R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
Natural language support but running in an English locale
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(12
+ ,20
+ ,22.5
+ ,1
+ ,0
+ ,0
+ ,2
+ ,0
+ ,3
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+ ,24
+ ,3
+ ,0
+ ,3.6
+ ,16
+ ,0
+ ,3)
+ ,dim=c(3
+ ,160)
+ ,dimnames=list(c('Sport_tv'
+ ,'sport_live'
+ ,'Sport_Totaal')
+ ,1:160))
> y <- array(NA,dim=c(3,160),dimnames=list(c('Sport_tv','sport_live','Sport_Totaal'),1:160))
> 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 = '3'
> #'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
Sport_Totaal Sport_tv sport_live
1 22.5 12 20
2 0.0 1 0
3 3.0 2 0
4 2.0 0 3
5 3.0 4 0
6 4.8 0 0
7 0.9 0 12
8 0.0 5 4
9 6.0 0 0
10 22.5 18 28
11 0.0 6 3
12 12.0 2 0
13 6.0 7 0
14 30.0 6 2
15 24.0 1 0
16 1.0 0 0
17 3.0 0 0
18 22.4 9 0
19 4.0 0 0
20 1.6 1 2
21 12.0 1 0
22 24.0 20 2
23 0.0 9 8
24 0.0 6 0
25 22.5 11 0
26 18.0 18 17
27 2.2 3 0
28 33.0 5 0
29 2.5 10 3
30 4.0 2 0
31 75.0 7 6
32 1.2 0 0
33 18.0 8 0
34 1.6 5 0
35 4.0 9 0
36 3.0 4 0
37 2.0 0 0
38 16.8 0 7
39 90.0 1 5
40 19.2 0 4
41 6.0 6 2
42 4.2 9 15
43 2.0 5 0
44 42.5 38 15
45 7.5 10 0
46 0.0 3 0
47 3.9 8 0
48 4.0 28 8
49 30.0 20 2
50 0.0 0 0
51 8.0 10 0
52 15.0 8 3
53 4.0 10 0
54 0.0 8 2
55 6.0 8 4
56 4.4 8 0
57 20.0 6 6
58 0.0 32 7
59 0.0 3 0
60 0.0 15 0
61 0.0 12 1
62 0.0 5 0
63 0.0 8 4
64 0.0 14 8
65 7.0 2 0
66 6.0 19 4
67 18.0 22 8
68 9.0 9 0
69 18.0 24 1
70 15.0 18 0
71 4.5 1 1
72 12.0 0 10
73 0.0 0 0
74 32.0 20 0
75 5.0 19 0
76 0.0 20 0
77 0.0 1 0
78 3.0 0 0
79 15.0 57 0
80 15.0 28 2
81 42.0 0 0
82 18.0 6 12
83 24.0 20 8
84 18.0 4 12
85 30.0 0 1
86 0.0 4 15
87 6.0 10 3
88 4.5 6 0
89 0.0 1 0
90 21.0 13 0
91 3.6 3 0
92 1.2 5 0
93 0.0 3 0
94 24.0 0 0
95 19.2 4 0
96 22.5 5 0
97 0.0 0 0
98 10.4 46 0
99 6.0 0 0
100 28.0 24 4
101 2.5 0 0
102 20.0 0 0
103 32.0 53 9
104 6.0 38 0
105 0.0 0 0
106 8.0 5 10
107 18.0 7 0
108 9.0 5 0
109 2.0 1 4
110 20.0 16 30
111 0.0 1 0
112 26.0 31 7
113 0.0 4 0
114 0.0 0 0
115 0.0 1 0
116 0.0 0 0
117 12.0 9 2
118 12.0 30 25
119 32.0 4 0
120 6.0 8 2
121 0.0 11 0
122 0.0 16 0
123 4.0 0 0
124 12.6 1 11
125 25.5 15 1
126 4.8 0 0
127 4.5 8 5
128 4.8 5 0
129 16.0 4 1
130 3.0 4 8
131 7.0 2 9
132 0.0 6 5
133 20.0 7 24
134 4.8 3 0
135 0.0 4 0
136 4.8 6 1
137 0.0 7 0
138 3.2 5 0
139 29.9 5 0
140 24.0 0 2
141 35.2 9 5
142 30.0 13 0
143 26.0 0 0
144 58.8 6 4
145 15.0 16 7
146 14.0 4 0
147 4.8 61 15
148 30.0 0 0
149 14.4 0 0
150 10.0 1 0
151 9.6 9 0
152 0.0 18 0
153 26.0 35 4
154 0.0 20 0
155 31.5 16 10
156 0.0 0 0
157 1.0 1 4
158 24.0 4 0
159 3.6 3 0
160 3.0 16 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Sport_tv sport_live
8.9386 0.1343 0.4174
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-18.595 -8.939 -4.964 5.430 78.840
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.9386 1.4218 6.287 3.07e-09 ***
Sport_tv 0.1343 0.1018 1.320 0.1888
sport_live 0.4174 0.2021 2.065 0.0406 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 13.64 on 157 degrees of freedom
Multiple R-squared: 0.05072, Adjusted R-squared: 0.03863
F-statistic: 4.194 on 2 and 157 DF, p-value: 0.01680
> 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,] 0.0077125811 1.542516e-02 9.922874e-01
[2,] 0.0046044216 9.208843e-03 9.953956e-01
[3,] 0.0068543915 1.370878e-02 9.931456e-01
[4,] 0.0045107522 9.021504e-03 9.954892e-01
[5,] 0.0016024745 3.204949e-03 9.983975e-01
