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(0,593,0,590,0,580,0,574,0,573,0,573,0,620,0,626,0,620,0,588,0,566,0,557,0,561,0,549,0,532,0,526,0,511,0,499,0,555,0,565,0,542,0,527,0,510,0,514,0,517,0,508,0,493,0,490,0,469,0,478,1,528,1,534,1,518,1,506,1,502,1,516,1,528,1,533,1,536,1,537,1,524,1,536,1,587,1,597,1,581,1,564,1,558,0,575,0,580,0,575,0,563,0,552,0,537,0,545,0,601),dim=c(2,55),dimnames=list(c('X','Y'),1:55))
> y <- array(NA,dim=c(2,55),dimnames=list(c('X','Y'),1:55))
> 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 = 'Include Monthly Dummies'
> par1 = '2'
> #'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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 593 0 1 0 0 0 0 0 0 0 0 0 0
2 590 0 0 1 0 0 0 0 0 0 0 0 0
3 580 0 0 0 1 0 0 0 0 0 0 0 0
4 574 0 0 0 0 1 0 0 0 0 0 0 0
5 573 0 0 0 0 0 1 0 0 0 0 0 0
6 573 0 0 0 0 0 0 1 0 0 0 0 0
7 620 0 0 0 0 0 0 0 1 0 0 0 0
8 626 0 0 0 0 0 0 0 0 1 0 0 0
9 620 0 0 0 0 0 0 0 0 0 1 0 0
10 588 0 0 0 0 0 0 0 0 0 0 1 0
11 566 0 0 0 0 0 0 0 0 0 0 0 1
12 557 0 0 0 0 0 0 0 0 0 0 0 0
13 561 0 1 0 0 0 0 0 0 0 0 0 0
14 549 0 0 1 0 0 0 0 0 0 0 0 0
15 532 0 0 0 1 0 0 0 0 0 0 0 0
16 526 0 0 0 0 1 0 0 0 0 0 0 0
17 511 0 0 0 0 0 1 0 0 0 0 0 0
18 499 0 0 0 0 0 0 1 0 0 0 0 0
19 555 0 0 0 0 0 0 0 1 0 0 0 0
20 565 0 0 0 0 0 0 0 0 1 0 0 0
21 542 0 0 0 0 0 0 0 0 0 1 0 0
22 527 0 0 0 0 0 0 0 0 0 0 1 0
23 510 0 0 0 0 0 0 0 0 0 0 0 1
24 514 0 0 0 0 0 0 0 0 0 0 0 0
25 517 0 1 0 0 0 0 0 0 0 0 0 0
26 508 0 0 1 0 0 0 0 0 0 0 0 0
27 493 0 0 0 1 0 0 0 0 0 0 0 0
28 490 0 0 0 0 1 0 0 0 0 0 0 0
29 469 0 0 0 0 0 1 0 0 0 0 0 0
30 478 0 0 0 0 0 0 1 0 0 0 0 0
31 528 1 0 0 0 0 0 0 1 0 0 0 0
32 534 1 0 0 0 0 0 0 0 1 0 0 0
33 518 1 0 0 0 0 0 0 0 0 1 0 0
34 506 1 0 0 0 0 0 0 0 0 0 1 0
35 502 1 0 0 0 0 0 0 0 0 0 0 1
36 516 1 0 0 0 0 0 0 0 0 0 0 0
37 528 1 1 0 0 0 0 0 0 0 0 0 0
38 533 1 0 1 0 0 0 0 0 0 0 0 0
39 536 1 0 0 1 0 0 0 0 0 0 0 0
40 537 1 0 0 0 1 0 0 0 0 0 0 0
41 524 1 0 0 0 0 1 0 0 0 0 0 0
42 536 1 0 0 0 0 0 1 0 0 0 0 0
43 587 1 0 0 0 0 0 0 1 0 0 0 0
44 597 1 0 0 0 0 0 0 0 1 0 0 0
45 581 1 0 0 0 0 0 0 0 0 1 0 0
46 564 1 0 0 0 0 0 0 0 0 0 1 0
47 558 1 0 0 0 0 0 0 0 0 0 0 1
48 575 0 0 0 0 0 0 0 0 0 0 0 0
49 580 0 1 0 0 0 0 0 0 0 0 0 0
50 575 0 0 1 0 0 0 0 0 0 0 0 0
51 563 0 0 0 1 0 0 0 0 0 0 0 0
52 552 0 0 0 0 1 0 0 0 0 0 0 0
53 537 0 0 0 0 0 1 0 0 0 0 0 0
54 545 0 0 0 0 0 0 1 0 0 0 0 0
55 601 0 0 0 0 0 0 0 1 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
545.065 -18.260 14.387 9.587 -0.613 -5.613
M5 M6 M7 M8 M9 M10
-18.613 -15.213 40.439 44.565 29.315 10.315
M11
-1.935
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-57.45 -30.68 10.55 25.26 46.55
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 545.065 17.614 30.946 <2e-16 ***
X -18.261 10.621 -1.719 0.0929 .
