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.
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(71.7,0,77.5,0,89.8,0,80.3,0,78.7,0,93.8,0,57.6,0,60.6,0,91,0,85.3,0,77.4,0,77.3,0,68.3,0,69.9,0,81.7,0,75.1,0,69.9,0,84,0,54.3,0,60,0,89.9,0,77,0,85.3,0,77.6,0,69.2,0,75.5,0,85.7,0,72.2,0,79.9,0,85.3,0,52.2,0,61.2,0,82.4,0,85.4,0,78.2,0,70.2,1,70.2,1,69.3,1,77.5,1,66.1,1,69,1,79.2,1,56.2,1,63.3,1,77.8,1,92,1,78.1,1,65.1,1,71.1,1,70.9,1,72,1,81.9,1,70.6,1,72.5,1,65.1,1,61.1,1),dim=c(2,56),dimnames=list(c('y','x'),1:56))
> y <- array(NA,dim=c(2,56),dimnames=list(c('y','x'),1:56))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
y x
1 71.7 0
2 77.5 0
3 89.8 0
4 80.3 0
5 78.7 0
6 93.8 0
7 57.6 0
8 60.6 0
9 91.0 0
10 85.3 0
11 77.4 0
12 77.3 0
13 68.3 0
14 69.9 0
15 81.7 0
16 75.1 0
17 69.9 0
18 84.0 0
19 54.3 0
20 60.0 0
21 89.9 0
22 77.0 0
23 85.3 0
24 77.6 0
25 69.2 0
26 75.5 0
27 85.7 0
28 72.2 0
29 79.9 0
30 85.3 0
31 52.2 0
32 61.2 0
33 82.4 0
34 85.4 0
35 78.2 0
36 70.2 1
37 70.2 1
38 69.3 1
39 77.5 1
40 66.1 1
41 69.0 1
42 79.2 1
43 56.2 1
44 63.3 1
45 77.8 1
46 92.0 1
47 78.1 1
48 65.1 1
49 71.1 1
50 70.9 1
51 72.0 1
52 81.9 1
53 70.6 1
54 72.5 1
55 65.1 1
56 61.1 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
76.034 -4.644
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-23.8343 -6.1343 0.7876 6.4845 20.6095
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 76.034 1.644 46.26 <2e-16 ***
x -4.644 2.684 -1.73 0.0893 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 9.724 on 54 degrees of freedom
Multiple R-squared: 0.05252, Adjusted R-squared: 0.03497
F-statistic: 2.993 on 1 and 54 DF, p-value: 0.08933
> 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,] 0.3681445 0.73628897 0.63185552
[2,] 0.5313492 0.93730163 0.46865081
[3,] 0.8874305 0.22513897 0.11256949
[4,] 0.9375300 0.12493999 0.06246999
[5,] 0.9545787 0.09084262 0.04542131
[6,] 0.9406197 0.11876062 0.05938031
[7,] 0.9049286 0.19014280 0.09507140
[8,] 0.8572093 0.28558138 0.14279069
[9,] 0.8412446 0.31751083 0.15875541
[10,] 0.8067771 0.38644582 0.19322291
[11,] 0.7560756 0.48784888 0.24392444
[12,] 0.6830543 0.63389144 0.31694572
[13,] 0.6361150 0.72776999 0.36388500
[14,] 0.6008152 0.79836968 0.39918484
[15,] 0.8454201 0.30915972 0.15457986
[16,] 0.9062350 0.18753010 0.09376505
[17,] 0.9316891 0.13662177 0.06831088
[18,] 0.9010577 0.19788457 0.09894228
[19,] 0.8958275 0.20834497 0.10417249
[20,] 0.8564132 0.28717358 0.14358679
[21,] 0.8296023 0.34079531 0.17039765
[22,] 0.7743958 0.45120843 0.22560421
[23,] 0.7744516 0.45109677 0.22554838
[24,] 0.7180411 0.56391780 0.28195890
[25,] 0.6629631 0.67407388 0.33703694
[26,] 0.6776648 0.64467049 0.32233524
[27,] 0.9127370 0.17452595 0.08726298
[28,] 0.9662863 0.06742734 0.03371367
[29,] 0.9504482 0.09910354 0.04955177
[30,] 0.9383369 0.12332622 0.06166311
[31,] 0.9083823 0.18323548 0.09161774
[32,] 0.8683191 0.26336171 0.13168085
[33,] 0.8169940 0.36601199 0.18300599
[34,] 0.7559716 0.48805680 0.24402840
[35,] 0.7123724 0.57525516 0.28762758
[36,] 0.6553183 0.68936334 0.34468167
[37,] 0.5724016 0.85519673 0.42759836
[38,] 0.5360593 0.92788148 0.46394074
[39,] 0.6743824 0.65123514 0.32561757
[40,] 0.6634649 0.67307014 0.33653507
[41,] 0.5950101 0.80997979 0.40498990
[42,] 0.9185744 0.16285118 0.08142559
[43,] 0.9108077 0.17838453 0.08919227
[44,] 0.8738645 0.25227090 0.12613545
[45,] 0.7802367 0.43952652 0.21976326
[46,] 0.6446929 0.71061428 0.35530714
[47,] 0.4751968 0.95039353 0.52480324
