R version 2.12.1 (2010-12-16)
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(13
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+ ,dim=c(6
+ ,144)
+ ,dimnames=list(c('Bloggedcomputations'
+ ,'characters'
+ ,'revisions'
+ ,'seconds'
+ ,'includedhyperlinks'
+ ,'includedblogs')
+ ,1:144))
> y <- array(NA,dim=c(6,144),dimnames=list(c('Bloggedcomputations','characters','revisions','seconds','includedhyperlinks','includedblogs'),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 = '4'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
seconds Bloggedcomputations characters revisions includedhyperlinks
1 10823 13 10345 3010 13
2 44480 26 17607 4344 27
3 1929 0 1423 603 0
4 30032 37 20050 6792 37
5 27669 47 21212 7843 39
6 114967 80 93979 13738 99
7 29951 21 15524 4120 21
8 38824 36 16182 4174 33
9 26517 35 19238 6202 36
10 63570 40 28909 8535 44
11 27131 35 22357 5818 33
12 41061 46 25560 9834 47
13 18810 20 9954 4145 19
14 27582 24 18490 4719 41
15 37026 19 17777 3981 22
16 24252 15 25268 3264 17
17 32579 48 37525 11276 46
18 0 0 6023 1 0
19 29666 38 25042 9480 31
20 7533 12 35713 1953 20
21 11892 10 7039 1801 10
22 51557 51 40841 7352 55
23 5737 4 9214 761 6
24 11203 24 17446 1147 17
25 28714 39 10295 3536 33
26 24268 19 13206 3146 33
27 30749 23 26093 6764 32
28 46643 39 20744 7038 37
29 64530 38 68013 8298 44
30 35346 20 12840 5718 22
31 5766 20 12672 2493 15
32 29217 41 10872 4226 18
33 15912 26 21325 3553 25
34 3728 0 24542 58 7
35 37494 31 16401 4425 35
36 0 0 0 0 0
37 13214 8 12821 3705 14
38 19576 35 14662 4968 31
39 13632 3 22190 2320 9
40 67378 47 37929 9820 59
41 29387 42 18009 3606 62
42 15936 11 11076 3987 12
43 18156 10 24981 2138 23
44 23750 26 30691 2299 31
45 15559 27 29164 3308 57
46 21713 0 13985 4721 23
47 12023 15 7588 1369 14
48 23588 32 20023 4118 31
49 28661 13 25524 5396 17
50 16874 25 14717 3704 24
51 11804 10 6832 1801 11
52 12949 14 9624 3814 16
53 38340 24 24300 5010 32
54 36573 29 21790 5369 36
55 40068 40 16493 3952 37
56 25561 22 9269 3264 25
57 31287 27 20105 4177 30
58 8383 8 11216 2352 10
59 29178 27 15569 5624 16
60 1237 0 21799 176 3
61 10241 0 3772 2356 0
62 8219 17 6057 1700 17
63 9348 7 20828 1262 9
64 25242 18 9976 2766 22
65 24267 7 14055 2536 5
66 25902 24 17455 4931 23
67 51849 18 39553 9606 16
68 29065 39 14818 4097 53
69 22417 17 17065 4537 23
70 1714 0 1536 516 0
71 29085 39 11938 2643 51
72 22118 21 24589 1277 25
73 14803 29 21332 3230 51
74 13243 27 13229 3356 46
75 13985 23 11331 2204 16
76 657 0 853 342 0
77 26171 31 19821 6783 25
78 34867 19 34666 4213 34
79 12297 12 15051 2822 14
80 17487 23 27969 5199 32
81 13461 33 17897 4780 24
82 15192 21 6031 2341 16
83 16584 17 7153 1825 19
84 22892 27 13365 4653 27
85 7081 14 11197 1524 24
86 21623 12 25291 2685 12
87 41992 21 28994 9230 43
88 11301 14 10461 2490 13
89 15230 14 16415 4718 19
90 14667 22 8495 2937 24
91 23795 25 18318 3599 27
92 28055 36 25143 4487 26
93 29162 10 20471 2149 14
94 14962 16 14561 1921 26
95 8749 12 16902 2896 15
96 37310 20 12994 5815 30
97 31551 38 29697 4679 33
98 9604 13 3895 786 14
99 13937 12 9807 4006 11
100 16850 11 10711 2686 12
101 3439 8 2325 593 8
102 16638 22 19000 2454 22
103 12847 14 22418 4061 12
104 13462 7 7872 2856 6
105 8086 14 5650 1678 10
106 2255 2 3979 460 1
107 25918 35 14956 5054 31
108 3255 5 3738 999 5
109 0 0 0 0 0
110 16138 34 10586 3685 35
111 5941 12 18122 503 15
112 27123 34 17899 3595 36
113 19148 30 10913 3367 27
114 15214 21 18060 1330 36
115 0 0 0 0 0
116 0 0 0 0 0
117 34998 28 15452 6878 29
