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(595,0,597,0,593,0,590,0,580,0,574,0,573,0,573,0,620,0,626,0,620,0,588,0,566,0,557,0,561,0,549,0,532,0,526,0,511,0,499,0,555,0,565,0,542,0,527,0,510,0,514,0,517,0,508,0,493,0,490,0,469,0,478,0,528,0,534,0,518,0,506,0,502,1,516,1,528,1,533,1,536,1,537,1,524,1,536,1,587,1,597,1,581,1,564,1,558,1,575,1,580,1,575,1,563,1,552,1,537,1,545,1,601,1,604,1,586,1,564,1,549,1),dim=c(2,61),dimnames=list(c('werkloosheid','X'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('werkloosheid','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])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> ylab = ''
> xlab = ''
> main = ''
> #'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
werkloosheid X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 595 0 1 0 0 0 0 0 0 0 0 0 0
2 597 0 0 1 0 0 0 0 0 0 0 0 0
3 593 0 0 0 1 0 0 0 0 0 0 0 0
4 590 0 0 0 0 1 0 0 0 0 0 0 0
5 580 0 0 0 0 0 1 0 0 0 0 0 0
6 574 0 0 0 0 0 0 1 0 0 0 0 0
7 573 0 0 0 0 0 0 0 1 0 0 0 0
8 573 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
10 626 0 0 0 0 0 0 0 0 0 0 1 0
11 620 0 0 0 0 0 0 0 0 0 0 0 1
12 588 0 0 0 0 0 0 0 0 0 0 0 0
13 566 0 1 0 0 0 0 0 0 0 0 0 0
14 557 0 0 1 0 0 0 0 0 0 0 0 0
15 561 0 0 0 1 0 0 0 0 0 0 0 0
16 549 0 0 0 0 1 0 0 0 0 0 0 0
17 532 0 0 0 0 0 1 0 0 0 0 0 0
18 526 0 0 0 0 0 0 1 0 0 0 0 0
19 511 0 0 0 0 0 0 0 1 0 0 0 0
20 499 0 0 0 0 0 0 0 0 1 0 0 0
21 555 0 0 0 0 0 0 0 0 0 1 0 0
22 565 0 0 0 0 0 0 0 0 0 0 1 0
23 542 0 0 0 0 0 0 0 0 0 0 0 1
24 527 0 0 0 0 0 0 0 0 0 0 0 0
25 510 0 1 0 0 0 0 0 0 0 0 0 0
26 514 0 0 1 0 0 0 0 0 0 0 0 0
27 517 0 0 0 1 0 0 0 0 0 0 0 0
28 508 0 0 0 0 1 0 0 0 0 0 0 0
29 493 0 0 0 0 0 1 0 0 0 0 0 0
30 490 0 0 0 0 0 0 1 0 0 0 0 0
31 469 0 0 0 0 0 0 0 1 0 0 0 0
32 478 0 0 0 0 0 0 0 0 1 0 0 0
33 528 0 0 0 0 0 0 0 0 0 1 0 0
34 534 0 0 0 0 0 0 0 0 0 0 1 0
35 518 0 0 0 0 0 0 0 0 0 0 0 1
36 506 0 0 0 0 0 0 0 0 0 0 0 0
37 502 1 1 0 0 0 0 0 0 0 0 0 0
38 516 1 0 1 0 0 0 0 0 0 0 0 0
39 528 1 0 0 1 0 0 0 0 0 0 0 0
40 533 1 0 0 0 1 0 0 0 0 0 0 0
41 536 1 0 0 0 0 1 0 0 0 0 0 0
42 537 1 0 0 0 0 0 1 0 0 0 0 0
43 524 1 0 0 0 0 0 0 1 0 0 0 0
44 536 1 0 0 0 0 0 0 0 1 0 0 0
45 587 1 0 0 0 0 0 0 0 0 1 0 0
46 597 1 0 0 0 0 0 0 0 0 0 1 0
47 581 1 0 0 0 0 0 0 0 0 0 0 1
48 564 1 0 0 0 0 0 0 0 0 0 0 0
49 558 1 1 0 0 0 0 0 0 0 0 0 0
50 575 1 0 1 0 0 0 0 0 0 0 0 0
51 580 1 0 0 1 0 0 0 0 0 0 0 0
52 575 1 0 0 0 1 0 0 0 0 0 0 0
53 563 1 0 0 0 0 1 0 0 0 0 0 0
54 552 1 0 0 0 0 0 1 0 0 0 0 0
55 537 1 0 0 0 0 0 0 1 0 0 0 0
56 545 1 0 0 0 0 0 0 0 1 0 0 0
57 601 1 0 0 0 0 0 0 0 0 1 0 0
58 604 1 0 0 0 0 0 0 0 0 0 1 0
59 586 1 0 0 0 0 0 0 0 0 0 0 1
60 564 1 0 0 0 0 0 0 0 0 0 0 0
61 549 1 1 0 0 0 0 0 0 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
545.544 10.639 -4.197 2.000 6.000 1.200
M5 M6 M7 M8 M9 M10
-9.000 -14.000 -27.000 -23.600 28.400 35.400
M11
19.600
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-49.986 -24.384 3.416 16.816 54.856
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 545.544 16.159 33.761 <2e-16 ***
X 10.639 9.178 1.159 0.252
M1 -4.197 21.327 -0.197 0.845
