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.
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(19,613,18,611,19,594,19,595,22,591,23,589,20,584,14,573,14,567,14,569,15,621,11,629,17,628,16,612,20,595,24,597,23,593,20,590,21,580,19,574,23,573,23,573,23,620,23,626,27,620,26,588,17,566,24,557,26,561,24,549,27,532,27,526,26,511,24,499,23,555,23,565,24,542,17,527,21,510,19,514,22,517,22,508,18,493,16,490,14,469,12,478,14,528,16,534,8,518,3,506,0,502,5,516,1,528,1,533,3,536,6,537,7,524,8,536,14,587,14,597,13,581),dim=c(2,61),dimnames=list(c('ICONS','WLH'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('ICONS','WLH'),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
ICONS WLH
1 19 613
2 18 611
3 19 594
4 19 595
5 22 591
6 23 589
7 20 584
8 14 573
9 14 567
10 14 569
11 15 621
12 11 629
13 17 628
14 16 612
15 20 595
16 24 597
17 23 593
18 20 590
19 21 580
20 19 574
21 23 573
22 23 573
23 23 620
24 23 626
25 27 620
26 26 588
27 17 566
28 24 557
29 26 561
30 24 549
31 27 532
32 27 526
33 26 511
34 24 499
35 23 555
36 23 565
37 24 542
38 17 527
39 21 510
40 19 514
41 22 517
42 22 508
43 18 493
44 16 490
45 14 469
46 12 478
47 14 528
48 16 534
49 8 518
50 3 506
51 0 502
52 5 516
53 1 528
54 1 533
55 3 536
56 6 537
57 7 524
58 8 536
59 14 587
60 14 597
61 13 581
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) WLH
-11.12504 0.05085
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-14.976 -4.009 1.126 4.991 11.380
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -11.12504 11.87874 -0.937 0.3528
WLH 0.05085 0.02123 2.395 0.0198 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.915 on 59 degrees of freedom
Multiple R-squared: 0.08861, Adjusted R-squared: 0.07316
F-statistic: 5.736 on 1 and 59 DF, p-value: 0.01981
> 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,] 9.079926e-03 0.0181598528 0.9909200736
[2,] 4.107559e-03 0.0082151175 0.9958924412
[3,] 1.325324e-03 0.0026506476 0.9986746762
[4,] 1.214301e-02 0.0242860217 0.9878569891
[5,] 7.411442e-03 0.0148228832 0.9925885584
[6,] 3.477136e-03 0.0069542715 0.9965228642
[7,] 5.611325e-03 0.0112226506 0.9943886747
[8,] 1.478427e-02 0.0295685356 0.9852157322
[9,] 7.249668e-03 0.0144993360 0.9927503320
[10,] 3.577289e-03 0.0071545789 0.9964227106
[11,] 1.942521e-03 0.0038850424 0.9980574788
[12,] 2.897149e-03 0.0057942979 0.9971028511
[13,] 2.536084e-03 0.0050721681 0.9974639160
[14,] 1.246487e-03 0.0024929747 0.9987535127
[15,] 6.363921e-04 0.0012727842 0.9993636079
[16,] 2.732484e-04 0.0005464968 0.9997267516
[17,] 1.802116e-04 0.0003604233 0.9998197884
[18,] 1.093033e-04 0.0002186066 0.9998906967
[19,] 1.011366e-04 0.0002022731 0.9998988634
[20,] 7.873001e-05 0.0001574600 0.9999212700
[21,] 1.752373e-04 0.0003504746 0.9998247627
[22,] 2.337470e-04 0.0004674941 0.9997662530
[23,] 1.230022e-04 0.0002460043 0.9998769978
[24,] 9.979478e-05 0.0001995896 0.9999002052
[25,] 1.282621e-04 0.0002565242 0.9998717379
[26,] 9.613571e-05 0.0001922714 0.9999038643