[6,] 0.0011282616 2.256523e-03 9.988717e-01
[7,] 0.0019686055 3.937211e-03 9.980314e-01
[8,] 0.0006941224 1.388245e-03 9.993059e-01
[9,] 0.0258442954 5.168859e-02 9.741557e-01
[10,] 0.0716896444 1.433793e-01 9.283104e-01
[11,] 0.0469532094 9.390642e-02 9.530468e-01
[12,] 0.0286819865 5.736397e-02 9.713180e-01
[13,] 0.0209893796 4.197876e-02 9.790106e-01
[14,] 0.0122142901 2.442858e-02 9.877857e-01
[15,] 0.0073860035 1.477201e-02 9.926140e-01
[16,] 0.0050479543 1.009591e-02 9.949520e-01
[17,] 0.0032475696 6.495139e-03 9.967524e-01
[18,] 0.0047814722 9.562944e-03 9.952185e-01
[19,] 0.0045466051 9.093210e-03 9.954534e-01
[20,] 0.0033270432 6.654086e-03 9.966730e-01
[21,] 0.0020044677 4.008935e-03 9.979955e-01
[22,] 0.0012796241 2.559248e-03 9.987204e-01
[23,] 0.0076572989 1.531460e-02 9.923427e-01
[24,] 0.0081515910 1.630318e-02 9.918484e-01
[25,] 0.0052621587 1.052432e-02 9.947378e-01
[26,] 0.8100369587 3.799261e-01 1.899630e-01
[27,] 0.7751263236 4.497474e-01 2.248737e-01
[28,] 0.7352835835 5.294328e-01 2.647164e-01
[29,] 0.7087227731 5.825545e-01 2.912772e-01
[30,] 0.6853671655 6.292657e-01 3.146328e-01
[31,] 0.6456336074 7.087328e-01 3.543664e-01
[32,] 0.5986523311 8.026953e-01 4.013477e-01
[33,] 0.5714576024 8.570848e-01 4.285424e-01
[34,] 0.9999762286 4.754286e-05 2.377143e-05
[35,] 0.9999663336 6.733272e-05 3.366636e-05
[36,] 0.9999475769 1.048461e-04 5.242305e-05
[37,] 0.9999431823 1.136354e-04 5.681768e-05
[38,] 0.9999203807 1.592387e-04 7.961935e-05
[39,] 0.9999394452 1.211095e-04 6.055476e-05
[40,] 0.9999067609 1.864783e-04 9.323914e-05
[41,] 0.9998785593 2.428814e-04 1.214407e-04
[42,] 0.9998286806 3.426388e-04 1.713194e-04
[43,] 0.9998480259 3.039482e-04 1.519741e-04
[44,] 0.9998651071 2.697859e-04 1.348929e-04
[45,] 0.9998199426 3.601148e-04 1.800574e-04
[46,] 0.9997251408 5.497183e-04 2.748592e-04
[47,] 0.9995859631 8.280738e-04 4.140369e-04
[48,] 0.9994342605 1.131479e-03 5.657395e-04
[49,] 0.9993462906 1.307419e-03 6.537094e-04
[50,] 0.9990915263 1.816947e-03 9.084737e-04
[51,] 0.9987472849 2.505430e-03 1.252715e-03
[52,] 0.9983668969 3.266206e-03 1.633103e-03
[53,] 0.9987268292 2.546342e-03 1.273171e-03
[54,] 0.9984243014 3.151397e-03 1.575699e-03
[55,] 0.9981851042 3.629792e-03 1.814896e-03
[56,] 0.9979084568 4.183086e-03 2.091543e-03
[57,] 0.9974675292 5.064942e-03 2.532471e-03
[58,] 0.9971966124 5.606775e-03 2.803388e-03
[59,] 0.9972602212 5.479558e-03 2.739779e-03
[60,] 0.9961567833 7.686433e-03 3.843217e-03
[61,] 0.9950542100 9.891580e-03 4.945790e-03
[62,] 0.9932384088 1.352318e-02 6.761591e-03
[63,] 0.9907701023 1.845980e-02 9.229898e-03
[64,] 0.9881528431 2.369431e-02 1.184716e-02
[65,] 0.9844732997 3.105340e-02 1.552670e-02
[66,] 0.9801697641 3.966047e-02 1.983024e-02
[67,] 0.9740227350 5.195453e-02 2.597726e-02
[68,] 0.9698486853 6.030263e-02 3.015131e-02
[69,] 0.9779341663 4.413167e-02 2.206583e-02
[70,] 0.9730107908 5.397842e-02 2.698921e-02
[71,] 0.9712970924 5.740582e-02 2.870291e-02
[72,] 0.9670377955 6.592441e-02 3.296220e-02
[73,] 0.9598528806 8.029424e-02 4.014712e-02
[74,] 0.9492064544 1.015871e-01 5.079355e-02
[75,] 0.9361595417 1.276809e-01 6.384046e-02
[76,] 0.9814969436 3.700611e-02 1.850306e-02
[77,] 0.9760484538 4.790309e-02 2.395155e-02
[78,] 0.9722325157 5.553497e-02 2.776748e-02
[79,] 0.9648164797 7.036704e-02 3.518352e-02
[80,] 0.9752205058 4.955899e-02 2.477949e-02
[81,] 0.9771736992 4.565260e-02 2.282630e-02