118 18998 17 33996 3080 19
119 10651 12 8877 1349 16
120 13465 14 18708 3339 15
121 13 7 2781 4 1
122 32505 41 20854 3446 36
123 15769 21 8179 1467 22
124 5936 28 7139 255 16
125 4174 1 13798 424 1
126 9876 10 5619 2374 10
127 17678 31 13050 3519 31
128 14633 7 11297 2650 22
129 13380 26 16170 2757 22
130 0 1 0 0 0
131 0 0 0 0 0
132 5652 12 20539 459 10
133 0 0 0 0 0
134 3636 18 10056 549 9
135 0 5 0 0 0
136 1695 4 2418 206 0
137 0 0 0 0 0
138 8778 6 11806 2885 7
139 4148 0 15924 1034 2
140 0 0 0 0 0
141 0 0 0 0 0
142 10404 15 7084 2558 16
143 20794 0 14831 5086 25
144 11200 12 6585 1392 6
includedblogs
1 13
2 24
3 0
4 37
5 38
6 96
7 21
8 33
9 35
10 40
11 33
12 47
13 19
14 40
15 22
16 17
17 46
18 0
19 31
20 20
21 10
22 55
23 6
24 17
25 33
26 33
27 32
28 36
29 39
30 22
31 15
32 18
33 24
34 7
35 34
36 0
37 7
38 31
39 9
40 52
41 60
42 11
43 20
44 31
45 56
46 23
47 14
48 30
49 17
50 24
51 11
52 16
53 30
54 35
55 37
56 25
57 30
58 9
59 16
60 3
61 0
62 19
63 9
64 18
65 5
66 22
67 16
68 53
69 23
70 0
71 50
72 25
73 48
74 46
75 16
76 0
77 25
78 33
79 14
80 30
81 23
82 16
83 19
84 27
85 24
86 12
87 43
88 13
89 19
90 24
91 27
92 26
93 14
94 26
95 15
96 29
97 33
98 14
99 11
100 11
101 8
102 22
103 11
104 6
105 10
106 0
107 30
108 5
109 0
110 34
111 15
112 34
113 28
114 36
115 0
116 0
117 29
118 19
119 15
120 15
121 1
122 36
123 22
124 16
125 1
126 10
127 31
128 22
129 21
130 0
131 0
132 10
133 0
134 9
135 0
136 0
137 0
138 7
139 2
140 0
141 0
142 16
143 25
144 6
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Bloggedcomputations characters
-1582.5573 199.4435 0.3307
revisions includedhyperlinks includedblogs
2.7039 1492.9494 -1382.2171
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-23403.8 -3369.0 127.3 3392.4 17261.0
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.583e+03 1.011e+03 -1.566 0.11974
Bloggedcomputations 1.994e+02 8.957e+01 2.227 0.02760 *
characters 3.307e-01 7.172e-02 4.611 9.06e-06 ***
revisions 2.704e+00 3.768e-01 7.176 4.02e-11 ***
includedhyperlinks 1.493e+03 5.141e+02 2.904 0.00429 **
includedblogs -1.382e+03 5.245e+02 -2.635 0.00937 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6708 on 138 degrees of freedom
Multiple R-squared: 0.8338, Adjusted R-squared: 0.8277
F-statistic: 138.4 on 5 and 138 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,] 0.8314765 3.370470e-01 1.685235e-01
[2,] 0.9068601 1.862797e-01 9.313986e-02
[3,] 0.8422151 3.155699e-01 1.577849e-01
[4,] 0.8467492 3.065016e-01 1.532508e-01
[5,] 0.7750827 4.498345e-01 2.249173e-01
[6,] 0.8830754 2.338492e-01 1.169246e-01
[7,] 0.9632933 7.341336e-02 3.670668e-02
[8,] 0.9539784 9.204314e-02 4.602157e-02
[9,] 0.9797907 4.041853e-02 2.020927e-02
[10,] 0.9850131 2.997373e-02 1.498686e-02
[11,] 0.9880347 2.393056e-02 1.196528e-02
[12,] 0.9996487 7.025251e-04 3.512625e-04
[13,] 0.9993882 1.223655e-03 6.118274e-04
[14,] 0.9989501 2.099725e-03 1.049863e-03
[15,] 0.9982264 3.547161e-03 1.773581e-03
[16,] 0.9983700 3.260053e-03 1.630026e-03
[17,] 0.9975256 4.948824e-03 2.474412e-03
[18,] 0.9964175 7.165013e-03 3.582506e-03
[19,] 0.9949878 1.002438e-02 5.012190e-03
[20,] 0.9961988 7.602399e-03 3.801199e-03
[21,] 0.9970159 5.968255e-03 2.984128e-03
[22,] 0.9993224 1.355222e-03 6.776112e-04
[23,] 0.9995366 9.268710e-04 4.634355e-04
[24,] 0.9996725 6.550890e-04 3.275445e-04
[25,] 0.9998602 2.795598e-04 1.397799e-04
[26,] 0.9997766 4.467982e-04 2.233991e-04
[27,] 0.9997989 4.021983e-04 2.010991e-04
[28,] 0.9996655 6.689316e-04 3.344658e-04
[29,] 0.9999869 2.619818e-05 1.309909e-05