> postscript(file="/var/www/html/rcomp/tmp/1zmdz1227349995.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2w51r1227349995.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wmpo1227349995.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4dij21227349995.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5efx31227349995.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 = 56
Frequency = 1
1 2 3 4 5 6
-4.3342857 1.4657143 13.7657143 4.2657143 2.6657143 17.7657143
7 8 9 10 11 12
-18.4342857 -15.4342857 14.9657143 9.2657143 1.3657143 1.2657143
13 14 15 16 17 18
-7.7342857 -6.1342857 5.6657143 -0.9342857 -6.1342857 7.9657143
19 20 21 22 23 24
-21.7342857 -16.0342857 13.8657143 0.9657143 9.2657143 1.5657143
25 26 27 28 29 30
-6.8342857 -0.5342857 9.6657143 -3.8342857 3.8657143 9.2657143
31 32 33 34 35 36
-23.8342857 -14.8342857 6.3657143 9.3657143 2.1657143 -1.1904762
37 38 39 40 41 42
-1.1904762 -2.0904762 6.1095238 -5.2904762 -2.3904762 7.8095238
43 44 45 46 47 48
-15.1904762 -8.0904762 6.4095238 20.6095238 6.7095238 -6.2904762
49 50 51 52 53 54
-0.2904762 -0.4904762 0.6095238 10.5095238 -0.7904762 1.1095238
55 56
-6.2904762 -10.2904762
> postscript(file="/var/www/html/rcomp/tmp/61e0l1227349995.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 = 56
Frequency = 1
lag(myerror, k = 1) myerror
0 -4.3342857 NA
1 1.4657143 -4.3342857
2 13.7657143 1.4657143
3 4.2657143 13.7657143
4 2.6657143 4.2657143
5 17.7657143 2.6657143
6 -18.4342857 17.7657143
7 -15.4342857 -18.4342857
8 14.9657143 -15.4342857
9 9.2657143 14.9657143
10 1.3657143 9.2657143
11 1.2657143 1.3657143
12 -7.7342857 1.2657143
13 -6.1342857 -7.7342857
14 5.6657143 -6.1342857
15 -0.9342857 5.6657143
16 -6.1342857 -0.9342857
17 7.9657143 -6.1342857
18 -21.7342857 7.9657143
19 -16.0342857 -21.7342857
20 13.8657143 -16.0342857
21 0.9657143 13.8657143
22 9.2657143 0.9657143
23 1.5657143 9.2657143
24 -6.8342857 1.5657143
25 -0.5342857 -6.8342857
26 9.6657143 -0.5342857
27 -3.8342857 9.6657143
28 3.8657143 -3.8342857
29 9.2657143 3.8657143
30 -23.8342857 9.2657143
31 -14.8342857 -23.8342857
32 6.3657143 -14.8342857
33 9.3657143 6.3657143
34 2.1657143 9.3657143
35 -1.1904762 2.1657143
36 -1.1904762 -1.1904762
37 -2.0904762 -1.1904762
38 6.1095238 -2.0904762
39 -5.2904762 6.1095238
40 -2.3904762 -5.2904762
41 7.8095238 -2.3904762
42 -15.1904762 7.8095238
43 -8.0904762 -15.1904762
44 6.4095238 -8.0904762
45 20.6095238 6.4095238
46 6.7095238 20.6095238
47 -6.2904762 6.7095238
48 -0.2904762 -6.2904762
49 -0.4904762 -0.2904762
50 0.6095238 -0.4904762
51 10.5095238 0.6095238
52 -0.7904762 10.5095238
53 1.1095238 -0.7904762
54 -6.2904762 1.1095238
55 -10.2904762 -6.2904762
56 NA -10.2904762
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.4657143 -4.3342857
[2,] 13.7657143 1.4657143
[3,] 4.2657143 13.7657143
[4,] 2.6657143 4.2657143
[5,] 17.7657143 2.6657143
[6,] -18.4342857 17.7657143
[7,] -15.4342857 -18.4342857
[8,] 14.9657143 -15.4342857
[9,] 9.2657143 14.9657143
[10,] 1.3657143 9.2657143
[11,] 1.2657143 1.3657143
[12,] -7.7342857 1.2657143
[13,] -6.1342857 -7.7342857
[14,] 5.6657143 -6.1342857
[15,] -0.9342857 5.6657143
[16,] -6.1342857 -0.9342857
[17,] 7.9657143 -6.1342857
[18,] -21.7342857 7.9657143
[19,] -16.0342857 -21.7342857
[20,] 13.8657143 -16.0342857
[21,] 0.9657143 13.8657143
[22,] 9.2657143 0.9657143
[23,] 1.5657143 9.2657143
[24,] -6.8342857 1.5657143
[25,] -0.5342857 -6.8342857
[26,] 9.6657143 -0.5342857
[27,] -3.8342857 9.6657143
[28,] 3.8657143 -3.8342857
[29,] 9.2657143 3.8657143
[30,] -23.8342857 9.2657143
