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.
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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
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> x <- array(list(0,0,9,0,1,0,4,0,6,0,21,0,24,0,23,0,22,0,21,0,20,0,16,0,18,0,18,0,24,0,16,0,15,0,24,0,18,0,15,0,4,0,3,0,6,0,5,0,12,0,12,0,12,0,14,0,12,0,17,0,12,0,20,0,21,0,15,0,22,0,19,0,19,0,26,0,25,0,19,0,20,0,30,0,31,0,35,0,33,0,26,0,25,0,17,0,14,0,8,0,12,0,7,0,4,0,10,0,8,0,16,1,14,1,20,1,9,1,10,1),dim=c(2,60),dimnames=list(c('Spa','Val'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Spa','Val'),1:60))
> 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
Spa Val
1 0 0
2 9 0
3 1 0
4 4 0
5 6 0
6 21 0
7 24 0
8 23 0
9 22 0
10 21 0
11 20 0
12 16 0
13 18 0
14 18 0
15 24 0
16 16 0
17 15 0
18 24 0
19 18 0
20 15 0
21 4 0
22 3 0
23 6 0
24 5 0
25 12 0
26 12 0
27 12 0
28 14 0
29 12 0
30 17 0
31 12 0
32 20 0
33 21 0
34 15 0
35 22 0
36 19 0
37 19 0
38 26 0
39 25 0
40 19 0
41 20 0
42 30 0
43 31 0
44 35 0
45 33 0
46 26 0
47 25 0
48 17 0
49 14 0
50 8 0
51 12 0
52 7 0
53 4 0
54 10 0
55 8 0
56 16 1
57 14 1
58 20 1
59 9 1
60 10 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Val
16.182 -2.382
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-16.1818 -4.3364 0.5091 5.0682 18.8182
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 16.182 1.090 14.840 <2e-16 ***
Val -2.382 3.777 -0.631 0.531
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.087 on 58 degrees of freedom
Multiple R-squared: 0.006808, Adjusted R-squared: -0.01032
F-statistic: 0.3976 on 1 and 58 DF, p-value: 0.5308
> 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,] 0.19374682 0.38749364 0.806253182
[2,] 0.72419056 0.55161888 0.275809439
[3,] 0.89774600 0.20450800 0.102254002
[4,] 0.92992377 0.14015246 0.070076229
[5,] 0.93213634 0.13572732 0.067863658
[6,] 0.92032956 0.15934087 0.079670436
[7,] 0.89654102 0.20691796 0.103458979
[8,] 0.84791946 0.30416107 0.152080536
[9,] 0.79538978 0.40922044 0.204610218
[10,] 0.73361518 0.53276963 0.266384817
[11,] 0.73604077 0.52791846 0.263959229
[12,] 0.65939529 0.68120942 0.340604710
[13,] 0.57713211 0.84573578 0.422867888
[14,] 0.57486761 0.85026479 0.425132393
[15,] 0.49638907 0.99277814 0.503610930
[16,] 0.41507659 0.83015319 0.584923406
[17,] 0.50027604 0.99944791 0.499723956
[18,] 0.60689700 0.78620600 0.393103000
[19,] 0.63562419 0.72875163 0.364375813
[20,] 0.68826524 0.62346952 0.311734761
[21,] 0.63666802 0.72666396 0.363331980
[22,] 0.58439416 0.83121167 0.415605837
[23,] 0.53274945 0.93450110 0.467250552
[24,] 0.46823241 0.93646482 0.531767589
[25,] 0.42081836 0.84163672 0.579181642
[26,] 0.35673614 0.71347229 0.643263857
[27,] 0.31668211 0.63336423 0.683317886
[28,] 0.27257593 0.54515186 0.727424068
[29,] 0.23736822 0.47473645 0.762631775
[30,] 0.19027696 0.38055391 0.809723045
[31,] 0.16665136 0.33330272 0.833348642
[32,] 0.12934845 0.25869691 0.870651546
[33,] 0.09775832 0.19551664 0.902241680
[34,] 0.10713119 0.21426239 0.892868807
[35,] 0.10571901 0.21143803 0.894280987
[36,] 0.07629068 0.15258135 0.923709323
[37,] 0.05469597 0.10939195 0.945304025
[38,] 0.09160592 0.18321184 0.908394078
[39,] 0.16783331 0.33566662 0.832166690
[40,] 0.46442023 0.92884047 0.535579766
[41,] 0.81604353 0.36791294 0.183956470
[42,] 0.92394867 0.15210265 0.076051326
[43,] 0.99066405 0.01867190 0.009335950
[44,] 0.99439603 0.01120794 0.005603969
[45,] 0.99428762 0.01142475 0.005712376
[46,] 0.98725440 0.02549121 0.012745604
[47,] 0.98206059 0.03587883 0.017939415
[48,] 0.96086295 0.07827409 0.039137046
[49,] 0.94560881 0.10878237 0.054391185
[50,] 0.88429741 0.23140517 0.115702587
[51,] 0.76456347 0.47087305 0.235436525
