R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'contributors()' for more information and
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Type 'q()' to quit R.
> x <- array(list(40399
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+ ,dim=c(10
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+ ,'X4')
+ ,1:125))
> y <- array(NA,dim=c(10,125),dimnames=list(c('OPENVAC','Y1','Y2','Y3','Y4','NWWZ','X1','X2','X3','X4'),1:125))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
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
OPENVAC Y1 Y2 Y3 Y4 NWWZ X1 X2 X3 X4
1 40399 44164 44496 43110 43880 195722 198563 229139 229527 211868
2 36763 40399 44164 44496 43110 202196 195722 198563 229139 229527
3 37903 36763 40399 44164 44496 205816 202196 195722 198563 229139
4 35532 37903 36763 40399 44164 212588 205816 202196 195722 198563
5 35533 35532 37903 36763 40399 214320 212588 205816 202196 195722
6 32110 35533 35532 37903 36763 220375 214320 212588 205816 202196
7 33374 32110 35533 35532 37903 204442 220375 214320 212588 205816
8 35462 33374 32110 35533 35532 206903 204442 220375 214320 212588
9 33508 35462 33374 32110 35533 214126 206903 204442 220375 214320
10 36080 33508 35462 33374 32110 226899 214126 206903 204442 220375
11 34560 36080 33508 35462 33374 223532 226899 214126 206903 204442
12 38737 34560 36080 33508 35462 195309 223532 226899 214126 206903
13 38144 38737 34560 36080 33508 186005 195309 223532 226899 214126
14 37594 38144 38737 34560 36080 188906 186005 195309 223532 226899
15 36424 37594 38144 38737 34560 191563 188906 186005 195309 223532
16 36843 36424 37594 38144 38737 189226 191563 188906 186005 195309
17 37246 36843 36424 37594 38144 186413 189226 191563 188906 186005
18 38661 37246 36843 36424 37594 178037 186413 189226 191563 188906
19 40454 38661 37246 36843 36424 166827 178037 186413 189226 191563
20 44928 40454 38661 37246 36843 169362 166827 178037 186413 189226
21 48441 44928 40454 38661 37246 174330 169362 166827 178037 186413
22 48140 48441 44928 40454 38661 187069 174330 169362 166827 178037
23 45998 48140 48441 44928 40454 186530 187069 174330 169362 166827
24 47369 45998 48140 48441 44928 158114 186530 187069 174330 169362
25 49554 47369 45998 48140 48441 151001 158114 186530 187069 174330
26 47510 49554 47369 45998 48140 159612 151001 158114 186530 187069
27 44873 47510 49554 47369 45998 161914 159612 151001 158114 186530
28 45344 44873 47510 49554 47369 164182 161914 159612 151001 158114
29 42413 45344 44873 47510 49554 169701 164182 161914 159612 151001
30 36912 42413 45344 44873 47510 171297 169701 164182 161914 159612
31 43452 36912 42413 45344 44873 166444 171297 169701 164182 161914
32 42142 43452 36912 42413 45344 173476 166444 171297 169701 164182
33 44382 42142 43452 36912 42413 182516 173476 166444 171297 169701
34 43636 44382 42142 43452 36912 202388 182516 173476 166444 171297
35 44167 43636 44382 42142 43452 202300 202388 182516 173476 166444
36 44423 44167 43636 44382 42142 168053 202300 202388 182516 173476
37 42868 44423 44167 43636 44382 167302 168053 202300 202388 182516
38 43908 42868 44423 44167 43636 172608 167302 168053 202300 202388
39 42013 43908 42868 44423 44167 178106 172608 167302 168053 202300
40 38846 42013 43908 42868 44423 185686 178106 172608 167302 168053
41 35087 38846 42013 43908 42868 194581 185686 178106 172608 167302
42 33026 35087 38846 42013 43908 194596 194581 185686 178106 172608
43 34646 33026 35087 38846 42013 197922 194596 194581 185686 178106
44 37135 34646 33026 35087 38846 208795 197922 194596 194581 185686
