R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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(41,0,35,0,34,0,36,0,39,0,40,0,30,0,33,0,30,0,32,0,41,0,40,0,41,0,40,0,39,0,34,0,34,0,46,0,45,0,44,0,40,0,39,0,37,0,39,0,35,0,26,0,26,0,33,0,27,0,30,0,26,0,27,0,18,0,19,0,13,0,14,0,41,0,21,0,16,0,17,0,9,0,14,0,14,0,16,0,11,0,10,0,6,0,9,0,5,0,7,0,2,0,0,0,8,0,13,0,11,0,19,1,23,1,23,1,43,1,59,1),dim=c(2,60),dimnames=list(c('Wer','Val'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Wer','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 = 'Include Monthly 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
Wer Val M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 41 0 1 0 0 0 0 0 0 0 0 0 0
2 35 0 0 1 0 0 0 0 0 0 0 0 0
3 34 0 0 0 1 0 0 0 0 0 0 0 0
4 36 0 0 0 0 1 0 0 0 0 0 0 0
5 39 0 0 0 0 0 1 0 0 0 0 0 0
6 40 0 0 0 0 0 0 1 0 0 0 0 0
7 30 0 0 0 0 0 0 0 1 0 0 0 0
8 33 0 0 0 0 0 0 0 0 1 0 0 0
9 30 0 0 0 0 0 0 0 0 0 1 0 0
10 32 0 0 0 0 0 0 0 0 0 0 1 0
11 41 0 0 0 0 0 0 0 0 0 0 0 1
12 40 0 0 0 0 0 0 0 0 0 0 0 0
13 41 0 1 0 0 0 0 0 0 0 0 0 0
14 40 0 0 1 0 0 0 0 0 0 0 0 0
15 39 0 0 0 1 0 0 0 0 0 0 0 0
16 34 0 0 0 0 1 0 0 0 0 0 0 0
17 34 0 0 0 0 0 1 0 0 0 0 0 0
18 46 0 0 0 0 0 0 1 0 0 0 0 0
19 45 0 0 0 0 0 0 0 1 0 0 0 0
20 44 0 0 0 0 0 0 0 0 1 0 0 0
21 40 0 0 0 0 0 0 0 0 0 1 0 0
22 39 0 0 0 0 0 0 0 0 0 0 1 0
23 37 0 0 0 0 0 0 0 0 0 0 0 1
24 39 0 0 0 0 0 0 0 0 0 0 0 0
25 35 0 1 0 0 0 0 0 0 0 0 0 0
26 26 0 0 1 0 0 0 0 0 0 0 0 0
27 26 0 0 0 1 0 0 0 0 0 0 0 0
28 33 0 0 0 0 1 0 0 0 0 0 0 0
29 27 0 0 0 0 0 1 0 0 0 0 0 0
30 30 0 0 0 0 0 0 1 0 0 0 0 0
31 26 0 0 0 0 0 0 0 1 0 0 0 0
32 27 0 0 0 0 0 0 0 0 1 0 0 0
33 18 0 0 0 0 0 0 0 0 0 1 0 0
34 19 0 0 0 0 0 0 0 0 0 0 1 0
35 13 0 0 0 0 0 0 0 0 0 0 0 1
36 14 0 0 0 0 0 0 0 0 0 0 0 0
37 41 0 1 0 0 0 0 0 0 0 0 0 0
38 21 0 0 1 0 0 0 0 0 0 0 0 0
39 16 0 0 0 1 0 0 0 0 0 0 0 0
40 17 0 0 0 0 1 0 0 0 0 0 0 0
41 9 0 0 0 0 0 1 0 0 0 0 0 0
42 14 0 0 0 0 0 0 1 0 0 0 0 0
43 14 0 0 0 0 0 0 0 1 0 0 0 0
44 16 0 0 0 0 0 0 0 0 1 0 0 0
45 11 0 0 0 0 0 0 0 0 0 1 0 0
46 10 0 0 0 0 0 0 0 0 0 0 1 0
47 6 0 0 0 0 0 0 0 0 0 0 0 1
48 9 0 0 0 0 0 0 0 0 0 0 0 0
49 5 0 1 0 0 0 0 0 0 0 0 0 0
50 7 0 0 1 0 0 0 0 0 0 0 0 0
51 2 0 0 0 1 0 0 0 0 0 0 0 0
52 0 0 0 0 0 1 0 0 0 0 0 0 0
53 8 0 0 0 0 0 1 0 0 0 0 0 0
54 13 0 0 0 0 0 0 1 0 0 0 0 0
55 11 0 0 0 0 0 0 0 1 0 0 0 0
56 19 1 0 0 0 0 0 0 0 1 0 0 0
57 23 1 0 0 0 0 0 0 0 0 1 0 0