[30,] 0.9999914 1.721678e-05 8.608392e-06
[31,] 0.9999859 2.810133e-05 1.405066e-05
[32,] 0.9999866 2.677203e-05 1.338602e-05
[33,] 0.9999968 6.346998e-06 3.173499e-06
[34,] 0.9999944 1.119339e-05 5.596694e-06
[35,] 0.9999921 1.573218e-05 7.866088e-06
[36,] 0.9999875 2.498624e-05 1.249312e-05
[37,] 0.9999986 2.732796e-06 1.366398e-06
[38,] 0.9999983 3.303806e-06 1.651903e-06
[39,] 0.9999972 5.568793e-06 2.784397e-06
[40,] 0.9999957 8.542327e-06 4.271163e-06
[41,] 0.9999935 1.294139e-05 6.470697e-06
[42,] 0.9999908 1.835673e-05 9.178363e-06
[43,] 0.9999856 2.882695e-05 1.441348e-05
[44,] 0.9999793 4.130687e-05 2.065344e-05
[45,] 0.9999863 2.735270e-05 1.367635e-05
[46,] 0.9999851 2.985543e-05 1.492772e-05
[47,] 0.9999975 5.074020e-06 2.537010e-06
[48,] 0.9999981 3.879715e-06 1.939857e-06
[49,] 0.9999981 3.797442e-06 1.898721e-06
[50,] 0.9999971 5.721663e-06 2.860832e-06
[51,] 0.9999957 8.647667e-06 4.323833e-06
[52,] 0.9999945 1.091779e-05 5.458896e-06
[53,] 0.9999924 1.526786e-05 7.633932e-06
[54,] 0.9999871 2.570536e-05 1.285268e-05
[55,] 0.9999786 4.272374e-05 2.136187e-05
[56,] 0.9999932 1.367261e-05 6.836305e-06
[57,] 0.9999988 2.319810e-06 1.159905e-06
[58,] 0.9999981 3.825732e-06 1.912866e-06
[59,] 0.9999995 9.342087e-07 4.671044e-07
[60,] 0.9999991 1.760939e-06 8.804695e-07
[61,] 0.9999984 3.262065e-06 1.631032e-06
[62,] 0.9999970 5.921421e-06 2.960710e-06
[63,] 0.9999975 4.926476e-06 2.463238e-06
[64,] 0.9999975 5.062398e-06 2.531199e-06
[65,] 0.9999991 1.877540e-06 9.387699e-07
[66,] 0.9999998 4.205115e-07 2.102557e-07
[67,] 0.9999996 7.955388e-07 3.977694e-07
[68,] 0.9999992 1.524734e-06 7.623670e-07
[69,] 0.9999990 2.042672e-06 1.021336e-06
[70,] 0.9999994 1.125986e-06 5.629929e-07
[71,] 0.9999990 1.955153e-06 9.775764e-07
[72,] 0.9999998 4.074194e-07 2.037097e-07
[73,] 1.0000000 2.980770e-08 1.490385e-08
[74,] 1.0000000 5.618029e-08 2.809014e-08
[75,] 1.0000000 6.530202e-08 3.265101e-08
[76,] 0.9999999 1.353689e-07 6.768444e-08
[77,] 0.9999999 1.414985e-07 7.074926e-08
[78,] 0.9999999 1.243667e-07 6.218333e-08
[79,] 0.9999999 2.521986e-07 1.260993e-07
[80,] 0.9999998 4.999855e-07 2.499928e-07
[81,] 0.9999998 3.639581e-07 1.819791e-07
[82,] 0.9999997 6.365235e-07 3.182618e-07
[83,] 0.9999994 1.210028e-06 6.050141e-07
[84,] 0.9999989 2.182841e-06 1.091420e-06
[85,] 1.0000000 9.942052e-10 4.971026e-10
[86,] 1.0000000 2.514834e-09 1.257417e-09
[87,] 1.0000000 1.428595e-09 7.142975e-10
[88,] 1.0000000 3.287638e-11 1.643819e-11
[89,] 1.0000000 4.750594e-11 2.375297e-11
[90,] 1.0000000 9.398188e-11 4.699094e-11
[91,] 1.0000000 2.153473e-10 1.076737e-10
[92,] 1.0000000 1.568810e-10 7.844051e-11
[93,] 1.0000000 4.381549e-10 2.190774e-10
[94,] 1.0000000 1.211556e-09 6.057781e-10
[95,] 1.0000000 8.091829e-10 4.045914e-10
[96,] 1.0000000 1.610942e-09 8.054709e-10
[97,] 1.0000000 4.498754e-09 2.249377e-09
[98,] 1.0000000 1.223940e-08 6.119701e-09
[99,] 1.0000000 3.241788e-08 1.620894e-08
[100,] 1.0000000 8.208610e-08 4.104305e-08
[101,] 0.9999999 2.152945e-07 1.076472e-07
[102,] 1.0000000 2.087533e-08 1.043767e-08
[103,] 1.0000000 5.215767e-08 2.607883e-08
[104,] 0.9999999 1.100378e-07 5.501892e-08
[105,] 0.9999999 1.993398e-07 9.966990e-08
[106,] 0.9999998 4.841641e-07 2.420820e-07
[107,] 0.9999993 1.342190e-06 6.710951e-07
[108,] 0.9999982 3.627521e-06 1.813761e-06
[109,] 0.9999989 2.106026e-06 1.053013e-06
[110,] 0.9999973 5.467575e-06 2.733788e-06
[111,] 0.9999952 9.650772e-06 4.825386e-06
[112,] 0.9999893 2.148193e-05 1.074097e-05
[113,] 0.9999719 5.618916e-05 2.809458e-05
