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(1683
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+ ,22)
+ ,dim=c(8
+ ,144)
+ ,dimnames=list(c('pageviews'
+ ,'timeRFC'
+ ,'logins'
+ ,'CCV'
+ ,'CV'
+ ,'Cauthors'
+ ,'bloggedC'
+ ,'reviewedC')
+ ,1:144))
> y <- array(NA,dim=c(8,144),dimnames=list(c('pageviews','timeRFC','logins','CCV','CV','Cauthors','bloggedC','reviewedC'),1:144))
> 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 = '2'
> #'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
timeRFC pageviews logins CCV CV Cauthors bloggedC reviewedC
1 150596 1683 84 535 109 0 37 18
2 154801 1323 50 396 73 1 42 20
3 7215 192 18 72 1 0 0 0
4 122139 2172 91 617 154 0 49 26
5 221399 3335 129 1118 124 0 76 30
6 441870 6310 237 1755 276 1 118 34
7 134379 1478 52 498 89 1 42 23
8 140428 1324 53 355 54 0 57 30
9 103255 1488 40 413 87 0 45 30
10 271630 2756 91 891 129 1 67 26
11 121593 1931 71 629 158 2 50 24
12 172071 1966 63 611 113 0 71 30
13 83707 1575 94 564 75 0 41 19
14 197412 2855 98 964 255 4 66 25
15 134398 1263 48 362 50 4 42 17
16 139224 1479 73 442 81 3 54 19
17 134153 1636 52 391 92 0 75 33
18 64149 1076 52 305 72 5 0 15
19 122294 2376 82 721 142 0 54 34
20 24889 678 22 206 47 0 13 15
21 52197 902 52 310 40 0 16 15
22 188915 2308 89 686 94 0 77 27
23 163147 1590 66 572 127 0 34 25
24 98575 1863 48 558 164 1 38 34
25 143546 1799 80 569 41 1 50 21
26 139780 1385 25 513 160 0 39 21
27 163784 1870 146 602 90 0 54 25
28 152479 1161 75 276 55 0 67 28
29 304108 2417 109 791 78 0 55 26
30 184024 1952 40 815 90 0 52 20
31 151621 1514 41 427 76 0 50 28
32 164516 1487 41 496 111 2 54 20
33 120179 2051 94 653 87 4 53 17
34 214701 2843 116 857 302 0 76 25
35 196865 2216 48 736 84 1 52 24
36 0 1 1 0 0 0 0 0
37 181527 1830 57 862 58 0 46 27
38 93107 1563 49 483 137 3 44 14
39 129352 2046 45 495 267 9 35 32
40 229143 2005 58 749 56 0 82 31
41 177063 1934 67 627 94 2 70 21
42 126602 1572 53 597 62 0 31 34
43 93742 950 29 348 35 2 25 23
44 152153 1877 72 711 59 1 48 24
45 95704 1036 42 322 46 2 44 22
46 139793 1097 84 280 40 2 40 22
47 76348 730 30 205 49 1 23 35
48 188980 1918 86 648 114 0 63 21
49 172100 1826 79 580 113 1 43 31
50 146552 2444 54 875 171 7 62 26
51 48188 658 28 205 37 0 12 22
52 109185 1425 60 363 51 0 63 21
53 263652 2246 68 757 89 0 60 27
54 215609 1899 75 647 67 0 53 26
55 174876 1630 54 584 49 1 53 33
56 115124 1496 49 457 74 6 35 11
57 179712 1681 60 438 58 0 49 26
58 70369 816 20 235 72 0 25 26
59 109215 902 58 312 30 0 47 21
60 166096 2606 85 877 59 10 30 38
61 130414 1557 51 454 65 6 50 29
62 102057 1780 71 668 81 0 36 19
63 115310 1265 56 346 84 11 43 19
64 101181 1117 32 377 46 3 44 24
65 135228 1069 31 365 56 0 14 26
66 94982 1229 37 391 36 0 38 29
67 166919 2155 67 476 84 8 58 34
68 118169 2500 64 747 152 2 68 25
69 102361 1003 36 246 48 0 48 24
70 31970 340 15 101 40 0 5 21
71 200413 2586 107 901 135 3 53 19
72 103381 1119 58 334 80 1 36 12
73 94940 1251 61 404 60 2 62 28
74 101560 1516 65 442 89 1 46 21
75 144176 2473 60 627 89 0 67 34
76 71921 1288 37 345 79 2 2 32
77 126905 1911 54 538 111 1 64 27
78 131184 2279 87 741 67 0 59 26
79 60138 816 23 253 76 0 16 21
80 84971 1234 71 395 105 0 34 31
81 80420 907 64 211 49 0 54 26
82 233569 1827 57 670 57 0 39 26
83 56252 841 25 244 49 0 26 23
84 97181 1309 32 438 132 0 37 25
85 50800 764 41 255 49 0 17 22
86 125941 1439 45 434 71 0 32 26