45 37985 37135 34646 33026 35087 230580 208795 197922 194596 194581
46 43121 37985 37135 34646 33026 240636 230580 208795 197922 194596
47 43722 43121 37985 37135 34646 240048 240636 230580 208795 197922
48 43630 43722 43121 37985 37135 211457 240048 240636 230580 208795
49 42234 43630 43722 43121 37985 211142 211457 240048 240636 230580
50 39351 42234 43630 43722 43121 214771 211142 211457 240048 240636
51 39327 39351 42234 43630 43722 212610 214771 211142 211457 240048
52 35704 39327 39351 42234 43630 219313 212610 214771 211142 211457
53 30466 35704 39327 39351 42234 219277 219313 212610 214771 211142
54 28155 30466 35704 39327 39351 231805 219277 219313 212610 214771
55 29257 28155 30466 35704 39327 229245 231805 219277 219313 212610
56 29998 29257 28155 30466 35704 241114 229245 231805 219277 219313
57 32529 29998 29257 28155 30466 248624 241114 229245 231805 219277
58 34787 32529 29998 29257 28155 265845 248624 241114 229245 231805
59 33855 34787 32529 29998 29257 256446 265845 248624 241114 229245
60 34556 33855 34787 32529 29998 219452 256446 265845 248624 241114
61 31348 34556 33855 34787 32529 217142 219452 256446 265845 248624
62 30805 31348 34556 33855 34787 221678 217142 219452 256446 265845
63 28353 30805 31348 34556 33855 227184 221678 217142 219452 256446
64 24514 28353 30805 31348 34556 230354 227184 221678 217142 219452
65 21106 24514 28353 30805 31348 235243 230354 227184 221678 217142
66 21346 21106 24514 28353 30805 237217 235243 230354 227184 221678
67 23335 21346 21106 24514 28353 233575 237217 235243 230354 227184
68 24379 23335 21346 21106 24514 244460 233575 237217 235243 230354
69 26290 24379 23335 21346 21106 243324 244460 233575 237217 235243
70 30084 26290 24379 23335 21346 260307 243324 244460 233575 237217
71 29429 30084 26290 24379 23335 241476 260307 243324 244460 233575
72 30632 29429 30084 26290 24379 203666 241476 260307 243324 244460
73 27349 30632 29429 30084 26290 200237 203666 241476 260307 243324
74 27264 27349 30632 29429 30084 204045 200237 203666 241476 260307
75 27474 27264 27349 30632 29429 209465 204045 200237 203666 241476
76 24482 27474 27264 27349 30632 213586 209465 204045 200237 203666
77 21453 24482 27474 27264 27349 216234 213586 209465 204045 200237
78 18788 21453 24482 27474 27264 213188 216234 213586 209465 204045
79 19282 18788 21453 24482 27474 208679 213188 216234 213586 209465
80 19713 19282 18788 21453 24482 217859 208679 213188 216234 213586
81 21917 19713 19282 18788 21453 227247 217859 208679 213188 216234
82 23812 21917 19713 19282 18788 243477 227247 217859 208679 213188
83 23785 23812 21917 19713 19282 232571 243477 227247 217859 208679
84 24696 23785 23812 21917 19713 191531 232571 243477 227247 217859
85 24562 24696 23785 23812 21917 186029 191531 232571 243477 227247
86 23580 24562 24696 23785 23812 189733 186029 191531 232571 243477
87 24939 23580 24562 24696 23785 190420 189733 186029 191531 232571
88 23899 24939 23580 24562 24696 194163 190420 189733 186029 191531
89 21454 23899 24939 23580 24562 198770 194163 190420 189733 186029
90 19761 21454 23899 24939 23580 195198 198770 194163 190420 189733
91 19815 19761 21454 23899 24939 193111 195198 198770 194163 190420
92 20780 19815 19761 21454 23899 195411 193111 195198 198770 194163
93 23462 20780 19815 19761 21454 202108 195411 193111 195198 198770
94 25005 23462 20780 19815 19761 215706 202108 195411 193111 195198
95 24725 25005 23462 20780 19815 206348 215706 202108 195411 193111
96 26198 24725 25005 23462 20780 166972 206348 215706 202108 195411
