R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
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(5,1,4,1,5,1,6,1,6,1,6,1,7,1,8,1,7,1,8,1,7,1,8,1,8,1,9,1,9,1,8,1,9,1,9,1,10,1,11,1,12,1,13,1,13,1,13,1,14,1,14,1,15,1,15,1,16,1,16,1,17,1,18,1,19,1,20,1,22,1,20,1,22,1,25,1,24,1,25,1,28,1,26,1,27,1,26,1,25,1,27,1,28,1,30,1,31,1,32,1,34,1,34,1,33,1,32,1,34,1,36,1,37,1,40,1,38,1,38,1,36,1,40,1,40,1,42,1,44,1,45,1,47,1,49,1,47,1,49,1,52,1,50,1,50,1,57,1,58,1,58,1,58,1,61,1,61,1,64,1,68,1,40,1,34,1,46,1,36,1,34,1,45,1,55,1,50,1,56,1,72,1,76,1,78,1,77,1,90,1,88,1,97,1,93,1,84,1,67,1,72,1,75,1,71,1,75,1,90,1,78,1,73,1,62,1,65,1,61,1,58,1,33,1,39,1,56,1,79,1,82,1,79,1,73,1,87,1,85,1,83,1,82,1,83,1,92,1,95,1,97,1,87,1,84,1,84,1,89,1,103,1,106,1,109,1,106,1,105,1,115,1,120,1,124,1,121,1,131,1,139,1,133,1,119,1,123,1,120,1,128,1,134,1,126,1,115,1,106,1,99,1,100,1,99,1,99,1,100,1,100,1,108,1,109,1,115,1,114,1,108,1,113,1,118,1,122,1,118,1,121,1,118,1,121,1,121,1,112,1,119,1,116,1,110,0,111,0,106,0,108,0),dim=c(2,176),dimnames=list(c('CO2-uitstoot','Dummy'),1:176))
> y <- array(NA,dim=c(2,176),dimnames=list(c('CO2-uitstoot','Dummy'),1:176))
> 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
CO2-uitstoot Dummy
1 5 1
2 4 1
3 5 1
4 6 1
5 6 1
6 6 1
7 7 1
8 8 1
9 7 1
10 8 1
11 7 1
12 8 1
13 8 1
14 9 1
15 9 1
16 8 1
17 9 1
18 9 1
19 10 1
20 11 1
21 12 1
22 13 1
23 13 1
24 13 1
25 14 1
26 14 1
27 15 1
28 15 1
29 16 1
30 16 1
31 17 1
32 18 1
33 19 1
34 20 1
35 22 1
36 20 1
37 22 1
38 25 1
39 24 1
40 25 1
41 28 1
42 26 1
43 27 1
44 26 1
45 25 1
46 27 1
47 28 1
48 30 1
49 31 1
50 32 1
51 34 1
52 34 1
53 33 1
54 32 1
55 34 1
56 36 1
57 37 1
58 40 1
59 38 1
60 38 1
61 36 1
62 40 1
63 40 1
64 42 1
65 44 1
66 45 1
67 47 1
68 49 1
69 47 1
70 49 1
71 52 1
72 50 1
73 50 1
74 57 1
75 58 1
76 58 1
77 58 1
78 61 1
79 61 1
80 64 1
81 68 1
82 40 1
83 34 1
84 46 1
85 36 1
86 34 1
87 45 1
88 55 1
89 50 1
90 56 1
91 72 1
92 76 1
93 78 1
94 77 1
95 90 1
96 88 1
97 97 1
98 93 1
99 84 1
100 67 1
101 72 1
102 75 1
103 71 1
104 75 1
105 90 1
106 78 1
107 73 1
108 62 1
109 65 1
110 61 1
111 58 1
112 33 1
113 39 1
114 56 1
115 79 1
116 82 1
117 79 1
118 73 1
119 87 1
120 85 1
121 83 1
122 82 1
123 83 1
124 92 1
125 95 1
126 97 1
127 87 1
128 84 1
129 84 1
130 89 1
131 103 1
132 106 1
133 109 1
134 106 1
135 105 1
136 115 1
137 120 1
138 124 1
139 121 1
140 131 1
141 139 1
142 133 1
143 119 1
144 123 1
145 120 1
146 128 1
147 134 1
148 126 1
149 115 1
150 106 1
151 99 1
152 100 1
153 99 1
154 99 1
155 100 1
156 100 1
157 108 1
158 109 1
159 115 1
160 114 1
161 108 1
162 113 1
163 118 1
164 122 1
165 118 1
166 121 1
167 118 1
168 121 1
169 121 1
170 112 1
171 119 1
172 116 1
173 110 0
174 111 0
175 106 0
176 108 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy
108.7 -47.5
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-57.25 -34.25 -3.25 34.25 77.75
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 108.75 19.51 5.574 9.34e-08 ***