87 211032 2500 210 613 100 0 55 33
88 71960 974 92 233 71 0 39 22
89 90379 1152 53 360 49 6 39 24
90 125650 1261 47 486 72 0 28 21
91 115572 1508 36 535 59 5 45 28
92 136266 2005 67 585 86 1 66 22
93 146715 1191 55 402 65 0 39 22
94 124626 1265 57 466 81 0 27 15
95 49176 761 33 291 30 0 22 13
96 212926 2156 102 691 166 0 43 36
97 173884 1689 55 515 89 0 88 24
98 19349 223 12 67 15 0 13 1
99 181141 2074 95 712 104 3 23 24
100 145502 1879 70 770 61 0 40 31
101 45448 566 26 247 11 0 8 4
102 58280 802 20 240 44 0 41 20
103 115944 1131 44 360 84 0 51 23
104 94341 981 52 249 66 1 24 23
105 59090 591 37 138 27 0 23 12
106 27676 596 22 194 59 0 2 16
107 120586 1261 41 285 126 0 78 28
108 88011 861 31 227 32 0 12 10
109 0 0 0 0 0 0 0 0
110 85610 1030 31 306 58 0 46 25
111 84193 991 58 328 52 0 22 21
112 117769 1178 39 397 49 0 49 21
113 107653 1200 56 369 64 0 52 21
114 71894 849 57 287 71 0 36 21
115 3616 78 5 14 5 0 0 0
116 0 0 0 0 0 0 0 0
117 154806 924 38 301 70 0 35 23
118 136061 1480 73 535 72 0 68 29
119 141822 1870 89 530 118 1 26 27
120 106515 861 37 272 56 0 32 23
121 43410 778 19 292 63 0 7 1
122 146920 1533 64 458 88 1 67 25
123 88874 889 38 241 46 0 30 17
124 111924 1705 49 497 60 8 55 29
125 60373 700 39 165 29 3 3 12
126 19764 285 12 75 19 1 10 2
127 121665 1490 46 461 58 2 46 18
128 108685 981 26 341 66 0 23 25
129 124493 1368 37 446 97 0 43 29
130 11796 256 9 79 22 0 1 2
131 10674 98 9 33 7 0 0 0
132 131263 1317 52 449 37 0 33 18
133 6836 41 3 11 5 0 0 1
134 153278 1768 55 606 48 5 48 21
135 5118 42 3 6 1 0 5 0
136 40248 528 16 183 34 1 8 4
137 0 0 0 0 0 0 0 0
138 100728 938 42 310 49 0 25 25
139 84267 1245 36 245 44 0 21 26
140 7131 81 4 27 0 1 0 0
141 8812 257 13 97 18 0 0 4
142 63952 891 22 247 48 1 15 17
143 120111 1114 47 273 54 0 47 21
144 94127 1079 18 386 50 1 17 22
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) pageviews logins CCV CV Cauthors
2405.20 21.48 205.04 108.68 -134.76 -1648.99
bloggedC reviewedC
609.77 676.24
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-66843 -17467 -820 12644 100851
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2405.20 5957.34 0.404 0.687040
pageviews 21.48 15.31 1.404 0.162713
logins 205.04 128.94 1.590 0.114106
CCV 108.68 35.61 3.052 0.002731 **
CV -134.76 70.99 -1.898 0.059765 .
Cauthors -1648.99 1146.27 -1.439 0.152568
bloggedC 609.77 175.03 3.484 0.000665 ***
reviewedC 676.24 349.41 1.935 0.055019 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 27460 on 136 degrees of freedom
Multiple R-squared: 0.8372, Adjusted R-squared: 0.8288
F-statistic: 99.9 on 7 and 136 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,] 0.9514248 9.715035e-02 4.857517e-02
[2,] 0.9399056 1.201889e-01 6.009445e-02
[3,] 0.9346796 1.306408e-01 6.532039e-02
[4,] 0.9013656 1.972687e-01 9.863436e-02
[5,] 0.8723525 2.552951e-01 1.276475e-01
[6,] 0.8150040 3.699920e-01 1.849960e-01
[7,] 0.8200412 3.599177e-01 1.799588e-01
[8,] 0.7522193 4.955614e-01 2.477807e-01
[9,] 0.7846373 4.307254e-01 2.153627e-01
[10,] 0.7604133 4.791735e-01 2.395867e-01
[11,] 0.7018331 5.963338e-01 2.981669e-01
[12,] 0.6494167 7.011666e-01 3.505833e-01
[13,] 0.8958647 2.082706e-01 1.041353e-01
[14,] 0.8788213 2.423575e-01 1.211787e-01
[15,] 0.8467024 3.065952e-01 1.532976e-01
[16,] 0.8306519 3.386961e-01 1.693481e-01
[17,] 0.8569072 2.861855e-01 1.430928e-01
[18,] 0.8511048 2.977905e-01 1.488952e-01