[114,] 0.9999997 5.562114e-07 2.781057e-07
[115,] 1.0000000 7.922185e-08 3.961092e-08
[116,] 0.9999998 3.584455e-07 1.792228e-07
[117,] 0.9999994 1.146108e-06 5.730541e-07
[118,] 0.9999975 4.972447e-06 2.486223e-06
[119,] 0.9999916 1.681700e-05 8.408500e-06
[120,] 0.9999731 5.380008e-05 2.690004e-05
[121,] 0.9998948 2.103565e-04 1.051783e-04
[122,] 0.9995972 8.055670e-04 4.027835e-04
[123,] 0.9985401 2.919760e-03 1.459880e-03
[124,] 0.9953891 9.221842e-03 4.610921e-03
[125,] 0.9852190 2.956210e-02 1.478105e-02
[126,] 0.9656338 6.873245e-02 3.436623e-02
[127,] 0.9046336 1.907329e-01 9.536644e-02
> postscript(file="/var/www/rcomp/tmp/13r8v1322153847.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/29hul1322153847.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3bwv71322153847.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/418pn1322153847.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5f50s1322153847.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
-3186.482931 16172.377675 1410.524536 -4857.253250 -14044.454798
6 7 8 9 10
17260.981081 8746.135719 12935.092368 -7381.017211 14135.942407
11 12 13 14 15
-5045.698045 -6777.990427 -199.643814 -418.521409 15740.105295
16 17 18 19 20
3779.103682 -23403.846381 -411.856997 -13677.239437 -12582.907113
21 22 23 24 25
3175.336722 3492.901558 752.775672 -2754.058909 5898.605945
26 27 28 29 30
5533.387468 -2716.996187 9077.981270 1822.372227 10796.524225
31 32 33 34 35
-9232.622852 5607.188139 -8500.399033 -3737.046355 10247.522216
36 37 38 39 40
1582.557318 -12282.521764 -7536.279344 8.639594 4282.881713
41 42 43 44 45
-2742.568937 -1829.549495 -2991.193340 348.963823 -14526.047557
46 47 48 49 50
3358.846555 2852.741541 -3782.623532 2737.558598 -4069.138807
51 52 53 54 55
3045.055991 -3527.659301 7245.734527 5280.111126 13435.818407
56 57 58 59 60
8096.755302 6219.895609 -4188.125792 3248.545979 -5197.114124
61 62 63 64 65
4205.759713 693.368416 -1761.985695 4491.621220 12394.861362
66 67 68 69 70
-336.314202 9016.364087 1022.370628 151.322474 1393.399071
71 72 73 74 75
4765.501499 5159.825568 -14980.150299 -9102.112063 -497.802858
76 77 78 79 80
1032.739994 -6092.741958 4657.864650 -2671.632472 -15132.144553
81 82 83 84 85
-14420.907375 2490.271678 5372.048658 -901.166765 -4609.686312
86 87 88 89 90
3860.065236 79.631162 -1540.242643 -6268.884085 -1546.378015
91 92 93 94 95
1612.783259 -868.371374 14619.691056 465.080722 -7142.551857
96 97 98 99 100
10179.241940 -571.474653 3630.235724 -2166.780132 2722.962067
101 102 103 104 105
167.879799 -1521.752099 -9467.590002 2658.491527 -636.533879
106 107 108 109 110
-613.878644 -2906.255453 -650.644482 1582.557318 -7782.972687
111 112 113 114 115
-3883.483943 -465.861361 426.810079 -946.501887 1582.557318
116 117 118 119 120
1582.557318 4077.544863 -4483.935989 103.217142 -4620.495042
121 122 123 124 125
-841.727950 5710.181987 4055.802269 -2887.834749 -262.863855
126 127 128 129 130
79.556736 -4185.449063 1482.190407 -6843.197802 1383.113789
131 132 133 134 135
1582.557318 -4299.112843 1582.557318 -4177.833793 585.339672
136 137 138 139 140
1123.179616 1582.557318 -3316.122515 -2552.583881 1582.557318
141 142 143 144
1582.557318 -2036.030145 951.688966 3783.416648
> postscript(file="/var/www/rcomp/tmp/6v6qg1322153847.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 -3186.482931 NA
1 16172.377675 -3186.482931
2 1410.524536 16172.377675
3 -4857.253250 1410.524536
4 -14044.454798 -4857.253250
5 17260.981081 -14044.454798
6 8746.135719 17260.981081
