090
[97,] 871.2121671 -213.7060924
[98,] -44.9489115 871.2121671
[99,] -116.1576981 -44.9489115
[100,] 46.7784508 -116.1576981
[101,] 461.7052750 46.7784508
[102,] -169.1852094 461.7052750
[103,] -72.0205059 -169.1852094
[104,] -248.6151489 -72.0205059
[105,] -398.8182936 -248.6151489
[106,] 324.1650705 -398.8182936
[107,] 321.2862420 324.1650705
[108,] 122.5701304 321.2862420
[109,] -195.7224776 122.5701304
[110,] -112.3105228 -195.7224776
[111,] -545.0662325 -112.3105228
[112,] 11.0814341 -545.0662325
[113,] 180.3095795 11.0814341
[114,] -317.0458449 180.3095795
[115,] 277.7865779 -317.0458449
[116,] 5.2671632 277.7865779
[117,] 91.5624732 5.2671632
[118,] -269.1043514 91.5624732
[119,] 431.8798353 -269.1043514
[120,] 203.1031453 431.8798353
[121,] 167.2731957 203.1031453
[122,] 625.9023007 167.2731957
[123,] 12.3594589 625.9023007
[124,] -544.1721132 12.3594589
[125,] -103.1586432 -544.1721132
[126,] -70.4130413 -103.1586432
[127,] 158.3611494 -70.4130413
[128,] -234.7327193 158.3611494
[129,] -48.1072071 -234.7327193
[130,] 69.1461050 -48.1072071
[131,] 42.0140873 69.1461050
[132,] -238.6460944 42.0140873
[133,] 756.6540953 -238.6460944
[134,] 79.1431234 756.6540953
[135,] -337.4707162 79.1431234
[136,] -72.0181407 -337.4707162
[137,] -64.9222086 -72.0181407
[138,] 134.7648395 -64.9222086
[139,] -92.4452450 134.7648395
[140,] 21.9187997 -92.4452450
[141,] 254.2357067 21.9187997
[142,] 36.4482120 254.2357067
[143,] 384.3621637 36.4482120
[144,] -77.0987144 384.3621637
[145,] 553.9109593 -77.0987144
[146,] -199.4321159 553.9109593
[147,] 69.3117898 -199.4321159
[148,] -97.0279717 69.3117898
[149,] 80.7723786 -97.0279717
[150,] -174.3574368 80.7723786
[151,] -511.0445444 -174.3574368
[152,] 158.9141314 -511.0445444
[153,] 143.8053521 158.9141314
[154,] -333.0380995 143.8053521
[155,] -74.3790826 -333.0380995
[156,] -404.5663166 -74.3790826
[157,] 91.3652980 -404.5663166
[158,] -6.5161534 91.3652980
[159,] -839.6583671 -6.5161534
[160,] 369.4757032 -839.6583671
[161,] 101.7115658 369.4757032
[162,] -223.2000068 101.7115658
[163,] 354.3684784 -223.2000068
[164,] 150.6051411 354.3684784
[165,] -348.4882417 150.6051411
[166,] 54.2119433 -348.4882417
[167,] -399.6674716 54.2119433
[168,] -378.0800972 -399.6674716
[169,] -347.9628718 -378.0800972
[170,] 684.5198057 -347.9628718
[171,] -210.7121032 684.5198057
[172,] 349.3922375 -210.7121032
[173,] -1.1037190 349.3922375
[174,] 220.9877039 -1.1037190
[175,] 305.7295450 220.9877039
[176,] 309.9641678 305.7295450
[177,] -41.4549346 309.9641678
[178,] -219.7220479 -41.4549346
[179,] -20.6594791 -219.7220479
[180,] 261.9315840 -20.6594791
[181,] 485.4548036 261.9315840
[182,] -179.2058613 485.4548036
[183,] -131.6214428 -179.2058613
[184,] -102.1111976 -131.6214428
[185,] -160.5245328 -102.1111976
[186,] -170.5388783 -160.5245328
[187,] -236.8788512 -170.5388783
[188,] 353.1536320 -236.8788512
[189,] -158.6115387 353.1536320
[190,] -155.1571872 -158.6115387
[191,] -63.3206739 -155.1571872
[192,] 404.4838794 -63.3206739
[193,] 530.4381415 404.4838794
[194,] -24.9924025 530.4381415
[195,] 158.4538376 -24.9924025
[196,] 28.0157256 158.4538376
[197,] -138.5221157 28.0157256