58 23 1 0 0 0 0 0 0 0 0 0 1 0
59 43 1 0 0 0 0 0 0 0 0 0 0 1
60 59 1 0 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) Val M1 M2 M3 M4
30.7 7.5 1.9 -4.9 -7.3 -6.7
M5 M6 M7 M8 M9 M10
-7.3 -2.1 -5.5 -4.4 -7.8 -7.6
M11
-4.2
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-27.60 -12.20 2.50 10.13 20.80
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 30.700 6.712 4.574 3.49e-05 ***
Val 7.500 7.323 1.024 0.311
M1 1.900 9.378 0.203 0.840
M2 -4.900 9.378 -0.523 0.604
M3 -7.300 9.378 -0.778 0.440
M4 -6.700 9.378 -0.714 0.478
M5 -7.300 9.378 -0.778 0.440
M6 -2.100 9.378 -0.224 0.824
M7 -5.500 9.378 -0.586 0.560
M8 -4.400 9.263 -0.475 0.637
M9 -7.800 9.263 -0.842 0.404
M10 -7.600 9.263 -0.820 0.416
M11 -4.200 9.263 -0.453 0.652
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 14.65 on 47 degrees of freedom
Multiple R-squared: 0.07283, Adjusted R-squared: -0.1639
F-statistic: 0.3077 on 12 and 47 DF, p-value: 0.9848
> 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,] 0.010251436 0.020502871 0.9897486
[2,] 0.003598986 0.007197973 0.9964010
[3,] 0.001844379 0.003688759 0.9981556
[4,] 0.009562862 0.019125725 0.9904371
[5,] 0.010349436 0.020698873 0.9896506
[6,] 0.010262283 0.020524566 0.9897377
[7,] 0.008281999 0.016563997 0.9917180
[8,] 0.005203114 0.010406229 0.9947969
[9,] 0.002716354 0.005432709 0.9972836
[10,] 0.001672983 0.003345966 0.9983270
[11,] 0.002344947 0.004689893 0.9976551
[12,] 0.002925554 0.005851108 0.9970744
[13,] 0.002592889 0.005185779 0.9974071
[14,] 0.003306058 0.006612116 0.9966939
[15,] 0.006017512 0.012035024 0.9939825
[16,] 0.007387743 0.014775486 0.9926123
[17,] 0.012185284 0.024370568 0.9878147
[18,] 0.022497181 0.044994362 0.9775028
[19,] 0.036601213 0.073202425 0.9633988
[20,] 0.079123386 0.158246772 0.9208766
[21,] 0.123981985 0.247963969 0.8760180
[22,] 0.299935288 0.599870577 0.7000647
[23,] 0.300549628 0.601099255 0.6994504
[24,] 0.324043562 0.648087123 0.6759564
[25,] 0.378138492 0.756276984 0.6218615
[26,] 0.353140797 0.706281593 0.6468592
[27,] 0.307075125 0.614150251 0.6929249
[28,] 0.227197139 0.454394277 0.7728029
[29,] 0.288874999 0.577749998 0.7111250
> postscript(file="/var/www/html/rcomp/tmp/11etj1228669980.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2tb5p1228669980.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/32soq1228669980.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4or3h1228669980.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/55fiw1228669980.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 7 8 9 10 11 12 13