[19,] 0.9986352 2.729678e-03 1.364839e-03
[20,] 0.9978862 4.227648e-03 2.113824e-03
[21,] 0.9974425 5.115057e-03 2.557529e-03
[22,] 0.9973711 5.257890e-03 2.628945e-03
[23,] 0.9990930 1.814073e-03 9.070364e-04
[24,] 0.9986555 2.688916e-03 1.344458e-03
[25,] 0.9981792 3.641634e-03 1.820817e-03
[26,] 0.9972619 5.476287e-03 2.738143e-03
[27,] 0.9958324 8.335277e-03 4.167639e-03
[28,] 0.9953827 9.234689e-03 4.617344e-03
[29,] 0.9952604 9.479150e-03 4.739575e-03
[30,] 0.9942313 1.153736e-02 5.768678e-03
[31,] 0.9920960 1.580798e-02 7.903989e-03
[32,] 0.9894857 2.102868e-02 1.051434e-02
[33,] 0.9851580 2.968398e-02 1.484199e-02
[34,] 0.9819576 3.608484e-02 1.804242e-02
[35,] 0.9758978 4.820431e-02 2.410216e-02
[36,] 0.9803178 3.936439e-02 1.968220e-02
[37,] 0.9735980 5.280410e-02 2.640205e-02
[38,] 0.9689757 6.204851e-02 3.102425e-02
[39,] 0.9666580 6.668396e-02 3.334198e-02
[40,] 0.9759731 4.805383e-02 2.402691e-02
[41,] 0.9692678 6.146441e-02 3.073221e-02
[42,] 0.9683387 6.332263e-02 3.166131e-02
[43,] 0.9956176 8.764847e-03 4.382423e-03
[44,] 0.9979742 4.051671e-03 2.025836e-03
[45,] 0.9974966 5.006747e-03 2.503374e-03
[46,] 0.9965464 6.907151e-03 3.453576e-03
[47,] 0.9981799 3.640156e-03 1.820078e-03
[48,] 0.9973213 5.357500e-03 2.678750e-03
[49,] 0.9961611 7.677849e-03 3.838924e-03
[50,] 0.9957575 8.485034e-03 4.242517e-03
[51,] 0.9939232 1.215370e-02 6.076848e-03
[52,] 0.9969276 6.144861e-03 3.072431e-03
[53,] 0.9964426 7.114703e-03 3.557352e-03
[54,] 0.9950521 9.895829e-03 4.947914e-03
[55,] 0.9975405 4.918986e-03 2.459493e-03
[56,] 0.9971548 5.690386e-03 2.845193e-03
[57,] 0.9974070 5.185911e-03 2.592955e-03
[58,] 0.9996944 6.112170e-04 3.056085e-04
[59,] 0.9995744 8.512945e-04 4.256473e-04
[60,] 0.9993414 1.317245e-03 6.586227e-04
[61,] 0.9990196 1.960790e-03 9.803951e-04
[62,] 0.9985795 2.840982e-03 1.420491e-03
[63,] 0.9988719 2.256175e-03 1.128088e-03
[64,] 0.9987553 2.489396e-03 1.244698e-03
[65,] 0.9992612 1.477590e-03 7.387952e-04
[66,] 0.9990626 1.874831e-03 9.374156e-04
[67,] 0.9991744 1.651256e-03 8.256281e-04
[68,] 0.9999661 6.784085e-05 3.392042e-05
[69,] 0.9999452 1.095183e-04 5.475915e-05
[70,] 0.9999540 9.198320e-05 4.599160e-05
[71,] 0.9999337 1.325722e-04 6.628609e-05
[72,] 0.9999991 1.734833e-06 8.674164e-07
[73,] 0.9999990 1.947409e-06 9.737043e-07
[74,] 0.9999991 1.747614e-06 8.738071e-07
[75,] 0.9999992 1.605238e-06 8.026190e-07
[76,] 0.9999985 3.085155e-06 1.542577e-06
[77,] 0.9999971 5.800474e-06 2.900237e-06
[78,] 0.9999984 3.195659e-06 1.597830e-06
[79,] 0.9999971 5.865721e-06 2.932861e-06
[80,] 0.9999950 9.956192e-06 4.978096e-06
[81,] 0.9999912 1.763248e-05 8.816240e-06
[82,] 0.9999954 9.287775e-06 4.643887e-06
[83,] 0.9999977 4.521094e-06 2.260547e-06
[84,] 0.9999962 7.537531e-06 3.768766e-06
[85,] 0.9999963 7.499748e-06 3.749874e-06
[86,] 0.9999962 7.628583e-06 3.814292e-06
[87,] 0.9999938 1.236275e-05 6.181374e-06
[88,] 0.9999878 2.446268e-05 1.223134e-05
[89,] 0.9999872 2.563158e-05 1.281579e-05
[90,] 0.9999917 1.665756e-05 8.328780e-06
[91,] 0.9999842 3.151751e-05 1.575876e-05
[92,] 0.9999881 2.383284e-05 1.191642e-05
[93,] 0.9999765 4.692612e-05 2.346306e-05
[94,] 0.9999591 8.175632e-05 4.087816e-05
[95,] 0.9999200 1.600993e-04 8.004964e-05
[96,] 0.9999321 1.357225e-04 6.786125e-05
[97,] 0.9998671 2.657916e-04 1.328958e-04
[98,] 0.9998748 2.504786e-04 1.252393e-04