> postscript(file="/var/www/html/rcomp/tmp/1rvqt1228496141.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/22rin1228496141.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3pjoa1228496141.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4wedp1228496141.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56eyy1228496141.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 = 60
Frequency = 1
1 2 3 4 5 6
-16.1818182 -7.1818182 -15.1818182 -12.1818182 -10.1818182 4.8181818
7 8 9 10 11 12
7.8181818 6.8181818 5.8181818 4.8181818 3.8181818 -0.1818182
13 14 15 16 17 18
1.8181818 1.8181818 7.8181818 -0.1818182 -1.1818182 7.8181818
19 20 21 22 23 24
1.8181818 -1.1818182 -12.1818182 -13.1818182 -10.1818182 -11.1818182
25 26 27 28 29 30
-4.1818182 -4.1818182 -4.1818182 -2.1818182 -4.1818182 0.8181818
31 32 33 34 35 36
-4.1818182 3.8181818 4.8181818 -1.1818182 5.8181818 2.8181818
37 38 39 40 41 42
2.8181818 9.8181818 8.8181818 2.8181818 3.8181818 13.8181818
43 44 45 46 47 48
14.8181818 18.8181818 16.8181818 9.8181818 8.8181818 0.8181818
49 50 51 52 53 54
-2.1818182 -8.1818182 -4.1818182 -9.1818182 -12.1818182 -6.1818182
55 56 57 58 59 60
-8.1818182 2.2000000 0.2000000 6.2000000 -4.8000000 -3.8000000
> postscript(file="/var/www/html/rcomp/tmp/60spt1228496141.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -16.1818182 NA
1 -7.1818182 -16.1818182
2 -15.1818182 -7.1818182
3 -12.1818182 -15.1818182
4 -10.1818182 -12.1818182
5 4.8181818 -10.1818182
6 7.8181818 4.8181818
7 6.8181818 7.8181818
8 5.8181818 6.8181818
9 4.8181818 5.8181818
10 3.8181818 4.8181818
11 -0.1818182 3.8181818
12 1.8181818 -0.1818182
13 1.8181818 1.8181818
14 7.8181818 1.8181818
15 -0.1818182 7.8181818
16 -1.1818182 -0.1818182
17 7.8181818 -1.1818182
18 1.8181818 7.8181818
19 -1.1818182 1.8181818
20 -12.1818182 -1.1818182
21 -13.1818182 -12.1818182
22 -10.1818182 -13.1818182
23 -11.1818182 -10.1818182
24 -4.1818182 -11.1818182
25 -4.1818182 -4.1818182
26 -4.1818182 -4.1818182
27 -2.1818182 -4.1818182
28 -4.1818182 -2.1818182
29 0.8181818 -4.1818182
30 -4.1818182 0.8181818
31 3.8181818 -4.1818182
32 4.8181818 3.8181818
33 -1.1818182 4.8181818
34 5.8181818 -1.1818182
35 2.8181818 5.8181818
36 2.8181818 2.8181818
37 9.8181818 2.8181818
38 8.8181818 9.8181818
39 2.8181818 8.8181818
40 3.8181818 2.8181818
41 13.8181818 3.8181818
42 14.8181818 13.8181818
43 18.8181818 14.8181818
44 16.8181818 18.8181818
45 9.8181818 16.8181818
46 8.8181818 9.8181818
47 0.8181818 8.8181818
48 -2.1818182 0.8181818
49 -8.1818182 -2.1818182
50 -4.1818182 -8.1818182
51 -9.1818182 -4.1818182
52 -12.1818182 -9.1818182
53 -6.1818182 -12.1818182
54 -8.1818182 -6.1818182
55 2.2000000 -8.1818182
56 0.2000000 2.2000000
57 6.2000000 0.2000000
58 -4.8000000 6.2000000
59 -3.8000000 -4.8000000
60 NA -3.8000000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7.1818182 -16.1818182
[2,] -15.1818182 -7.1818182
[3,] -12.1818182 -15.1818182
[4,] -10.1818182 -12.1818182
[5,] 4.8181818 -10.1818182
[6,] 7.8181818 4.8181818
[7,] 6.8181818 7.8181818
[8,] 5.8181818 6.8181818
[9,] 4.8181818 5.8181818
[10,] 3.8181818 4.8181818
[11,] -0.1818182 3.8181818
[12,] 1.8181818 -0.1818182
[13,] 1.8181818 1.8181818
[14,] 7.8181818 1.8181818
[15,] -0.1818182 7.8181818
[16,] -1.1818182 -0.1818182
[17,] 7.8181818 -1.1818182
[18,] 1.8181818 7.8181818
[19,] -1.1818182 1.8181818
[20,] -12.1818182 -1.1818182
[21,] -13.1818182 -12.1818182
[22,] -10.1818182 -13.1818182
[23,] -11.1818182 -10.1818182
[24,] -4.1818182 -11.1818182
[25,] -4.1818182 -4.1818182
[26,] -4.1818182 -4.1818182
[27,] -2.1818182 -4.1818182
[28,] -4.1818182 -2.1818182
[29,] 0.8181818 -4.1818182
[30,] -4.1818182 0.8181818
[31,] 3.8181818 -4.1818182
