R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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.
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Type 'contributors()' for more information and
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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(21.8,74.5,22,21.5,74.6,21.8,21.3,75.5,21.5,21.1,76.9,21.3,21.2,76.3,21.1,21,73.8,21.2,20.8,73.4,21,20.5,75.8,20.8,20.4,76.9,20.5,20.1,73.2,20.4,19.9,72.1,20.1,19.6,74.3,19.9,19.4,73.1,19.6,19.2,72.2,19.4,19.1,69.4,19.2,19.1,70.8,19.1,18.9,71.1,19.1,18.7,71.2,18.9,18.7,70.6,18.7,18.7,71.1,18.7,18.4,70.3,18.7,18.4,68.3,18.4,18.3,68.9,18.4,18.4,71.9,18.3,18.3,73.3,18.4,18.3,70.9,18.3,18,70,18.3,17.7,65.5,18,17.7,70.1,17.7,17.9,66.6,17.7,17.6,67.4,17.9,17.7,67.8,17.6,17.4,69.4,17.7,17.1,69.4,17.4,16.8,66.7,17.1,16.5,65,16.8,16.2,63.1,16.5,15.8,65,16.2,15.5,63.9,15.8,15.2,63,15.5,14.9,62.2,15.2,14.6,61.4,14.9,14.4,61,14.6,14.5,58.8,14.4,14.2,61,14.5),dim=c(3,45),dimnames=list(c('Constant','Mortality','Marriages'),1:45))
> y <- array(NA,dim=c(3,45),dimnames=list(c('Constant','Mortality','Marriages'),1:45))
> 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'
> library(lattice)
> library(lmtest)
Loading required package: zoo
> 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
Constant Mortality Marriages
1 21.8 74.5 22.0
2 21.5 74.6 21.8
3 21.3 75.5 21.5
4 21.1 76.9 21.3
5 21.2 76.3 21.1
6 21.0 73.8 21.2
7 20.8 73.4 21.0
8 20.5 75.8 20.8
9 20.4 76.9 20.5
10 20.1 73.2 20.4
11 19.9 72.1 20.1
12 19.6 74.3 19.9
13 19.4 73.1 19.6
14 19.2 72.2 19.4
15 19.1 69.4 19.2
16 19.1 70.8 19.1
17 18.9 71.1 19.1
18 18.7 71.2 18.9
19 18.7 70.6 18.7
20 18.7 71.1 18.7
21 18.4 70.3 18.7
22 18.4 68.3 18.4
23 18.3 68.9 18.4
24 18.4 71.9 18.3
25 18.3 73.3 18.4
26 18.3 70.9 18.3
27 18.0 70.0 18.3
28 17.7 65.5 18.0
29 17.7 70.1 17.7
30 17.9 66.6 17.7
31 17.6 67.4 17.9
32 17.7 67.8 17.6
33 17.4 69.4 17.7
34 17.1 69.4 17.4
35 16.8 66.7 17.1
36 16.5 65.0 16.8
37 16.2 63.1 16.5
38 15.8 65.0 16.2
39 15.5 63.9 15.8
40 15.2 63.0 15.5
41 14.9 62.2 15.2
42 14.6 61.4 14.9
43 14.4 61.0 14.6
44 14.5 58.8 14.4
45 14.2 61.0 14.5
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Mortality Marriages
-0.73127 0.01468 0.97490
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.21611 -0.10866 -0.03934 0.09461 0.39806
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.73127 0.48600 -1.505 0.140
Mortality 0.01468 0.01495 0.982 0.332
Marriages 0.97490 0.03429 28.429 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.151 on 42 degrees of freedom
Multiple R-squared: 0.995, Adjusted R-squared: 0.9948
F-statistic: 4177 on 2 and 42 DF, p-value: < 2.2e-16
> 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)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.46483894 0.92967789 0.53516106
[2,] 0.30636114 0.61272228 0.69363886
[3,] 0.42333182 0.84666363 0.57666818
[4,] 0.29057124 0.58114248 0.70942876
[5,] 0.21739808 0.43479615 0.78260192
[6,] 0.15459798 0.30919596 0.84540202
[7,] 0.13970672 0.27941343 0.86029328
[8,] 0.09232647 0.18465294 0.90767353
[9,] 0.06033292 0.12066584 0.93966708
[10,] 0.06651500 0.13303000 0.93348500
[11,] 0.08023112 0.16046223 0.91976888
[12,] 0.05338374 0.10676747 0.94661626
[13,] 0.03463552 0.06927104 0.96536448
[14,] 0.03402607 0.06805214 0.96597393
[15,] 0.02858369 0.05716739 0.97141631
[16,] 0.03831886 0.07663771 0.96168114
[17,] 0.03477413 0.06954825 0.96522587
[18,] 0.02050000 0.04100000 0.97950000
[19,] 0.03226948 0.06453897 0.96773052
[20,] 0.02053086 0.04106171 0.97946914
[21,] 0.01839986 0.03679972 0.98160014
[22,] 0.02458014 0.04916027 0.97541986
[23,] 0.02912258 0.05824515 0.97087742
[24,] 0.04501403 0.09002807 0.95498597