[99,] 0.9997569 4.862769e-04 2.431384e-04
[100,] 0.9997702 4.595903e-04 2.297952e-04
[101,] 0.9996455 7.089719e-04 3.544859e-04
[102,] 0.9993214 1.357202e-03 6.786010e-04
[103,] 0.9989123 2.175341e-03 1.087670e-03
[104,] 0.9993560 1.288024e-03 6.440119e-04
[105,] 0.9987644 2.471144e-03 1.235572e-03
[106,] 0.9977005 4.599043e-03 2.299522e-03
[107,] 0.9999890 2.194086e-05 1.097043e-05
[108,] 0.9999999 1.029258e-07 5.146291e-08
[109,] 0.9999999 2.523331e-07 1.261666e-07
[110,] 0.9999997 6.826780e-07 3.413390e-07
[111,] 0.9999989 2.128855e-06 1.064428e-06
[112,] 0.9999970 5.937814e-06 2.968907e-06
[113,] 0.9999894 2.129251e-05 1.064625e-05
[114,] 0.9999969 6.124252e-06 3.062126e-06
[115,] 0.9999960 8.004197e-06 4.002099e-06
[116,] 0.9999822 3.551792e-05 1.775896e-05
[117,] 0.9999534 9.311917e-05 4.655958e-05
[118,] 0.9999728 5.446236e-05 2.723118e-05
[119,] 0.9999547 9.065089e-05 4.532544e-05
[120,] 0.9997682 4.636273e-04 2.318137e-04
[121,] 0.9990508 1.898464e-03 9.492322e-04
[122,] 0.9972503 5.499434e-03 2.749717e-03
[123,] 0.9873971 2.520577e-02 1.260288e-02
> postscript(file="/var/www/rcomp/tmp/1gko71324297793.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2ajwr1324297793.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/37yge1324297793.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/44sik1324297793.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5xczg1324297793.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 = 144
Frequency = 1
1 2 3 4 5 6
16620.0196 43033.8161 -10696.2597 -39352.5931 -50531.8386 8467.2578
7 8 9 10 11 12
7913.4494 12361.9638 -20208.1727 55116.6224 -27344.7954 -246.8550
13 14 15 16 17 18
-60848.2298 -7384.5380 31901.3323 12125.1074 -12207.0316 2621.0353
19 20 21 22 23 24
-63113.9268 -30718.5656 -28449.8732 -8422.9240 30359.7120 -36754.9735
25 26 27 28 29 30
-13267.6701 30319.0677 -11863.8554 27379.5492 100850.6226 9799.5385
31 32 33 34 35 36
22693.8896 39655.1525 -42026.9030 11741.0004 22050.1778 -2631.7229
37 38 39 40 41 42
-4057.7641 -18306.1184 27806.9727 26948.8991 10306.8922 -18866.5312
43 44 45 46 47 48
4376.1891 -18512.7540 -4776.0490 35586.0681 387.7972 20055.1266
49 50 51 52 53 54
20924.6480 -35330.3817 -13582.9496 -21332.3791 73927.4863 45839.1158
55 56 57 58 59 60
16527.7409 11949.6560 41642.4089 -2331.8043 2812.7115 -24588.9187
61 62 63 64 65 66
3313.5410 -49632.2282 27031.5930 -4669.9537 45258.6959 -21839.0383
67 68 69 70 71 72
18898.9150 -66842.9843 5260.1856 -3651.6152 561.2596 11106.3880
73 74 75 76 77 78
-36113.4304 -23387.6822 -43657.9319 -12152.4187 -26775.3864 -63085.0143
79 80 81 82 83 84
-5726.1190 -28978.3704 -21431.8557 73725.9996 -20669.8302 -9189.8531
85 86 87 88 89 90
-22779.6315 8698.6625 2859.5217 -24647.2013 -10281.9703 12125.0297
91 92 93 94 95 96
-14936.1357 -28414.9208 33856.0653 17018.4347 -26134.7058 39993.4248
97 98 99 100 101 102
10048.1865 -4171.1270 26024.8627 -32444.0207 -7393.6548 -24135.6496
103 104 105 106 107 108
5761.2953 13491.4824 2902.2627 -17217.3670 2192.0354 26313.7577
109 110 111 112 113 114
-2405.2002 -15675.8375 -7651.3311 1435.7791 -9403.2256 -18214.8394
115 116 117 118 119 120
-2337.8790 -2405.2002 64582.6010 -22625.9753 6830.0134 20944.5875
121 122 123 124 125 126
-7795.5847 4428.3715 9795.5701 -23044.0327 15910.8372 -2616.4737
127 128 129 130 131 132
-1393.2966 20775.8157 3879.7440 -5537.8766 1674.8092 13794.3070
133 134 135 136 137 138
