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.
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Type 'license()' or 'licence()' for distribution details.
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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.
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> x <- array(list(8,5560,8.1,3922,7.7,3759,7.5,4138,7.6,4634,7.8,3996,7.8,4308,7.8,4143,7.5,4429,7.5,5219,7.1,4929,7.5,5755,7.5,5592,7.6,4163,7.7,4962,7.7,5208,7.9,4755,8.1,4491,8.2,5732,8.2,5731,8.2,5040,7.9,6102,7.3,4904,6.9,5369,6.7,5578,6.7,4619,6.9,4731,7,5011,7.1,5299,7.2,4146,7.1,4625,6.9,4736,7,4219,6.8,5116,6.4,4205,6.7,4121,6.6,5103,6.4,4300,6.3,4578,6.2,3809,6.5,5526,6.8,4247,6.8,3830,6.4,4394,6.1,4826,5.8,4409,6.1,4569,7.2,4106,7.3,4794,6.9,3914,6.1,3793,5.8,4405,6.2,4022,7.1,4100,7.7,4788,7.9,3163,7.7,3585,7.4,3903,7.5,4178,8,3863,8.1,4187),dim=c(2,61),dimnames=list(c('Y','X'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Y','X'),1:61))
> 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
Y X
1 8.0 5560
2 8.1 3922
3 7.7 3759
4 7.5 4138
5 7.6 4634
6 7.8 3996
7 7.8 4308
8 7.8 4143
9 7.5 4429
10 7.5 5219
11 7.1 4929
12 7.5 5755
13 7.5 5592
14 7.6 4163
15 7.7 4962
16 7.7 5208
17 7.9 4755
18 8.1 4491
19 8.2 5732
20 8.2 5731
21 8.2 5040
22 7.9 6102
23 7.3 4904
24 6.9 5369
25 6.7 5578
26 6.7 4619
27 6.9 4731
28 7.0 5011
29 7.1 5299
30 7.2 4146
31 7.1 4625
32 6.9 4736
33 7.0 4219
34 6.8 5116
35 6.4 4205
36 6.7 4121
37 6.6 5103
38 6.4 4300
39 6.3 4578
40 6.2 3809
41 6.5 5526
42 6.8 4247
43 6.8 3830
44 6.4 4394
45 6.1 4826
46 5.8 4409
47 6.1 4569
48 7.2 4106
49 7.3 4794
50 6.9 3914
51 6.1 3793
52 5.8 4405
53 6.2 4022
54 7.1 4100
55 7.7 4788
56 7.9 3163
57 7.7 3585
58 7.4 3903
59 7.5 4178
60 8.0 3863
61 8.1 4187
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
6.5720606 0.0001345
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.36496 -0.46003 0.07041 0.50738 1.00053
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.5720606 0.6239929 10.532 3.56e-15 ***
X 0.0001345 0.0001349 0.997 0.323
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.6616 on 59 degrees of freedom
Multiple R-squared: 0.01657, Adjusted R-squared: -9.434e-05
F-statistic: 0.9943 on 1 and 59 DF, p-value: 0.3228
> 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,] 9.929856e-02 1.985971e-01 0.90070144
[2,] 3.657416e-02 7.314833e-02 0.96342584
[3,] 1.228895e-02 2.457790e-02 0.98771105
[4,] 3.937798e-03 7.875596e-03 0.99606220
[5,] 2.628571e-03 5.257142e-03 0.99737143
[6,] 1.516607e-03 3.033215e-03 0.99848339
[7,] 4.695256e-03 9.390511e-03 0.99530474
[8,] 1.803247e-03 3.606493e-03 0.99819675
[9,] 6.630540e-04 1.326108e-03 0.99933695
[10,] 2.691591e-04 5.383181e-04 0.99973084
[11,] 1.048250e-04 2.096501e-04 0.99989517
[12,] 4.082927e-05 8.165854e-05 0.99995917
[13,] 2.738935e-05 5.477869e-05 0.99997261
[14,] 4.787958e-05 9.575915e-05 0.99995212
[15,] 1.869124e-04 3.738248e-04 0.99981309
[16,] 4.070785e-04 8.141570e-04 0.99959292
[17,] 9.045483e-04 1.809097e-03 0.99909545
[18,] 9.749429e-04 1.949886e-03 0.99902506