Dummy -47.50 19.74 -2.407 0.0171 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 39.02 on 174 degrees of freedom
Multiple R-squared: 0.03222, Adjusted R-squared: 0.02666
F-statistic: 5.793 on 1 and 174 DF, p-value: 0.01714
> 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,] 2.215154e-05 4.430307e-05 9.999778e-01
[2,] 6.576798e-07 1.315360e-06 9.999993e-01
[3,] 5.286653e-08 1.057331e-07 9.999999e-01
[4,] 9.255217e-09 1.851043e-08 1.000000e+00
[5,] 4.321260e-10 8.642519e-10 1.000000e+00
[6,] 4.067973e-11 8.135946e-11 1.000000e+00
[7,] 1.731660e-12 3.463319e-12 1.000000e+00
[8,] 1.335809e-13 2.671619e-13 1.000000e+00
[9,] 9.325427e-15 1.865085e-14 1.000000e+00
[10,] 1.451227e-15 2.902454e-15 1.000000e+00
[11,] 1.789681e-16 3.579361e-16 1.000000e+00
[12,] 1.036232e-17 2.072464e-17 1.000000e+00
[13,] 1.089003e-18 2.178006e-18 1.000000e+00
[14,] 1.054518e-19 2.109036e-19 1.000000e+00
[15,] 2.171323e-20 4.342646e-20 1.000000e+00
[16,] 9.398465e-21 1.879693e-20 1.000000e+00
[17,] 7.223985e-21 1.444797e-20 1.000000e+00
[18,] 8.113079e-21 1.622616e-20 1.000000e+00
[19,] 5.119219e-21 1.023844e-20 1.000000e+00
[20,] 2.327490e-21 4.654981e-21 1.000000e+00
[21,] 1.600089e-21 3.200179e-21 1.000000e+00
[22,] 8.287863e-22 1.657573e-21 1.000000e+00
[23,] 6.179075e-22 1.235815e-21 1.000000e+00
[24,] 3.599701e-22 7.199403e-22 1.000000e+00
[25,] 2.905205e-22 5.810409e-22 1.000000e+00
[26,] 1.887623e-22 3.775247e-22 1.000000e+00
[27,] 1.647909e-22 3.295818e-22 1.000000e+00
[28,] 1.852594e-22 3.705188e-22 1.000000e+00
[29,] 2.566961e-22 5.133921e-22 1.000000e+00
[30,] 4.210006e-22 8.420012e-22 1.000000e+00
[31,] 1.216284e-21 2.432568e-21 1.000000e+00
[32,] 1.166920e-21 2.333840e-21 1.000000e+00
[33,] 1.919497e-21 3.838993e-21 1.000000e+00
[34,] 7.438257e-21 1.487651e-20 1.000000e+00
[35,] 1.404291e-20 2.808582e-20 1.000000e+00
[36,] 2.908705e-20 5.817410e-20 1.000000e+00
[37,] 1.197770e-19 2.395540e-19 1.000000e+00
[38,] 2.054199e-19 4.108397e-19 1.000000e+00
[39,] 3.879216e-19 7.758433e-19 1.000000e+00
[40,] 5.129405e-19 1.025881e-18 1.000000e+00
[41,] 5.245760e-19 1.049152e-18 1.000000e+00
[42,] 7.420062e-19 1.484012e-18 1.000000e+00
[43,] 1.180385e-18 2.360771e-18 1.000000e+00
[44,] 2.545373e-18 5.090746e-18 1.000000e+00
[45,] 5.902586e-18 1.180517e-17 1.000000e+00
[46,] 1.456780e-17 2.913560e-17 1.000000e+00
[47,] 4.578375e-17 9.156750e-17 1.000000e+00
[48,] 1.221603e-16 2.443206e-16 1.000000e+00
[49,] 2.463694e-16 4.927389e-16 1.000000e+00
[50,] 4.046767e-16 8.093534e-16 1.000000e+00
[51,] 8.300185e-16 1.660037e-15 1.000000e+00
[52,] 2.096037e-15 4.192075e-15 1.000000e+00
[53,] 5.533403e-15 1.106681e-14 1.000000e+00
[54,] 2.005905e-14 4.011810e-14 1.000000e+00
[55,] 4.878684e-14 9.757368e-14 1.000000e+00
[56,] 1.105264e-13 2.210527e-13 1.000000e+00
[57,] 1.965660e-13 3.931321e-13 1.000000e+00
[58,] 5.008438e-13 1.001688e-12 1.000000e+00
[59,] 1.195130e-12 2.390259e-12 1.000000e+00
[60,] 3.266214e-12 6.532427e-12 1.000000e+00
[61,] 1.003849e-11 2.007698e-11 1.000000e+00
[62,] 3.083503e-11 6.167006e-11 1.000000e+00
