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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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(95556
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+ ,41243
+ ,49)
+ ,dim=c(4
+ ,164)
+ ,dimnames=list(c('Characters'
+ ,'Revisions'
+ ,'Seconds'
+ ,'Hyperlinks')
+ ,1:164))
> y <- array(NA,dim=c(4,164),dimnames=list(c('Characters','Revisions','Seconds','Hyperlinks'),1:164))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Characters Revisions Seconds Hyperlinks
1 95556 21387 114468 127
2 54565 12341 88594 90
3 63016 11397 74151 68
4 79774 25533 77921 111
5 31258 6630 53212 51
6 52491 7745 34956 33
7 91256 25304 149703 123
8 22807 1271 6853 5
9 77411 18035 58907 63
10 48821 13284 67067 66
11 52295 15628 110563 99
12 63262 13990 58126 72
13 50466 8532 57113 55
14 62932 13953 77993 116
15 38439 7210 68091 71
16 70817 22436 124676 125
17 105965 20238 109522 123
18 73795 10244 75865 74
19 82043 17390 79746 116
20 74349 9917 77844 117
21 82204 29625 98681 98
22 55709 13193 105531 101
23 37137 6815 51428 43
24 70780 11807 65703 103
25 55027 21472 72562 107
26 56699 19589 81728 77
27 65911 12266 95580 87
28 56316 18391 98278 99
29 26982 6711 46629 46
30 54628 9004 115189 96
31 96750 34301 124865 92
32 53009 8061 59392 96
33 64664 19463 127818 96
34 36990 2053 17821 15
35 85224 29618 154076 147
36 37048 3963 64881 56
37 59635 17609 136506 81
38 42051 11738 66524 69
39 26998 11082 45988 34
40 63717 22648 107445 98
41 55071 16538 102772 82
42 40001 10149 46657 64
43 54506 19787 97563 61
44 35838 7740 36663 45
45 50838 5873 55369 37
46 86997 11694 77921 64
47 33032 7935 56968 21
48 61704 15093 77519 104
49 117986 14533 129805 126
50 56733 15834 72761 104
51 55064 15699 81278 87
52 5950 2694 15049 7
53 84607 13834 113935 130
54 32551 3597 25109 21
55 31701 5296 45824 35
56 71170 21637 89644 97
57 101773 18081 109011 103
58 101653 29016 134245 210
59 81493 27279 136692 151
60 55901 12889 50741 57
61 109104 21550 149510 117
62 114425 34042 147888 152
63 36311 8190 54987 52
64 70027 16163 74467 83
65 73713 23471 100033 87
66 40671 14220 85505 80
67 89041 12759 62426 88
68 57231 18142 82932 83
69 68608 12416 72002 120
70 59155 14069 65469 76
71 55827 11131 63572 70
72 22618 3007 23824 26
73 58425 12530 73831 66
74 65724 13205 63551 89
75 56979 13025 56756 100
76 72369 18778 81399 98
77 79194 19793 117881 109
78 202316 8238 70711 51
79 44970 11285 50495 82
80 49319 10490 53845 65
81 36252 10457 51390 46
82 75741 17313 104953 104
83 38417 9592 65983 36
84 64102 14282 76839 123
85 56622 7905 55792 59
86 15430 4525 25155 27
87 72571 21179 55291 84
88 67271 13724 84279 61
89 43460 18446 99692 46
90 99501 25961 59633 125
91 28340 6602 63249 58
92 76013 16795 82928 152
93 37361 5463 50000 52
94 48204 11299 69455 85
95 76168 20390 84068 95
96 85168 18558 76195 78
97 125410 26262 114634 144
98 123328 25267 139357 149
99 83038 21091 110044 101
100 120087 32425 155118 205
101 91939 24380 83061 61
102 103646 20460 127122 145
103 29467 6515 45653 28
104 43750 7409 19630 49
105 34497 12300 67229 68
106 66477 27127 86060 142
107 71181 27687 88003 82
108 74482 19255 95815 105
109 174949 15070 85499 52
110 46765 6291 27220 56
111 90257 16577 109882 81
112 51370 13027 72579 100
113 1168 238 5841 11
114 51360 17103 68369 87
115 25162 3913 24610 31
116 21067 5654 30995 67
117 58233 14354 150662 150
118 855 338 6622 4
119 85903 8852 93694 75
120 14116 3988 13155 39
121 57637 15964 111908 88
122 94137 14784 57550 67
123 62147 2667 16356 24
124 62832 7164 40174 58
125 8773 1888 13983 16
126 63785 12367 52316 49
127 65196 20505 99585 109
128 73087 18330 86271 124
129 72631 24993 131012 115
130 86281 11869 130274 128