[19,] 1.269826e-03 2.539652e-03 0.99873017
[20,] 5.841397e-03 1.168279e-02 0.99415860
[21,] 2.257171e-02 4.514342e-02 0.97742829
[22,] 5.002027e-02 1.000405e-01 0.94997973
[23,] 5.894444e-02 1.178889e-01 0.94105556
[24,] 5.914122e-02 1.182824e-01 0.94085878
[25,] 5.753206e-02 1.150641e-01 0.94246794
[26,] 4.634683e-02 9.269367e-02 0.95365317
[27,] 4.039402e-02 8.078805e-02 0.95960598
[28,] 3.982348e-02 7.964697e-02 0.96017652
[29,] 3.324372e-02 6.648744e-02 0.96675628
[30,] 3.538368e-02 7.076737e-02 0.96461632
[31,] 5.776423e-02 1.155285e-01 0.94223577
[32,] 5.386484e-02 1.077297e-01 0.94613516
[33,] 5.682544e-02 1.136509e-01 0.94317456
[34,] 6.773194e-02 1.354639e-01 0.93226806
[35,] 8.305368e-02 1.661074e-01 0.91694632
[36,] 1.240148e-01 2.480296e-01 0.87598518
[37,] 1.278922e-01 2.557844e-01 0.87210781
[38,] 9.629102e-02 1.925820e-01 0.90370898
[39,] 7.377746e-02 1.475549e-01 0.92622254
[40,] 6.822836e-02 1.364567e-01 0.93177164
[41,] 8.045244e-02 1.609049e-01 0.91954756
[42,] 1.673193e-01 3.346386e-01 0.83268071
[43,] 2.184281e-01 4.368562e-01 0.78157189
[44,] 1.573750e-01 3.147500e-01 0.84262500
[45,] 1.139875e-01 2.279749e-01 0.88601254
[46,] 7.949786e-02 1.589957e-01 0.92050214
[47,] 1.653518e-01 3.307036e-01 0.83464819
[48,] 5.027421e-01 9.945158e-01 0.49725791
[49,] 9.346804e-01 1.306393e-01 0.06531963
[50,] 9.654158e-01 6.916837e-02 0.03458418
[51,] 9.158294e-01 1.683413e-01 0.08417065
[52,] 8.350924e-01 3.298152e-01 0.16490761
> postscript(file="/var/www/html/rcomp/tmp/1u91a1258728493.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/29fn21258728493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3c6fq1258728493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4hfs11258728493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ukt91258728493.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 = 61
Frequency = 1
1 2 3 4 5 6
0.68026141 1.00053057 0.62244990 0.37148409 0.40478475 0.69057946
7 8 9 10 11 12
0.64862343 0.67081171 0.33235202 0.22611720 -0.13488521 0.15403889
13 14 15 16 17 18
0.17595822 0.46812222 0.46067713 0.42759642 0.68851335 0.92401460
19 20 21 22 23 24
0.85713180 0.85726627 0.95018812 0.50737625 0.06847665 -0.39405397
25 26 27 28 29 30
-0.62215913 -0.49319813 -0.30825927 -0.24591212 -0.18464076 0.07040829
31 32 33 34 35 36
-0.09400498 -0.30893164 -0.13940835 -0.46003193 -0.73752570 -0.42622985
37 38 39 40 41 42
-0.65828377 -0.75030078 -0.88768468 -0.88427382 -0.81516646 -0.34317363
43 44 45 46 47 48
-0.28709778 -0.76294138 -1.12103434 -1.36495849 -1.08647441 0.07578727
49 50 51 52 53 54
0.08326884 -0.19839364 -0.98212223 -1.36442059 -0.91291688 -0.02340589
55 56 57 58 59 60
0.48407569 0.90259668 0.64584846 0.30308558 0.36610511 0.90846456
61
0.96489484
> postscript(file="/var/www/html/rcomp/tmp/6pth71258728493.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 0.68026141 NA
1 1.00053057 0.68026141
2 0.62244990 1.00053057
3 0.37148409 0.62244990
4 0.40478475 0.37148409
5 0.69057946 0.40478475
6 0.64862343 0.69057946
7 0.67081171 0.64862343
8 0.33235202 0.67081171
9 0.22611720 0.33235202