[82,] 0.9714593843 5.708123e-02 2.854062e-02
[83,] 0.9645239698 7.095206e-02 3.547603e-02
[84,] 0.9595875443 8.082491e-02 4.041246e-02
[85,] 0.9548964852 9.020703e-02 4.510351e-02
[86,] 0.9453475674 1.093049e-01 5.465243e-02
[87,] 0.9375455545 1.249089e-01 6.245445e-02
[88,] 0.9306017069 1.387966e-01 6.939829e-02
[89,] 0.9334496100 1.331008e-01 6.655039e-02
[90,] 0.9252313328 1.495373e-01 7.476867e-02
[91,] 0.9231564148 1.536872e-01 7.684359e-02
[92,] 0.9137921360 1.724157e-01 8.620786e-02
[93,] 0.8965683881 2.068632e-01 1.034316e-01
[94,] 0.8750018068 2.499964e-01 1.249982e-01
[95,] 0.8770379648 2.459241e-01 1.229620e-01
[96,] 0.8581089688 2.837821e-01 1.418910e-01
[97,] 0.8475778575 3.048443e-01 1.524221e-01
[98,] 0.8500498871 2.999002e-01 1.499501e-01
[99,] 0.8279734245 3.440532e-01 1.720266e-01
[100,] 0.8125550682 3.748899e-01 1.874449e-01
[101,] 0.7845236887 4.309526e-01 2.154763e-01
[102,] 0.7593694214 4.812612e-01 2.406306e-01
[103,] 0.7195256776 5.609486e-01 2.804743e-01
[104,] 0.6975591103 6.048818e-01 3.024409e-01
[105,] 0.6553418658 6.893163e-01 3.446581e-01
[106,] 0.6347806202 7.304388e-01 3.652194e-01
[107,] 0.6247756883 7.504486e-01 3.752243e-01
[108,] 0.6052573328 7.894853e-01 3.947427e-01
[109,] 0.5869116329 8.261767e-01 4.130884e-01
[110,] 0.5701315363 8.597369e-01 4.298685e-01
[111,] 0.5555940767 8.888118e-01 4.444059e-01
[112,] 0.5038739882 9.922520e-01 4.961260e-01
[113,] 0.4723747569 9.447495e-01 5.276252e-01
[114,] 0.5427569163 9.144862e-01 4.572431e-01
[115,] 0.4990194666 9.980389e-01 5.009805e-01
[116,] 0.4803994701 9.607989e-01 5.196005e-01
[117,] 0.4638109164 9.276218e-01 5.361891e-01
[118,] 0.4277705932 8.555412e-01 5.722294e-01
[119,] 0.3778159615 7.556319e-01 6.221840e-01
[120,] 0.3756756232 7.513512e-01 6.243244e-01
[121,] 0.3380751669 6.761503e-01 6.619248e-01
[122,] 0.3102829176 6.205658e-01 6.897171e-01
[123,] 0.2753611014 5.507222e-01 7.246389e-01
[124,] 0.2322516334 4.645033e-01 7.677484e-01
[125,] 0.2263921553 4.527843e-01 7.736078e-01
[126,] 0.2097069648 4.194139e-01 7.902930e-01
[127,] 0.2229624189 4.459248e-01 7.770376e-01
[128,] 0.2708028156 5.416056e-01 7.291972e-01
[129,] 0.2411776386 4.823553e-01 7.588224e-01
[130,] 0.2398426529 4.796853e-01 7.601573e-01
[131,] 0.2190093564 4.380187e-01 7.809906e-01
[132,] 0.2165133601 4.330267e-01 7.834866e-01
[133,] 0.2045015311 4.090031e-01 7.954985e-01
[134,] 0.2126548177 4.253096e-01 7.873452e-01
[135,] 0.1736919527 3.473839e-01 8.263080e-01
[136,] 0.1770935853 3.541872e-01 8.229064e-01
[137,] 0.2203908213 4.407816e-01 7.796092e-01
[138,] 0.1987243492 3.974487e-01 8.012757e-01
[139,] 0.8048164657 3.903671e-01 1.951835e-01
[140,] 0.7375276908 5.249446e-01 2.624723e-01
[141,] 0.6616438539 6.767123e-01 3.383561e-01
[142,] 0.7209019729 5.581961e-01 2.790980e-01
[143,] 0.8813930992 2.372138e-01 1.186069e-01
[144,] 0.8584826586 2.830347e-01 1.415173e-01
[145,] 0.8029185775 3.941628e-01 1.970814e-01
[146,] 0.7194645167 5.610710e-01 2.805355e-01
[147,] 0.6391770287 7.216459e-01 3.608230e-01
[148,] 0.5313426529 9.373147e-01 4.686573e-01
[149,] 0.4221102530 8.442205e-01 5.778897e-01
> postscript(file="/var/www/html/freestat/rcomp/tmp/1xr161290515977.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2xr161290515977.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3701r1290515977.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4701r1290515977.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5701r1290515977.ps",horizontal=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 = 160