[198,] 236.1009433 -138.5221157
[199,] -115.7809266 236.1009433
[200,] -282.7776286 -115.7809266
[201,] -183.0648276 -282.7776286
[202,] -81.1096116 -183.0648276
[203,] -22.0061268 -81.1096116
[204,] 514.8702994 -22.0061268
[205,] -84.0399691 514.8702994
[206,] 71.7947070 -84.0399691
[207,] -146.6370136 71.7947070
[208,] -150.6638507 -146.6370136
[209,] -41.5142594 -150.6638507
[210,] 159.0494865 -41.5142594
[211,] 27.0273089 159.0494865
[212,] -39.6560395 27.0273089
[213,] -282.6268897 -39.6560395
[214,] 300.1442270 -282.6268897
[215,] 8.8493429 300.1442270
[216,] 262.7477647 8.8493429
[217,] -32.1536827 262.7477647
[218,] -86.9460848 -32.1536827
[219,] -256.4138573 -86.9460848
[220,] 101.7367811 -256.4138573
[221,] 414.0920853 101.7367811
[222,] 892.3013951 414.0920853
[223,] -81.6384371 892.3013951
[224,] -211.0602931 -81.6384371
[225,] 263.8143782 -211.0602931
[226,] -97.6494322 263.8143782
[227,] -11.7390782 -97.6494322
[228,] 309.2496426 -11.7390782
[229,] 571.9689779 309.2496426
[230,] 62.9185478 571.9689779
[231,] 197.4860775 62.9185478
[232,] 377.3107155 197.4860775
[233,] 75.4669865 377.3107155
[234,] 36.1284502 75.4669865
[235,] -166.9154909 36.1284502
[236,] -221.3480959 -166.9154909
[237,] 32.7756400 -221.3480959
[238,] 210.2325020 32.7756400
[239,] -30.1927565 210.2325020
[240,] 66.3965974 -30.1927565
[241,] -250.5070292 66.3965974
[242,] -114.4543700 -250.5070292
[243,] -112.3234196 -114.4543700
[244,] -44.3861717 -112.3234196
[245,] 113.5499933 -44.3861717
[246,] 455.8734877 113.5499933
[247,] -302.7845971 455.8734877
[248,] -77.8988784 -302.7845971
[249,] -40.2640218 -77.8988784
[250,] -17.8244007 -40.2640218
[251,] -82.0549394 -17.8244007
[252,] -199.4254648 -82.0549394
[253,] 0.1766904 -199.4254648
[254,] 116.7603214 0.1766904
[255,] -102.7453570 116.7603214
[256,] 20.6740452 -102.7453570
[257,] -156.5061150 20.6740452
[258,] -231.4426328 -156.5061150
[259,] -191.7888354 -231.4426328
[260,] 55.4612436 -191.7888354
[261,] -50.3470857 55.4612436
[262,] -76.5458624 -50.3470857
[263,] 29.7201723 -76.5458624
[264,] -118.7140983 29.7201723
[265,] -61.1261925 -118.7140983
[266,] -44.1528551 -61.1261925
[267,] -228.7423997 -44.1528551
[268,] -456.6979730 -228.7423997
[269,] -37.8031645 -456.6979730
[270,] 201.8663294 -37.8031645
[271,] -167.0629902 201.8663294
[272,] 159.6329920 -167.0629902
[273,] -31.2191966 159.6329920
[274,] -101.6055846 -31.2191966
[275,] 246.9418931 -101.6055846
[276,] -80.6068907 246.9418931
[277,] -144.4185090 -80.6068907
[278,] 185.1900942 -144.4185090
[279,] -151.6468653 185.1900942
[280,] 42.8528062 -151.6468653
[281,] -169.0665633 42.8528062
[282,] 205.1208569 -169.0665633
[283,] -54.0955262 205.1208569
[284,] -152.2506093 -54.0955262
[285,] 270.2168182 -152.2506093
[286,] 115.9716019 270.2168182
[287,] -70.9610424 115.9716019
[288,] 115.5349417 -70.9610424
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -444.0627384 -471.6874076
2 -128.4473462 -444.0627384
3 308.8967806 -128.4473462
4 -340.8778615 308.8967806
5 -247.2237718 -340.8778615
6 -0.3954483 -247.2237718
7 -176.3732701 -0.3954483
8 -34.3920197 -176.3732701
9 153.8700842 -34.3920197
10 -36.5437864 153.8700842