[63,] 1.032811e-10 2.065623e-10 1.000000e+00
[64,] 3.691667e-10 7.383333e-10 1.000000e+00
[65,] 9.930174e-10 1.986035e-09 1.000000e+00
[66,] 2.863456e-09 5.726911e-09 1.000000e+00
[67,] 9.374931e-09 1.874986e-08 1.000000e+00
[68,] 2.395699e-08 4.791399e-08 1.000000e+00
[69,] 5.714084e-08 1.142817e-07 9.999999e-01
[70,] 1.946007e-07 3.892015e-07 9.999998e-01
[71,] 6.103870e-07 1.220774e-06 9.999994e-01
[72,] 1.675660e-06 3.351319e-06 9.999983e-01
[73,] 4.122477e-06 8.244954e-06 9.999959e-01
[74,] 1.061335e-05 2.122671e-05 9.999894e-01
[75,] 2.447469e-05 4.894937e-05 9.999755e-01
[76,] 5.805295e-05 1.161059e-04 9.999419e-01
[77,] 1.454002e-04 2.908003e-04 9.998546e-01
[78,] 2.142916e-04 4.285831e-04 9.997857e-01
[79,] 3.667253e-04 7.334507e-04 9.996333e-01
[80,] 5.613759e-04 1.122752e-03 9.994386e-01
[81,] 1.012808e-03 2.025615e-03 9.989872e-01
[82,] 2.038940e-03 4.077879e-03 9.979611e-01
[83,] 3.493620e-03 6.987241e-03 9.965064e-01
[84,] 5.852354e-03 1.170471e-02 9.941476e-01
[85,] 9.808359e-03 1.961672e-02 9.901916e-01
[86,] 1.614006e-02 3.228012e-02 9.838599e-01
[87,] 2.980313e-02 5.960627e-02 9.701969e-01
[88,] 5.310431e-02 1.062086e-01 9.468957e-01
[89,] 8.750889e-02 1.750178e-01 9.124911e-01
[90,] 1.292406e-01 2.584812e-01 8.707594e-01
[91,] 2.102593e-01 4.205187e-01 7.897407e-01
[92,] 2.926951e-01 5.853902e-01 7.073049e-01
[93,] 4.122022e-01 8.244044e-01 5.877978e-01
[94,] 5.053561e-01 9.892877e-01 4.946439e-01
[95,] 5.609325e-01 8.781349e-01 4.390675e-01
[96,] 6.000091e-01 7.999817e-01 3.999909e-01
[97,] 6.361625e-01 7.276750e-01 3.638375e-01
[98,] 6.702171e-01 6.595657e-01 3.297829e-01
[99,] 7.027253e-01 5.945495e-01 2.972747e-01
[100,] 7.320677e-01 5.358647e-01 2.679323e-01
[101,] 7.689708e-01 4.620584e-01 2.310292e-01
[102,] 7.909063e-01 4.181874e-01 2.090937e-01
[103,] 8.124712e-01 3.750577e-01 1.875288e-01
[104,] 8.464929e-01 3.070142e-01 1.535071e-01
[105,] 8.742936e-01 2.514128e-01 1.257064e-01
[106,] 9.060952e-01 1.878097e-01 9.390483e-02
[107,] 9.381932e-01 1.236136e-01 6.180678e-02
[108,] 9.890282e-01 2.194362e-02 1.097181e-02
[109,] 9.989424e-01 2.115111e-03 1.057556e-03
[110,] 9.998269e-01 3.461055e-04 1.730528e-04
[111,] 9.999130e-01 1.739181e-04 8.695904e-05
[112,] 9.999535e-01 9.304288e-05 4.652144e-05
[113,] 9.999795e-01 4.105052e-05 2.052526e-05
[114,] 9.999948e-01 1.048133e-05 5.240663e-06
[115,] 9.999972e-01 5.628889e-06 2.814445e-06
[116,] 9.999987e-01 2.630188e-06 1.315094e-06
[117,] 9.999995e-01 9.957219e-07 4.978609e-07
[118,] 9.999998e-01 3.033154e-07 1.516577e-07
[119,] 1.000000e+00 8.477027e-08 4.238514e-08
[120,] 1.000000e+00 4.475891e-08 2.237945e-08
[121,] 1.000000e+00 2.800729e-08 1.400365e-08
[122,] 1.000000e+00 1.964476e-08 9.822379e-09
[123,] 1.000000e+00 5.764879e-09 2.882439e-09
[124,] 1.000000e+00 8.580365e-10 4.290183e-10
[125,] 1.000000e+00 7.757499e-11 3.878750e-11
[126,] 1.000000e+00 1.067370e-11 5.336850e-12
[127,] 1.000000e+00 8.631207e-12 4.315604e-12
[128,] 1.000000e+00 8.911549e-12 4.455775e-12