97 27543 26198 24725 25005 23462 166070 166972 206348 215706 202108
98 26471 27543 26198 24725 25005 169292 166070 166972 206348 215706
99 26558 26471 27543 26198 24725 175041 169292 166070 166972 206348
100 25317 26558 26471 27543 26198 177876 175041 169292 166070 166972
101 22896 25317 26558 26471 27543 181140 177876 175041 169292 166070
102 22248 22896 25317 26558 26471 179566 181140 177876 175041 169292
103 23406 22248 22896 25317 26558 175335 179566 181140 177876 175041
104 25073 23406 22248 22896 25317 184128 175335 179566 181140 177876
105 27691 25073 23406 22248 22896 189917 184128 175335 179566 181140
106 30599 27691 25073 23406 22248 194690 189917 184128 175335 179566
107 31948 30599 27691 25073 23406 179612 194690 189917 184128 175335
108 32946 31948 30599 27691 25073 150605 179612 194690 189917 184128
109 34012 32946 31948 30599 27691 150569 150605 179612 194690 189917
110 32936 34012 32946 31948 30599 153745 150569 150605 179612 194690
111 32974 32936 34012 32946 31948 155511 153745 150569 150605 179612
112 30951 32974 32936 34012 32946 159044 155511 153745 150569 150605
113 29812 30951 32974 32936 34012 163095 159044 155511 153745 150569
114 29010 29812 30951 32974 32936 159585 163095 159044 155511 153745
115 31068 29010 29812 30951 32974 158644 159585 163095 159044 155511
116 32447 31068 29010 29812 30951 166618 158644 159585 163095 159044
117 34844 32447 31068 29010 29812 176512 166618 158644 159585 163095
118 35676 34844 32447 31068 29010 200765 176512 166618 158644 159585
119 35387 35676 34844 32447 31068 182698 200765 176512 166618 158644
120 36488 35387 35676 34844 32447 153730 182698 200765 176512 166618
121 35652 36488 35387 35676 34844 156145 153730 182698 200765 176512
122 33488 35652 36488 35387 35676 161570 156145 153730 182698 200765
123 32914 33488 35652 36488 35387 165688 161570 156145 153730 182698
124 29781 32914 33488 35652 36488 173666 165688 161570 156145 153730
125 27951 29781 32914 33488 35652 180144 173666 165688 161570 156145
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Y1 Y2 Y3 Y4 NWWZ
2.916e+03 1.207e+00 -7.694e-02 -2.950e-01 1.061e-01 -1.906e-02
X1 X2 X3 X4
8.303e-03 4.169e-02 -6.189e-02 2.551e-02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4559.9 -1385.0 -52.1 1303.2 8560.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.916e+03 2.007e+03 1.453 0.1489
Y1 1.207e+00 9.634e-02 12.532 <2e-16 ***
Y2 -7.694e-02 1.526e-01 -0.504 0.6151
Y3 -2.950e-01 1.520e-01 -1.941 0.0547 .
Y4 1.061e-01 1.001e-01 1.060 0.2915
NWWZ -1.906e-02 1.908e-02 -0.999 0.3198
X1 8.303e-03 2.962e-02 0.280 0.7798
X2 4.169e-02 3.111e-02 1.340 0.1828
X3 -6.189e-02 2.857e-02 -2.166 0.0324 *
X4 2.551e-02 1.805e-02 1.414 0.1602
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 2053 on 115 degrees of freedom
Multiple R-squared: 0.9361, Adjusted R-squared: 0.9311
F-statistic: 187.1 on 9 and 115 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,] 0.26396106 5.279221e-01 7.360389e-01
[2,] 0.16993592 3.398718e-01 8.300641e-01
[3,] 0.12204144 2.440829e-01 8.779586e-01
[4,] 0.09155697 1.831139e-01 9.084430e-01
[5,] 0.08870044 1.774009e-01 9.112996e-01
[6,] 0.06917355 1.383471e-01 9.308264e-01
[7,] 0.04569638 9.139277e-02 9.543036e-01
[8,] 0.28298737 5.659747e-01 7.170126e-01
[9,] 0.46945928 9.389186e-01 5.305407e-01
[10,] 0.41872969 8.374594e-01 5.812703e-01
[11,] 0.33958699 6.791740e-01 6.604130e-01
[12,] 0.29544958 5.908992e-01 7.045504e-01
[13,] 0.33031095 6.606219e-01 6.696891e-01
[14,] 0.26846727 5.369345e-01 7.315327e-01
[15,] 0.44192483 8.838497e-01 5.580752e-01