11 -443.6634533 -36.5437864
12 -324.3296286 -443.6634533
13 -12.6336347 -324.3296286
14 -31.5868230 -12.6336347
15 -254.3546172 -31.5868230
16 898.4739760 -254.3546172
17 -296.3027559 898.4739760
18 -239.5371129 -296.3027559
19 -290.0039576 -239.5371129
20 16.8357150 -290.0039576
21 1.4606144 16.8357150
22 -604.3289934 1.4606144
23 -181.7319814 -604.3289934
24 -15.4489320 -181.7319814
25 665.3782131 -15.4489320
26 256.7040392 665.3782131
27 69.8413497 256.7040392
28 -423.9268113 69.8413497
29 -30.3427095 -423.9268113
30 -88.2309595 -30.3427095
31 -233.1174726 -88.2309595
32 -82.0774370 -233.1174726
33 -578.3899521 -82.0774370
34 -141.0946623 -578.3899521
35 -85.1930291 -141.0946623
36 -238.7001913 -85.1930291
37 73.2763005 -238.7001913
38 -189.2439660 73.2763005
39 -189.3604048 -189.2439660
40 -165.9381593 -189.3604048
41 -215.9795050 -165.9381593
42 529.8991455 -215.9795050
43 -194.3533099 529.8991455
44 421.9779530 -194.3533099
45 -169.4402969 421.9779530
46 765.3455071 -169.4402969
47 -145.2079661 765.3455071
48 42.9833314 -145.2079661
49 788.6073191 42.9833314
50 1111.6186061 788.6073191
51 -49.9325135 1111.6186061
52 65.8698979 -49.9325135
53 877.3634043 65.8698979
54 273.8156223 877.3634043
55 -235.0625236 273.8156223
56 -25.7698095 -235.0625236
57 -1478.0304626 -25.7698095
58 -2.3302906 -1478.0304626
59 -67.2100341 -2.3302906
60 490.7434318 -67.2100341
61 -22.2059265 490.7434318
62 1366.2863084 -22.2059265
63 -20.2698745 1366.2863084
64 255.3148533 -20.2698745
65 -470.0643849 255.3148533
66 -170.2338992 -470.0643849
67 314.8658179 -170.2338992
68 222.0776424 314.8658179
69 267.0821810 222.0776424
70 13.5895784 267.0821810
71 -576.9774244 13.5895784
72 -249.2132512 -576.9774244
73 -210.4273088 -249.2132512
74 182.4501035 -210.4273088
75 60.2526312 182.4501035
76 -11.1284026 60.2526312
77 258.7691221 -11.1284026
78 11.9488448 258.7691221
79 -57.5442199 11.9488448
80 -149.6210256 -57.5442199
81 19.2233602 -149.6210256
82 -484.4626169 19.2233602
83 -358.0598714 -484.4626169
84 -379.3556550 -358.0598714
85 87.2077493 -379.3556550
86 -77.8804084 87.2077493
87 209.1239879 -77.8804084
88 29.6617353 209.1239879
89 -192.4623118 29.6617353
90 -250.3392129 -192.4623118
91 -21.0950761 -250.3392129
92 388.0978563 -21.0950761
93 -267.3204428 388.0978563
94 -242.4063131 -267.3204428
95 160.5827090 -242.4063131
96 -213.7060924 160.5827090
97 871.2121671 -213.7060924
98 -44.9489115 871.2121671
99 -116.1576981 -44.9489115
100 46.7784508 -116.1576981
101 461.7052750 46.7784508
102 -169.1852094 461.7052750
103 -72.0205059 -169.1852094
104 -248.6151489 -72.0205059
105 -398.8182936 -248.6151489
106 324.1650705 -398.8182936
107 321.2862420 324.1650705
108 122.5701304 321.2862420
109 -195.7224776 122.5701304
110 -112.3105228 -195.7224776
111 -545.0662325 -112.3105228
112 11.0814341 -545.0662325
113 180.3095795 11.0814341
114 -317.0458449 180.3095795
115 277.7865779 -317.0458449
116 5.2671632 277.7865779
117 91.5624732 5.2671632
118 -269.1043514 91.5624732
119 431.8798353 -269.1043514
120 203.1031453 431.8798353
121 167.2731957 203.1031453
122 625.9023007 167.2731957
123 12.3594589 625.9023007
124 -544.1721132 12.3594589
125 -103.1586432 -544.1721132