[27,] 1.342556e-04 0.0002685111 0.9998657444
[28,] 1.820464e-04 0.0003640927 0.9998179536
[29,] 2.147491e-04 0.0004294983 0.9997852509
[30,] 2.442099e-04 0.0004884198 0.9997557901
[31,] 2.271747e-04 0.0004543493 0.9997728253
[32,] 2.564715e-04 0.0005129430 0.9997435285
[33,] 4.391660e-04 0.0008783319 0.9995608340
[34,] 6.482154e-04 0.0012964307 0.9993517846
[35,] 9.015784e-04 0.0018031569 0.9990984216
[36,] 1.219420e-03 0.0024388394 0.9987805803
[37,] 2.729393e-03 0.0054587865 0.9972706068
[38,] 9.026823e-03 0.0180536455 0.9909731772
[39,] 2.227947e-02 0.0445589329 0.9777205336
[40,] 5.349221e-02 0.1069844261 0.9465077869
[41,] 1.612851e-01 0.3225701294 0.8387149353
[42,] 4.374501e-01 0.8749001399 0.5625499300
[43,] 6.391208e-01 0.7217583304 0.3608791652
[44,] 9.438700e-01 0.1122600368 0.0561300184
[45,] 9.789751e-01 0.0420497638 0.0210248819
[46,] 9.841178e-01 0.0317644339 0.0158822169
[47,] 9.836394e-01 0.0327211215 0.0163605607
[48,] 9.816427e-01 0.0367145432 0.0183572716
[49,] 9.819989e-01 0.0360022820 0.0180011410
[50,] 9.928416e-01 0.0143167858 0.0071583929
[51,] 9.988801e-01 0.0022398318 0.0011199159
[52,] 9.996258e-01 0.0007484942 0.0003742471
> postscript(file="/var/www/html/rcomp/tmp/16p1y1258650213.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2kqih1258650213.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/31h5f1258650213.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/45lrj1258650213.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/59jwu1258650213.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
-1.04323601 -1.94154507 -0.07717208 -0.12801755 3.07536433 4.17705526
7 8 9 10 11 12
1.43128261 -4.00941722 -3.70434440 -3.80603534 -5.44999977 -9.85676353
13 14 15 16 17 18
-3.80591806 -3.99239054 0.87198245 4.77029151 3.97367339 1.12620980
19 20 21 22 23 24
2.63466449 0.93973731 4.99058278 4.99058278 2.60084570 2.29577288
25 26 27 28 29 30
6.60084570 7.22790073 -0.65349893 6.80411030 8.60072842 7.21087406
31 32 33 34 35 36
11.07524704 11.38031986 11.14300191 9.75314755 5.90580124 5.39734654
37 38 39 40 41 42
7.56679234 1.32947439 6.19384738 3.99046550 6.83792909 7.29553832
43 44 45 46 47 48
4.05822036 2.21075677 1.27851164 -1.17909759 -1.72137108 -0.02644390
49 50 51 52 53 54
-7.21291638 -11.60277074 -14.39938886 -10.11122544 -14.72137108 -14.97559843
55 56 57 58 59 60
-13.12813484 -10.17898031 -8.51798920 -8.12813484 -4.72125380 -5.22970849
61
-5.41618098
> postscript(file="/var/www/html/rcomp/tmp/6gc0h1258650213.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 -1.04323601 NA
1 -1.94154507 -1.04323601
2 -0.07717208 -1.94154507
3 -0.12801755 -0.07717208
4 3.07536433 -0.12801755
5 4.17705526 3.07536433
6 1.43128261 4.17705526
7 -4.00941722 1.43128261
8 -3.70434440 -4.00941722
9 -3.80603534 -3.70434440
10 -5.44999977 -3.80603534
11 -9.85676353 -5.44999977
12 -3.80591806 -9.85676353
13 -3.99239054 -3.80591806
14 0.87198245 -3.99239054
15 4.77029151 0.87198245
16 3.97367339 4.77029151
17 1.12620980 3.97367339