131 162365 31156 159051 159
132 56530 15234 76506 75
133 35606 6645 49145 30
134 70111 15007 66398 83
135 92046 16597 127546 135
136 63989 317 6802 8
137 104911 27627 99509 115
138 43448 8658 43106 60
139 60029 20493 108303 99
140 38650 8877 64167 98
141 47261 867 8579 36
142 73586 13259 97811 93
143 83042 20613 84365 158
144 37238 2805 10901 16
145 63958 20588 91346 100
146 78956 9812 33660 49
147 99518 20001 93634 89
148 111436 23042 109348 153
149 0 0 0 0
150 6023 2065 7953 5
151 0 0 0 0
152 0 0 0 0
153 0 0 0 0
154 0 0 0 0
155 42564 10902 63538 80
156 38885 11309 108281 122
157 0 0 0 0
158 0 0 0 0
159 1644 556 4245 6
160 6179 2089 21509 13
161 3926 2658 7670 3
162 23238 1419 10641 18
163 0 0 0 0
164 49288 10699 41243 49
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Revisions Seconds Hyperlinks
1.336e+04 1.351e+00 2.401e-01 1.418e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-33047 -13360 -4042 7549 153619
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.336e+04 3.585e+03 3.726 0.000269 ***
Revisions 1.351e+00 4.174e-01 3.237 0.001470 **
Seconds 2.401e-01 9.616e-02 2.497 0.013547 *
Hyperlinks 1.418e+02 8.395e+01 1.689 0.093206 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 21960 on 160 degrees of freedom
Multiple R-squared: 0.5784, Adjusted R-squared: 0.5705
F-statistic: 73.17 on 3 and 160 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,] 2.174427e-01 4.348853e-01 7.825573e-01
[2,] 1.030408e-01 2.060816e-01 8.969592e-01
[3,] 5.639000e-02 1.127800e-01 9.436100e-01
[4,] 3.628582e-02 7.257163e-02 9.637142e-01
[5,] 3.125493e-02 6.250985e-02 9.687451e-01
[6,] 1.480032e-02 2.960065e-02 9.851997e-01
[7,] 7.028611e-03 1.405722e-02 9.929714e-01
[8,] 2.970581e-03 5.941162e-03 9.970294e-01
[9,] 1.272312e-03 2.544624e-03 9.987277e-01
[10,] 9.345067e-04 1.869013e-03 9.990655e-01
[11,] 6.192237e-03 1.238447e-02 9.938078e-01
[12,] 9.744432e-03 1.948886e-02 9.902556e-01
[13,] 5.609822e-03 1.121964e-02 9.943902e-01
[14,] 3.789219e-03 7.578437e-03 9.962108e-01
[15,] 2.424749e-03 4.849497e-03 9.975753e-01
[16,] 1.508192e-03 3.016383e-03 9.984918e-01
[17,] 7.827912e-04 1.565582e-03 9.992172e-01
[18,] 3.922334e-04 7.844667e-04 9.996078e-01
[19,] 1.141374e-03 2.282748e-03 9.988586e-01
[20,] 7.554920e-04 1.510984e-03 9.992445e-01
[21,] 4.161497e-04 8.322993e-04 9.995839e-01
[22,] 3.644654e-04 7.289309e-04 9.996355e-01
[23,] 3.134839e-04 6.269679e-04 9.996865e-01
[24,] 1.669084e-04 3.338169e-04 9.998331e-01
[25,] 1.010844e-04 2.021687e-04 9.998989e-01
[26,] 5.175838e-05 1.035168e-04 9.999482e-01
[27,] 2.960217e-05 5.920434e-05 9.999704e-01
[28,] 1.908768e-05 3.817535e-05 9.999809e-01
[29,] 1.442968e-05 2.885937e-05 9.999856e-01
[30,] 7.090739e-06 1.418148e-05 9.999929e-01
[31,] 3.889913e-06 7.779826e-06 9.999961e-01
[32,] 2.832388e-06 5.664776e-06 9.999972e-01
[33,] 3.007434e-06 6.014868e-06 9.999970e-01
[34,] 2.104681e-06 4.209363e-06 9.999979e-01
[35,] 1.193064e-06 2.386128e-06 9.999988e-01
[36,] 7.612674e-07 1.522535e-06 9.999992e-01
[37,] 4.218434e-07 8.436868e-07 9.999996e-01
[38,] 2.105590e-07 4.211180e-07 9.999998e-01
[39,] 1.951077e-07 3.902155e-07 9.999998e-01
[40,] 2.797037e-06 5.594075e-06 9.999972e-01
[41,] 1.475605e-06 2.951211e-06 9.999985e-01
[42,] 7.853210e-07 1.570642e-06 9.999992e-01
[43,] 2.097057e-05 4.194114e-05 9.999790e-01
[44,] 1.468127e-05 2.936254e-05 9.999853e-01
[45,] 9.312777e-06 1.862555e-05 9.999907e-01
[46,] 8.581839e-06 1.716368e-05 9.999914e-01
[47,] 5.042593e-06 1.008519e-05 9.999950e-01
[48,] 2.824928e-06 5.649856e-06 9.999972e-01
[49,] 1.538078e-06 3.076156e-06 9.999985e-01
[50,] 8.275338e-07 1.655068e-06 9.999992e-01
[51,] 2.153309e-06 4.306618e-06 9.999978e-01
[52,] 1.695077e-06 3.390154e-06 9.999983e-01