126 -70.4130413 -103.1586432
127 158.3611494 -70.4130413
128 -234.7327193 158.3611494
129 -48.1072071 -234.7327193
130 69.1461050 -48.1072071
131 42.0140873 69.1461050
132 -238.6460944 42.0140873
133 756.6540953 -238.6460944
134 79.1431234 756.6540953
135 -337.4707162 79.1431234
136 -72.0181407 -337.4707162
137 -64.9222086 -72.0181407
138 134.7648395 -64.9222086
139 -92.4452450 134.7648395
140 21.9187997 -92.4452450
141 254.2357067 21.9187997
142 36.4482120 254.2357067
143 384.3621637 36.4482120
144 -77.0987144 384.3621637
145 553.9109593 -77.0987144
146 -199.4321159 553.9109593
147 69.3117898 -199.4321159
148 -97.0279717 69.3117898
149 80.7723786 -97.0279717
150 -174.3574368 80.7723786
151 -511.0445444 -174.3574368
152 158.9141314 -511.0445444
153 143.8053521 158.9141314
154 -333.0380995 143.8053521
155 -74.3790826 -333.0380995
156 -404.5663166 -74.3790826
157 91.3652980 -404.5663166
158 -6.5161534 91.3652980
159 -839.6583671 -6.5161534
160 369.4757032 -839.6583671
161 101.7115658 369.4757032
162 -223.2000068 101.7115658
163 354.3684784 -223.2000068
164 150.6051411 354.3684784
165 -348.4882417 150.6051411
166 54.2119433 -348.4882417
167 -399.6674716 54.2119433
168 -378.0800972 -399.6674716
169 -347.9628718 -378.0800972
170 684.5198057 -347.9628718
171 -210.7121032 684.5198057
172 349.3922375 -210.7121032
173 -1.1037190 349.3922375
174 220.9877039 -1.1037190
175 305.7295450 220.9877039
176 309.9641678 305.7295450
177 -41.4549346 309.9641678
178 -219.7220479 -41.4549346
179 -20.6594791 -219.7220479
180 261.9315840 -20.6594791
181 485.4548036 261.9315840
182 -179.2058613 485.4548036
183 -131.6214428 -179.2058613
184 -102.1111976 -131.6214428
185 -160.5245328 -102.1111976
186 -170.5388783 -160.5245328
187 -236.8788512 -170.5388783
188 353.1536320 -236.8788512
189 -158.6115387 353.1536320
190 -155.1571872 -158.6115387
191 -63.3206739 -155.1571872
192 404.4838794 -63.3206739
193 530.4381415 404.4838794
194 -24.9924025 530.4381415
195 158.4538376 -24.9924025
196 28.0157256 158.4538376
197 -138.5221157 28.0157256
198 236.1009433 -138.5221157
199 -115.7809266 236.1009433
200 -282.7776286 -115.7809266
201 -183.0648276 -282.7776286
202 -81.1096116 -183.0648276
203 -22.0061268 -81.1096116
204 514.8702994 -22.0061268
205 -84.0399691 514.8702994
206 71.7947070 -84.0399691
207 -146.6370136 71.7947070
208 -150.6638507 -146.6370136
209 -41.5142594 -150.6638507
210 159.0494865 -41.5142594
211 27.0273089 159.0494865
212 -39.6560395 27.0273089
213 -282.6268897 -39.6560395
214 300.1442270 -282.6268897
215 8.8493429 300.1442270
216 262.7477647 8.8493429
217 -32.1536827 262.7477647
218 -86.9460848 -32.1536827
219 -256.4138573 -86.9460848
220 101.7367811 -256.4138573
221 414.0920853 101.7367811
222 892.3013951 414.0920853
223 -81.6384371 892.3013951
224 -211.0602931 -81.6384371
225 263.8143782 -211.0602931
226 -97.6494322 263.8143782
227 -11.7390782 -97.6494322
228 309.2496426 -11.7390782
229 571.9689779 309.2496426
230 62.9185478 571.9689779
231 197.4860775 62.9185478
232 377.3107155 197.4860775
233 75.4669865 377.3107155
234 36.1284502 75.4669865
235 -166.9154909 36.1284502
236 -221.3480959 -166.9154909
237 32.7756400 -221.3480959