7 12935.092368 8746.135719
8 -7381.017211 12935.092368
9 14135.942407 -7381.017211
10 -5045.698045 14135.942407
11 -6777.990427 -5045.698045
12 -199.643814 -6777.990427
13 -418.521409 -199.643814
14 15740.105295 -418.521409
15 3779.103682 15740.105295
16 -23403.846381 3779.103682
17 -411.856997 -23403.846381
18 -13677.239437 -411.856997
19 -12582.907113 -13677.239437
20 3175.336722 -12582.907113
21 3492.901558 3175.336722
22 752.775672 3492.901558
23 -2754.058909 752.775672
24 5898.605945 -2754.058909
25 5533.387468 5898.605945
26 -2716.996187 5533.387468
27 9077.981270 -2716.996187
28 1822.372227 9077.981270
29 10796.524225 1822.372227
30 -9232.622852 10796.524225
31 5607.188139 -9232.622852
32 -8500.399033 5607.188139
33 -3737.046355 -8500.399033
34 10247.522216 -3737.046355
35 1582.557318 10247.522216
36 -12282.521764 1582.557318
37 -7536.279344 -12282.521764
38 8.639594 -7536.279344
39 4282.881713 8.639594
40 -2742.568937 4282.881713
41 -1829.549495 -2742.568937
42 -2991.193340 -1829.549495
43 348.963823 -2991.193340
44 -14526.047557 348.963823
45 3358.846555 -14526.047557
46 2852.741541 3358.846555
47 -3782.623532 2852.741541
48 2737.558598 -3782.623532
49 -4069.138807 2737.558598
50 3045.055991 -4069.138807
51 -3527.659301 3045.055991
52 7245.734527 -3527.659301
53 5280.111126 7245.734527
54 13435.818407 5280.111126
55 8096.755302 13435.818407
56 6219.895609 8096.755302
57 -4188.125792 6219.895609
58 3248.545979 -4188.125792
59 -5197.114124 3248.545979
60 4205.759713 -5197.114124
61 693.368416 4205.759713
62 -1761.985695 693.368416
63 4491.621220 -1761.985695
64 12394.861362 4491.621220
65 -336.314202 12394.861362
66 9016.364087 -336.314202
67 1022.370628 9016.364087
68 151.322474 1022.370628
69 1393.399071 151.322474
70 4765.501499 1393.399071
71 5159.825568 4765.501499
72 -14980.150299 5159.825568
73 -9102.112063 -14980.150299
74 -497.802858 -9102.112063
75 1032.739994 -497.802858
76 -6092.741958 1032.739994
77 4657.864650 -6092.741958
78 -2671.632472 4657.864650
79 -15132.144553 -2671.632472
80 -14420.907375 -15132.144553
81 2490.271678 -14420.907375
82 5372.048658 2490.271678
83 -901.166765 5372.048658
84 -4609.686312 -901.166765
85 3860.065236 -4609.686312
86 79.631162 3860.065236
87 -1540.242643 79.631162
88 -6268.884085 -1540.242643
89 -1546.378015 -6268.884085
90 1612.783259 -1546.378015
91 -868.371374 1612.783259
92 14619.691056 -868.371374
93 465.080722 14619.691056
94 -7142.551857 465.080722
95 10179.241940 -7142.551857
96 -571.474653 10179.241940
97 3630.235724 -571.474653
98 -2166.780132 3630.235724
99 2722.962067 -2166.780132
100 167.879799 2722.962067
101 -1521.752099 167.879799
102 -9467.590002 -1521.752099
103 2658.491527 -9467.590002
104 -636.533879 2658.491527
105 -613.878644 -636.533879
106 -2906.255453 -613.878644
107 -650.644482 -2906.255453
108 1582.557318 -650.644482
109 -7782.972687 1582.557318
110 -3883.483943 -7782.972687
111 -465.861361 -3883.483943
112 426.810079 -465.861361
113 -946.501887 426.810079
114 1582.557318 -946.501887
115 1582.557318 1582.557318
116 4077.544863 1582.557318
117 -4483.935989 4077.544863
118 103.217142 -4483.935989
119 -4620.495042 103.217142
120 -841.727950 -4620.495042
121 5710.181987 -841.727950
122 4055.802269 5710.181987
123 -2887.834749 4055.802269
124 -262.863855 -2887.834749
125 79.556736 -262.863855
126 -4185.449063 79.556736
127 1482.190407 -4185.449063
128 -6843.197802 1482.190407
129 1383.113789 -6843.197802
130 1582.557318 1383.113789
131 -4299.112843 1582.557318
132 1582.557318 -4299.112843