Frequency = 1
1 2 3 4 5 6
3.6003200 -9.0728974 -6.2072431 -8.1908987 -6.4759345 -4.1385517
7 8 9 10 11 12
-13.0479397 -11.2800762 -2.9385517 -0.5453462 -10.9969729 2.7927569
13 14 15 16 17 18
-3.8789716 19.4204761 14.9271026 -7.9385517 -5.9385517 12.2523370
19 20 21 22 23 24
-4.9385517 -8.3077954 2.9271026 11.5396363 -13.4872550 -9.7446259
25 26 27 28 29 30
12.0836456 -0.4534072 -7.1415888 23.3897198 -9.0343557 -5.2072431
31 32 33 34 35 36
62.6163344 -7.7385517 7.9866827 -8.0102802 -6.1476630 -6.4759345
37 38 39 40 41 42
-6.9385517 4.9393053 78.8398576 8.5916523 -4.5795239 -12.2093979
43 44 45 46 47 48
-7.6102802 22.1945767 -2.7820087 -9.3415888 -6.1133173 -12.0398233
49 50 51 52 53 54
17.5396363 -8.9385517 -2.2820087 3.7343357 -6.2820087 -10.8482153
55 56 57 58 59 60
-5.6831133 -5.6133173 7.7506801 -16.1597571 -9.3415888 -10.9537372
61 62 63 64 65 66
-10.9681491 -9.6102802 -11.6831133 -14.1589835 -2.2072431 -7.1609160
67 68 69 70 71 72
2.7662509 -1.1476630 5.4197025 3.6432257 -4.9903464 -1.1130417
73 74 75 76 77 78
-8.9385517 20.3745343 -6.4911200 -11.6254657 -9.0728974 -5.9385517
79 80 81 82 83 84
-1.5962567 1.4648707 33.0614483 3.2459861 9.0349423 3.5146775
85 86 87 88 89 90
20.6439993 -15.7376694 -5.5343557 -5.2446259 -9.0728974 10.3149542
91 92 93 94 95 96
-5.7415888 -8.4102802 -9.3415888 15.0614483 9.7240655 12.8897198
97 98 99 100 101 102
-8.9385517 -4.7184540 -2.9385517 14.1673555 -6.4385517 11.0614483
103 104 105 106 107 108
12.1840852 -8.0436884 -8.9385517 -5.7847702 8.1210284 -0.6102802
109 110 111 112 113 114
-8.7426934 -3.6115528 -9.0728974 9.9745886 -9.4759345 -8.9385517
115 116 117 118 119 120
-9.0728974 -8.9385517 1.0174390 -11.4051476 22.5240655 -4.8482153
121 122 123 124 125 126
-10.4163544 -11.0880829 -4.9385517 -1.0648364 14.1288138 -4.1385517
127 128 129 130 131 132
-7.6005623 -4.8102802 6.1066165 -9.8155265 -5.9642841 -11.8318709
133 134 135 136 137 138
0.1022525 -4.5415888 -9.4759345 -5.3620749 -9.8789716 -6.4102802
139 140 141 142 143 144
20.2897198 14.2265503 22.9650920 19.3149542 17.0614483 47.3855781
145 146 147 148 149 150
0.9897741 4.5240655 -18.5953744 21.0614483 5.4614483 0.9271026
151 152 153 154 155 156
-0.5476630 -11.3567743 10.6895528 -11.6254657 16.2374271 -8.9385517
157 158 159 160
-9.7426934 14.5240655 -5.7415888 -8.0880829
> postscript(file="/var/www/html/freestat/rcomp/tmp/609ic1290515977.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 160
Frequency = 1
lag(myerror, k = 1) myerror
0 3.6003200 NA
1 -9.0728974 3.6003200
2 -6.2072431 -9.0728974
3 -8.1908987 -6.2072431
4 -6.4759345 -8.1908987
5 -4.1385517 -6.4759345
6 -13.0479397 -4.1385517
7 -11.2800762 -13.0479397
8 -2.9385517 -11.2800762
9 -0.5453462 -2.9385517
10 -10.9969729 -0.5453462
11 2.7927569 -10.9969729
12 -3.8789716 2.7927569
13 19.4204761 -3.8789716
14 14.9271026 19.4204761
15 -7.9385517 14.9271026
16 -5.9385517 -7.9385517
17 12.2523370 -5.9385517
18 -4.9385517 12.2523370
19 -8.3077954 -4.9385517
20 2.9271026 -8.3077954
21 11.5396363 2.9271026
22 -13.4872550 11.5396363
23 -9.7446259 -13.4872550
24 12.0836456 -9.7446259
25 -0.4534072 12.0836456
26 -7.1415888 -0.4534072
27 23.3897198 -7.1415888
28 -9.0343557 23.3897198
29 -5.2072431 -9.0343557
30 62.6163344 -5.2072431
31 -7.7385517 62.6163344
32 7.9866827 -7.7385517