[53,] 1.584547e-06 3.169094e-06 9.999984e-01
[54,] 9.206639e-07 1.841328e-06 9.999991e-01
[55,] 1.313299e-06 2.626598e-06 9.999987e-01
[56,] 8.792701e-07 1.758540e-06 9.999991e-01
[57,] 5.318909e-07 1.063782e-06 9.999995e-01
[58,] 3.163676e-07 6.327351e-07 9.999997e-01
[59,] 1.802235e-07 3.604470e-07 9.999998e-01
[60,] 2.384602e-07 4.769205e-07 9.999998e-01
[61,] 7.367681e-07 1.473536e-06 9.999993e-01
[62,] 4.766437e-07 9.532874e-07 9.999995e-01
[63,] 2.597183e-07 5.194366e-07 9.999997e-01
[64,] 1.376426e-07 2.752852e-07 9.999999e-01
[65,] 7.236803e-08 1.447361e-07 9.999999e-01
[66,] 3.976982e-08 7.953963e-08 1.000000e+00
[67,] 2.089290e-08 4.178580e-08 1.000000e+00
[68,] 1.128659e-08 2.257318e-08 1.000000e+00
[69,] 5.836566e-09 1.167313e-08 1.000000e+00
[70,] 2.932147e-09 5.864293e-09 1.000000e+00
[71,] 1.511600e-09 3.023199e-09 1.000000e+00
[72,] 6.434125e-01 7.131749e-01 3.565875e-01
[73,] 6.058598e-01 7.882804e-01 3.941402e-01
[74,] 5.616390e-01 8.767220e-01 4.383610e-01
[75,] 5.285654e-01 9.428693e-01 4.714346e-01
[76,] 4.837451e-01 9.674901e-01 5.162549e-01
[77,] 4.490020e-01 8.980040e-01 5.509980e-01
[78,] 4.062144e-01 8.124288e-01 5.937856e-01
[79,] 3.724961e-01 7.449922e-01 6.275039e-01
[80,] 3.506985e-01 7.013970e-01 6.493015e-01
[81,] 3.169533e-01 6.339066e-01 6.830467e-01
[82,] 2.803842e-01 5.607685e-01 7.196158e-01
[83,] 3.182993e-01 6.365986e-01 6.817007e-01
[84,] 3.117572e-01 6.235144e-01 6.882428e-01
[85,] 3.001535e-01 6.003071e-01 6.998465e-01
[86,] 2.656676e-01 5.313352e-01 7.343324e-01
[87,] 2.309044e-01 4.618088e-01 7.690956e-01
[88,] 2.032183e-01 4.064367e-01 7.967817e-01
[89,] 1.742761e-01 3.485522e-01 8.257239e-01
[90,] 1.609116e-01 3.218232e-01 8.390884e-01
[91,] 1.804883e-01 3.609766e-01 8.195117e-01
[92,] 1.765537e-01 3.531074e-01 8.234463e-01
[93,] 1.506156e-01 3.012312e-01 8.493844e-01
[94,] 1.254673e-01 2.509346e-01 8.745327e-01
[95,] 1.144998e-01 2.289996e-01 8.855002e-01
[96,] 9.932079e-02 1.986416e-01 9.006792e-01
[97,] 8.434422e-02 1.686884e-01 9.156558e-01
[98,] 7.118233e-02 1.423647e-01 9.288177e-01
[99,] 7.221008e-02 1.444202e-01 9.277899e-01
[100,] 7.624559e-02 1.524912e-01 9.237544e-01
[101,] 8.764261e-02 1.752852e-01 9.123574e-01
[102,] 7.258868e-02 1.451774e-01 9.274113e-01
[103,] 9.147981e-01 1.704038e-01 8.520190e-02
[104,] 8.996281e-01 2.007438e-01 1.003719e-01
[105,] 8.912502e-01 2.174996e-01 1.087498e-01
[106,] 8.737405e-01 2.525190e-01 1.262595e-01
[107,] 8.576219e-01 2.847562e-01 1.423781e-01
[108,] 8.519340e-01 2.961319e-01 1.480660e-01
[109,] 8.211852e-01 3.576295e-01 1.788148e-01
[110,] 8.086418e-01 3.827165e-01 1.913582e-01
[111,] 8.245101e-01 3.509798e-01 1.754899e-01
[112,] 8.028813e-01 3.942374e-01 1.971187e-01
[113,] 8.527662e-01 2.944675e-01 1.472338e-01
[114,] 8.384293e-01 3.231415e-01 1.615707e-01
[115,] 8.157950e-01 3.684101e-01 1.842050e-01
[116,] 8.625187e-01 2.749626e-01 1.374813e-01
[117,] 9.261121e-01 1.477758e-01 7.388792e-02
[118,] 9.298973e-01 1.402054e-01 7.010268e-02
[119,] 9.137747e-01 1.724507e-01 8.622533e-02
[120,] 8.999880e-01 2.000240e-01 1.000120e-01
[121,] 8.961545e-01 2.076911e-01 1.038455e-01
[122,] 8.748313e-01 2.503374e-01 1.251687e-01
[123,] 8.992933e-01 2.014134e-01 1.007067e-01
[124,] 8.917101e-01 2.165797e-01 1.082899e-01
[125,] 9.505581e-01 9.888377e-02 4.944188e-02
[126,] 9.342725e-01 1.314550e-01 6.572748e-02
[127,] 9.138326e-01 1.723347e-01 8.616737e-02
[128,] 8.880291e-01 2.239419e-01 1.119709e-01
[129,] 8.874208e-01 2.251584e-01 1.125792e-01
[130,] 9.907875e-01 1.842490e-02 9.212451e-03
[131,] 9.863828e-01 2.723445e-02 1.361723e-02
[132,] 9.788497e-01 4.230067e-02 2.115033e-02
[133,] 9.804707e-01 3.905857e-02 1.952928e-02
[134,] 9.719067e-01 5.618656e-02 2.809328e-02