M2 2.000 22.255 0.090 0.929
M3 6.000 22.255 0.270 0.789
M4 1.200 22.255 0.054 0.957
M5 -9.000 22.255 -0.404 0.688
M6 -14.000 22.255 -0.629 0.532
M7 -27.000 22.255 -1.213 0.231
M8 -23.600 22.255 -1.060 0.294
M9 28.400 22.255 1.276 0.208
M10 35.400 22.255 1.591 0.118
M11 19.600 22.255 0.881 0.383
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 35.19 on 48 degrees of freedom
Multiple R-squared: 0.269, Adjusted R-squared: 0.08624
F-statistic: 1.472 on 12 and 48 DF, p-value: 0.1681
> 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,] 0.9193260 0.1613479953 8.067400e-02
[2,] 0.9550165 0.0899670593 4.498353e-02
[3,] 0.9738513 0.0522974719 2.614874e-02
[4,] 0.9920488 0.0159024045 7.951202e-03
[5,] 0.9975433 0.0049134209 2.456710e-03
[6,] 0.9985839 0.0028322239 1.416112e-03
[7,] 0.9990113 0.0019773576 9.886788e-04
[8,] 0.9994906 0.0010187302 5.093651e-04
[9,] 0.9995162 0.0009675605 4.837803e-04
[10,] 0.9997858 0.0004284682 2.142341e-04
[11,] 0.9998439 0.0003121887 1.560944e-04
[12,] 0.9998524 0.0002951863 1.475931e-04
[13,] 0.9998257 0.0003486067 1.743034e-04
[14,] 0.9997562 0.0004875750 2.437875e-04
[15,] 0.9996317 0.0007365940 3.682970e-04
[16,] 0.9995036 0.0009927485 4.963742e-04
[17,] 0.9991291 0.0017418215 8.709107e-04
[18,] 0.9984805 0.0030390425 1.519521e-03
[19,] 0.9973834 0.0052332113 2.616606e-03
[20,] 0.9955325 0.0089350858 4.467543e-03
[21,] 0.9915956 0.0168087932 8.404397e-03
[22,] 0.9950524 0.0098951116 4.947556e-03
[23,] 0.9981520 0.0036960209 1.848010e-03
[24,] 0.9995134 0.0009731662 4.865831e-04
[25,] 0.9999020 0.0001959721 9.798604e-05
[26,] 0.9999488 0.0001024660 5.123302e-05
[27,] 0.9998868 0.0002264978 1.132489e-04
[28,] 0.9996893 0.0006213899 3.106949e-04
[29,] 0.9986513 0.0026973655 1.348683e-03
[30,] 0.9973411 0.0053178011 2.658901e-03
> postscript(file="/var/www/html/freestat/rcomp/tmp/1lnu21293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2lnu21293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3lnu21293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4exu51293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5exu51293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 61
Frequency = 1
1 2 3 4 5 6 7
53.653061 49.455782 41.455782 43.255782 43.455782 42.455782 54.455782
8 9 10 11 12 13 14
51.055782 46.055782 45.055782 54.855782 42.455782 24.653061 9.455782
15 16 17 18 19 20 21
9.455782 2.255782 -4.544218 -5.544218 -7.544218 -22.944218 -18.944218
22 23 24 25 26 27 28
-15.944218 -23.144218 -18.544218 -31.346939 -33.544218 -34.544218 -38.744218
29 30 31 32 33 34 35
-43.544218 -41.544218 -49.544218 -43.944218 -45.944218 -46.944218 -47.144218
36 37 38 39 40 41 42
-39.544218 -49.986395 -42.183673 -34.183673 -24.383673 -11.183673 -5.183673
43 44 45 46 47 48 49
-5.183673 3.416327 2.416327 5.416327 5.216327 7.816327 6.013605
50 51 52 53 54 55 56
16.816327 17.816327 17.616327 15.816327 9.816327 7.816327 12.416327
57 58 59 60 61
16.416327 12.416327 10.216327 7.816327 -2.986395
> postscript(file="/var/www/html/freestat/rcomp/tmp/6exu51293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 53.653061 NA