33 -8.0102802 7.9866827
34 -6.1476630 -8.0102802
35 -6.4759345 -6.1476630
36 -6.9385517 -6.4759345
37 4.9393053 -6.9385517
38 78.8398576 4.9393053
39 8.5916523 78.8398576
40 -4.5795239 8.5916523
41 -12.2093979 -4.5795239
42 -7.6102802 -12.2093979
43 22.1945767 -7.6102802
44 -2.7820087 22.1945767
45 -9.3415888 -2.7820087
46 -6.1133173 -9.3415888
47 -12.0398233 -6.1133173
48 17.5396363 -12.0398233
49 -8.9385517 17.5396363
50 -2.2820087 -8.9385517
51 3.7343357 -2.2820087
52 -6.2820087 3.7343357
53 -10.8482153 -6.2820087
54 -5.6831133 -10.8482153
55 -5.6133173 -5.6831133
56 7.7506801 -5.6133173
57 -16.1597571 7.7506801
58 -9.3415888 -16.1597571
59 -10.9537372 -9.3415888
60 -10.9681491 -10.9537372
61 -9.6102802 -10.9681491
62 -11.6831133 -9.6102802
63 -14.1589835 -11.6831133
64 -2.2072431 -14.1589835
65 -7.1609160 -2.2072431
66 2.7662509 -7.1609160
67 -1.1476630 2.7662509
68 5.4197025 -1.1476630
69 3.6432257 5.4197025
70 -4.9903464 3.6432257
71 -1.1130417 -4.9903464
72 -8.9385517 -1.1130417
73 20.3745343 -8.9385517
74 -6.4911200 20.3745343
75 -11.6254657 -6.4911200
76 -9.0728974 -11.6254657
77 -5.9385517 -9.0728974
78 -1.5962567 -5.9385517
79 1.4648707 -1.5962567
80 33.0614483 1.4648707
81 3.2459861 33.0614483
82 9.0349423 3.2459861
83 3.5146775 9.0349423
84 20.6439993 3.5146775
85 -15.7376694 20.6439993
86 -5.5343557 -15.7376694
87 -5.2446259 -5.5343557
88 -9.0728974 -5.2446259
89 10.3149542 -9.0728974
90 -5.7415888 10.3149542
91 -8.4102802 -5.7415888
92 -9.3415888 -8.4102802
93 15.0614483 -9.3415888
94 9.7240655 15.0614483
95 12.8897198 9.7240655
96 -8.9385517 12.8897198
97 -4.7184540 -8.9385517
98 -2.9385517 -4.7184540
99 14.1673555 -2.9385517
100 -6.4385517 14.1673555
101 11.0614483 -6.4385517
102 12.1840852 11.0614483
103 -8.0436884 12.1840852
104 -8.9385517 -8.0436884
105 -5.7847702 -8.9385517
106 8.1210284 -5.7847702
107 -0.6102802 8.1210284
108 -8.7426934 -0.6102802
109 -3.6115528 -8.7426934
110 -9.0728974 -3.6115528
111 9.9745886 -9.0728974
112 -9.4759345 9.9745886
113 -8.9385517 -9.4759345
114 -9.0728974 -8.9385517
115 -8.9385517 -9.0728974
116 1.0174390 -8.9385517
117 -11.4051476 1.0174390
118 22.5240655 -11.4051476
119 -4.8482153 22.5240655
120 -10.4163544 -4.8482153
121 -11.0880829 -10.4163544
122 -4.9385517 -11.0880829
123 -1.0648364 -4.9385517
124 14.1288138 -1.0648364
125 -4.1385517 14.1288138
126 -7.6005623 -4.1385517
127 -4.8102802 -7.6005623
128 6.1066165 -4.8102802
129 -9.8155265 6.1066165
130 -5.9642841 -9.8155265
131 -11.8318709 -5.9642841
132 0.1022525 -11.8318709
133 -4.5415888 0.1022525
134 -9.4759345 -4.5415888
135 -5.3620749 -9.4759345
136 -9.8789716 -5.3620749
137 -6.4102802 -9.8789716
138 20.2897198 -6.4102802
139 14.2265503 20.2897198
140 22.9650920 14.2265503
141 19.3149542 22.9650920
142 17.0614483 19.3149542
143 47.3855781 17.0614483
144 0.9897741 47.3855781
145 4.5240655 0.9897741
146 -18.5953744 4.5240655
147 21.0614483 -18.5953744
148 5.4614483 21.0614483
149 0.9271026 5.4614483
150 -0.5476630 0.9271026
151 -11.3567743 -0.5476630
152 10.6895528 -11.3567743
153 -11.6254657 10.6895528
154 16.2374271 -11.6254657
155 -8.9385517 16.2374271
156 -9.7426934 -8.9385517
157 14.5240655 -9.7426934
158 -5.7415888 14.5240655
159 -8.0880829 -5.7415888
160 NA -8.0880829
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -9.0728974 3.6003200
[2,] -6.2072431 -9.0728974
[3,] -8.1908987 -6.2072431
[4,] -6.4759345 -8.1908987