[129,] 1.000000e+00 1.113459e-11 5.567297e-12
[130,] 1.000000e+00 1.239123e-11 6.195614e-12
[131,] 1.000000e+00 1.307527e-11 6.537637e-12
[132,] 1.000000e+00 2.062473e-11 1.031236e-11
[133,] 1.000000e+00 2.983696e-11 1.491848e-11
[134,] 1.000000e+00 3.507167e-11 1.753583e-11
[135,] 1.000000e+00 5.386906e-11 2.693453e-11
[136,] 1.000000e+00 3.122878e-11 1.561439e-11
[137,] 1.000000e+00 3.312657e-12 1.656328e-12
[138,] 1.000000e+00 1.001511e-12 5.007553e-13
[139,] 1.000000e+00 2.193802e-12 1.096901e-12
[140,] 1.000000e+00 3.402693e-12 1.701347e-12
[141,] 1.000000e+00 7.205029e-12 3.602515e-12
[142,] 1.000000e+00 5.273891e-12 2.636945e-12
[143,] 1.000000e+00 6.777571e-13 3.388786e-13
[144,] 1.000000e+00 4.640103e-13 2.320052e-13
[145,] 1.000000e+00 1.572737e-12 7.863684e-13
[146,] 1.000000e+00 5.178142e-12 2.589071e-12
[147,] 1.000000e+00 6.416149e-12 3.208075e-12
[148,] 1.000000e+00 8.176965e-12 4.088483e-12
[149,] 1.000000e+00 6.454117e-12 3.227059e-12
[150,] 1.000000e+00 3.182777e-12 1.591388e-12
[151,] 1.000000e+00 1.041702e-12 5.208510e-13
[152,] 1.000000e+00 7.138941e-14 3.569471e-14
[153,] 1.000000e+00 9.894031e-14 4.947016e-14
[154,] 1.000000e+00 1.406687e-13 7.033437e-14
[155,] 1.000000e+00 1.112464e-12 5.562321e-13
[156,] 1.000000e+00 7.290124e-12 3.645062e-12
[157,] 1.000000e+00 1.762798e-12 8.813992e-13
[158,] 1.000000e+00 4.262287e-12 2.131144e-12
[159,] 1.000000e+00 5.267385e-11 2.633693e-11
[160,] 1.000000e+00 3.181893e-10 1.590947e-10
[161,] 1.000000e+00 4.070853e-09 2.035427e-09
[162,] 1.000000e+00 3.230060e-08 1.615030e-08
[163,] 9.999998e-01 4.047598e-07 2.023799e-07
[164,] 9.999986e-01 2.720214e-06 1.360107e-06
[165,] 9.999943e-01 1.144098e-05 5.720489e-06
[166,] 9.999803e-01 3.942280e-05 1.971140e-05
[167,] 9.997527e-01 4.946680e-04 2.473340e-04
> postscript(file="/var/www/html/rcomp/tmp/1f7d21292338939.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2f7d21292338939.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3f7d21292338939.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/47yu51292338939.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/57yu51292338939.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 = 176
Frequency = 1
1 2 3 4 5 6 7 8 9 10 11
-56.25 -57.25 -56.25 -55.25 -55.25 -55.25 -54.25 -53.25 -54.25 -53.25 -54.25
12 13 14 15 16 17 18 19 20 21 22
-53.25 -53.25 -52.25 -52.25 -53.25 -52.25 -52.25 -51.25 -50.25 -49.25 -48.25
23 24 25 26 27 28 29 30 31 32 33
-48.25 -48.25 -47.25 -47.25 -46.25 -46.25 -45.25 -45.25 -44.25 -43.25 -42.25
34 35 36 37 38 39 40 41 42 43 44
-41.25 -39.25 -41.25 -39.25 -36.25 -37.25 -36.25 -33.25 -35.25 -34.25 -35.25
45 46 47 48 49 50 51 52 53 54 55
-36.25 -34.25 -33.25 -31.25 -30.25 -29.25 -27.25 -27.25 -28.25 -29.25 -27.25
56 57 58 59 60 61 62 63 64 65 66
-25.25 -24.25 -21.25 -23.25 -23.25 -25.25 -21.25 -21.25 -19.25 -17.25 -16.25
67 68 69 70 71 72 73 74 75 76 77
-14.25 -12.25 -14.25 -12.25 -9.25 -11.25 -11.25 -4.25 -3.25 -3.25 -3.25
78 79 80 81 82 83 84 85 86 87 88