133 -4177.833793 1582.557318
134 585.339672 -4177.833793
135 1123.179616 585.339672
136 1582.557318 1123.179616
137 -3316.122515 1582.557318
138 -2552.583881 -3316.122515
139 1582.557318 -2552.583881
140 1582.557318 1582.557318
141 -2036.030145 1582.557318
142 951.688966 -2036.030145
143 3783.416648 951.688966
144 NA 3783.416648
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 16172.377675 -3186.482931
[2,] 1410.524536 16172.377675
[3,] -4857.253250 1410.524536
[4,] -14044.454798 -4857.253250
[5,] 17260.981081 -14044.454798
[6,] 8746.135719 17260.981081
[7,] 12935.092368 8746.135719
[8,] -7381.017211 12935.092368
[9,] 14135.942407 -7381.017211
[10,] -5045.698045 14135.942407
[11,] -6777.990427 -5045.698045
[12,] -199.643814 -6777.990427
[13,] -418.521409 -199.643814
[14,] 15740.105295 -418.521409
[15,] 3779.103682 15740.105295
[16,] -23403.846381 3779.103682
[17,] -411.856997 -23403.846381
[18,] -13677.239437 -411.856997
[19,] -12582.907113 -13677.239437
[20,] 3175.336722 -12582.907113
[21,] 3492.901558 3175.336722
[22,] 752.775672 3492.901558
[23,] -2754.058909 752.775672
[24,] 5898.605945 -2754.058909
[25,] 5533.387468 5898.605945
[26,] -2716.996187 5533.387468
[27,] 9077.981270 -2716.996187
[28,] 1822.372227 9077.981270
[29,] 10796.524225 1822.372227
[30,] -9232.622852 10796.524225
[31,] 5607.188139 -9232.622852
[32,] -8500.399033 5607.188139
[33,] -3737.046355 -8500.399033
[34,] 10247.522216 -3737.046355
[35,] 1582.557318 10247.522216
[36,] -12282.521764 1582.557318
[37,] -7536.279344 -12282.521764
[38,] 8.639594 -7536.279344
[39,] 4282.881713 8.639594
[40,] -2742.568937 4282.881713
[41,] -1829.549495 -2742.568937
[42,] -2991.193340 -1829.549495
[43,] 348.963823 -2991.193340
[44,] -14526.047557 348.963823
[45,] 3358.846555 -14526.047557
[46,] 2852.741541 3358.846555
[47,] -3782.623532 2852.741541
[48,] 2737.558598 -3782.623532
[49,] -4069.138807 2737.558598
[50,] 3045.055991 -4069.138807
[51,] -3527.659301 3045.055991
[52,] 7245.734527 -3527.659301
[53,] 5280.111126 7245.734527
[54,] 13435.818407 5280.111126
[55,] 8096.755302 13435.818407
[56,] 6219.895609 8096.755302
[57,] -4188.125792 6219.895609
[58,] 3248.545979 -4188.125792
[59,] -5197.114124 3248.545979
[60,] 4205.759713 -5197.114124
[61,] 693.368416 4205.759713
[62,] -1761.985695 693.368416
[63,] 4491.621220 -1761.985695
[64,] 12394.861362 4491.621220
[65,] -336.314202 12394.861362
[66,] 9016.364087 -336.314202
[67,] 1022.370628 9016.364087
[68,] 151.322474 1022.370628
[69,] 1393.399071 151.322474
[70,] 4765.501499 1393.399071
[71,] 5159.825568 4765.501499
[72,] -14980.150299 5159.825568
[73,] -9102.112063 -14980.150299
[74,] -497.802858 -9102.112063
[75,] 1032.739994 -497.802858
[76,] -6092.741958 1032.739994
[77,] 4657.864650 -6092.741958
[78,] -2671.632472 4657.864650
[79,] -15132.144553 -2671.632472
[80,] -14420.907375 -15132.144553
[81,] 2490.271678 -14420.907375
[82,] 5372.048658 2490.271678
[83,] -901.166765 5372.048658
[84,] -4609.686312 -901.166765
[85,] 3860.065236 -4609.686312
[86,] 79.631162 3860.065236
[87,] -1540.242643 79.631162
[88,] -6268.884085 -1540.242643
[89,] -1546.378015 -6268.884085
[90,] 1612.783259 -1546.378015
[91,] -868.371374 1612.783259
[92,] 14619.691056 -868.371374
[93,] 465.080722 14619.691056
[94,] -7142.551857 465.080722
[95,] 10179.241940 -7142.551857
[96,] -571.474653 10179.241940
[97,] 3630.235724 -571.474653
[98,] -2166.780132 3630.235724
[99,] 2722.962067 -2166.780132
[100,] 167.879799 2722.962067
[101,] -1521.752099 167.879799
[102,] -9467.590002 -1521.752099