[5,] -4.1385517 -6.4759345
[6,] -13.0479397 -4.1385517
[7,] -11.2800762 -13.0479397
[8,] -2.9385517 -11.2800762
[9,] -0.5453462 -2.9385517
[10,] -10.9969729 -0.5453462
[11,] 2.7927569 -10.9969729
[12,] -3.8789716 2.7927569
[13,] 19.4204761 -3.8789716
[14,] 14.9271026 19.4204761
[15,] -7.9385517 14.9271026
[16,] -5.9385517 -7.9385517
[17,] 12.2523370 -5.9385517
[18,] -4.9385517 12.2523370
[19,] -8.3077954 -4.9385517
[20,] 2.9271026 -8.3077954
[21,] 11.5396363 2.9271026
[22,] -13.4872550 11.5396363
[23,] -9.7446259 -13.4872550
[24,] 12.0836456 -9.7446259
[25,] -0.4534072 12.0836456
[26,] -7.1415888 -0.4534072
[27,] 23.3897198 -7.1415888
[28,] -9.0343557 23.3897198
[29,] -5.2072431 -9.0343557
[30,] 62.6163344 -5.2072431
[31,] -7.7385517 62.6163344
[32,] 7.9866827 -7.7385517
[33,] -8.0102802 7.9866827
[34,] -6.1476630 -8.0102802
[35,] -6.4759345 -6.1476630
[36,] -6.9385517 -6.4759345
[37,] 4.9393053 -6.9385517
[38,] 78.8398576 4.9393053
[39,] 8.5916523 78.8398576
[40,] -4.5795239 8.5916523
[41,] -12.2093979 -4.5795239
[42,] -7.6102802 -12.2093979
[43,] 22.1945767 -7.6102802
[44,] -2.7820087 22.1945767
[45,] -9.3415888 -2.7820087
[46,] -6.1133173 -9.3415888
[47,] -12.0398233 -6.1133173
[48,] 17.5396363 -12.0398233
[49,] -8.9385517 17.5396363
[50,] -2.2820087 -8.9385517
[51,] 3.7343357 -2.2820087
[52,] -6.2820087 3.7343357
[53,] -10.8482153 -6.2820087
[54,] -5.6831133 -10.8482153
[55,] -5.6133173 -5.6831133
[56,] 7.7506801 -5.6133173
[57,] -16.1597571 7.7506801
[58,] -9.3415888 -16.1597571
[59,] -10.9537372 -9.3415888
[60,] -10.9681491 -10.9537372
[61,] -9.6102802 -10.9681491
[62,] -11.6831133 -9.6102802
[63,] -14.1589835 -11.6831133
[64,] -2.2072431 -14.1589835
[65,] -7.1609160 -2.2072431
[66,] 2.7662509 -7.1609160
[67,] -1.1476630 2.7662509
[68,] 5.4197025 -1.1476630
[69,] 3.6432257 5.4197025
[70,] -4.9903464 3.6432257
[71,] -1.1130417 -4.9903464
[72,] -8.9385517 -1.1130417
[73,] 20.3745343 -8.9385517
[74,] -6.4911200 20.3745343
[75,] -11.6254657 -6.4911200
[76,] -9.0728974 -11.6254657
[77,] -5.9385517 -9.0728974
[78,] -1.5962567 -5.9385517
[79,] 1.4648707 -1.5962567
[80,] 33.0614483 1.4648707
[81,] 3.2459861 33.0614483
[82,] 9.0349423 3.2459861
[83,] 3.5146775 9.0349423
[84,] 20.6439993 3.5146775
[85,] -15.7376694 20.6439993
[86,] -5.5343557 -15.7376694
[87,] -5.2446259 -5.5343557
[88,] -9.0728974 -5.2446259
[89,] 10.3149542 -9.0728974
[90,] -5.7415888 10.3149542
[91,] -8.4102802 -5.7415888
[92,] -9.3415888 -8.4102802
[93,] 15.0614483 -9.3415888
[94,] 9.7240655 15.0614483
[95,] 12.8897198 9.7240655
[96,] -8.9385517 12.8897198
[97,] -4.7184540 -8.9385517
[98,] -2.9385517 -4.7184540
[99,] 14.1673555 -2.9385517
[100,] -6.4385517 14.1673555
[101,] 11.0614483 -6.4385517
[102,] 12.1840852 11.0614483
[103,] -8.0436884 12.1840852
[104,] -8.9385517 -8.0436884
[105,] -5.7847702 -8.9385517
[106,] 8.1210284 -5.7847702
[107,] -0.6102802 8.1210284
[108,] -8.7426934 -0.6102802
[109,] -3.6115528 -8.7426934
[110,] -9.0728974 -3.6115528
[111,] 9.9745886 -9.0728974
[112,] -9.4759345 9.9745886
[113,] -8.9385517 -9.4759345
[114,] -9.0728974 -8.9385517
[115,] -8.9385517 -9.0728974
[116,] 1.0174390 -8.9385517
[117,] -11.4051476 1.0174390
[118,] 22.5240655 -11.4051476
[119,] -4.8482153 22.5240655
[120,] -10.4163544 -4.8482153
[121,] -11.0880829 -10.4163544
[122,] -4.9385517 -11.0880829
[123,] -1.0648364 -4.9385517
[124,] 14.1288138 -1.0648364
[125,] -4.1385517 14.1288138