[25,] 0.25544369 0.51088739 0.74455631
[26,] 0.25412634 0.50825268 0.74587366
[27,] 0.76121625 0.47756749 0.23878375
[28,] 0.77305912 0.45388175 0.22694088
[29,] 0.90790240 0.18419520 0.09209760
[30,] 0.94831964 0.10336072 0.05168036
[31,] 0.92775419 0.14449161 0.07224581
[32,] 0.98286691 0.03426618 0.01713309
[33,] 0.95656867 0.08686266 0.04343133
[34,] 0.93529256 0.12941488 0.06470744
> postscript(file="/var/wessaorg/rcomp/tmp/1mkyi1321886405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2qydb1321886405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3pf2r1321886405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4q7q21321886405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5e6kh1321886405.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 45
Frequency = 1
1 2 3 4 5 6
-0.009951883 -0.116440439 -0.037181697 -0.062751524 0.241034451 -0.019760413
7 8 9 10 11 12
-0.018910018 -0.159157746 0.017165415 -0.131036733 -0.022422189 -0.159734337
13 14 15 16 17 18
-0.049652003 -0.041462657 0.094614701 0.171555257 -0.032848113 -0.039336669
19 20 21 22 23 24
0.164449307 0.157110356 -0.131147323 0.190677332 0.081870592 0.235326505
25 26 27 28 29 30
0.017287826 0.150004406 -0.136785482 -0.078266074 0.146684432 0.398057087
31 32 33 34 35 36
-0.108664469 0.277933222 -0.143041037 -0.150572185 -0.118472999 -0.101051714
37 38 39 40 41 42
-0.080694850 -0.216114010 -0.110009849 -0.104330885 -0.100119712 -0.095908539
43 44 45
0.002431474 0.329702092 -0.100078908
> postscript(file="/var/wessaorg/rcomp/tmp/6f3uj1321886405.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 = 45
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.009951883 NA
1 -0.116440439 -0.009951883
2 -0.037181697 -0.116440439
3 -0.062751524 -0.037181697
4 0.241034451 -0.062751524
5 -0.019760413 0.241034451
6 -0.018910018 -0.019760413
7 -0.159157746 -0.018910018
8 0.017165415 -0.159157746
9 -0.131036733 0.017165415
10 -0.022422189 -0.131036733
11 -0.159734337 -0.022422189
12 -0.049652003 -0.159734337
13 -0.041462657 -0.049652003
14 0.094614701 -0.041462657
15 0.171555257 0.094614701
16 -0.032848113 0.171555257
17 -0.039336669 -0.032848113
18 0.164449307 -0.039336669
19 0.157110356 0.164449307
20 -0.131147323 0.157110356
21 0.190677332 -0.131147323
22 0.081870592 0.190677332
23 0.235326505 0.081870592
24 0.017287826 0.235326505
25 0.150004406 0.017287826
26 -0.136785482 0.150004406
27 -0.078266074 -0.136785482
28 0.146684432 -0.078266074
29 0.398057087 0.146684432
30 -0.108664469 0.398057087
31 0.277933222 -0.108664469
32 -0.143041037 0.277933222
33 -0.150572185 -0.143041037
34 -0.118472999 -0.150572185
35 -0.101051714 -0.118472999
36 -0.080694850 -0.101051714
37 -0.216114010 -0.080694850
38 -0.110009849 -0.216114010
39 -0.104330885 -0.110009849
40 -0.100119712 -0.104330885
41 -0.095908539 -0.100119712
42 0.002431474 -0.095908539
43 0.329702092 0.002431474
44 -0.100078908 0.329702092
45 NA -0.100078908
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.116440439 -0.009951883
[2,] -0.037181697 -0.116440439
[3,] -0.062751524 -0.037181697
[4,] 0.241034451 -0.062751524
[5,] -0.019760413 0.241034451
[6,] -0.018910018 -0.019760413
[7,] -0.159157746 -0.018910018
[8,] 0.017165415 -0.159157746
[9,] -0.131036733 0.017165415
[10,] -0.022422189 -0.131036733
[11,] -0.159734337 -0.022422189
[12,] -0.049652003 -0.159734337
[13,] -0.041462657 -0.049652003
[14,] 0.094614701 -0.041462657
[15,] 0.171555257 0.094614701
[16,] -0.032848113 0.171555257
[17,] -0.039336669 -0.032848113
[18,] 0.164449307 -0.039336669
[19,] 0.157110356 0.164449307
[20,] -0.131147323 0.157110356
[21,] 0.190677332 -0.131147323
[22,] 0.081870592 0.190677332
[23,] 0.235326505 0.081870592
[24,] 0.017287826 0.235326505
[25,] 0.150004406 0.017287826