-0.25 -0.25 2.75 6.75 -21.25 -27.25 -15.25 -25.25 -27.25 -16.25 -6.25
89 90 91 92 93 94 95 96 97 98 99
-11.25 -5.25 10.75 14.75 16.75 15.75 28.75 26.75 35.75 31.75 22.75
100 101 102 103 104 105 106 107 108 109 110
5.75 10.75 13.75 9.75 13.75 28.75 16.75 11.75 0.75 3.75 -0.25
111 112 113 114 115 116 117 118 119 120 121
-3.25 -28.25 -22.25 -5.25 17.75 20.75 17.75 11.75 25.75 23.75 21.75
122 123 124 125 126 127 128 129 130 131 132
20.75 21.75 30.75 33.75 35.75 25.75 22.75 22.75 27.75 41.75 44.75
133 134 135 136 137 138 139 140 141 142 143
47.75 44.75 43.75 53.75 58.75 62.75 59.75 69.75 77.75 71.75 57.75
144 145 146 147 148 149 150 151 152 153 154
61.75 58.75 66.75 72.75 64.75 53.75 44.75 37.75 38.75 37.75 37.75
155 156 157 158 159 160 161 162 163 164 165
38.75 38.75 46.75 47.75 53.75 52.75 46.75 51.75 56.75 60.75 56.75
166 167 168 169 170 171 172 173 174 175 176
59.75 56.75 59.75 59.75 50.75 57.75 54.75 1.25 2.25 -2.75 -0.75
> postscript(file="/var/www/html/rcomp/tmp/60qtq1292338939.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 = 176
Frequency = 1
lag(myerror, k = 1) myerror
0 -56.25 NA
1 -57.25 -56.25
2 -56.25 -57.25
3 -55.25 -56.25
4 -55.25 -55.25
5 -55.25 -55.25
6 -54.25 -55.25
7 -53.25 -54.25
8 -54.25 -53.25
9 -53.25 -54.25
10 -54.25 -53.25
11 -53.25 -54.25
12 -53.25 -53.25
13 -52.25 -53.25
14 -52.25 -52.25
15 -53.25 -52.25
16 -52.25 -53.25
17 -52.25 -52.25
18 -51.25 -52.25
19 -50.25 -51.25
20 -49.25 -50.25
21 -48.25 -49.25
22 -48.25 -48.25
23 -48.25 -48.25
24 -47.25 -48.25
25 -47.25 -47.25
26 -46.25 -47.25
27 -46.25 -46.25
28 -45.25 -46.25
29 -45.25 -45.25
30 -44.25 -45.25
31 -43.25 -44.25
32 -42.25 -43.25
33 -41.25 -42.25
34 -39.25 -41.25
35 -41.25 -39.25
36 -39.25 -41.25
37 -36.25 -39.25
38 -37.25 -36.25
39 -36.25 -37.25
40 -33.25 -36.25
41 -35.25 -33.25
42 -34.25 -35.25
43 -35.25 -34.25
44 -36.25 -35.25
45 -34.25 -36.25
46 -33.25 -34.25
47 -31.25 -33.25
48 -30.25 -31.25
49 -29.25 -30.25
50 -27.25 -29.25
51 -27.25 -27.25
52 -28.25 -27.25
53 -29.25 -28.25
54 -27.25 -29.25
55 -25.25 -27.25
56 -24.25 -25.25
57 -21.25 -24.25
58 -23.25 -21.25
59 -23.25 -23.25
60 -25.25 -23.25
61 -21.25 -25.25
62 -21.25 -21.25
63 -19.25 -21.25
64 -17.25 -19.25
65 -16.25 -17.25
66 -14.25 -16.25
67 -12.25 -14.25
68 -14.25 -12.25
69 -12.25 -14.25
70 -9.25 -12.25
71 -11.25 -9.25
72 -11.25 -11.25
73 -4.25 -11.25
74 -3.25 -4.25
75 -3.25 -3.25
76 -3.25 -3.25
77 -0.25 -3.25
78 -0.25 -0.25
79 2.75 -0.25
80 6.75 2.75
81 -21.25 6.75
82 -27.25 -21.25
83 -15.25 -27.25
84 -25.25 -15.25
85 -27.25 -25.25
86 -16.25 -27.25
87 -6.25 -16.25
88 -11.25 -6.25
89 -5.25 -11.25
90 10.75 -5.25
91 14.75 10.75
92 16.75 14.75
93 15.75 16.75
94 28.75 15.75
95 26.75 28.75
96 35.75 26.75
97 31.75 35.75
98 22.75 31.75
99 5.75 22.75
100 10.75 5.75
101 13.75 10.75
102 9.75 13.75
103 13.75 9.75
104 28.75 13.75
105 16.75 28.75
106 11.75 16.75
107 0.75 11.75
108 3.75 0.75
109 -0.25 3.75
110 -3.25 -0.25
111 -28.25 -3.25
112 -22.25 -28.25
113 -5.25 -22.25
114 17.75 -5.25
115 20.75 17.75
116 17.75 20.75
117 11.75 17.75