[16,] 0.38388659 7.677732e-01 6.161134e-01
[17,] 0.36401243 7.280249e-01 6.359876e-01
[18,] 0.68526663 6.294667e-01 3.147334e-01
[19,] 0.97966642 4.066716e-02 2.033358e-02
[20,] 0.97399968 5.200063e-02 2.600032e-02
[21,] 0.97250819 5.498361e-02 2.749181e-02
[22,] 0.96330811 7.338378e-02 3.669189e-02
[23,] 0.96898268 6.203463e-02 3.101732e-02
[24,] 0.95905646 8.188708e-02 4.094354e-02
[25,] 0.95072511 9.854977e-02 4.927489e-02
[26,] 0.97181269 5.637462e-02 2.818731e-02
[27,] 0.96628196 6.743607e-02 3.371804e-02
[28,] 0.97405143 5.189715e-02 2.594857e-02
[29,] 0.97984550 4.030901e-02 2.015450e-02
[30,] 0.97646228 4.707544e-02 2.353772e-02
[31,] 0.97903765 4.192470e-02 2.096235e-02
[32,] 0.98506246 2.987509e-02 1.493754e-02
[33,] 0.98281770 3.436461e-02 1.718230e-02
[34,] 0.99940458 1.190848e-03 5.954241e-04
[35,] 0.99920764 1.584722e-03 7.923608e-04
[36,] 0.99877408 2.451847e-03 1.225923e-03
[37,] 0.99826823 3.463545e-03 1.731773e-03
[38,] 0.99750044 4.999129e-03 2.499565e-03
[39,] 0.99776012 4.479762e-03 2.239881e-03
[40,] 0.99751708 4.965843e-03 2.482922e-03
[41,] 0.99899409 2.011823e-03 1.005912e-03
[42,] 0.99863486 2.730281e-03 1.365141e-03
[43,] 0.99934242 1.315158e-03 6.575790e-04
[44,] 0.99896917 2.061658e-03 1.030829e-03
[45,] 0.99933022 1.339555e-03 6.697774e-04
[46,] 0.99937646 1.247080e-03 6.235402e-04
[47,] 0.99915136 1.697273e-03 8.486364e-04
[48,] 0.99910583 1.788333e-03 8.941666e-04
[49,] 0.99917196 1.656075e-03 8.280373e-04
[50,] 0.99946065 1.078691e-03 5.393453e-04
[51,] 0.99953535 9.293024e-04 4.646512e-04
[52,] 0.99988208 2.358322e-04 1.179161e-04
[53,] 0.99991660 1.668094e-04 8.340468e-05
[54,] 0.99993274 1.345164e-04 6.725819e-05
[55,] 0.99992206 1.558745e-04 7.793726e-05
[56,] 0.99988124 2.375162e-04 1.187581e-04
[57,] 0.99988205 2.359090e-04 1.179545e-04
[58,] 0.99997555 4.889787e-05 2.444894e-05
[59,] 0.99996798 6.403887e-05 3.201944e-05
[60,] 0.99995075 9.849153e-05 4.924577e-05
[61,] 0.99996399 7.202377e-05 3.601188e-05
[62,] 0.99999069 1.862652e-05 9.313259e-06
[63,] 0.99998484 3.031655e-05 1.515827e-05
[64,] 0.99999946 1.077631e-06 5.388156e-07
[65,] 0.99999949 1.018756e-06 5.093782e-07
[66,] 0.99999922 1.563836e-06 7.819178e-07
[67,] 0.99999888 2.236822e-06 1.118411e-06
[68,] 0.99999777 4.455625e-06 2.227813e-06
[69,] 0.99999716 5.683853e-06 2.841927e-06
[70,] 0.99999547 9.055516e-06 4.527758e-06
[71,] 0.99999181 1.638512e-05 8.192558e-06
[72,] 0.99998365 3.269814e-05 1.634907e-05
[73,] 0.99996899 6.201779e-05 3.100890e-05
[74,] 0.99994576 1.084899e-04 5.424496e-05
[75,] 0.99992176 1.564710e-04 7.823549e-05
[76,] 0.99996713 6.574705e-05 3.287352e-05
[77,] 0.99998811 2.378000e-05 1.189000e-05
[78,] 0.99997683 4.634038e-05 2.317019e-05
[79,] 0.99995251 9.497815e-05 4.748907e-05
[80,] 0.99989638 2.072428e-04 1.036214e-04
[81,] 0.99985094 2.981255e-04 1.490628e-04
[82,] 0.99968334 6.333175e-04 3.166588e-04
[83,] 0.99965974 6.805219e-04 3.402610e-04
[84,] 0.99931982 1.360361e-03 6.801805e-04
[85,] 0.99864856 2.702889e-03 1.351445e-03
[86,] 0.99773793 4.524134e-03 2.262067e-03
[87,] 0.99654001 6.919980e-03 3.459990e-03
[88,] 0.99438918 1.122165e-02 5.610823e-03
[89,] 0.99944058 1.118832e-03 5.594161e-04
[90,] 0.99867082 2.658359e-03 1.329180e-03
[91,] 0.99756040 4.879208e-03 2.439604e-03
[92,] 0.99652631 6.947371e-03 3.473686e-03
[93,] 0.99270721 1.458559e-02 7.292793e-03
[94,] 0.98428061 3.143877e-02 1.571939e-02
[95,] 0.97415874 5.168253e-02 2.584126e-02
[96,] 0.99206000 1.587999e-02 7.939995e-03
[97,] 0.98558647 2.882706e-02 1.441353e-02
[98,] 0.98153769 3.692461e-02 1.846231e-02