238 210.2325020 32.7756400
239 -30.1927565 210.2325020
240 66.3965974 -30.1927565
241 -250.5070292 66.3965974
242 -114.4543700 -250.5070292
243 -112.3234196 -114.4543700
244 -44.3861717 -112.3234196
245 113.5499933 -44.3861717
246 455.8734877 113.5499933
247 -302.7845971 455.8734877
248 -77.8988784 -302.7845971
249 -40.2640218 -77.8988784
250 -17.8244007 -40.2640218
251 -82.0549394 -17.8244007
252 -199.4254648 -82.0549394
253 0.1766904 -199.4254648
254 116.7603214 0.1766904
255 -102.7453570 116.7603214
256 20.6740452 -102.7453570
257 -156.5061150 20.6740452
258 -231.4426328 -156.5061150
259 -191.7888354 -231.4426328
260 55.4612436 -191.7888354
261 -50.3470857 55.4612436
262 -76.5458624 -50.3470857
263 29.7201723 -76.5458624
264 -118.7140983 29.7201723
265 -61.1261925 -118.7140983
266 -44.1528551 -61.1261925
267 -228.7423997 -44.1528551
268 -456.6979730 -228.7423997
269 -37.8031645 -456.6979730
270 201.8663294 -37.8031645
271 -167.0629902 201.8663294
272 159.6329920 -167.0629902
273 -31.2191966 159.6329920
274 -101.6055846 -31.2191966
275 246.9418931 -101.6055846
276 -80.6068907 246.9418931
277 -144.4185090 -80.6068907
278 185.1900942 -144.4185090
279 -151.6468653 185.1900942
280 42.8528062 -151.6468653
281 -169.0665633 42.8528062
282 205.1208569 -169.0665633
283 -54.0955262 205.1208569
284 -152.2506093 -54.0955262
285 270.2168182 -152.2506093
286 115.9716019 270.2168182
287 -70.9610424 115.9716019
288 115.5349417 -70.9610424
> 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/7sboz1355868156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8drgj1355868156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9sy151355868156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/107av31355868156.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11n3um1355868156.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/12daxx1355868156.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/13avt61355868156.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/146fnq1355868157.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/156wgr1355868157.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/16tbju1355868157.tab")
+ }
>
> try(system("convert tmp/1c9e91355868156.ps tmp/1c9e91355868156.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lir01355868156.ps tmp/2lir01355868156.png",intern=TRUE))
character(0)
> try(system("convert tmp/3adeb1355868156.ps tmp/3adeb1355868156.png",intern=TRUE))
character(0)
> try(system("convert tmp/4dtm31355868156.ps tmp/4dtm31355868156.png",intern=TRUE))
character(0)
> try(system("convert tmp/5eefc1355868156.ps tmp/5eefc1355868156.png",intern=TRUE))
character(0)
> try(system("convert tmp/6elnt1355868156.ps tmp/6elnt1355868156.png",intern=TRUE))
character(0)
> try(system("convert tmp/7sboz1355868156.ps tmp/7sboz1355868156.png",intern=TRUE))
character(0)
> try(system("convert tmp/8drgj1355868156.ps tmp/8drgj1355868156.png",intern=TRUE))
character(0)
> try(system("convert tmp/9sy151355868156.ps tmp/9sy151355868156.png",intern=TRUE))
character(0)
> try(system("convert tmp/107av31355868156.ps tmp/107av31355868156.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
14.24 1.37 15.68