[135,] 9.940073e-01 1.198547e-02 5.992737e-03
[136,] 9.948815e-01 1.023703e-02 5.118515e-03
[137,] 9.969620e-01 6.075908e-03 3.037954e-03
[138,] 9.979483e-01 4.103380e-03 2.051690e-03
[139,] 9.999020e-01 1.959032e-04 9.795161e-05
[140,] 9.999989e-01 2.133426e-06 1.066713e-06
[141,] 9.999999e-01 2.426506e-07 1.213253e-07
[142,] 9.999994e-01 1.160305e-06 5.801527e-07
[143,] 9.999974e-01 5.234696e-06 2.617348e-06
[144,] 9.999883e-01 2.344447e-05 1.172224e-05
[145,] 9.999511e-01 9.778264e-05 4.889132e-05
[146,] 9.998055e-01 3.889164e-04 1.944582e-04
[147,] 9.992669e-01 1.466163e-03 7.330813e-04
[148,] 9.974001e-01 5.199780e-03 2.599890e-03
[149,] 9.944374e-01 1.112512e-02 5.562560e-03
[150,] 9.991333e-01 1.733485e-03 8.667427e-04
[151,] 9.936435e-01 1.271298e-02 6.356489e-03
> postscript(file="/var/www/rcomp/tmp/1rip61321953372.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2qfq91321953372.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/34hwe1321953372.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4bcer1321953372.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5uo2k1321953372.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 = 164
Frequency = 1
1 2 3 4 5 6
7813.7792 -9498.0024 6815.1045 -2526.6632 -11065.1491 15596.5226
7 8 9 10 11 12
-9670.4413 5376.0291 16610.7881 -7944.9475 -22759.2720 6838.1421
13 14 15 16 17 18
4069.5101 -4450.0287 -11075.5981 -20509.6670 21529.6897 17889.6371
19 20 21 22 23 24
9596.6415 12313.6850 -8766.0475 -15130.9901 -3873.5237 11091.0688
25 26 27 28 29 30
-19933.4231 -13664.6217 697.4350 -19521.6998 -13161.1942 -12162.3944
31 32 33 34 35 36
-5973.1206 888.6428 -19288.7616 14451.4620 -25983.3975 -5182.4348
37 38 39 40 41 42
-21772.1028 -12921.2469 -17195.2356 -19931.0760 -16931.9123 -7345.7968
43 44 45 46 47 48
-17658.3650 -3160.9264 11004.6529 30056.8570 -7702.5441 -5403.0139
49 50 51 52 53 54
35963.2779 -10232.7963 -11353.9257 -15654.7745 6771.6649 5326.0557
55 56 57 58 59 60
-4777.6330 -6696.6582 23210.1580 -12912.1960 -22947.8466 4864.3682
61 62 63 64 65 66
14146.3192 -1982.5782 -8687.6750 5184.5457 -7707.8591 -23771.1333
67 68 69 70 71 72
30979.3786 -12317.4454 4173.7143 294.3407 2241.7725 -4210.2402
73 74 75 76 77 78
1053.7876 6647.9458 -1782.0899 202.6316 -4662.0343 153619.1606
79 80 81 82 83 84
-7385.0719 -356.0078 -10095.1654 -951.7741 -8847.2768 -4439.9277
85 86 87 88 89 90
10822.6266 -13910.4255 5413.9109 6487.1676 -25277.0625 19027.8324
91 92 93 94 95 96
-17347.5249 -1497.5881 -2756.1355 -9147.3429 1608.3428 17383.8903
97 98 99 100 101 102
28631.4087 21249.1451 444.1387 -3386.2149 17051.1065 11566.0718
103 104 105 106 107 108
-7625.0026 8720.5036 -21261.9993 -24326.4723 -12338.6348 -2782.3424
109 110 111 112 113 114
113329.8232 10431.2292 16636.1750 -11192.6573 -15475.0892 -13855.5023
115 116 117 118 119 120
-3787.8804 -16872.0884 -31958.1004 -15118.2267 27456.0015 -13319.2857
121 122 123 124 125 126
-16634.5322 37487.6279 37854.6252 21925.1629 -12762.9547 14209.7202
127 128 129 130 131 132
-15229.3661 -3330.1261 -22253.5918 7461.2360 46183.9296 -6412.6361
133 134 135 136 137 138
-2783.5754 8767.5726 6501.0875 47433.8031 14031.2161 -464.7556
139 140 141 142 143 144
-21055.3992 -16002.7599 25566.2261 5644.5515 -822.4797 15203.1006
145 146 147 148 149 150
-13325.4061 37311.6062 24037.9263 19000.7530 -13359.6121 -12744.7755
151 152 153 154 155 156
-13359.6121 -13359.6121 -13359.6121 -13359.6121 -12121.4964 -33047.3126
157 158 159 160 161 162
-13359.6121 -13359.6121 -14336.6304 -17010.0452 -15291.4240 2854.4753
163 164
-13359.6121 4624.6854
> postscript(file="/var/www/rcomp/tmp/6w0j41321953372.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 = 164
Frequency = 1
lag(myerror, k = 1) myerror