[103,] 2658.491527 -9467.590002
[104,] -636.533879 2658.491527
[105,] -613.878644 -636.533879
[106,] -2906.255453 -613.878644
[107,] -650.644482 -2906.255453
[108,] 1582.557318 -650.644482
[109,] -7782.972687 1582.557318
[110,] -3883.483943 -7782.972687
[111,] -465.861361 -3883.483943
[112,] 426.810079 -465.861361
[113,] -946.501887 426.810079
[114,] 1582.557318 -946.501887
[115,] 1582.557318 1582.557318
[116,] 4077.544863 1582.557318
[117,] -4483.935989 4077.544863
[118,] 103.217142 -4483.935989
[119,] -4620.495042 103.217142
[120,] -841.727950 -4620.495042
[121,] 5710.181987 -841.727950
[122,] 4055.802269 5710.181987
[123,] -2887.834749 4055.802269
[124,] -262.863855 -2887.834749
[125,] 79.556736 -262.863855
[126,] -4185.449063 79.556736
[127,] 1482.190407 -4185.449063
[128,] -6843.197802 1482.190407
[129,] 1383.113789 -6843.197802
[130,] 1582.557318 1383.113789
[131,] -4299.112843 1582.557318
[132,] 1582.557318 -4299.112843
[133,] -4177.833793 1582.557318
[134,] 585.339672 -4177.833793
[135,] 1123.179616 585.339672
[136,] 1582.557318 1123.179616
[137,] -3316.122515 1582.557318
[138,] -2552.583881 -3316.122515
[139,] 1582.557318 -2552.583881
[140,] 1582.557318 1582.557318
[141,] -2036.030145 1582.557318
[142,] 951.688966 -2036.030145
[143,] 3783.416648 951.688966
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 16172.377675 -3186.482931
2 1410.524536 16172.377675
3 -4857.253250 1410.524536
4 -14044.454798 -4857.253250
5 17260.981081 -14044.454798
6 8746.135719 17260.981081
7 12935.092368 8746.135719
8 -7381.017211 12935.092368
9 14135.942407 -7381.017211
10 -5045.698045 14135.942407
11 -6777.990427 -5045.698045
12 -199.643814 -6777.990427
13 -418.521409 -199.643814
14 15740.105295 -418.521409
15 3779.103682 15740.105295
16 -23403.846381 3779.103682
17 -411.856997 -23403.846381
18 -13677.239437 -411.856997
19 -12582.907113 -13677.239437
20 3175.336722 -12582.907113
21 3492.901558 3175.336722
22 752.775672 3492.901558
23 -2754.058909 752.775672
24 5898.605945 -2754.058909
25 5533.387468 5898.605945
26 -2716.996187 5533.387468
27 9077.981270 -2716.996187
28 1822.372227 9077.981270
29 10796.524225 1822.372227
30 -9232.622852 10796.524225
31 5607.188139 -9232.622852
32 -8500.399033 5607.188139
33 -3737.046355 -8500.399033
34 10247.522216 -3737.046355
35 1582.557318 10247.522216
36 -12282.521764 1582.557318
37 -7536.279344 -12282.521764
38 8.639594 -7536.279344
39 4282.881713 8.639594
40 -2742.568937 4282.881713
41 -1829.549495 -2742.568937
42 -2991.193340 -1829.549495
43 348.963823 -2991.193340
44 -14526.047557 348.963823
45 3358.846555 -14526.047557
46 2852.741541 3358.846555
47 -3782.623532 2852.741541
48 2737.558598 -3782.623532
49 -4069.138807 2737.558598
50 3045.055991 -4069.138807
51 -3527.659301 3045.055991
52 7245.734527 -3527.659301
53 5280.111126 7245.734527
54 13435.818407 5280.111126
55 8096.755302 13435.818407
56 6219.895609 8096.755302
57 -4188.125792 6219.895609
58 3248.545979 -4188.125792
59 -5197.114124 3248.545979
60 4205.759713 -5197.114124
61 693.368416 4205.759713
62 -1761.985695 693.368416
63 4491.621220 -1761.985695
64 12394.861362 4491.621220
65 -336.314202 12394.861362
66 9016.364087 -336.314202
67 1022.370628 9016.364087
68 151.322474 1022.370628
69 1393.399071 151.322474
70 4765.501499 1393.399071
71 5159.825568 4765.501499
72 -14980.150299 5159.825568
73 -9102.112063 -14980.150299
74 -497.802858 -9102.112063
75 1032.739994 -497.802858
76 -6092.741958 1032.739994
77 4657.864650 -6092.741958
78 -2671.632472 4657.864650
79 -15132.144553 -2671.632472