[32,] 4.8181818 3.8181818
[33,] -1.1818182 4.8181818
[34,] 5.8181818 -1.1818182
[35,] 2.8181818 5.8181818
[36,] 2.8181818 2.8181818
[37,] 9.8181818 2.8181818
[38,] 8.8181818 9.8181818
[39,] 2.8181818 8.8181818
[40,] 3.8181818 2.8181818
[41,] 13.8181818 3.8181818
[42,] 14.8181818 13.8181818
[43,] 18.8181818 14.8181818
[44,] 16.8181818 18.8181818
[45,] 9.8181818 16.8181818
[46,] 8.8181818 9.8181818
[47,] 0.8181818 8.8181818
[48,] -2.1818182 0.8181818
[49,] -8.1818182 -2.1818182
[50,] -4.1818182 -8.1818182
[51,] -9.1818182 -4.1818182
[52,] -12.1818182 -9.1818182
[53,] -6.1818182 -12.1818182
[54,] -8.1818182 -6.1818182
[55,] 2.2000000 -8.1818182
[56,] 0.2000000 2.2000000
[57,] 6.2000000 0.2000000
[58,] -4.8000000 6.2000000
[59,] -3.8000000 -4.8000000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7.1818182 -16.1818182
2 -15.1818182 -7.1818182
3 -12.1818182 -15.1818182
4 -10.1818182 -12.1818182
5 4.8181818 -10.1818182
6 7.8181818 4.8181818
7 6.8181818 7.8181818
8 5.8181818 6.8181818
9 4.8181818 5.8181818
10 3.8181818 4.8181818
11 -0.1818182 3.8181818
12 1.8181818 -0.1818182
13 1.8181818 1.8181818
14 7.8181818 1.8181818
15 -0.1818182 7.8181818
16 -1.1818182 -0.1818182
17 7.8181818 -1.1818182
18 1.8181818 7.8181818
19 -1.1818182 1.8181818
20 -12.1818182 -1.1818182
21 -13.1818182 -12.1818182
22 -10.1818182 -13.1818182
23 -11.1818182 -10.1818182
24 -4.1818182 -11.1818182
25 -4.1818182 -4.1818182
26 -4.1818182 -4.1818182
27 -2.1818182 -4.1818182
28 -4.1818182 -2.1818182
29 0.8181818 -4.1818182
30 -4.1818182 0.8181818
31 3.8181818 -4.1818182
32 4.8181818 3.8181818
33 -1.1818182 4.8181818
34 5.8181818 -1.1818182
35 2.8181818 5.8181818
36 2.8181818 2.8181818
37 9.8181818 2.8181818
38 8.8181818 9.8181818
39 2.8181818 8.8181818
40 3.8181818 2.8181818
41 13.8181818 3.8181818
42 14.8181818 13.8181818
43 18.8181818 14.8181818
44 16.8181818 18.8181818
45 9.8181818 16.8181818
46 8.8181818 9.8181818
47 0.8181818 8.8181818
48 -2.1818182 0.8181818
49 -8.1818182 -2.1818182
50 -4.1818182 -8.1818182
51 -9.1818182 -4.1818182
52 -12.1818182 -9.1818182
53 -6.1818182 -12.1818182
54 -8.1818182 -6.1818182
55 2.2000000 -8.1818182
56 0.2000000 2.2000000
57 6.2000000 0.2000000
58 -4.8000000 6.2000000
59 -3.8000000 -4.8000000
> 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/7tyji1228496141.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8rbw21228496141.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ujcf1228496141.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10crnx1228496141.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/113mo71228496141.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/12uwpr1228496141.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/13fj5r1228496141.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/14vgcx1228496141.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/15p6h21228496141.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/16y4x21228496141.tab")
+ }
>
> system("convert tmp/1rvqt1228496141.ps tmp/1rvqt1228496141.png")
> system("convert tmp/22rin1228496141.ps tmp/22rin1228496141.png")
> system("convert tmp/3pjoa1228496141.ps tmp/3pjoa1228496141.png")
> system("convert tmp/4wedp1228496141.ps tmp/4wedp1228496141.png")
> system("convert tmp/56eyy1228496141.ps tmp/56eyy1228496141.png")
> system("convert tmp/60spt1228496141.ps tmp/60spt1228496141.png")
> system("convert tmp/7tyji1228496141.ps tmp/7tyji1228496141.png")
> system("convert tmp/8rbw21228496141.ps tmp/8rbw21228496141.png")
> system("convert tmp/9ujcf1228496141.ps tmp/9ujcf1228496141.png")
> system("convert tmp/10crnx1228496141.ps tmp/10crnx1228496141.png")
>
>
> proc.time()
user system elapsed
2.531 1.572 2.981