1 49.455782 53.653061
2 41.455782 49.455782
3 43.255782 41.455782
4 43.455782 43.255782
5 42.455782 43.455782
6 54.455782 42.455782
7 51.055782 54.455782
8 46.055782 51.055782
9 45.055782 46.055782
10 54.855782 45.055782
11 42.455782 54.855782
12 24.653061 42.455782
13 9.455782 24.653061
14 9.455782 9.455782
15 2.255782 9.455782
16 -4.544218 2.255782
17 -5.544218 -4.544218
18 -7.544218 -5.544218
19 -22.944218 -7.544218
20 -18.944218 -22.944218
21 -15.944218 -18.944218
22 -23.144218 -15.944218
23 -18.544218 -23.144218
24 -31.346939 -18.544218
25 -33.544218 -31.346939
26 -34.544218 -33.544218
27 -38.744218 -34.544218
28 -43.544218 -38.744218
29 -41.544218 -43.544218
30 -49.544218 -41.544218
31 -43.944218 -49.544218
32 -45.944218 -43.944218
33 -46.944218 -45.944218
34 -47.144218 -46.944218
35 -39.544218 -47.144218
36 -49.986395 -39.544218
37 -42.183673 -49.986395
38 -34.183673 -42.183673
39 -24.383673 -34.183673
40 -11.183673 -24.383673
41 -5.183673 -11.183673
42 -5.183673 -5.183673
43 3.416327 -5.183673
44 2.416327 3.416327
45 5.416327 2.416327
46 5.216327 5.416327
47 7.816327 5.216327
48 6.013605 7.816327
49 16.816327 6.013605
50 17.816327 16.816327
51 17.616327 17.816327
52 15.816327 17.616327
53 9.816327 15.816327
54 7.816327 9.816327
55 12.416327 7.816327
56 16.416327 12.416327
57 12.416327 16.416327
58 10.216327 12.416327
59 7.816327 10.216327
60 -2.986395 7.816327
61 NA -2.986395
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 49.455782 53.653061
[2,] 41.455782 49.455782
[3,] 43.255782 41.455782
[4,] 43.455782 43.255782
[5,] 42.455782 43.455782
[6,] 54.455782 42.455782
[7,] 51.055782 54.455782
[8,] 46.055782 51.055782
[9,] 45.055782 46.055782
[10,] 54.855782 45.055782
[11,] 42.455782 54.855782
[12,] 24.653061 42.455782
[13,] 9.455782 24.653061
[14,] 9.455782 9.455782
[15,] 2.255782 9.455782
[16,] -4.544218 2.255782
[17,] -5.544218 -4.544218
[18,] -7.544218 -5.544218
[19,] -22.944218 -7.544218
[20,] -18.944218 -22.944218
[21,] -15.944218 -18.944218
[22,] -23.144218 -15.944218
[23,] -18.544218 -23.144218
[24,] -31.346939 -18.544218
[25,] -33.544218 -31.346939
[26,] -34.544218 -33.544218
[27,] -38.744218 -34.544218
[28,] -43.544218 -38.744218
[29,] -41.544218 -43.544218
[30,] -49.544218 -41.544218
[31,] -43.944218 -49.544218
[32,] -45.944218 -43.944218
[33,] -46.944218 -45.944218
[34,] -47.144218 -46.944218
[35,] -39.544218 -47.144218
[36,] -49.986395 -39.544218
[37,] -42.183673 -49.986395
[38,] -34.183673 -42.183673
[39,] -24.383673 -34.183673
[40,] -11.183673 -24.383673
[41,] -5.183673 -11.183673
[42,] -5.183673 -5.183673
[43,] 3.416327 -5.183673
[44,] 2.416327 3.416327
[45,] 5.416327 2.416327
[46,] 5.216327 5.416327
[47,] 7.816327 5.216327
[48,] 6.013605 7.816327
[49,] 16.816327 6.013605
[50,] 17.816327 16.816327
[51,] 17.616327 17.816327
[52,] 15.816327 17.616327
[53,] 9.816327 15.816327
[54,] 7.816327 9.816327
[55,] 12.416327 7.816327
[56,] 16.416327 12.416327
[57,] 12.416327 16.416327
[58,] 10.216327 12.416327
[59,] 7.816327 10.216327
[60,] -2.986395 7.816327
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 49.455782 53.653061