[126,] -7.6005623 -4.1385517
[127,] -4.8102802 -7.6005623
[128,] 6.1066165 -4.8102802
[129,] -9.8155265 6.1066165
[130,] -5.9642841 -9.8155265
[131,] -11.8318709 -5.9642841
[132,] 0.1022525 -11.8318709
[133,] -4.5415888 0.1022525
[134,] -9.4759345 -4.5415888
[135,] -5.3620749 -9.4759345
[136,] -9.8789716 -5.3620749
[137,] -6.4102802 -9.8789716
[138,] 20.2897198 -6.4102802
[139,] 14.2265503 20.2897198
[140,] 22.9650920 14.2265503
[141,] 19.3149542 22.9650920
[142,] 17.0614483 19.3149542
[143,] 47.3855781 17.0614483
[144,] 0.9897741 47.3855781
[145,] 4.5240655 0.9897741
[146,] -18.5953744 4.5240655
[147,] 21.0614483 -18.5953744
[148,] 5.4614483 21.0614483
[149,] 0.9271026 5.4614483
[150,] -0.5476630 0.9271026
[151,] -11.3567743 -0.5476630
[152,] 10.6895528 -11.3567743
[153,] -11.6254657 10.6895528
[154,] 16.2374271 -11.6254657
[155,] -8.9385517 16.2374271
[156,] -9.7426934 -8.9385517
[157,] 14.5240655 -9.7426934
[158,] -5.7415888 14.5240655
[159,] -8.0880829 -5.7415888
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -9.0728974 3.6003200
2 -6.2072431 -9.0728974
3 -8.1908987 -6.2072431
4 -6.4759345 -8.1908987
5 -4.1385517 -6.4759345
6 -13.0479397 -4.1385517
7 -11.2800762 -13.0479397
8 -2.9385517 -11.2800762
9 -0.5453462 -2.9385517
10 -10.9969729 -0.5453462
11 2.7927569 -10.9969729
12 -3.8789716 2.7927569
13 19.4204761 -3.8789716
14 14.9271026 19.4204761
15 -7.9385517 14.9271026
16 -5.9385517 -7.9385517
17 12.2523370 -5.9385517
18 -4.9385517 12.2523370
19 -8.3077954 -4.9385517
20 2.9271026 -8.3077954
21 11.5396363 2.9271026
22 -13.4872550 11.5396363
23 -9.7446259 -13.4872550
24 12.0836456 -9.7446259
25 -0.4534072 12.0836456
26 -7.1415888 -0.4534072
27 23.3897198 -7.1415888
28 -9.0343557 23.3897198
29 -5.2072431 -9.0343557
30 62.6163344 -5.2072431
31 -7.7385517 62.6163344
32 7.9866827 -7.7385517
33 -8.0102802 7.9866827
34 -6.1476630 -8.0102802
35 -6.4759345 -6.1476630
36 -6.9385517 -6.4759345
37 4.9393053 -6.9385517
38 78.8398576 4.9393053
39 8.5916523 78.8398576
40 -4.5795239 8.5916523
41 -12.2093979 -4.5795239
42 -7.6102802 -12.2093979
43 22.1945767 -7.6102802
44 -2.7820087 22.1945767
45 -9.3415888 -2.7820087
46 -6.1133173 -9.3415888
47 -12.0398233 -6.1133173
48 17.5396363 -12.0398233
49 -8.9385517 17.5396363
50 -2.2820087 -8.9385517
51 3.7343357 -2.2820087
52 -6.2820087 3.7343357
53 -10.8482153 -6.2820087
54 -5.6831133 -10.8482153
55 -5.6133173 -5.6831133
56 7.7506801 -5.6133173
57 -16.1597571 7.7506801
58 -9.3415888 -16.1597571
59 -10.9537372 -9.3415888
60 -10.9681491 -10.9537372
61 -9.6102802 -10.9681491
62 -11.6831133 -9.6102802
63 -14.1589835 -11.6831133
64 -2.2072431 -14.1589835
65 -7.1609160 -2.2072431
66 2.7662509 -7.1609160
67 -1.1476630 2.7662509
68 5.4197025 -1.1476630
69 3.6432257 5.4197025
70 -4.9903464 3.6432257
71 -1.1130417 -4.9903464
72 -8.9385517 -1.1130417
73 20.3745343 -8.9385517
74 -6.4911200 20.3745343
75 -11.6254657 -6.4911200
76 -9.0728974 -11.6254657
77 -5.9385517 -9.0728974
78 -1.5962567 -5.9385517
79 1.4648707 -1.5962567
80 33.0614483 1.4648707
81 3.2459861 33.0614483
82 9.0349423 3.2459861
83 3.5146775 9.0349423
84 20.6439993 3.5146775
85 -15.7376694 20.6439993
86 -5.5343557 -15.7376694
87 -5.2446259 -5.5343557
88 -9.0728974 -5.2446259
89 10.3149542 -9.0728974
90 -5.7415888 10.3149542
91 -8.4102802 -5.7415888
92 -9.3415888 -8.4102802
93 15.0614483 -9.3415888
94 9.7240655 15.0614483
95 12.8897198 9.7240655