10 -0.13488521 0.22611720
11 0.15403889 -0.13488521
12 0.17595822 0.15403889
13 0.46812222 0.17595822
14 0.46067713 0.46812222
15 0.42759642 0.46067713
16 0.68851335 0.42759642
17 0.92401460 0.68851335
18 0.85713180 0.92401460
19 0.85726627 0.85713180
20 0.95018812 0.85726627
21 0.50737625 0.95018812
22 0.06847665 0.50737625
23 -0.39405397 0.06847665
24 -0.62215913 -0.39405397
25 -0.49319813 -0.62215913
26 -0.30825927 -0.49319813
27 -0.24591212 -0.30825927
28 -0.18464076 -0.24591212
29 0.07040829 -0.18464076
30 -0.09400498 0.07040829
31 -0.30893164 -0.09400498
32 -0.13940835 -0.30893164
33 -0.46003193 -0.13940835
34 -0.73752570 -0.46003193
35 -0.42622985 -0.73752570
36 -0.65828377 -0.42622985
37 -0.75030078 -0.65828377
38 -0.88768468 -0.75030078
39 -0.88427382 -0.88768468
40 -0.81516646 -0.88427382
41 -0.34317363 -0.81516646
42 -0.28709778 -0.34317363
43 -0.76294138 -0.28709778
44 -1.12103434 -0.76294138
45 -1.36495849 -1.12103434
46 -1.08647441 -1.36495849
47 0.07578727 -1.08647441
48 0.08326884 0.07578727
49 -0.19839364 0.08326884
50 -0.98212223 -0.19839364
51 -1.36442059 -0.98212223
52 -0.91291688 -1.36442059
53 -0.02340589 -0.91291688
54 0.48407569 -0.02340589
55 0.90259668 0.48407569
56 0.64584846 0.90259668
57 0.30308558 0.64584846
58 0.36610511 0.30308558
59 0.90846456 0.36610511
60 0.96489484 0.90846456
61 NA 0.96489484
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.00053057 0.68026141
[2,] 0.62244990 1.00053057
[3,] 0.37148409 0.62244990
[4,] 0.40478475 0.37148409
[5,] 0.69057946 0.40478475
[6,] 0.64862343 0.69057946
[7,] 0.67081171 0.64862343
[8,] 0.33235202 0.67081171
[9,] 0.22611720 0.33235202
[10,] -0.13488521 0.22611720
[11,] 0.15403889 -0.13488521
[12,] 0.17595822 0.15403889
[13,] 0.46812222 0.17595822
[14,] 0.46067713 0.46812222
[15,] 0.42759642 0.46067713
[16,] 0.68851335 0.42759642
[17,] 0.92401460 0.68851335
[18,] 0.85713180 0.92401460
[19,] 0.85726627 0.85713180
[20,] 0.95018812 0.85726627
[21,] 0.50737625 0.95018812
[22,] 0.06847665 0.50737625
[23,] -0.39405397 0.06847665
[24,] -0.62215913 -0.39405397
[25,] -0.49319813 -0.62215913
[26,] -0.30825927 -0.49319813
[27,] -0.24591212 -0.30825927
[28,] -0.18464076 -0.24591212
[29,] 0.07040829 -0.18464076
[30,] -0.09400498 0.07040829
[31,] -0.30893164 -0.09400498
[32,] -0.13940835 -0.30893164
[33,] -0.46003193 -0.13940835
[34,] -0.73752570 -0.46003193
[35,] -0.42622985 -0.73752570
[36,] -0.65828377 -0.42622985
[37,] -0.75030078 -0.65828377
[38,] -0.88768468 -0.75030078
[39,] -0.88427382 -0.88768468
[40,] -0.81516646 -0.88427382
[41,] -0.34317363 -0.81516646
[42,] -0.28709778 -0.34317363
[43,] -0.76294138 -0.28709778
[44,] -1.12103434 -0.76294138
[45,] -1.36495849 -1.12103434
[46,] -1.08647441 -1.36495849
[47,] 0.07578727 -1.08647441
[48,] 0.08326884 0.07578727
[49,] -0.19839364 0.08326884
[50,] -0.98212223 -0.19839364
[51,] -1.36442059 -0.98212223
[52,] -0.91291688 -1.36442059
[53,] -0.02340589 -0.91291688
[54,] 0.48407569 -0.02340589
[55,] 0.90259668 0.48407569
[56,] 0.64584846 0.90259668
[57,] 0.30308558 0.64584846
[58,] 0.36610511 0.30308558