118 25.75 11.75
119 23.75 25.75
120 21.75 23.75
121 20.75 21.75
122 21.75 20.75
123 30.75 21.75
124 33.75 30.75
125 35.75 33.75
126 25.75 35.75
127 22.75 25.75
128 22.75 22.75
129 27.75 22.75
130 41.75 27.75
131 44.75 41.75
132 47.75 44.75
133 44.75 47.75
134 43.75 44.75
135 53.75 43.75
136 58.75 53.75
137 62.75 58.75
138 59.75 62.75
139 69.75 59.75
140 77.75 69.75
141 71.75 77.75
142 57.75 71.75
143 61.75 57.75
144 58.75 61.75
145 66.75 58.75
146 72.75 66.75
147 64.75 72.75
148 53.75 64.75
149 44.75 53.75
150 37.75 44.75
151 38.75 37.75
152 37.75 38.75
153 37.75 37.75
154 38.75 37.75
155 38.75 38.75
156 46.75 38.75
157 47.75 46.75
158 53.75 47.75
159 52.75 53.75
160 46.75 52.75
161 51.75 46.75
162 56.75 51.75
163 60.75 56.75
164 56.75 60.75
165 59.75 56.75
166 56.75 59.75
167 59.75 56.75
168 59.75 59.75
169 50.75 59.75
170 57.75 50.75
171 54.75 57.75
172 1.25 54.75
173 2.25 1.25
174 -2.75 2.25
175 -0.75 -2.75
176 NA -0.75
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -57.25 -56.25
[2,] -56.25 -57.25
[3,] -55.25 -56.25
[4,] -55.25 -55.25
[5,] -55.25 -55.25
[6,] -54.25 -55.25
[7,] -53.25 -54.25
[8,] -54.25 -53.25
[9,] -53.25 -54.25
[10,] -54.25 -53.25
[11,] -53.25 -54.25
[12,] -53.25 -53.25
[13,] -52.25 -53.25
[14,] -52.25 -52.25
[15,] -53.25 -52.25
[16,] -52.25 -53.25
[17,] -52.25 -52.25
[18,] -51.25 -52.25
[19,] -50.25 -51.25
[20,] -49.25 -50.25
[21,] -48.25 -49.25
[22,] -48.25 -48.25
[23,] -48.25 -48.25
[24,] -47.25 -48.25
[25,] -47.25 -47.25
[26,] -46.25 -47.25
[27,] -46.25 -46.25
[28,] -45.25 -46.25
[29,] -45.25 -45.25
[30,] -44.25 -45.25
[31,] -43.25 -44.25
[32,] -42.25 -43.25
[33,] -41.25 -42.25
[34,] -39.25 -41.25
[35,] -41.25 -39.25
[36,] -39.25 -41.25
[37,] -36.25 -39.25
[38,] -37.25 -36.25
[39,] -36.25 -37.25
[40,] -33.25 -36.25
[41,] -35.25 -33.25
[42,] -34.25 -35.25
[43,] -35.25 -34.25
[44,] -36.25 -35.25
[45,] -34.25 -36.25
[46,] -33.25 -34.25
[47,] -31.25 -33.25
[48,] -30.25 -31.25
[49,] -29.25 -30.25
[50,] -27.25 -29.25
[51,] -27.25 -27.25
[52,] -28.25 -27.25
[53,] -29.25 -28.25
[54,] -27.25 -29.25
[55,] -25.25 -27.25
[56,] -24.25 -25.25
[57,] -21.25 -24.25
[58,] -23.25 -21.25
[59,] -23.25 -23.25
[60,] -25.25 -23.25
[61,] -21.25 -25.25
[62,] -21.25 -21.25
[63,] -19.25 -21.25
[64,] -17.25 -19.25
[65,] -16.25 -17.25
[66,] -14.25 -16.25
[67,] -12.25 -14.25
[68,] -14.25 -12.25
[69,] -12.25 -14.25
[70,] -9.25 -12.25
[71,] -11.25 -9.25
[72,] -11.25 -11.25
[73,] -4.25 -11.25
[74,] -3.25 -4.25
[75,] -3.25 -3.25
[76,] -3.25 -3.25
[77,] -0.25 -3.25
[78,] -0.25 -0.25
[79,] 2.75 -0.25
[80,] 6.75 2.75
[81,] -21.25 6.75
[82,] -27.25 -21.25
[83,] -15.25 -27.25
[84,] -25.25 -15.25
[85,] -27.25 -25.25
[86,] -16.25 -27.25
[87,] -6.25 -16.25
[88,] -11.25 -6.25
[89,] -5.25 -11.25
[90,] 10.75 -5.25
[91,] 14.75 10.75
[92,] 16.75 14.75
[93,] 15.75 16.75
[94,] 28.75 15.75
[95,] 26.75 28.75
[96,] 35.75 26.75
[97,] 31.75 35.75
[98,] 22.75 31.75
[99,] 5.75 22.75
[100,] 10.75 5.75
[101,] 13.75 10.75
[102,] 9.75 13.75
[103,] 13.75 9.75
[104,] 28.75 13.75