0 7813.7792 NA
1 -9498.0024 7813.7792
2 6815.1045 -9498.0024
3 -2526.6632 6815.1045
4 -11065.1491 -2526.6632
5 15596.5226 -11065.1491
6 -9670.4413 15596.5226
7 5376.0291 -9670.4413
8 16610.7881 5376.0291
9 -7944.9475 16610.7881
10 -22759.2720 -7944.9475
11 6838.1421 -22759.2720
12 4069.5101 6838.1421
13 -4450.0287 4069.5101
14 -11075.5981 -4450.0287
15 -20509.6670 -11075.5981
16 21529.6897 -20509.6670
17 17889.6371 21529.6897
18 9596.6415 17889.6371
19 12313.6850 9596.6415
20 -8766.0475 12313.6850
21 -15130.9901 -8766.0475
22 -3873.5237 -15130.9901
23 11091.0688 -3873.5237
24 -19933.4231 11091.0688
25 -13664.6217 -19933.4231
26 697.4350 -13664.6217
27 -19521.6998 697.4350
28 -13161.1942 -19521.6998
29 -12162.3944 -13161.1942
30 -5973.1206 -12162.3944
31 888.6428 -5973.1206
32 -19288.7616 888.6428
33 14451.4620 -19288.7616
34 -25983.3975 14451.4620
35 -5182.4348 -25983.3975
36 -21772.1028 -5182.4348
37 -12921.2469 -21772.1028
38 -17195.2356 -12921.2469
39 -19931.0760 -17195.2356
40 -16931.9123 -19931.0760
41 -7345.7968 -16931.9123
42 -17658.3650 -7345.7968
43 -3160.9264 -17658.3650
44 11004.6529 -3160.9264
45 30056.8570 11004.6529
46 -7702.5441 30056.8570
47 -5403.0139 -7702.5441
48 35963.2779 -5403.0139
49 -10232.7963 35963.2779
50 -11353.9257 -10232.7963
51 -15654.7745 -11353.9257
52 6771.6649 -15654.7745
53 5326.0557 6771.6649
54 -4777.6330 5326.0557
55 -6696.6582 -4777.6330
56 23210.1580 -6696.6582
57 -12912.1960 23210.1580
58 -22947.8466 -12912.1960
59 4864.3682 -22947.8466
60 14146.3192 4864.3682
61 -1982.5782 14146.3192
62 -8687.6750 -1982.5782
63 5184.5457 -8687.6750
64 -7707.8591 5184.5457
65 -23771.1333 -7707.8591
66 30979.3786 -23771.1333
67 -12317.4454 30979.3786
68 4173.7143 -12317.4454
69 294.3407 4173.7143
70 2241.7725 294.3407
71 -4210.2402 2241.7725
72 1053.7876 -4210.2402
73 6647.9458 1053.7876
74 -1782.0899 6647.9458
75 202.6316 -1782.0899
76 -4662.0343 202.6316
77 153619.1606 -4662.0343
78 -7385.0719 153619.1606
79 -356.0078 -7385.0719
80 -10095.1654 -356.0078
81 -951.7741 -10095.1654
82 -8847.2768 -951.7741
83 -4439.9277 -8847.2768
84 10822.6266 -4439.9277
85 -13910.4255 10822.6266
86 5413.9109 -13910.4255
87 6487.1676 5413.9109
88 -25277.0625 6487.1676
89 19027.8324 -25277.0625
90 -17347.5249 19027.8324
91 -1497.5881 -17347.5249
92 -2756.1355 -1497.5881
93 -9147.3429 -2756.1355
94 1608.3428 -9147.3429
95 17383.8903 1608.3428
96 28631.4087 17383.8903
97 21249.1451 28631.4087
98 444.1387 21249.1451
99 -3386.2149 444.1387
100 17051.1065 -3386.2149
101 11566.0718 17051.1065
102 -7625.0026 11566.0718
103 8720.5036 -7625.0026
104 -21261.9993 8720.5036
105 -24326.4723 -21261.9993
106 -12338.6348 -24326.4723
107 -2782.3424 -12338.6348
108 113329.8232 -2782.3424
109 10431.2292 113329.8232
110 16636.1750 10431.2292
111 -11192.6573 16636.1750
112 -15475.0892 -11192.6573
113 -13855.5023 -15475.0892
114 -3787.8804 -13855.5023
115 -16872.0884 -3787.8804
116 -31958.1004 -16872.0884
117 -15118.2267 -31958.1004
118 27456.0015 -15118.2267
119 -13319.2857 27456.0015
120 -16634.5322 -13319.2857
121 37487.6279 -16634.5322
122 37854.6252 37487.6279
123 21925.1629 37854.6252
124 -12762.9547 21925.1629
125 14209.7202 -12762.9547
126 -15229.3661 14209.7202
127 -3330.1261 -15229.3661
128 -22253.5918 -3330.1261
129 7461.2360 -22253.5918
130 46183.9296 7461.2360
131 -6412.6361 46183.9296
132 -2783.5754 -6412.6361
133 8767.5726 -2783.5754
134 6501.0875 8767.5726
135 47433.8031 6501.0875
136 14031.2161 47433.8031
137 -464.7556 14031.2161
138 -21055.3992 -464.7556
139 -16002.7599 -21055.3992
140 25566.2261 -16002.7599
141 5644.5515 25566.2261
142 -822.4797 5644.5515
143 15203.1006 -822.4797
144 -13325.4061 15203.1006
145 37311.6062 -13325.4061
146 24037.9263 37311.6062