1736.9038 6993.7861 -2370.8026 1977.4417 -2405.2002 10320.7145
139 140 141 142 143 144
-3351.9201 879.9885 -12601.5942 -1475.8577 18882.6528 6042.0536
> postscript(file="/var/www/rcomp/tmp/6d2ab1324297793.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 = 144
Frequency = 1
lag(myerror, k = 1) myerror
0 16620.0196 NA
1 43033.8161 16620.0196
2 -10696.2597 43033.8161
3 -39352.5931 -10696.2597
4 -50531.8386 -39352.5931
5 8467.2578 -50531.8386
6 7913.4494 8467.2578
7 12361.9638 7913.4494
8 -20208.1727 12361.9638
9 55116.6224 -20208.1727
10 -27344.7954 55116.6224
11 -246.8550 -27344.7954
12 -60848.2298 -246.8550
13 -7384.5380 -60848.2298
14 31901.3323 -7384.5380
15 12125.1074 31901.3323
16 -12207.0316 12125.1074
17 2621.0353 -12207.0316
18 -63113.9268 2621.0353
19 -30718.5656 -63113.9268
20 -28449.8732 -30718.5656
21 -8422.9240 -28449.8732
22 30359.7120 -8422.9240
23 -36754.9735 30359.7120
24 -13267.6701 -36754.9735
25 30319.0677 -13267.6701
26 -11863.8554 30319.0677
27 27379.5492 -11863.8554
28 100850.6226 27379.5492
29 9799.5385 100850.6226
30 22693.8896 9799.5385
31 39655.1525 22693.8896
32 -42026.9030 39655.1525
33 11741.0004 -42026.9030
34 22050.1778 11741.0004
35 -2631.7229 22050.1778
36 -4057.7641 -2631.7229
37 -18306.1184 -4057.7641
38 27806.9727 -18306.1184
39 26948.8991 27806.9727
40 10306.8922 26948.8991
41 -18866.5312 10306.8922
42 4376.1891 -18866.5312
43 -18512.7540 4376.1891
44 -4776.0490 -18512.7540
45 35586.0681 -4776.0490
46 387.7972 35586.0681
47 20055.1266 387.7972
48 20924.6480 20055.1266
49 -35330.3817 20924.6480
50 -13582.9496 -35330.3817
51 -21332.3791 -13582.9496
52 73927.4863 -21332.3791
53 45839.1158 73927.4863
54 16527.7409 45839.1158
55 11949.6560 16527.7409
56 41642.4089 11949.6560
57 -2331.8043 41642.4089
58 2812.7115 -2331.8043
59 -24588.9187 2812.7115
60 3313.5410 -24588.9187
61 -49632.2282 3313.5410
62 27031.5930 -49632.2282
63 -4669.9537 27031.5930
64 45258.6959 -4669.9537
65 -21839.0383 45258.6959
66 18898.9150 -21839.0383
67 -66842.9843 18898.9150
68 5260.1856 -66842.9843
69 -3651.6152 5260.1856
70 561.2596 -3651.6152
71 11106.3880 561.2596
72 -36113.4304 11106.3880
73 -23387.6822 -36113.4304
74 -43657.9319 -23387.6822
75 -12152.4187 -43657.9319
76 -26775.3864 -12152.4187
77 -63085.0143 -26775.3864
78 -5726.1190 -63085.0143
79 -28978.3704 -5726.1190
80 -21431.8557 -28978.3704
81 73725.9996 -21431.8557
82 -20669.8302 73725.9996
83 -9189.8531 -20669.8302
84 -22779.6315 -9189.8531
85 8698.6625 -22779.6315
86 2859.5217 8698.6625
87 -24647.2013 2859.5217
88 -10281.9703 -24647.2013
89 12125.0297 -10281.9703
90 -14936.1357 12125.0297
91 -28414.9208 -14936.1357
92 33856.0653 -28414.9208
93 17018.4347 33856.0653
94 -26134.7058 17018.4347
95 39993.4248 -26134.7058
96 10048.1865 39993.4248
97 -4171.1270 10048.1865
98 26024.8627 -4171.1270
99 -32444.0207 26024.8627
100 -7393.6548 -32444.0207
101 -24135.6496 -7393.6548
102 5761.2953 -24135.6496
103 13491.4824 5761.2953
104 2902.2627 13491.4824
105 -17217.3670 2902.2627
106 2192.0354 -17217.3670
107 26313.7577 2192.0354
108 -2405.2002 26313.7577
109 -15675.8375 -2405.2002
110 -7651.3311 -15675.8375
111 1435.7791 -7651.3311
112 -9403.2256 1435.7791
113 -18214.8394 -9403.2256
114 -2337.8790 -18214.8394
115 -2405.2002 -2337.8790
116 64582.6010 -2405.2002
117 -22625.9753 64582.6010
118 6830.0134 -22625.9753
119 20944.5875 6830.0134
120 -7795.5847 20944.5875