[99,] 0.96677361 6.645278e-02 3.322639e-02
[100,] 0.91691318 1.661736e-01 8.308682e-02
> postscript(file="/var/www/html/freestat/rcomp/tmp/1nxjy1291972173.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2y70j1291972173.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/freestat/rcomp/tmp/3y70j1291972173.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4y70j1291972173.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5jq2g1291972174.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 = 125
Frequency = 1
1 2 3 4 5 6
-3017.62577 -695.90197 2550.25802 -2119.05419 457.80293 -2549.22990
7 8 9 10 11 12
1927.54484 2339.17647 -1936.20761 2831.72058 -1374.41464 3379.29700
13 14 15 16 17 18
-603.72044 -62.67304 -467.24414 660.50487 640.18123 1365.62479
19 20 21 22 23 24
1489.76130 4358.55441 3077.20971 -1126.12493 -1385.02133 2285.17012
25 26 27 28 29 30
2973.32884 -1153.49244 -1999.12376 1947.15157 -1885.32472 -4559.86522
31 32 33 34 35 36
8560.31715 -1591.64349 1695.30498 326.60756 865.87031 122.73750
37 38 39 40 41 42
-885.09396 3310.54616 -1965.84059 -2546.16569 -1930.79138 -551.33146
43 44 45 46 47 48
2555.65588 2693.43899 414.17535 5174.98708 -211.57220 -535.62584
49 50 51 52 53 54
-26.67487 -627.95435 817.52960 -2696.12285 -3998.06697 -232.05653
55 56 57 58 59 60
2509.33513 133.04174 2655.69837 1778.35167 -1418.56945 66.35303
61 62 63 64 65 66
-2132.66230 1363.72729 -2260.20749 -3575.18413 -2180.02628 1303.16494
67 68 69 70 71 72
1633.80985 73.93157 1347.12099 3079.24018 -1598.09949 -479.81975
73 74 75 76 77 78
-2235.14527 1218.93317 58.17777 -3662.95818 -2627.02494 -1807.94737
79 80 81 82 83 84
711.16928 162.67066 1454.03957 797.08691 -1324.22813 -651.87286
85 86 87 88 89 90
-106.86205 -327.65426 428.02440 -1846.77576 -2809.43566 -1439.92837
91 92 93 94 95 96
30.85484 589.15292 1727.11767 371.60516 -1660.82021 73.82619
97 98 99 100 101 102
1160.40491 -883.82107 -1012.84885 -1380.17010 -2733.74741 -316.70139
103 104 105 106 107 108
887.14626 921.71917 1714.95689 1455.51694 -52.09527 -356.17748
109 110 111 112 113 114
1205.52328 -775.89924 -607.43635 -1892.45501 -844.96850 -521.74074
115 116 117 118 119 120
1831.93860 1009.96722 1625.70967 441.18424 -920.03785 150.38580
121 122 123 124 125
242.68634 -1446.65470 -516.24483 -2706.02795 -1187.81692
> postscript(file="/var/www/html/freestat/rcomp/tmp/6jq2g1291972174.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 = 125
Frequency = 1
lag(myerror, k = 1) myerror
0 -3017.62577 NA
1 -695.90197 -3017.62577
2 2550.25802 -695.90197
3 -2119.05419 2550.25802
4 457.80293 -2119.05419
5 -2549.22990 457.80293
6 1927.54484 -2549.22990
7 2339.17647 1927.54484
8 -1936.20761 2339.17647
9 2831.72058 -1936.20761
10 -1374.41464 2831.72058
11 3379.29700 -1374.41464
12 -603.72044 3379.29700
13 -62.67304 -603.72044
14 -467.24414 -62.67304
15 660.50487 -467.24414
16 640.18123 660.50487
17 1365.62479 640.18123
18 1489.76130 1365.62479
19 4358.55441 1489.76130
20 3077.20971 4358.55441
21 -1126.12493 3077.20971
22 -1385.02133 -1126.12493
23 2285.17012 -1385.02133
24 2973.32884 2285.17012
25 -1153.49244 2973.32884
26 -1999.12376 -1153.49244
27 1947.15157 -1999.12376
28 -1885.32472 1947.15157
29 -4559.86522 -1885.32472
30 8560.31715 -4559.86522
31 -1591.64349 8560.31715
32 1695.30498 -1591.64349
33 326.60756 1695.30498
34 865.87031 326.60756
35 122.73750 865.87031
36 -885.09396 122.73750
37 3310.54616 -885.09396
38 -1965.84059 3310.54616
39 -2546.16569 -1965.84059
40 -1930.79138 -2546.16569
41 -551.33146 -1930.79138
42 2555.65588 -551.33146
43 2693.43899 2555.65588