147 19000.7530 24037.9263
148 -13359.6121 19000.7530
149 -12744.7755 -13359.6121
150 -13359.6121 -12744.7755
151 -13359.6121 -13359.6121
152 -13359.6121 -13359.6121
153 -13359.6121 -13359.6121
154 -12121.4964 -13359.6121
155 -33047.3126 -12121.4964
156 -13359.6121 -33047.3126
157 -13359.6121 -13359.6121
158 -14336.6304 -13359.6121
159 -17010.0452 -14336.6304
160 -15291.4240 -17010.0452
161 2854.4753 -15291.4240
162 -13359.6121 2854.4753
163 4624.6854 -13359.6121
164 NA 4624.6854
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -9498.0024 7813.7792
[2,] 6815.1045 -9498.0024
[3,] -2526.6632 6815.1045
[4,] -11065.1491 -2526.6632
[5,] 15596.5226 -11065.1491
[6,] -9670.4413 15596.5226
[7,] 5376.0291 -9670.4413
[8,] 16610.7881 5376.0291
[9,] -7944.9475 16610.7881
[10,] -22759.2720 -7944.9475
[11,] 6838.1421 -22759.2720
[12,] 4069.5101 6838.1421
[13,] -4450.0287 4069.5101
[14,] -11075.5981 -4450.0287
[15,] -20509.6670 -11075.5981
[16,] 21529.6897 -20509.6670
[17,] 17889.6371 21529.6897
[18,] 9596.6415 17889.6371
[19,] 12313.6850 9596.6415
[20,] -8766.0475 12313.6850
[21,] -15130.9901 -8766.0475
[22,] -3873.5237 -15130.9901
[23,] 11091.0688 -3873.5237
[24,] -19933.4231 11091.0688
[25,] -13664.6217 -19933.4231
[26,] 697.4350 -13664.6217
[27,] -19521.6998 697.4350
[28,] -13161.1942 -19521.6998
[29,] -12162.3944 -13161.1942
[30,] -5973.1206 -12162.3944
[31,] 888.6428 -5973.1206
[32,] -19288.7616 888.6428
[33,] 14451.4620 -19288.7616
[34,] -25983.3975 14451.4620
[35,] -5182.4348 -25983.3975
[36,] -21772.1028 -5182.4348
[37,] -12921.2469 -21772.1028
[38,] -17195.2356 -12921.2469
[39,] -19931.0760 -17195.2356
[40,] -16931.9123 -19931.0760
[41,] -7345.7968 -16931.9123
[42,] -17658.3650 -7345.7968
[43,] -3160.9264 -17658.3650
[44,] 11004.6529 -3160.9264
[45,] 30056.8570 11004.6529
[46,] -7702.5441 30056.8570
[47,] -5403.0139 -7702.5441
[48,] 35963.2779 -5403.0139
[49,] -10232.7963 35963.2779
[50,] -11353.9257 -10232.7963
[51,] -15654.7745 -11353.9257
[52,] 6771.6649 -15654.7745
[53,] 5326.0557 6771.6649
[54,] -4777.6330 5326.0557
[55,] -6696.6582 -4777.6330
[56,] 23210.1580 -6696.6582
[57,] -12912.1960 23210.1580
[58,] -22947.8466 -12912.1960
[59,] 4864.3682 -22947.8466
[60,] 14146.3192 4864.3682
[61,] -1982.5782 14146.3192
[62,] -8687.6750 -1982.5782
[63,] 5184.5457 -8687.6750
[64,] -7707.8591 5184.5457
[65,] -23771.1333 -7707.8591
[66,] 30979.3786 -23771.1333
[67,] -12317.4454 30979.3786
[68,] 4173.7143 -12317.4454
[69,] 294.3407 4173.7143
[70,] 2241.7725 294.3407
[71,] -4210.2402 2241.7725
[72,] 1053.7876 -4210.2402
[73,] 6647.9458 1053.7876
[74,] -1782.0899 6647.9458
[75,] 202.6316 -1782.0899
[76,] -4662.0343 202.6316
[77,] 153619.1606 -4662.0343
[78,] -7385.0719 153619.1606
[79,] -356.0078 -7385.0719
[80,] -10095.1654 -356.0078
[81,] -951.7741 -10095.1654
[82,] -8847.2768 -951.7741
[83,] -4439.9277 -8847.2768
[84,] 10822.6266 -4439.9277
[85,] -13910.4255 10822.6266
[86,] 5413.9109 -13910.4255
[87,] 6487.1676 5413.9109
[88,] -25277.0625 6487.1676
[89,] 19027.8324 -25277.0625
[90,] -17347.5249 19027.8324
[91,] -1497.5881 -17347.5249
[92,] -2756.1355 -1497.5881
[93,] -9147.3429 -2756.1355
[94,] 1608.3428 -9147.3429
[95,] 17383.8903 1608.3428
[96,] 28631.4087 17383.8903
[97,] 21249.1451 28631.4087
[98,] 444.1387 21249.1451
[99,] -3386.2149 444.1387
[100,] 17051.1065 -3386.2149
[101,] 11566.0718 17051.1065
[102,] -7625.0026 11566.0718
[103,] 8720.5036 -7625.0026
[104,] -21261.9993 8720.5036
[105,] -24326.4723 -21261.9993
[106,] -12338.6348 -24326.4723
[107,] -2782.3424 -12338.6348
[108,] 113329.8232 -2782.3424
[109,] 10431.2292 113329.8232
[110,] 16636.1750 10431.2292
[111,] -11192.6573 16636.1750
[112,] -15475.0892 -11192.6573
[113,] -13855.5023 -15475.0892