121 4428.3715 -7795.5847
122 9795.5701 4428.3715
123 -23044.0327 9795.5701
124 15910.8372 -23044.0327
125 -2616.4737 15910.8372
126 -1393.2966 -2616.4737
127 20775.8157 -1393.2966
128 3879.7440 20775.8157
129 -5537.8766 3879.7440
130 1674.8092 -5537.8766
131 13794.3070 1674.8092
132 1736.9038 13794.3070
133 6993.7861 1736.9038
134 -2370.8026 6993.7861
135 1977.4417 -2370.8026
136 -2405.2002 1977.4417
137 10320.7145 -2405.2002
138 -3351.9201 10320.7145
139 879.9885 -3351.9201
140 -12601.5942 879.9885
141 -1475.8577 -12601.5942
142 18882.6528 -1475.8577
143 6042.0536 18882.6528
144 NA 6042.0536
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 43033.8161 16620.0196
[2,] -10696.2597 43033.8161
[3,] -39352.5931 -10696.2597
[4,] -50531.8386 -39352.5931
[5,] 8467.2578 -50531.8386
[6,] 7913.4494 8467.2578
[7,] 12361.9638 7913.4494
[8,] -20208.1727 12361.9638
[9,] 55116.6224 -20208.1727
[10,] -27344.7954 55116.6224
[11,] -246.8550 -27344.7954
[12,] -60848.2298 -246.8550
[13,] -7384.5380 -60848.2298
[14,] 31901.3323 -7384.5380
[15,] 12125.1074 31901.3323
[16,] -12207.0316 12125.1074
[17,] 2621.0353 -12207.0316
[18,] -63113.9268 2621.0353
[19,] -30718.5656 -63113.9268
[20,] -28449.8732 -30718.5656
[21,] -8422.9240 -28449.8732
[22,] 30359.7120 -8422.9240
[23,] -36754.9735 30359.7120
[24,] -13267.6701 -36754.9735
[25,] 30319.0677 -13267.6701
[26,] -11863.8554 30319.0677
[27,] 27379.5492 -11863.8554
[28,] 100850.6226 27379.5492
[29,] 9799.5385 100850.6226
[30,] 22693.8896 9799.5385
[31,] 39655.1525 22693.8896
[32,] -42026.9030 39655.1525
[33,] 11741.0004 -42026.9030
[34,] 22050.1778 11741.0004
[35,] -2631.7229 22050.1778
[36,] -4057.7641 -2631.7229
[37,] -18306.1184 -4057.7641
[38,] 27806.9727 -18306.1184
[39,] 26948.8991 27806.9727
[40,] 10306.8922 26948.8991
[41,] -18866.5312 10306.8922
[42,] 4376.1891 -18866.5312
[43,] -18512.7540 4376.1891
[44,] -4776.0490 -18512.7540
[45,] 35586.0681 -4776.0490
[46,] 387.7972 35586.0681
[47,] 20055.1266 387.7972
[48,] 20924.6480 20055.1266
[49,] -35330.3817 20924.6480
[50,] -13582.9496 -35330.3817
[51,] -21332.3791 -13582.9496
[52,] 73927.4863 -21332.3791
[53,] 45839.1158 73927.4863
[54,] 16527.7409 45839.1158
[55,] 11949.6560 16527.7409
[56,] 41642.4089 11949.6560
[57,] -2331.8043 41642.4089
[58,] 2812.7115 -2331.8043
[59,] -24588.9187 2812.7115
[60,] 3313.5410 -24588.9187
[61,] -49632.2282 3313.5410
[62,] 27031.5930 -49632.2282
[63,] -4669.9537 27031.5930
[64,] 45258.6959 -4669.9537
[65,] -21839.0383 45258.6959
[66,] 18898.9150 -21839.0383
[67,] -66842.9843 18898.9150
[68,] 5260.1856 -66842.9843
[69,] -3651.6152 5260.1856
[70,] 561.2596 -3651.6152
[71,] 11106.3880 561.2596
[72,] -36113.4304 11106.3880
[73,] -23387.6822 -36113.4304
[74,] -43657.9319 -23387.6822
[75,] -12152.4187 -43657.9319
[76,] -26775.3864 -12152.4187
[77,] -63085.0143 -26775.3864
[78,] -5726.1190 -63085.0143
[79,] -28978.3704 -5726.1190
[80,] -21431.8557 -28978.3704
[81,] 73725.9996 -21431.8557
[82,] -20669.8302 73725.9996
[83,] -9189.8531 -20669.8302
[84,] -22779.6315 -9189.8531
[85,] 8698.6625 -22779.6315
[86,] 2859.5217 8698.6625
[87,] -24647.2013 2859.5217
[88,] -10281.9703 -24647.2013
[89,] 12125.0297 -10281.9703
[90,] -14936.1357 12125.0297
[91,] -28414.9208 -14936.1357
[92,] 33856.0653 -28414.9208
[93,] 17018.4347 33856.0653
[94,] -26134.7058 17018.4347
[95,] 39993.4248 -26134.7058
[96,] 10048.1865 39993.4248