44 414.17535 2693.43899
45 5174.98708 414.17535
46 -211.57220 5174.98708
47 -535.62584 -211.57220
48 -26.67487 -535.62584
49 -627.95435 -26.67487
50 817.52960 -627.95435
51 -2696.12285 817.52960
52 -3998.06697 -2696.12285
53 -232.05653 -3998.06697
54 2509.33513 -232.05653
55 133.04174 2509.33513
56 2655.69837 133.04174
57 1778.35167 2655.69837
58 -1418.56945 1778.35167
59 66.35303 -1418.56945
60 -2132.66230 66.35303
61 1363.72729 -2132.66230
62 -2260.20749 1363.72729
63 -3575.18413 -2260.20749
64 -2180.02628 -3575.18413
65 1303.16494 -2180.02628
66 1633.80985 1303.16494
67 73.93157 1633.80985
68 1347.12099 73.93157
69 3079.24018 1347.12099
70 -1598.09949 3079.24018
71 -479.81975 -1598.09949
72 -2235.14527 -479.81975
73 1218.93317 -2235.14527
74 58.17777 1218.93317
75 -3662.95818 58.17777
76 -2627.02494 -3662.95818
77 -1807.94737 -2627.02494
78 711.16928 -1807.94737
79 162.67066 711.16928
80 1454.03957 162.67066
81 797.08691 1454.03957
82 -1324.22813 797.08691
83 -651.87286 -1324.22813
84 -106.86205 -651.87286
85 -327.65426 -106.86205
86 428.02440 -327.65426
87 -1846.77576 428.02440
88 -2809.43566 -1846.77576
89 -1439.92837 -2809.43566
90 30.85484 -1439.92837
91 589.15292 30.85484
92 1727.11767 589.15292
93 371.60516 1727.11767
94 -1660.82021 371.60516
95 73.82619 -1660.82021
96 1160.40491 73.82619
97 -883.82107 1160.40491
98 -1012.84885 -883.82107
99 -1380.17010 -1012.84885
100 -2733.74741 -1380.17010
101 -316.70139 -2733.74741
102 887.14626 -316.70139
103 921.71917 887.14626
104 1714.95689 921.71917
105 1455.51694 1714.95689
106 -52.09527 1455.51694
107 -356.17748 -52.09527
108 1205.52328 -356.17748
109 -775.89924 1205.52328
110 -607.43635 -775.89924
111 -1892.45501 -607.43635
112 -844.96850 -1892.45501
113 -521.74074 -844.96850
114 1831.93860 -521.74074
115 1009.96722 1831.93860
116 1625.70967 1009.96722
117 441.18424 1625.70967
118 -920.03785 441.18424
119 150.38580 -920.03785
120 242.68634 150.38580
121 -1446.65470 242.68634
122 -516.24483 -1446.65470
123 -2706.02795 -516.24483
124 -1187.81692 -2706.02795
125 NA -1187.81692
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -695.90197 -3017.62577
[2,] 2550.25802 -695.90197
[3,] -2119.05419 2550.25802
[4,] 457.80293 -2119.05419
[5,] -2549.22990 457.80293
[6,] 1927.54484 -2549.22990
[7,] 2339.17647 1927.54484
[8,] -1936.20761 2339.17647
[9,] 2831.72058 -1936.20761
[10,] -1374.41464 2831.72058
[11,] 3379.29700 -1374.41464
[12,] -603.72044 3379.29700
[13,] -62.67304 -603.72044
[14,] -467.24414 -62.67304
[15,] 660.50487 -467.24414
[16,] 640.18123 660.50487
[17,] 1365.62479 640.18123
[18,] 1489.76130 1365.62479
[19,] 4358.55441 1489.76130
[20,] 3077.20971 4358.55441
[21,] -1126.12493 3077.20971
[22,] -1385.02133 -1126.12493
[23,] 2285.17012 -1385.02133
[24,] 2973.32884 2285.17012
[25,] -1153.49244 2973.32884
[26,] -1999.12376 -1153.49244
[27,] 1947.15157 -1999.12376
[28,] -1885.32472 1947.15157
[29,] -4559.86522 -1885.32472
[30,] 8560.31715 -4559.86522
[31,] -1591.64349 8560.31715
[32,] 1695.30498 -1591.64349
[33,] 326.60756 1695.30498
[34,] 865.87031 326.60756
[35,] 122.73750 865.87031
[36,] -885.09396 122.73750
[37,] 3310.54616 -885.09396
[38,] -1965.84059 3310.54616
[39,] -2546.16569 -1965.84059
[40,] -1930.79138 -2546.16569
[41,] -551.33146 -1930.79138
[42,] 2555.65588 -551.33146
[43,] 2693.43899 2555.65588
[44,] 414.17535 2693.43899
[45,] 5174.98708 414.17535
[46,] -211.57220 5174.98708
[47,] -535.62584 -211.57220
[48,] -26.67487 -535.62584
[49,] -627.95435 -26.67487
[50,] 817.52960 -627.95435
[51,] -2696.12285 817.52960