[59,] 0.90846456 0.36610511
[60,] 0.96489484 0.90846456
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.00053057 0.68026141
2 0.62244990 1.00053057
3 0.37148409 0.62244990
4 0.40478475 0.37148409
5 0.69057946 0.40478475
6 0.64862343 0.69057946
7 0.67081171 0.64862343
8 0.33235202 0.67081171
9 0.22611720 0.33235202
10 -0.13488521 0.22611720
11 0.15403889 -0.13488521
12 0.17595822 0.15403889
13 0.46812222 0.17595822
14 0.46067713 0.46812222
15 0.42759642 0.46067713
16 0.68851335 0.42759642
17 0.92401460 0.68851335
18 0.85713180 0.92401460
19 0.85726627 0.85713180
20 0.95018812 0.85726627
21 0.50737625 0.95018812
22 0.06847665 0.50737625
23 -0.39405397 0.06847665
24 -0.62215913 -0.39405397
25 -0.49319813 -0.62215913
26 -0.30825927 -0.49319813
27 -0.24591212 -0.30825927
28 -0.18464076 -0.24591212
29 0.07040829 -0.18464076
30 -0.09400498 0.07040829
31 -0.30893164 -0.09400498
32 -0.13940835 -0.30893164
33 -0.46003193 -0.13940835
34 -0.73752570 -0.46003193
35 -0.42622985 -0.73752570
36 -0.65828377 -0.42622985
37 -0.75030078 -0.65828377
38 -0.88768468 -0.75030078
39 -0.88427382 -0.88768468
40 -0.81516646 -0.88427382
41 -0.34317363 -0.81516646
42 -0.28709778 -0.34317363
43 -0.76294138 -0.28709778
44 -1.12103434 -0.76294138
45 -1.36495849 -1.12103434
46 -1.08647441 -1.36495849
47 0.07578727 -1.08647441
48 0.08326884 0.07578727
49 -0.19839364 0.08326884
50 -0.98212223 -0.19839364
51 -1.36442059 -0.98212223
52 -0.91291688 -1.36442059
53 -0.02340589 -0.91291688
54 0.48407569 -0.02340589
55 0.90259668 0.48407569
56 0.64584846 0.90259668
57 0.30308558 0.64584846
58 0.36610511 0.30308558
59 0.90846456 0.36610511
60 0.96489484 0.90846456
> 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/7jq5l1258728493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8fpec1258728493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9cs0b1258728493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10xkpz1258728493.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11vyn81258728493.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/12y1bf1258728493.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/13pet61258728493.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/14hlhm1258728493.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/15sfys1258728493.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/16zce41258728493.tab")
+ }
>
> system("convert tmp/1u91a1258728493.ps tmp/1u91a1258728493.png")
> system("convert tmp/29fn21258728493.ps tmp/29fn21258728493.png")
> system("convert tmp/3c6fq1258728493.ps tmp/3c6fq1258728493.png")
> system("convert tmp/4hfs11258728493.ps tmp/4hfs11258728493.png")
> system("convert tmp/5ukt91258728493.ps tmp/5ukt91258728493.png")
> system("convert tmp/6pth71258728493.ps tmp/6pth71258728493.png")
> system("convert tmp/7jq5l1258728493.ps tmp/7jq5l1258728493.png")
> system("convert tmp/8fpec1258728493.ps tmp/8fpec1258728493.png")
> system("convert tmp/9cs0b1258728493.ps tmp/9cs0b1258728493.png")
> system("convert tmp/10xkpz1258728493.ps tmp/10xkpz1258728493.png")
>
>
> proc.time()
user system elapsed
2.522 1.565 5.316