[97,] -4171.1270 10048.1865
[98,] 26024.8627 -4171.1270
[99,] -32444.0207 26024.8627
[100,] -7393.6548 -32444.0207
[101,] -24135.6496 -7393.6548
[102,] 5761.2953 -24135.6496
[103,] 13491.4824 5761.2953
[104,] 2902.2627 13491.4824
[105,] -17217.3670 2902.2627
[106,] 2192.0354 -17217.3670
[107,] 26313.7577 2192.0354
[108,] -2405.2002 26313.7577
[109,] -15675.8375 -2405.2002
[110,] -7651.3311 -15675.8375
[111,] 1435.7791 -7651.3311
[112,] -9403.2256 1435.7791
[113,] -18214.8394 -9403.2256
[114,] -2337.8790 -18214.8394
[115,] -2405.2002 -2337.8790
[116,] 64582.6010 -2405.2002
[117,] -22625.9753 64582.6010
[118,] 6830.0134 -22625.9753
[119,] 20944.5875 6830.0134
[120,] -7795.5847 20944.5875
[121,] 4428.3715 -7795.5847
[122,] 9795.5701 4428.3715
[123,] -23044.0327 9795.5701
[124,] 15910.8372 -23044.0327
[125,] -2616.4737 15910.8372
[126,] -1393.2966 -2616.4737
[127,] 20775.8157 -1393.2966
[128,] 3879.7440 20775.8157
[129,] -5537.8766 3879.7440
[130,] 1674.8092 -5537.8766
[131,] 13794.3070 1674.8092
[132,] 1736.9038 13794.3070
[133,] 6993.7861 1736.9038
[134,] -2370.8026 6993.7861
[135,] 1977.4417 -2370.8026
[136,] -2405.2002 1977.4417
[137,] 10320.7145 -2405.2002
[138,] -3351.9201 10320.7145
[139,] 879.9885 -3351.9201
[140,] -12601.5942 879.9885
[141,] -1475.8577 -12601.5942
[142,] 18882.6528 -1475.8577
[143,] 6042.0536 18882.6528
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 43033.8161 16620.0196
2 -10696.2597 43033.8161
3 -39352.5931 -10696.2597
4 -50531.8386 -39352.5931
5 8467.2578 -50531.8386
6 7913.4494 8467.2578
7 12361.9638 7913.4494
8 -20208.1727 12361.9638
9 55116.6224 -20208.1727
10 -27344.7954 55116.6224
11 -246.8550 -27344.7954
12 -60848.2298 -246.8550
13 -7384.5380 -60848.2298
14 31901.3323 -7384.5380
15 12125.1074 31901.3323
16 -12207.0316 12125.1074
17 2621.0353 -12207.0316
18 -63113.9268 2621.0353
19 -30718.5656 -63113.9268
20 -28449.8732 -30718.5656
21 -8422.9240 -28449.8732
22 30359.7120 -8422.9240
23 -36754.9735 30359.7120
24 -13267.6701 -36754.9735
25 30319.0677 -13267.6701
26 -11863.8554 30319.0677
27 27379.5492 -11863.8554
28 100850.6226 27379.5492
29 9799.5385 100850.6226
30 22693.8896 9799.5385
31 39655.1525 22693.8896
32 -42026.9030 39655.1525
33 11741.0004 -42026.9030
34 22050.1778 11741.0004
35 -2631.7229 22050.1778
36 -4057.7641 -2631.7229
37 -18306.1184 -4057.7641
38 27806.9727 -18306.1184
39 26948.8991 27806.9727
40 10306.8922 26948.8991
41 -18866.5312 10306.8922
42 4376.1891 -18866.5312
43 -18512.7540 4376.1891
44 -4776.0490 -18512.7540
45 35586.0681 -4776.0490
46 387.7972 35586.0681
47 20055.1266 387.7972
48 20924.6480 20055.1266
49 -35330.3817 20924.6480
50 -13582.9496 -35330.3817
51 -21332.3791 -13582.9496
52 73927.4863 -21332.3791
53 45839.1158 73927.4863
54 16527.7409 45839.1158
55 11949.6560 16527.7409
56 41642.4089 11949.6560
57 -2331.8043 41642.4089
58 2812.7115 -2331.8043
59 -24588.9187 2812.7115
60 3313.5410 -24588.9187
61 -49632.2282 3313.5410
62 27031.5930 -49632.2282
63 -4669.9537 27031.5930
64 45258.6959 -4669.9537
65 -21839.0383 45258.6959
66 18898.9150 -21839.0383
67 -66842.9843 18898.9150
68 5260.1856 -66842.9843
69 -3651.6152 5260.1856
70 561.2596 -3651.6152
71 11106.3880 561.2596
72 -36113.4304 11106.3880
73 -23387.6822 -36113.4304
74 -43657.9319 -23387.6822
75 -12152.4187 -43657.9319
76 -26775.3864 -12152.4187
77 -63085.0143 -26775.3864
78 -5726.1190 -63085.0143