[105,] 16.75 28.75
[106,] 11.75 16.75
[107,] 0.75 11.75
[108,] 3.75 0.75
[109,] -0.25 3.75
[110,] -3.25 -0.25
[111,] -28.25 -3.25
[112,] -22.25 -28.25
[113,] -5.25 -22.25
[114,] 17.75 -5.25
[115,] 20.75 17.75
[116,] 17.75 20.75
[117,] 11.75 17.75
[118,] 25.75 11.75
[119,] 23.75 25.75
[120,] 21.75 23.75
[121,] 20.75 21.75
[122,] 21.75 20.75
[123,] 30.75 21.75
[124,] 33.75 30.75
[125,] 35.75 33.75
[126,] 25.75 35.75
[127,] 22.75 25.75
[128,] 22.75 22.75
[129,] 27.75 22.75
[130,] 41.75 27.75
[131,] 44.75 41.75
[132,] 47.75 44.75
[133,] 44.75 47.75
[134,] 43.75 44.75
[135,] 53.75 43.75
[136,] 58.75 53.75
[137,] 62.75 58.75
[138,] 59.75 62.75
[139,] 69.75 59.75
[140,] 77.75 69.75
[141,] 71.75 77.75
[142,] 57.75 71.75
[143,] 61.75 57.75
[144,] 58.75 61.75
[145,] 66.75 58.75
[146,] 72.75 66.75
[147,] 64.75 72.75
[148,] 53.75 64.75
[149,] 44.75 53.75
[150,] 37.75 44.75
[151,] 38.75 37.75
[152,] 37.75 38.75
[153,] 37.75 37.75
[154,] 38.75 37.75
[155,] 38.75 38.75
[156,] 46.75 38.75
[157,] 47.75 46.75
[158,] 53.75 47.75
[159,] 52.75 53.75
[160,] 46.75 52.75
[161,] 51.75 46.75
[162,] 56.75 51.75
[163,] 60.75 56.75
[164,] 56.75 60.75
[165,] 59.75 56.75
[166,] 56.75 59.75
[167,] 59.75 56.75
[168,] 59.75 59.75
[169,] 50.75 59.75
[170,] 57.75 50.75
[171,] 54.75 57.75
[172,] 1.25 54.75
[173,] 2.25 1.25
[174,] -2.75 2.25
[175,] -0.75 -2.75
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -57.25 -56.25
2 -56.25 -57.25
3 -55.25 -56.25
4 -55.25 -55.25
5 -55.25 -55.25
6 -54.25 -55.25
7 -53.25 -54.25
8 -54.25 -53.25
9 -53.25 -54.25
10 -54.25 -53.25
11 -53.25 -54.25
12 -53.25 -53.25
13 -52.25 -53.25
14 -52.25 -52.25
15 -53.25 -52.25
16 -52.25 -53.25
17 -52.25 -52.25
18 -51.25 -52.25
19 -50.25 -51.25
20 -49.25 -50.25
21 -48.25 -49.25
22 -48.25 -48.25
23 -48.25 -48.25
24 -47.25 -48.25
25 -47.25 -47.25
26 -46.25 -47.25
27 -46.25 -46.25
28 -45.25 -46.25
29 -45.25 -45.25
30 -44.25 -45.25
31 -43.25 -44.25
32 -42.25 -43.25
33 -41.25 -42.25
34 -39.25 -41.25
35 -41.25 -39.25
36 -39.25 -41.25
37 -36.25 -39.25
38 -37.25 -36.25
39 -36.25 -37.25
40 -33.25 -36.25
41 -35.25 -33.25
42 -34.25 -35.25
43 -35.25 -34.25
44 -36.25 -35.25
45 -34.25 -36.25
46 -33.25 -34.25
47 -31.25 -33.25
48 -30.25 -31.25
49 -29.25 -30.25
50 -27.25 -29.25
51 -27.25 -27.25
52 -28.25 -27.25
53 -29.25 -28.25
54 -27.25 -29.25
55 -25.25 -27.25
56 -24.25 -25.25
57 -21.25 -24.25
58 -23.25 -21.25
59 -23.25 -23.25
60 -25.25 -23.25
61 -21.25 -25.25
62 -21.25 -21.25
63 -19.25 -21.25
64 -17.25 -19.25
65 -16.25 -17.25
66 -14.25 -16.25
67 -12.25 -14.25
68 -14.25 -12.25
69 -12.25 -14.25
70 -9.25 -12.25
71 -11.25 -9.25
72 -11.25 -11.25
73 -4.25 -11.25
74 -3.25 -4.25
75 -3.25 -3.25
76 -3.25 -3.25
77 -0.25 -3.25
78 -0.25 -0.25
79 2.75 -0.25
80 6.75 2.75
81 -21.25 6.75
82 -27.25 -21.25
83 -15.25 -27.25
84 -25.25 -15.25
85 -27.25 -25.25
86 -16.25 -27.25
87 -6.25 -16.25
88 -11.25 -6.25
89 -5.25 -11.25
90 10.75 -5.25
91 14.75 10.75
92 16.75 14.75
93 15.75 16.75
94 28.75 15.75
95 26.75 28.75
96 35.75 26.75
97 31.75 35.75
98 22.75 31.75