[52,] -3998.06697 -2696.12285
[53,] -232.05653 -3998.06697
[54,] 2509.33513 -232.05653
[55,] 133.04174 2509.33513
[56,] 2655.69837 133.04174
[57,] 1778.35167 2655.69837
[58,] -1418.56945 1778.35167
[59,] 66.35303 -1418.56945
[60,] -2132.66230 66.35303
[61,] 1363.72729 -2132.66230
[62,] -2260.20749 1363.72729
[63,] -3575.18413 -2260.20749
[64,] -2180.02628 -3575.18413
[65,] 1303.16494 -2180.02628
[66,] 1633.80985 1303.16494
[67,] 73.93157 1633.80985
[68,] 1347.12099 73.93157
[69,] 3079.24018 1347.12099
[70,] -1598.09949 3079.24018
[71,] -479.81975 -1598.09949
[72,] -2235.14527 -479.81975
[73,] 1218.93317 -2235.14527
[74,] 58.17777 1218.93317
[75,] -3662.95818 58.17777
[76,] -2627.02494 -3662.95818
[77,] -1807.94737 -2627.02494
[78,] 711.16928 -1807.94737
[79,] 162.67066 711.16928
[80,] 1454.03957 162.67066
[81,] 797.08691 1454.03957
[82,] -1324.22813 797.08691
[83,] -651.87286 -1324.22813
[84,] -106.86205 -651.87286
[85,] -327.65426 -106.86205
[86,] 428.02440 -327.65426
[87,] -1846.77576 428.02440
[88,] -2809.43566 -1846.77576
[89,] -1439.92837 -2809.43566
[90,] 30.85484 -1439.92837
[91,] 589.15292 30.85484
[92,] 1727.11767 589.15292
[93,] 371.60516 1727.11767
[94,] -1660.82021 371.60516
[95,] 73.82619 -1660.82021
[96,] 1160.40491 73.82619
[97,] -883.82107 1160.40491
[98,] -1012.84885 -883.82107
[99,] -1380.17010 -1012.84885
[100,] -2733.74741 -1380.17010
[101,] -316.70139 -2733.74741
[102,] 887.14626 -316.70139
[103,] 921.71917 887.14626
[104,] 1714.95689 921.71917
[105,] 1455.51694 1714.95689
[106,] -52.09527 1455.51694
[107,] -356.17748 -52.09527
[108,] 1205.52328 -356.17748
[109,] -775.89924 1205.52328
[110,] -607.43635 -775.89924
[111,] -1892.45501 -607.43635
[112,] -844.96850 -1892.45501
[113,] -521.74074 -844.96850
[114,] 1831.93860 -521.74074
[115,] 1009.96722 1831.93860
[116,] 1625.70967 1009.96722
[117,] 441.18424 1625.70967
[118,] -920.03785 441.18424
[119,] 150.38580 -920.03785
[120,] 242.68634 150.38580
[121,] -1446.65470 242.68634
[122,] -516.24483 -1446.65470
[123,] -2706.02795 -516.24483
[124,] -1187.81692 -2706.02795
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -695.90197 -3017.62577
2 2550.25802 -695.90197
3 -2119.05419 2550.25802
4 457.80293 -2119.05419
5 -2549.22990 457.80293
6 1927.54484 -2549.22990
7 2339.17647 1927.54484
8 -1936.20761 2339.17647
9 2831.72058 -1936.20761
10 -1374.41464 2831.72058
11 3379.29700 -1374.41464
12 -603.72044 3379.29700
13 -62.67304 -603.72044
14 -467.24414 -62.67304
15 660.50487 -467.24414
16 640.18123 660.50487
17 1365.62479 640.18123
18 1489.76130 1365.62479
19 4358.55441 1489.76130
20 3077.20971 4358.55441
21 -1126.12493 3077.20971
22 -1385.02133 -1126.12493
23 2285.17012 -1385.02133
24 2973.32884 2285.17012
25 -1153.49244 2973.32884
26 -1999.12376 -1153.49244
27 1947.15157 -1999.12376
28 -1885.32472 1947.15157
29 -4559.86522 -1885.32472
30 8560.31715 -4559.86522
31 -1591.64349 8560.31715
32 1695.30498 -1591.64349
33 326.60756 1695.30498
34 865.87031 326.60756
35 122.73750 865.87031
36 -885.09396 122.73750
37 3310.54616 -885.09396
38 -1965.84059 3310.54616
39 -2546.16569 -1965.84059
40 -1930.79138 -2546.16569
41 -551.33146 -1930.79138
42 2555.65588 -551.33146
43 2693.43899 2555.65588
44 414.17535 2693.43899
45 5174.98708 414.17535
46 -211.57220 5174.98708
47 -535.62584 -211.57220
48 -26.67487 -535.62584
49 -627.95435 -26.67487
50 817.52960 -627.95435
51 -2696.12285 817.52960
52 -3998.06697 -2696.12285
53 -232.05653 -3998.06697
54 2509.33513 -232.05653
55 133.04174 2509.33513
56 2655.69837 133.04174
57 1778.35167 2655.69837
58 -1418.56945 1778.35167