[114,] -3787.8804 -13855.5023
[115,] -16872.0884 -3787.8804
[116,] -31958.1004 -16872.0884
[117,] -15118.2267 -31958.1004
[118,] 27456.0015 -15118.2267
[119,] -13319.2857 27456.0015
[120,] -16634.5322 -13319.2857
[121,] 37487.6279 -16634.5322
[122,] 37854.6252 37487.6279
[123,] 21925.1629 37854.6252
[124,] -12762.9547 21925.1629
[125,] 14209.7202 -12762.9547
[126,] -15229.3661 14209.7202
[127,] -3330.1261 -15229.3661
[128,] -22253.5918 -3330.1261
[129,] 7461.2360 -22253.5918
[130,] 46183.9296 7461.2360
[131,] -6412.6361 46183.9296
[132,] -2783.5754 -6412.6361
[133,] 8767.5726 -2783.5754
[134,] 6501.0875 8767.5726
[135,] 47433.8031 6501.0875
[136,] 14031.2161 47433.8031
[137,] -464.7556 14031.2161
[138,] -21055.3992 -464.7556
[139,] -16002.7599 -21055.3992
[140,] 25566.2261 -16002.7599
[141,] 5644.5515 25566.2261
[142,] -822.4797 5644.5515
[143,] 15203.1006 -822.4797
[144,] -13325.4061 15203.1006
[145,] 37311.6062 -13325.4061
[146,] 24037.9263 37311.6062
[147,] 19000.7530 24037.9263
[148,] -13359.6121 19000.7530
[149,] -12744.7755 -13359.6121
[150,] -13359.6121 -12744.7755
[151,] -13359.6121 -13359.6121
[152,] -13359.6121 -13359.6121
[153,] -13359.6121 -13359.6121
[154,] -12121.4964 -13359.6121
[155,] -33047.3126 -12121.4964
[156,] -13359.6121 -33047.3126
[157,] -13359.6121 -13359.6121
[158,] -14336.6304 -13359.6121
[159,] -17010.0452 -14336.6304
[160,] -15291.4240 -17010.0452
[161,] 2854.4753 -15291.4240
[162,] -13359.6121 2854.4753
[163,] 4624.6854 -13359.6121
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -9498.0024 7813.7792
2 6815.1045 -9498.0024
3 -2526.6632 6815.1045
4 -11065.1491 -2526.6632
5 15596.5226 -11065.1491
6 -9670.4413 15596.5226
7 5376.0291 -9670.4413
8 16610.7881 5376.0291
9 -7944.9475 16610.7881
10 -22759.2720 -7944.9475
11 6838.1421 -22759.2720
12 4069.5101 6838.1421
13 -4450.0287 4069.5101
14 -11075.5981 -4450.0287
15 -20509.6670 -11075.5981
16 21529.6897 -20509.6670
17 17889.6371 21529.6897
18 9596.6415 17889.6371
19 12313.6850 9596.6415
20 -8766.0475 12313.6850
21 -15130.9901 -8766.0475
22 -3873.5237 -15130.9901
23 11091.0688 -3873.5237
24 -19933.4231 11091.0688
25 -13664.6217 -19933.4231
26 697.4350 -13664.6217
27 -19521.6998 697.4350
28 -13161.1942 -19521.6998
29 -12162.3944 -13161.1942
30 -5973.1206 -12162.3944
31 888.6428 -5973.1206
32 -19288.7616 888.6428
33 14451.4620 -19288.7616
34 -25983.3975 14451.4620
35 -5182.4348 -25983.3975
36 -21772.1028 -5182.4348
37 -12921.2469 -21772.1028
38 -17195.2356 -12921.2469
39 -19931.0760 -17195.2356
40 -16931.9123 -19931.0760
41 -7345.7968 -16931.9123
42 -17658.3650 -7345.7968
43 -3160.9264 -17658.3650
44 11004.6529 -3160.9264
45 30056.8570 11004.6529
46 -7702.5441 30056.8570
47 -5403.0139 -7702.5441
48 35963.2779 -5403.0139
49 -10232.7963 35963.2779
50 -11353.9257 -10232.7963
51 -15654.7745 -11353.9257
52 6771.6649 -15654.7745
53 5326.0557 6771.6649
54 -4777.6330 5326.0557
55 -6696.6582 -4777.6330
56 23210.1580 -6696.6582
57 -12912.1960 23210.1580
58 -22947.8466 -12912.1960
59 4864.3682 -22947.8466
60 14146.3192 4864.3682
61 -1982.5782 14146.3192
62 -8687.6750 -1982.5782
63 5184.5457 -8687.6750
64 -7707.8591 5184.5457
65 -23771.1333 -7707.8591
66 30979.3786 -23771.1333
67 -12317.4454 30979.3786
68 4173.7143 -12317.4454
69 294.3407 4173.7143
70 2241.7725 294.3407
71 -4210.2402 2241.7725
72 1053.7876 -4210.2402
73 6647.9458 1053.7876
74 -1782.0899 6647.9458
75 202.6316 -1782.0899
76 -4662.0343 202.6316
77 153619.1606 -4662.0343
78 -7385.0719 153619.1606
79 -356.0078 -7385.0719
80 -10095.1654 -356.0078
81 -951.7741 -10095.1654
82 -8847.2768 -951.7741
83 -4439.9277 -8847.2768
84 10822.6266 -4439.9277
85 -13910.4255 10822.6266
86 5413.9109 -13910.4255
87 6487.1676 5413.9109