99 5.75 22.75
100 10.75 5.75
101 13.75 10.75
102 9.75 13.75
103 13.75 9.75
104 28.75 13.75
105 16.75 28.75
106 11.75 16.75
107 0.75 11.75
108 3.75 0.75
109 -0.25 3.75
110 -3.25 -0.25
111 -28.25 -3.25
112 -22.25 -28.25
113 -5.25 -22.25
114 17.75 -5.25
115 20.75 17.75
116 17.75 20.75
117 11.75 17.75
118 25.75 11.75
119 23.75 25.75
120 21.75 23.75
121 20.75 21.75
122 21.75 20.75
123 30.75 21.75
124 33.75 30.75
125 35.75 33.75
126 25.75 35.75
127 22.75 25.75
128 22.75 22.75
129 27.75 22.75
130 41.75 27.75
131 44.75 41.75
132 47.75 44.75
133 44.75 47.75
134 43.75 44.75
135 53.75 43.75
136 58.75 53.75
137 62.75 58.75
138 59.75 62.75
139 69.75 59.75
140 77.75 69.75
141 71.75 77.75
142 57.75 71.75
143 61.75 57.75
144 58.75 61.75
145 66.75 58.75
146 72.75 66.75
147 64.75 72.75
148 53.75 64.75
149 44.75 53.75
150 37.75 44.75
151 38.75 37.75
152 37.75 38.75
153 37.75 37.75
154 38.75 37.75
155 38.75 38.75
156 46.75 38.75
157 47.75 46.75
158 53.75 47.75
159 52.75 53.75
160 46.75 52.75
161 51.75 46.75
162 56.75 51.75
163 60.75 56.75
164 56.75 60.75
165 59.75 56.75
166 56.75 59.75
167 59.75 56.75
168 59.75 59.75
169 50.75 59.75
170 57.75 50.75
171 54.75 57.75
172 1.25 54.75
173 2.25 1.25
174 -2.75 2.25
175 -0.75 -2.75
> 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/rcomp/tmp/70qtq1292338939.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8bzbt1292338939.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9bzbt1292338939.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1038sw1292338939.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/117rq21292338939.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/rcomp/tmp/12srp81292338939.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/rcomp/tmp/136jny1292338939.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/rcomp/tmp/14f5sb1292338939.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/rcomp/tmp/15vkka1292338939.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/rcomp/tmp/16hlig1292338939.tab")
+ }
>
> try(system("convert tmp/1f7d21292338939.ps tmp/1f7d21292338939.png",intern=TRUE))
character(0)
> try(system("convert tmp/2f7d21292338939.ps tmp/2f7d21292338939.png",intern=TRUE))
character(0)
> try(system("convert tmp/3f7d21292338939.ps tmp/3f7d21292338939.png",intern=TRUE))
character(0)
> try(system("convert tmp/47yu51292338939.ps tmp/47yu51292338939.png",intern=TRUE))
character(0)
> try(system("convert tmp/57yu51292338939.ps tmp/57yu51292338939.png",intern=TRUE))
character(0)
> try(system("convert tmp/60qtq1292338939.ps tmp/60qtq1292338939.png",intern=TRUE))
character(0)
> try(system("convert tmp/70qtq1292338939.ps tmp/70qtq1292338939.png",intern=TRUE))
character(0)
> try(system("convert tmp/8bzbt1292338939.ps tmp/8bzbt1292338939.png",intern=TRUE))
character(0)
> try(system("convert tmp/9bzbt1292338939.ps tmp/9bzbt1292338939.png",intern=TRUE))
character(0)
> try(system("convert tmp/1038sw1292338939.ps tmp/1038sw1292338939.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.042 1.876 13.138