2 41.455782 49.455782
3 43.255782 41.455782
4 43.455782 43.255782
5 42.455782 43.455782
6 54.455782 42.455782
7 51.055782 54.455782
8 46.055782 51.055782
9 45.055782 46.055782
10 54.855782 45.055782
11 42.455782 54.855782
12 24.653061 42.455782
13 9.455782 24.653061
14 9.455782 9.455782
15 2.255782 9.455782
16 -4.544218 2.255782
17 -5.544218 -4.544218
18 -7.544218 -5.544218
19 -22.944218 -7.544218
20 -18.944218 -22.944218
21 -15.944218 -18.944218
22 -23.144218 -15.944218
23 -18.544218 -23.144218
24 -31.346939 -18.544218
25 -33.544218 -31.346939
26 -34.544218 -33.544218
27 -38.744218 -34.544218
28 -43.544218 -38.744218
29 -41.544218 -43.544218
30 -49.544218 -41.544218
31 -43.944218 -49.544218
32 -45.944218 -43.944218
33 -46.944218 -45.944218
34 -47.144218 -46.944218
35 -39.544218 -47.144218
36 -49.986395 -39.544218
37 -42.183673 -49.986395
38 -34.183673 -42.183673
39 -24.383673 -34.183673
40 -11.183673 -24.383673
41 -5.183673 -11.183673
42 -5.183673 -5.183673
43 3.416327 -5.183673
44 2.416327 3.416327
45 5.416327 2.416327
46 5.216327 5.416327
47 7.816327 5.216327
48 6.013605 7.816327
49 16.816327 6.013605
50 17.816327 16.816327
51 17.616327 17.816327
52 15.816327 17.616327
53 9.816327 15.816327
54 7.816327 9.816327
55 12.416327 7.816327
56 16.416327 12.416327
57 12.416327 16.416327
58 10.216327 12.416327
59 7.816327 10.216327
60 -2.986395 7.816327
> 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/7potp1293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8hfas1293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9hfas1293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10hfas1293210230.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11w7qj1293210230.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/126y741293210230.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/13vhmg1293210230.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/14orl11293210230.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/15992p1293210230.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/16510f1293210230.tab")
+ }
>
> try(system("convert tmp/1lnu21293210230.ps tmp/1lnu21293210230.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lnu21293210230.ps tmp/2lnu21293210230.png",intern=TRUE))
character(0)
> try(system("convert tmp/3lnu21293210230.ps tmp/3lnu21293210230.png",intern=TRUE))
character(0)
> try(system("convert tmp/4exu51293210230.ps tmp/4exu51293210230.png",intern=TRUE))
character(0)
> try(system("convert tmp/5exu51293210230.ps tmp/5exu51293210230.png",intern=TRUE))
character(0)
> try(system("convert tmp/6exu51293210230.ps tmp/6exu51293210230.png",intern=TRUE))
character(0)
> try(system("convert tmp/7potp1293210230.ps tmp/7potp1293210230.png",intern=TRUE))
character(0)
> try(system("convert tmp/8hfas1293210230.ps tmp/8hfas1293210230.png",intern=TRUE))
character(0)
> try(system("convert tmp/9hfas1293210230.ps tmp/9hfas1293210230.png",intern=TRUE))
character(0)
> try(system("convert tmp/10hfas1293210230.ps tmp/10hfas1293210230.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.759 2.459 6.097