88 -25277.0625 6487.1676
89 19027.8324 -25277.0625
90 -17347.5249 19027.8324
91 -1497.5881 -17347.5249
92 -2756.1355 -1497.5881
93 -9147.3429 -2756.1355
94 1608.3428 -9147.3429
95 17383.8903 1608.3428
96 28631.4087 17383.8903
97 21249.1451 28631.4087
98 444.1387 21249.1451
99 -3386.2149 444.1387
100 17051.1065 -3386.2149
101 11566.0718 17051.1065
102 -7625.0026 11566.0718
103 8720.5036 -7625.0026
104 -21261.9993 8720.5036
105 -24326.4723 -21261.9993
106 -12338.6348 -24326.4723
107 -2782.3424 -12338.6348
108 113329.8232 -2782.3424
109 10431.2292 113329.8232
110 16636.1750 10431.2292
111 -11192.6573 16636.1750
112 -15475.0892 -11192.6573
113 -13855.5023 -15475.0892
114 -3787.8804 -13855.5023
115 -16872.0884 -3787.8804
116 -31958.1004 -16872.0884
117 -15118.2267 -31958.1004
118 27456.0015 -15118.2267
119 -13319.2857 27456.0015
120 -16634.5322 -13319.2857
121 37487.6279 -16634.5322
122 37854.6252 37487.6279
123 21925.1629 37854.6252
124 -12762.9547 21925.1629
125 14209.7202 -12762.9547
126 -15229.3661 14209.7202
127 -3330.1261 -15229.3661
128 -22253.5918 -3330.1261
129 7461.2360 -22253.5918
130 46183.9296 7461.2360
131 -6412.6361 46183.9296
132 -2783.5754 -6412.6361
133 8767.5726 -2783.5754
134 6501.0875 8767.5726
135 47433.8031 6501.0875
136 14031.2161 47433.8031
137 -464.7556 14031.2161
138 -21055.3992 -464.7556
139 -16002.7599 -21055.3992
140 25566.2261 -16002.7599
141 5644.5515 25566.2261
142 -822.4797 5644.5515
143 15203.1006 -822.4797
144 -13325.4061 15203.1006
145 37311.6062 -13325.4061
146 24037.9263 37311.6062
147 19000.7530 24037.9263
148 -13359.6121 19000.7530
149 -12744.7755 -13359.6121
150 -13359.6121 -12744.7755
151 -13359.6121 -13359.6121
152 -13359.6121 -13359.6121
153 -13359.6121 -13359.6121
154 -12121.4964 -13359.6121
155 -33047.3126 -12121.4964
156 -13359.6121 -33047.3126
157 -13359.6121 -13359.6121
158 -14336.6304 -13359.6121
159 -17010.0452 -14336.6304
160 -15291.4240 -17010.0452
161 2854.4753 -15291.4240
162 -13359.6121 2854.4753
163 4624.6854 -13359.6121
> 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/7sm6c1321953372.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8gnb81321953372.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/961ew1321953372.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10g46l1321953372.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11l3zx1321953372.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/12fep91321953372.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/133suz1321953372.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/14td4m1321953372.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/15zayf1321953372.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/16yan51321953372.tab")
+ }
>
> try(system("convert tmp/1rip61321953372.ps tmp/1rip61321953372.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qfq91321953372.ps tmp/2qfq91321953372.png",intern=TRUE))
character(0)
> try(system("convert tmp/34hwe1321953372.ps tmp/34hwe1321953372.png",intern=TRUE))
character(0)
> try(system("convert tmp/4bcer1321953372.ps tmp/4bcer1321953372.png",intern=TRUE))
character(0)
> try(system("convert tmp/5uo2k1321953372.ps tmp/5uo2k1321953372.png",intern=TRUE))
character(0)
> try(system("convert tmp/6w0j41321953372.ps tmp/6w0j41321953372.png",intern=TRUE))
character(0)
> try(system("convert tmp/7sm6c1321953372.ps tmp/7sm6c1321953372.png",intern=TRUE))
character(0)
> try(system("convert tmp/8gnb81321953372.ps tmp/8gnb81321953372.png",intern=TRUE))
character(0)
> try(system("convert tmp/961ew1321953372.ps tmp/961ew1321953372.png",intern=TRUE))
character(0)
> try(system("convert tmp/10g46l1321953372.ps tmp/10g46l1321953372.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.240 0.652 7.370