M1 14.387 23.367 0.616 0.5414
M2 9.587 23.367 0.410 0.6837
M3 -0.613 23.367 -0.026 0.9792
M4 -5.613 23.367 -0.240 0.8113
M5 -18.613 23.367 -0.797 0.4302
M6 -15.213 23.367 -0.651 0.5186
M7 40.439 23.415 1.727 0.0915 .
M8 44.565 24.767 1.799 0.0792 .
M9 29.315 24.767 1.184 0.2432
M10 10.315 24.767 0.416 0.6792
M11 -1.935 24.767 -0.078 0.9381
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 34.82 on 42 degrees of freedom
Multiple R-squared: 0.2966, Adjusted R-squared: 0.09562
F-statistic: 1.476 on 12 and 42 DF, p-value: 0.1719
> 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,] 0.6475006 0.7049988398 0.3524994199
[2,] 0.6847461 0.6305078654 0.3152539327
[3,] 0.7565723 0.4868554155 0.2434277078
[4,] 0.7646850 0.4706299459 0.2353149730
[5,] 0.7496127 0.5007745276 0.2503872638
[6,] 0.7741599 0.4516801265 0.2258400633
[7,] 0.7475352 0.5049295672 0.2524647836
[8,] 0.7130557 0.5738885282 0.2869442641
[9,] 0.6643369 0.6713261119 0.3356630560
[10,] 0.6708519 0.6582962938 0.3291481469
[11,] 0.6940225 0.6119549962 0.3059774981
[12,] 0.7448019 0.5103961441 0.2551980720
[13,] 0.7901738 0.4196524476 0.2098262238
[14,] 0.8741610 0.2516779467 0.1258389734
[15,] 0.9392794 0.1214411018 0.0607205509
[16,] 0.9404119 0.1191761541 0.0595880771
[17,] 0.9528818 0.0942364151 0.0471182075
[18,] 0.9703103 0.0593793713 0.0296896856
[19,] 0.9844868 0.0310264541 0.0155132271
[20,] 0.9963191 0.0073618352 0.0036809176
[21,] 0.9970967 0.0058065570 0.0029032785
[22,] 0.9982700 0.0034600558 0.0017300279
[23,] 0.9995018 0.0009963821 0.0004981910
[24,] 0.9998396 0.0003208633 0.0001604316
> postscript(file="/var/www/html/rcomp/tmp/1gz581291031089.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2q8nb1291031089.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3q8nb1291031089.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4q8nb1291031089.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5jhmw1291031089.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 = 55
Frequency = 1
1 2 3 4 5 6 7
33.547907 35.347907 35.547907 34.547907 46.547907 43.147907 34.495814
8 9 10 11 12 13 14
36.369767 45.619767 32.619767 22.869767 11.934884 1.547907 -5.652093
15 16 17 18 19 20 21
-12.452093 -13.452093 -15.452093 -30.852093 -30.504186 -24.630233 -32.380233
22 23 24 25 26 27 28
-28.380233 -33.130233 -31.065116 -42.452093 -46.652093 -51.452093 -49.452093
29 30 31 32 33 34 35
-57.452093 -51.852093 -39.243721 -37.369767 -38.119767 -31.119767 -22.869767
36 37 38 39 40 41 42
-10.804651 -13.191628 -3.391628 9.808372 15.808372 15.808372 24.408372
43 44 45 46 47 48 49
19.756279 25.630233 24.880233 26.880233 33.130233 29.934884 20.547907
50 51 52 53 54 55
20.347907 18.547907 12.547907 10.547907 15.147907 15.495814
> postscript(file="/var/www/html/rcomp/tmp/6jhmw1291031089.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 = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 33.547907 NA