[31,] -14.8342857 -23.8342857
[32,] 6.3657143 -14.8342857
[33,] 9.3657143 6.3657143
[34,] 2.1657143 9.3657143
[35,] -1.1904762 2.1657143
[36,] -1.1904762 -1.1904762
[37,] -2.0904762 -1.1904762
[38,] 6.1095238 -2.0904762
[39,] -5.2904762 6.1095238
[40,] -2.3904762 -5.2904762
[41,] 7.8095238 -2.3904762
[42,] -15.1904762 7.8095238
[43,] -8.0904762 -15.1904762
[44,] 6.4095238 -8.0904762
[45,] 20.6095238 6.4095238
[46,] 6.7095238 20.6095238
[47,] -6.2904762 6.7095238
[48,] -0.2904762 -6.2904762
[49,] -0.4904762 -0.2904762
[50,] 0.6095238 -0.4904762
[51,] 10.5095238 0.6095238
[52,] -0.7904762 10.5095238
[53,] 1.1095238 -0.7904762
[54,] -6.2904762 1.1095238
[55,] -10.2904762 -6.2904762
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.4657143 -4.3342857
2 13.7657143 1.4657143
3 4.2657143 13.7657143
4 2.6657143 4.2657143
5 17.7657143 2.6657143
6 -18.4342857 17.7657143
7 -15.4342857 -18.4342857
8 14.9657143 -15.4342857
9 9.2657143 14.9657143
10 1.3657143 9.2657143
11 1.2657143 1.3657143
12 -7.7342857 1.2657143
13 -6.1342857 -7.7342857
14 5.6657143 -6.1342857
15 -0.9342857 5.6657143
16 -6.1342857 -0.9342857
17 7.9657143 -6.1342857
18 -21.7342857 7.9657143
19 -16.0342857 -21.7342857
20 13.8657143 -16.0342857
21 0.9657143 13.8657143
22 9.2657143 0.9657143
23 1.5657143 9.2657143
24 -6.8342857 1.5657143
25 -0.5342857 -6.8342857
26 9.6657143 -0.5342857
27 -3.8342857 9.6657143
28 3.8657143 -3.8342857
29 9.2657143 3.8657143
30 -23.8342857 9.2657143
31 -14.8342857 -23.8342857
32 6.3657143 -14.8342857
33 9.3657143 6.3657143
34 2.1657143 9.3657143
35 -1.1904762 2.1657143
36 -1.1904762 -1.1904762
37 -2.0904762 -1.1904762
38 6.1095238 -2.0904762
39 -5.2904762 6.1095238
40 -2.3904762 -5.2904762
41 7.8095238 -2.3904762
42 -15.1904762 7.8095238
43 -8.0904762 -15.1904762
44 6.4095238 -8.0904762
45 20.6095238 6.4095238
46 6.7095238 20.6095238
47 -6.2904762 6.7095238
48 -0.2904762 -6.2904762
49 -0.4904762 -0.2904762
50 0.6095238 -0.4904762
51 10.5095238 0.6095238
52 -0.7904762 10.5095238
53 1.1095238 -0.7904762
54 -6.2904762 1.1095238
55 -10.2904762 -6.2904762
> 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/7340r1227349995.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ncns1227349995.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9z4oh1227349995.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/101ucz1227349995.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11xd2o1227349995.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/12tzdq1227349995.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/13fsdo1227349996.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/149nuf1227349996.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/15hara1227349996.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/168xnc1227349996.tab")
+ }
>
> system("convert tmp/1zmdz1227349995.ps tmp/1zmdz1227349995.png")
> system("convert tmp/2w51r1227349995.ps tmp/2w51r1227349995.png")
> system("convert tmp/3wmpo1227349995.ps tmp/3wmpo1227349995.png")
> system("convert tmp/4dij21227349995.ps tmp/4dij21227349995.png")
> system("convert tmp/5efx31227349995.ps tmp/5efx31227349995.png")
> system("convert tmp/61e0l1227349995.ps tmp/61e0l1227349995.png")
> system("convert tmp/7340r1227349995.ps tmp/7340r1227349995.png")
> system("convert tmp/8ncns1227349995.ps tmp/8ncns1227349995.png")
> system("convert tmp/9z4oh1227349995.ps tmp/9z4oh1227349995.png")
> system("convert tmp/101ucz1227349995.ps tmp/101ucz1227349995.png")
>
>
> proc.time()
user system elapsed
2.413 1.568 5.559