79 -28978.3704 -5726.1190
80 -21431.8557 -28978.3704
81 73725.9996 -21431.8557
82 -20669.8302 73725.9996
83 -9189.8531 -20669.8302
84 -22779.6315 -9189.8531
85 8698.6625 -22779.6315
86 2859.5217 8698.6625
87 -24647.2013 2859.5217
88 -10281.9703 -24647.2013
89 12125.0297 -10281.9703
90 -14936.1357 12125.0297
91 -28414.9208 -14936.1357
92 33856.0653 -28414.9208
93 17018.4347 33856.0653
94 -26134.7058 17018.4347
95 39993.4248 -26134.7058
96 10048.1865 39993.4248
97 -4171.1270 10048.1865
98 26024.8627 -4171.1270
99 -32444.0207 26024.8627
100 -7393.6548 -32444.0207
101 -24135.6496 -7393.6548
102 5761.2953 -24135.6496
103 13491.4824 5761.2953
104 2902.2627 13491.4824
105 -17217.3670 2902.2627
106 2192.0354 -17217.3670
107 26313.7577 2192.0354
108 -2405.2002 26313.7577
109 -15675.8375 -2405.2002
110 -7651.3311 -15675.8375
111 1435.7791 -7651.3311
112 -9403.2256 1435.7791
113 -18214.8394 -9403.2256
114 -2337.8790 -18214.8394
115 -2405.2002 -2337.8790
116 64582.6010 -2405.2002
117 -22625.9753 64582.6010
118 6830.0134 -22625.9753
119 20944.5875 6830.0134
120 -7795.5847 20944.5875
121 4428.3715 -7795.5847
122 9795.5701 4428.3715
123 -23044.0327 9795.5701
124 15910.8372 -23044.0327
125 -2616.4737 15910.8372
126 -1393.2966 -2616.4737
127 20775.8157 -1393.2966
128 3879.7440 20775.8157
129 -5537.8766 3879.7440
130 1674.8092 -5537.8766
131 13794.3070 1674.8092
132 1736.9038 13794.3070
133 6993.7861 1736.9038
134 -2370.8026 6993.7861
135 1977.4417 -2370.8026
136 -2405.2002 1977.4417
137 10320.7145 -2405.2002
138 -3351.9201 10320.7145
139 879.9885 -3351.9201
140 -12601.5942 879.9885
141 -1475.8577 -12601.5942
142 18882.6528 -1475.8577
143 6042.0536 18882.6528
> 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/7a48p1324297793.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/828ii1324297793.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9s6q21324297793.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10qmux1324297793.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11labp1324297793.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/123ua01324297793.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/1369hj1324297793.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/14brvm1324297793.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/15v3by1324297793.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/16cug41324297793.tab")
+ }
>
> try(system("convert tmp/1gko71324297793.ps tmp/1gko71324297793.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ajwr1324297793.ps tmp/2ajwr1324297793.png",intern=TRUE))
character(0)
> try(system("convert tmp/37yge1324297793.ps tmp/37yge1324297793.png",intern=TRUE))
character(0)
> try(system("convert tmp/44sik1324297793.ps tmp/44sik1324297793.png",intern=TRUE))
character(0)
> try(system("convert tmp/5xczg1324297793.ps tmp/5xczg1324297793.png",intern=TRUE))
character(0)
> try(system("convert tmp/6d2ab1324297793.ps tmp/6d2ab1324297793.png",intern=TRUE))
character(0)
> try(system("convert tmp/7a48p1324297793.ps tmp/7a48p1324297793.png",intern=TRUE))
character(0)
> try(system("convert tmp/828ii1324297793.ps tmp/828ii1324297793.png",intern=TRUE))
character(0)
> try(system("convert tmp/9s6q21324297793.ps tmp/9s6q21324297793.png",intern=TRUE))
character(0)
> try(system("convert tmp/10qmux1324297793.ps tmp/10qmux1324297793.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.310 0.360 5.674