1 35.347907 33.547907
2 35.547907 35.347907
3 34.547907 35.547907
4 46.547907 34.547907
5 43.147907 46.547907
6 34.495814 43.147907
7 36.369767 34.495814
8 45.619767 36.369767
9 32.619767 45.619767
10 22.869767 32.619767
11 11.934884 22.869767
12 1.547907 11.934884
13 -5.652093 1.547907
14 -12.452093 -5.652093
15 -13.452093 -12.452093
16 -15.452093 -13.452093
17 -30.852093 -15.452093
18 -30.504186 -30.852093
19 -24.630233 -30.504186
20 -32.380233 -24.630233
21 -28.380233 -32.380233
22 -33.130233 -28.380233
23 -31.065116 -33.130233
24 -42.452093 -31.065116
25 -46.652093 -42.452093
26 -51.452093 -46.652093
27 -49.452093 -51.452093
28 -57.452093 -49.452093
29 -51.852093 -57.452093
30 -39.243721 -51.852093
31 -37.369767 -39.243721
32 -38.119767 -37.369767
33 -31.119767 -38.119767
34 -22.869767 -31.119767
35 -10.804651 -22.869767
36 -13.191628 -10.804651
37 -3.391628 -13.191628
38 9.808372 -3.391628
39 15.808372 9.808372
40 15.808372 15.808372
41 24.408372 15.808372
42 19.756279 24.408372
43 25.630233 19.756279
44 24.880233 25.630233
45 26.880233 24.880233
46 33.130233 26.880233
47 29.934884 33.130233
48 20.547907 29.934884
49 20.347907 20.547907
50 18.547907 20.347907
51 12.547907 18.547907
52 10.547907 12.547907
53 15.147907 10.547907
54 15.495814 15.147907
55 NA 15.495814
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 35.347907 33.547907
[2,] 35.547907 35.347907
[3,] 34.547907 35.547907
[4,] 46.547907 34.547907
[5,] 43.147907 46.547907
[6,] 34.495814 43.147907
[7,] 36.369767 34.495814
[8,] 45.619767 36.369767
[9,] 32.619767 45.619767
[10,] 22.869767 32.619767
[11,] 11.934884 22.869767
[12,] 1.547907 11.934884
[13,] -5.652093 1.547907
[14,] -12.452093 -5.652093
[15,] -13.452093 -12.452093
[16,] -15.452093 -13.452093
[17,] -30.852093 -15.452093
[18,] -30.504186 -30.852093
[19,] -24.630233 -30.504186
[20,] -32.380233 -24.630233
[21,] -28.380233 -32.380233
[22,] -33.130233 -28.380233
[23,] -31.065116 -33.130233
[24,] -42.452093 -31.065116
[25,] -46.652093 -42.452093
[26,] -51.452093 -46.652093
[27,] -49.452093 -51.452093
[28,] -57.452093 -49.452093
[29,] -51.852093 -57.452093
[30,] -39.243721 -51.852093
[31,] -37.369767 -39.243721
[32,] -38.119767 -37.369767
[33,] -31.119767 -38.119767
[34,] -22.869767 -31.119767
[35,] -10.804651 -22.869767
[36,] -13.191628 -10.804651
[37,] -3.391628 -13.191628
[38,] 9.808372 -3.391628
[39,] 15.808372 9.808372
[40,] 15.808372 15.808372
[41,] 24.408372 15.808372
[42,] 19.756279 24.408372
[43,] 25.630233 19.756279
[44,] 24.880233 25.630233
[45,] 26.880233 24.880233
[46,] 33.130233 26.880233
[47,] 29.934884 33.130233
[48,] 20.547907 29.934884
[49,] 20.347907 20.547907
[50,] 18.547907 20.347907
[51,] 12.547907 18.547907
[52,] 10.547907 12.547907
[53,] 15.147907 10.547907
[54,] 15.495814 15.147907
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 35.347907 33.547907
2 35.547907 35.347907
3 34.547907 35.547907
4 46.547907 34.547907