[26,] -0.136785482 0.150004406
[27,] -0.078266074 -0.136785482
[28,] 0.146684432 -0.078266074
[29,] 0.398057087 0.146684432
[30,] -0.108664469 0.398057087
[31,] 0.277933222 -0.108664469
[32,] -0.143041037 0.277933222
[33,] -0.150572185 -0.143041037
[34,] -0.118472999 -0.150572185
[35,] -0.101051714 -0.118472999
[36,] -0.080694850 -0.101051714
[37,] -0.216114010 -0.080694850
[38,] -0.110009849 -0.216114010
[39,] -0.104330885 -0.110009849
[40,] -0.100119712 -0.104330885
[41,] -0.095908539 -0.100119712
[42,] 0.002431474 -0.095908539
[43,] 0.329702092 0.002431474
[44,] -0.100078908 0.329702092
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.116440439 -0.009951883
2 -0.037181697 -0.116440439
3 -0.062751524 -0.037181697
4 0.241034451 -0.062751524
5 -0.019760413 0.241034451
6 -0.018910018 -0.019760413
7 -0.159157746 -0.018910018
8 0.017165415 -0.159157746
9 -0.131036733 0.017165415
10 -0.022422189 -0.131036733
11 -0.159734337 -0.022422189
12 -0.049652003 -0.159734337
13 -0.041462657 -0.049652003
14 0.094614701 -0.041462657
15 0.171555257 0.094614701
16 -0.032848113 0.171555257
17 -0.039336669 -0.032848113
18 0.164449307 -0.039336669
19 0.157110356 0.164449307
20 -0.131147323 0.157110356
21 0.190677332 -0.131147323
22 0.081870592 0.190677332
23 0.235326505 0.081870592
24 0.017287826 0.235326505
25 0.150004406 0.017287826
26 -0.136785482 0.150004406
27 -0.078266074 -0.136785482
28 0.146684432 -0.078266074
29 0.398057087 0.146684432
30 -0.108664469 0.398057087
31 0.277933222 -0.108664469
32 -0.143041037 0.277933222
33 -0.150572185 -0.143041037
34 -0.118472999 -0.150572185
35 -0.101051714 -0.118472999
36 -0.080694850 -0.101051714
37 -0.216114010 -0.080694850
38 -0.110009849 -0.216114010
39 -0.104330885 -0.110009849
40 -0.100119712 -0.104330885
41 -0.095908539 -0.100119712
42 0.002431474 -0.095908539
43 0.329702092 0.002431474
44 -0.100078908 0.329702092
> 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/wessaorg/rcomp/tmp/79h261321886405.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/wessaorg/rcomp/tmp/8zptm1321886405.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/wessaorg/rcomp/tmp/9ar411321886405.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/wessaorg/rcomp/tmp/10qicf1321886405.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11xf7o1321886406.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12nxr11321886406.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/134bij1321886406.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14ed3o1321886406.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/wessaorg/rcomp/tmp/15v6uu1321886406.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/wessaorg/rcomp/tmp/16wog61321886406.tab")
+ }
>
> try(system("convert tmp/1mkyi1321886405.ps tmp/1mkyi1321886405.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qydb1321886405.ps tmp/2qydb1321886405.png",intern=TRUE))
character(0)
> try(system("convert tmp/3pf2r1321886405.ps tmp/3pf2r1321886405.png",intern=TRUE))
character(0)
> try(system("convert tmp/4q7q21321886405.ps tmp/4q7q21321886405.png",intern=TRUE))
character(0)
> try(system("convert tmp/5e6kh1321886405.ps tmp/5e6kh1321886405.png",intern=TRUE))
character(0)
> try(system("convert tmp/6f3uj1321886405.ps tmp/6f3uj1321886405.png",intern=TRUE))
character(0)
> try(system("convert tmp/79h261321886405.ps tmp/79h261321886405.png",intern=TRUE))
character(0)
> try(system("convert tmp/8zptm1321886405.ps tmp/8zptm1321886405.png",intern=TRUE))
character(0)
> try(system("convert tmp/9ar411321886405.ps tmp/9ar411321886405.png",intern=TRUE))
character(0)
> try(system("convert tmp/10qicf1321886405.ps tmp/10qicf1321886405.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.096 0.490 3.636