8.4 9.2 10.6 12.0 15.6 11.4 4.8 6.7 7.1 8.9 14.5 9.3 8.4
14 15 16 17 18 19 20 21 22 23 24 25 26
14.2 15.6 10.0 10.6 17.4 19.8 17.7 17.1 15.9 10.5 8.3 2.4 0.2
27 28 29 30 31 32 33 34 35 36 37 38 39
2.6 9.0 3.6 1.4 0.8 0.7 -4.9 -4.1 -13.5 -16.7 8.4 -4.8 -7.4
40 41 42 43 44 45 46 47 48 49 50 51 52
-7.0 -14.4 -14.6 -11.2 -10.3 -11.9 -13.1 -20.5 -21.7 -27.6 -18.8 -21.4 -24.0
53 54 55 56 57 58 59 60
-15.4 -15.6 -14.2 -14.8 -7.4 -7.6 9.0 20.8
> postscript(file="/var/www/html/rcomp/tmp/6cy921228669980.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 8.4 NA
1 9.2 8.4
2 10.6 9.2
3 12.0 10.6
4 15.6 12.0
5 11.4 15.6
6 4.8 11.4
7 6.7 4.8
8 7.1 6.7
9 8.9 7.1
10 14.5 8.9
11 9.3 14.5
12 8.4 9.3
13 14.2 8.4
14 15.6 14.2
15 10.0 15.6
16 10.6 10.0
17 17.4 10.6
18 19.8 17.4
19 17.7 19.8
20 17.1 17.7
21 15.9 17.1
22 10.5 15.9
23 8.3 10.5
24 2.4 8.3
25 0.2 2.4
26 2.6 0.2
27 9.0 2.6
28 3.6 9.0
29 1.4 3.6
30 0.8 1.4
31 0.7 0.8
32 -4.9 0.7
33 -4.1 -4.9
34 -13.5 -4.1
35 -16.7 -13.5
36 8.4 -16.7
37 -4.8 8.4
38 -7.4 -4.8
39 -7.0 -7.4
40 -14.4 -7.0
41 -14.6 -14.4
42 -11.2 -14.6
43 -10.3 -11.2
44 -11.9 -10.3
45 -13.1 -11.9
46 -20.5 -13.1
47 -21.7 -20.5
48 -27.6 -21.7
49 -18.8 -27.6
50 -21.4 -18.8
51 -24.0 -21.4
52 -15.4 -24.0
53 -15.6 -15.4
54 -14.2 -15.6
55 -14.8 -14.2
56 -7.4 -14.8
57 -7.6 -7.4
58 9.0 -7.6
59 20.8 9.0
60 NA 20.8
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 9.2 8.4
[2,] 10.6 9.2
[3,] 12.0 10.6
[4,] 15.6 12.0
[5,] 11.4 15.6
[6,] 4.8 11.4
[7,] 6.7 4.8
[8,] 7.1 6.7
[9,] 8.9 7.1
[10,] 14.5 8.9
[11,] 9.3 14.5
[12,] 8.4 9.3
[13,] 14.2 8.4
[14,] 15.6 14.2
[15,] 10.0 15.6
[16,] 10.6 10.0
[17,] 17.4 10.6
[18,] 19.8 17.4
[19,] 17.7 19.8
[20,] 17.1 17.7
[21,] 15.9 17.1
[22,] 10.5 15.9
[23,] 8.3 10.5
[24,] 2.4 8.3
[25,] 0.2 2.4
[26,] 2.6 0.2
[27,] 9.0 2.6
[28,] 3.6 9.0
[29,] 1.4 3.6
[30,] 0.8 1.4
[31,] 0.7 0.8
[32,] -4.9 0.7
[33,] -4.1 -4.9
[34,] -13.5 -4.1
[35,] -16.7 -13.5
[36,] 8.4 -16.7
[37,] -4.8 8.4
[38,] -7.4 -4.8
[39,] -7.0 -7.4
[40,] -14.4 -7.0
[41,] -14.6 -14.4
[42,] -11.2 -14.6
[43,] -10.3 -11.2
[44,] -11.9 -10.3
[45,] -13.1 -11.9
[46,] -20.5 -13.1
[47,] -21.7 -20.5
[48,] -27.6 -21.7
[49,] -18.8 -27.6
[50,] -21.4 -18.8
[51,] -24.0 -21.4
[52,] -15.4 -24.0