18 2.63466449 1.12620980
19 0.93973731 2.63466449
20 4.99058278 0.93973731
21 4.99058278 4.99058278
22 2.60084570 4.99058278
23 2.29577288 2.60084570
24 6.60084570 2.29577288
25 7.22790073 6.60084570
26 -0.65349893 7.22790073
27 6.80411030 -0.65349893
28 8.60072842 6.80411030
29 7.21087406 8.60072842
30 11.07524704 7.21087406
31 11.38031986 11.07524704
32 11.14300191 11.38031986
33 9.75314755 11.14300191
34 5.90580124 9.75314755
35 5.39734654 5.90580124
36 7.56679234 5.39734654
37 1.32947439 7.56679234
38 6.19384738 1.32947439
39 3.99046550 6.19384738
40 6.83792909 3.99046550
41 7.29553832 6.83792909
42 4.05822036 7.29553832
43 2.21075677 4.05822036
44 1.27851164 2.21075677
45 -1.17909759 1.27851164
46 -1.72137108 -1.17909759
47 -0.02644390 -1.72137108
48 -7.21291638 -0.02644390
49 -11.60277074 -7.21291638
50 -14.39938886 -11.60277074
51 -10.11122544 -14.39938886
52 -14.72137108 -10.11122544
53 -14.97559843 -14.72137108
54 -13.12813484 -14.97559843
55 -10.17898031 -13.12813484
56 -8.51798920 -10.17898031
57 -8.12813484 -8.51798920
58 -4.72125380 -8.12813484
59 -5.22970849 -4.72125380
60 -5.41618098 -5.22970849
61 NA -5.41618098
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.94154507 -1.04323601
[2,] -0.07717208 -1.94154507
[3,] -0.12801755 -0.07717208
[4,] 3.07536433 -0.12801755
[5,] 4.17705526 3.07536433
[6,] 1.43128261 4.17705526
[7,] -4.00941722 1.43128261
[8,] -3.70434440 -4.00941722
[9,] -3.80603534 -3.70434440
[10,] -5.44999977 -3.80603534
[11,] -9.85676353 -5.44999977
[12,] -3.80591806 -9.85676353
[13,] -3.99239054 -3.80591806
[14,] 0.87198245 -3.99239054
[15,] 4.77029151 0.87198245
[16,] 3.97367339 4.77029151
[17,] 1.12620980 3.97367339
[18,] 2.63466449 1.12620980
[19,] 0.93973731 2.63466449
[20,] 4.99058278 0.93973731
[21,] 4.99058278 4.99058278
[22,] 2.60084570 4.99058278
[23,] 2.29577288 2.60084570
[24,] 6.60084570 2.29577288
[25,] 7.22790073 6.60084570
[26,] -0.65349893 7.22790073
[27,] 6.80411030 -0.65349893
[28,] 8.60072842 6.80411030
[29,] 7.21087406 8.60072842
[30,] 11.07524704 7.21087406
[31,] 11.38031986 11.07524704
[32,] 11.14300191 11.38031986
[33,] 9.75314755 11.14300191
[34,] 5.90580124 9.75314755
[35,] 5.39734654 5.90580124
[36,] 7.56679234 5.39734654
[37,] 1.32947439 7.56679234
[38,] 6.19384738 1.32947439
[39,] 3.99046550 6.19384738
[40,] 6.83792909 3.99046550
[41,] 7.29553832 6.83792909
[42,] 4.05822036 7.29553832
[43,] 2.21075677 4.05822036
[44,] 1.27851164 2.21075677
[45,] -1.17909759 1.27851164
[46,] -1.72137108 -1.17909759
[47,] -0.02644390 -1.72137108
[48,] -7.21291638 -0.02644390
[49,] -11.60277074 -7.21291638
[50,] -14.39938886 -11.60277074
[51,] -10.11122544 -14.39938886
[52,] -14.72137108 -10.11122544
[53,] -14.97559843 -14.72137108
[54,] -13.12813484 -14.97559843
[55,] -10.17898031 -13.12813484
[56,] -8.51798920 -10.17898031
[57,] -8.12813484 -8.51798920
[58,] -4.72125380 -8.12813484
[59,] -5.22970849 -4.72125380
[60,] -5.41618098 -5.22970849
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.94154507 -1.04323601