80 -14420.907375 -15132.144553
81 2490.271678 -14420.907375
82 5372.048658 2490.271678
83 -901.166765 5372.048658
84 -4609.686312 -901.166765
85 3860.065236 -4609.686312
86 79.631162 3860.065236
87 -1540.242643 79.631162
88 -6268.884085 -1540.242643
89 -1546.378015 -6268.884085
90 1612.783259 -1546.378015
91 -868.371374 1612.783259
92 14619.691056 -868.371374
93 465.080722 14619.691056
94 -7142.551857 465.080722
95 10179.241940 -7142.551857
96 -571.474653 10179.241940
97 3630.235724 -571.474653
98 -2166.780132 3630.235724
99 2722.962067 -2166.780132
100 167.879799 2722.962067
101 -1521.752099 167.879799
102 -9467.590002 -1521.752099
103 2658.491527 -9467.590002
104 -636.533879 2658.491527
105 -613.878644 -636.533879
106 -2906.255453 -613.878644
107 -650.644482 -2906.255453
108 1582.557318 -650.644482
109 -7782.972687 1582.557318
110 -3883.483943 -7782.972687
111 -465.861361 -3883.483943
112 426.810079 -465.861361
113 -946.501887 426.810079
114 1582.557318 -946.501887
115 1582.557318 1582.557318
116 4077.544863 1582.557318
117 -4483.935989 4077.544863
118 103.217142 -4483.935989
119 -4620.495042 103.217142
120 -841.727950 -4620.495042
121 5710.181987 -841.727950
122 4055.802269 5710.181987
123 -2887.834749 4055.802269
124 -262.863855 -2887.834749
125 79.556736 -262.863855
126 -4185.449063 79.556736
127 1482.190407 -4185.449063
128 -6843.197802 1482.190407
129 1383.113789 -6843.197802
130 1582.557318 1383.113789
131 -4299.112843 1582.557318
132 1582.557318 -4299.112843
133 -4177.833793 1582.557318
134 585.339672 -4177.833793
135 1123.179616 585.339672
136 1582.557318 1123.179616
137 -3316.122515 1582.557318
138 -2552.583881 -3316.122515
139 1582.557318 -2552.583881
140 1582.557318 1582.557318
141 -2036.030145 1582.557318
142 951.688966 -2036.030145
143 3783.416648 951.688966
> 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/70wnj1322153847.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8oh0s1322153847.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/988ni1322153847.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10qh321322153847.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ezaf1322153847.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/128z3n1322153847.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/1354g01322153848.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/14b6hb1322153848.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/1524ur1322153848.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/16mvjv1322153848.tab")
+ }
>
> try(system("convert tmp/13r8v1322153847.ps tmp/13r8v1322153847.png",intern=TRUE))
character(0)
> try(system("convert tmp/29hul1322153847.ps tmp/29hul1322153847.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bwv71322153847.ps tmp/3bwv71322153847.png",intern=TRUE))
character(0)
> try(system("convert tmp/418pn1322153847.ps tmp/418pn1322153847.png",intern=TRUE))
character(0)
> try(system("convert tmp/5f50s1322153847.ps tmp/5f50s1322153847.png",intern=TRUE))
character(0)
> try(system("convert tmp/6v6qg1322153847.ps tmp/6v6qg1322153847.png",intern=TRUE))
character(0)
> try(system("convert tmp/70wnj1322153847.ps tmp/70wnj1322153847.png",intern=TRUE))
character(0)
> try(system("convert tmp/8oh0s1322153847.ps tmp/8oh0s1322153847.png",intern=TRUE))
character(0)
> try(system("convert tmp/988ni1322153847.ps tmp/988ni1322153847.png",intern=TRUE))
character(0)
> try(system("convert tmp/10qh321322153847.ps tmp/10qh321322153847.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.084 0.676 13.688