[53,] -15.6 -15.4
[54,] -14.2 -15.6
[55,] -14.8 -14.2
[56,] -7.4 -14.8
[57,] -7.6 -7.4
[58,] 9.0 -7.6
[59,] 20.8 9.0
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 9.2 8.4
2 10.6 9.2
3 12.0 10.6
4 15.6 12.0
5 11.4 15.6
6 4.8 11.4
7 6.7 4.8
8 7.1 6.7
9 8.9 7.1
10 14.5 8.9
11 9.3 14.5
12 8.4 9.3
13 14.2 8.4
14 15.6 14.2
15 10.0 15.6
16 10.6 10.0
17 17.4 10.6
18 19.8 17.4
19 17.7 19.8
20 17.1 17.7
21 15.9 17.1
22 10.5 15.9
23 8.3 10.5
24 2.4 8.3
25 0.2 2.4
26 2.6 0.2
27 9.0 2.6
28 3.6 9.0
29 1.4 3.6
30 0.8 1.4
31 0.7 0.8
32 -4.9 0.7
33 -4.1 -4.9
34 -13.5 -4.1
35 -16.7 -13.5
36 8.4 -16.7
37 -4.8 8.4
38 -7.4 -4.8
39 -7.0 -7.4
40 -14.4 -7.0
41 -14.6 -14.4
42 -11.2 -14.6
43 -10.3 -11.2
44 -11.9 -10.3
45 -13.1 -11.9
46 -20.5 -13.1
47 -21.7 -20.5
48 -27.6 -21.7
49 -18.8 -27.6
50 -21.4 -18.8
51 -24.0 -21.4
52 -15.4 -24.0
53 -15.6 -15.4
54 -14.2 -15.6
55 -14.8 -14.2
56 -7.4 -14.8
57 -7.6 -7.4
58 9.0 -7.6
59 20.8 9.0
> 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/7eov11228669980.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ghgo1228669980.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/91l9x1228669980.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10vt6s1228669980.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11dd7o1228669980.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/12lsz61228669980.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/13h0vs1228669980.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/14xctw1228669980.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/150cey1228669980.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/160etu1228669980.tab")
+ }
>
> system("convert tmp/11etj1228669980.ps tmp/11etj1228669980.png")
> system("convert tmp/2tb5p1228669980.ps tmp/2tb5p1228669980.png")
> system("convert tmp/32soq1228669980.ps tmp/32soq1228669980.png")
> system("convert tmp/4or3h1228669980.ps tmp/4or3h1228669980.png")
> system("convert tmp/55fiw1228669980.ps tmp/55fiw1228669980.png")
> system("convert tmp/6cy921228669980.ps tmp/6cy921228669980.png")
> system("convert tmp/7eov11228669980.ps tmp/7eov11228669980.png")
> system("convert tmp/8ghgo1228669980.ps tmp/8ghgo1228669980.png")
> system("convert tmp/91l9x1228669980.ps tmp/91l9x1228669980.png")
> system("convert tmp/10vt6s1228669980.ps tmp/10vt6s1228669980.png")
>
>
> proc.time()
user system elapsed
2.358 1.552 2.843