59 66.35303 -1418.56945
60 -2132.66230 66.35303
61 1363.72729 -2132.66230
62 -2260.20749 1363.72729
63 -3575.18413 -2260.20749
64 -2180.02628 -3575.18413
65 1303.16494 -2180.02628
66 1633.80985 1303.16494
67 73.93157 1633.80985
68 1347.12099 73.93157
69 3079.24018 1347.12099
70 -1598.09949 3079.24018
71 -479.81975 -1598.09949
72 -2235.14527 -479.81975
73 1218.93317 -2235.14527
74 58.17777 1218.93317
75 -3662.95818 58.17777
76 -2627.02494 -3662.95818
77 -1807.94737 -2627.02494
78 711.16928 -1807.94737
79 162.67066 711.16928
80 1454.03957 162.67066
81 797.08691 1454.03957
82 -1324.22813 797.08691
83 -651.87286 -1324.22813
84 -106.86205 -651.87286
85 -327.65426 -106.86205
86 428.02440 -327.65426
87 -1846.77576 428.02440
88 -2809.43566 -1846.77576
89 -1439.92837 -2809.43566
90 30.85484 -1439.92837
91 589.15292 30.85484
92 1727.11767 589.15292
93 371.60516 1727.11767
94 -1660.82021 371.60516
95 73.82619 -1660.82021
96 1160.40491 73.82619
97 -883.82107 1160.40491
98 -1012.84885 -883.82107
99 -1380.17010 -1012.84885
100 -2733.74741 -1380.17010
101 -316.70139 -2733.74741
102 887.14626 -316.70139
103 921.71917 887.14626
104 1714.95689 921.71917
105 1455.51694 1714.95689
106 -52.09527 1455.51694
107 -356.17748 -52.09527
108 1205.52328 -356.17748
109 -775.89924 1205.52328
110 -607.43635 -775.89924
111 -1892.45501 -607.43635
112 -844.96850 -1892.45501
113 -521.74074 -844.96850
114 1831.93860 -521.74074
115 1009.96722 1831.93860
116 1625.70967 1009.96722
117 441.18424 1625.70967
118 -920.03785 441.18424
119 150.38580 -920.03785
120 242.68634 150.38580
121 -1446.65470 242.68634
122 -516.24483 -1446.65470
123 -2706.02795 -516.24483
124 -1187.81692 -2706.02795
> 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/html/freestat/rcomp/tmp/7uhjj1291972174.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8uhjj1291972174.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9nr1m1291972174.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10nr1m1291972174.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/html/freestat/rcomp/tmp/11q9za1291972174.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/html/freestat/rcomp/tmp/12t9yy1291972174.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/html/freestat/rcomp/tmp/13iavs1291972174.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/html/freestat/rcomp/tmp/14rw0m1291972174.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/html/freestat/rcomp/tmp/157ta31291972174.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/html/freestat/rcomp/tmp/16ac8r1291972174.tab")
+ }
>
> try(system("convert tmp/1nxjy1291972173.ps tmp/1nxjy1291972173.png",intern=TRUE))
character(0)
> try(system("convert tmp/2y70j1291972173.ps tmp/2y70j1291972173.png",intern=TRUE))
character(0)
> try(system("convert tmp/3y70j1291972173.ps tmp/3y70j1291972173.png",intern=TRUE))
character(0)
> try(system("convert tmp/4y70j1291972173.ps tmp/4y70j1291972173.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jq2g1291972174.ps tmp/5jq2g1291972174.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jq2g1291972174.ps tmp/6jq2g1291972174.png",intern=TRUE))
character(0)
> try(system("convert tmp/7uhjj1291972174.ps tmp/7uhjj1291972174.png",intern=TRUE))
character(0)
> try(system("convert tmp/8uhjj1291972174.ps tmp/8uhjj1291972174.png",intern=TRUE))
character(0)
> try(system("convert tmp/9nr1m1291972174.ps tmp/9nr1m1291972174.png",intern=TRUE))
character(0)
> try(system("convert tmp/10nr1m1291972174.ps tmp/10nr1m1291972174.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.578 2.751 5.972