2 -0.07717208 -1.94154507
3 -0.12801755 -0.07717208
4 3.07536433 -0.12801755
5 4.17705526 3.07536433
6 1.43128261 4.17705526
7 -4.00941722 1.43128261
8 -3.70434440 -4.00941722
9 -3.80603534 -3.70434440
10 -5.44999977 -3.80603534
11 -9.85676353 -5.44999977
12 -3.80591806 -9.85676353
13 -3.99239054 -3.80591806
14 0.87198245 -3.99239054
15 4.77029151 0.87198245
16 3.97367339 4.77029151
17 1.12620980 3.97367339
18 2.63466449 1.12620980
19 0.93973731 2.63466449
20 4.99058278 0.93973731
21 4.99058278 4.99058278
22 2.60084570 4.99058278
23 2.29577288 2.60084570
24 6.60084570 2.29577288
25 7.22790073 6.60084570
26 -0.65349893 7.22790073
27 6.80411030 -0.65349893
28 8.60072842 6.80411030
29 7.21087406 8.60072842
30 11.07524704 7.21087406
31 11.38031986 11.07524704
32 11.14300191 11.38031986
33 9.75314755 11.14300191
34 5.90580124 9.75314755
35 5.39734654 5.90580124
36 7.56679234 5.39734654
37 1.32947439 7.56679234
38 6.19384738 1.32947439
39 3.99046550 6.19384738
40 6.83792909 3.99046550
41 7.29553832 6.83792909
42 4.05822036 7.29553832
43 2.21075677 4.05822036
44 1.27851164 2.21075677
45 -1.17909759 1.27851164
46 -1.72137108 -1.17909759
47 -0.02644390 -1.72137108
48 -7.21291638 -0.02644390
49 -11.60277074 -7.21291638
50 -14.39938886 -11.60277074
51 -10.11122544 -14.39938886
52 -14.72137108 -10.11122544
53 -14.97559843 -14.72137108
54 -13.12813484 -14.97559843
55 -10.17898031 -13.12813484
56 -8.51798920 -10.17898031
57 -8.12813484 -8.51798920
58 -4.72125380 -8.12813484
59 -5.22970849 -4.72125380
60 -5.41618098 -5.22970849
> 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/7ftuv1258650213.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/86s321258650213.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/94wkf1258650213.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10bwry1258650213.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11dxtg1258650213.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/12lr8w1258650213.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/13zaim1258650213.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/14lmik1258650213.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/15iloz1258650213.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/16lu871258650213.tab")
+ }
>
> system("convert tmp/16p1y1258650213.ps tmp/16p1y1258650213.png")
> system("convert tmp/2kqih1258650213.ps tmp/2kqih1258650213.png")
> system("convert tmp/31h5f1258650213.ps tmp/31h5f1258650213.png")
> system("convert tmp/45lrj1258650213.ps tmp/45lrj1258650213.png")
> system("convert tmp/59jwu1258650213.ps tmp/59jwu1258650213.png")
> system("convert tmp/6gc0h1258650213.ps tmp/6gc0h1258650213.png")
> system("convert tmp/7ftuv1258650213.ps tmp/7ftuv1258650213.png")
> system("convert tmp/86s321258650213.ps tmp/86s321258650213.png")
> system("convert tmp/94wkf1258650213.ps tmp/94wkf1258650213.png")
> system("convert tmp/10bwry1258650213.ps tmp/10bwry1258650213.png")
>
>
> proc.time()
user system elapsed
2.476 1.559 2.856