5 43.147907 46.547907
6 34.495814 43.147907
7 36.369767 34.495814
8 45.619767 36.369767
9 32.619767 45.619767
10 22.869767 32.619767
11 11.934884 22.869767
12 1.547907 11.934884
13 -5.652093 1.547907
14 -12.452093 -5.652093
15 -13.452093 -12.452093
16 -15.452093 -13.452093
17 -30.852093 -15.452093
18 -30.504186 -30.852093
19 -24.630233 -30.504186
20 -32.380233 -24.630233
21 -28.380233 -32.380233
22 -33.130233 -28.380233
23 -31.065116 -33.130233
24 -42.452093 -31.065116
25 -46.652093 -42.452093
26 -51.452093 -46.652093
27 -49.452093 -51.452093
28 -57.452093 -49.452093
29 -51.852093 -57.452093
30 -39.243721 -51.852093
31 -37.369767 -39.243721
32 -38.119767 -37.369767
33 -31.119767 -38.119767
34 -22.869767 -31.119767
35 -10.804651 -22.869767
36 -13.191628 -10.804651
37 -3.391628 -13.191628
38 9.808372 -3.391628
39 15.808372 9.808372
40 15.808372 15.808372
41 24.408372 15.808372
42 19.756279 24.408372
43 25.630233 19.756279
44 24.880233 25.630233
45 26.880233 24.880233
46 33.130233 26.880233
47 29.934884 33.130233
48 20.547907 29.934884
49 20.347907 20.547907
50 18.547907 20.347907
51 12.547907 18.547907
52 10.547907 12.547907
53 15.147907 10.547907
54 15.495814 15.147907
> 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/7u9lh1291031089.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8u9lh1291031089.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9u9lh1291031089.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/104ik21291031089.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11801q1291031089.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/12t1iw1291031089.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/130kfp1291031089.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/14bbea1291031089.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/15euug1291031089.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/16a3s71291031089.tab")
+ }
> try(system("convert tmp/1gz581291031089.ps tmp/1gz581291031089.png",intern=TRUE))
character(0)
> try(system("convert tmp/2q8nb1291031089.ps tmp/2q8nb1291031089.png",intern=TRUE))
character(0)
> try(system("convert tmp/3q8nb1291031089.ps tmp/3q8nb1291031089.png",intern=TRUE))
character(0)
> try(system("convert tmp/4q8nb1291031089.ps tmp/4q8nb1291031089.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jhmw1291031089.ps tmp/5jhmw1291031089.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jhmw1291031089.ps tmp/6jhmw1291031089.png",intern=TRUE))
character(0)
> try(system("convert tmp/7u9lh1291031089.ps tmp/7u9lh1291031089.png",intern=TRUE))
character(0)
> try(system("convert tmp/8u9lh1291031089.ps tmp/8u9lh1291031089.png",intern=TRUE))
character(0)
> try(system("convert tmp/9u9lh1291031089.ps tmp/9u9lh1291031089.png",intern=TRUE))
character(0)
> try(system("convert tmp/104ik21291031089.ps tmp/104ik21291031089.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.310 1.516 5.455