96 -8.9385517 12.8897198
97 -4.7184540 -8.9385517
98 -2.9385517 -4.7184540
99 14.1673555 -2.9385517
100 -6.4385517 14.1673555
101 11.0614483 -6.4385517
102 12.1840852 11.0614483
103 -8.0436884 12.1840852
104 -8.9385517 -8.0436884
105 -5.7847702 -8.9385517
106 8.1210284 -5.7847702
107 -0.6102802 8.1210284
108 -8.7426934 -0.6102802
109 -3.6115528 -8.7426934
110 -9.0728974 -3.6115528
111 9.9745886 -9.0728974
112 -9.4759345 9.9745886
113 -8.9385517 -9.4759345
114 -9.0728974 -8.9385517
115 -8.9385517 -9.0728974
116 1.0174390 -8.9385517
117 -11.4051476 1.0174390
118 22.5240655 -11.4051476
119 -4.8482153 22.5240655
120 -10.4163544 -4.8482153
121 -11.0880829 -10.4163544
122 -4.9385517 -11.0880829
123 -1.0648364 -4.9385517
124 14.1288138 -1.0648364
125 -4.1385517 14.1288138
126 -7.6005623 -4.1385517
127 -4.8102802 -7.6005623
128 6.1066165 -4.8102802
129 -9.8155265 6.1066165
130 -5.9642841 -9.8155265
131 -11.8318709 -5.9642841
132 0.1022525 -11.8318709
133 -4.5415888 0.1022525
134 -9.4759345 -4.5415888
135 -5.3620749 -9.4759345
136 -9.8789716 -5.3620749
137 -6.4102802 -9.8789716
138 20.2897198 -6.4102802
139 14.2265503 20.2897198
140 22.9650920 14.2265503
141 19.3149542 22.9650920
142 17.0614483 19.3149542
143 47.3855781 17.0614483
144 0.9897741 47.3855781
145 4.5240655 0.9897741
146 -18.5953744 4.5240655
147 21.0614483 -18.5953744
148 5.4614483 21.0614483
149 0.9271026 5.4614483
150 -0.5476630 0.9271026
151 -11.3567743 -0.5476630
152 10.6895528 -11.3567743
153 -11.6254657 10.6895528
154 16.2374271 -11.6254657
155 -8.9385517 16.2374271
156 -9.7426934 -8.9385517
157 14.5240655 -9.7426934
158 -5.7415888 14.5240655
159 -8.0880829 -5.7415888
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/7bizf1290515977.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8bizf1290515977.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9bizf1290515977.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/108d6o1290515977.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/11pafo1290515977.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/12stdu1290515977.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/13o2t21290515977.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/freestat/rcomp/tmp/14slaq1290515977.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/15dlqe1290515977.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/freestat/rcomp/tmp/16g47k1290515977.tab")
+ }
>
> try(system("convert tmp/1xr161290515977.ps tmp/1xr161290515977.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xr161290515977.ps tmp/2xr161290515977.png",intern=TRUE))
character(0)
> try(system("convert tmp/3701r1290515977.ps tmp/3701r1290515977.png",intern=TRUE))
character(0)
> try(system("convert tmp/4701r1290515977.ps tmp/4701r1290515977.png",intern=TRUE))
character(0)
> try(system("convert tmp/5701r1290515977.ps tmp/5701r1290515977.png",intern=TRUE))
character(0)
> try(system("convert tmp/609ic1290515977.ps tmp/609ic1290515977.png",intern=TRUE))
character(0)
> try(system("convert tmp/7bizf1290515977.ps tmp/7bizf1290515977.png",intern=TRUE))
character(0)
> try(system("convert tmp/8bizf1290515977.ps tmp/8bizf1290515977.png",intern=TRUE))
character(0)
> try(system("convert tmp/9bizf1290515977.ps tmp/9bizf1290515977.png",intern=TRUE))
character(0)
> try(system("convert tmp/108d6o1290515977.ps tmp/108d6o1290515977.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.530 2.705 9.858