R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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> x <- array(list(0.916,1.5,0.900,3.5,0.898,3.1,0.894,4.1,-0.305,5.0,-0.300,3.7,-0.299,3.6,-0.298,1.8,5.395,-2.5,5.300,-1.4,5.627,-2.3,5.981,-1.5,-0.527,4.2,-0.700,2.8,-1.600,4.4,-2.177,5.0,-1.648,2.8,-1.666,3.5,-1.335,2.6,-1.394,2.7,-1.300,2.7,-1.134,2.1,-0.602,2.3,-0.370,2.3,-0.151,1.8,0.400,1.1,0.238,0.4,0.441,0.3),dim=c(2,28),dimnames=list(c('dch','cr'),1:28))
> y <- array(NA,dim=c(2,28),dimnames=list(c('dch','cr'),1:28))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par5 = '0'
> par4 = '0'
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> par5 <- '0'
> par4 <- '0'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '1'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Sun, 06 Dec 2015 16:18:54 +0000)
> #Author: root
> #To cite this work: Wessa P., (2015), Multiple Regression (v1.0.38) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_multipleregression.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following objects are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> mywarning <- ''
> par1 <- as.numeric(par1)
> if(is.na(par1)) {
+ par1 <- 1
+ mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.'
+ }
> if (par4=='') par4 <- 0
> par4 <- as.numeric(par4)
> if (par5=='') par5 <- 0
> par5 <- as.numeric(par5)
> x <- na.omit(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'){
+ (n <- n -1)
+ x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par3 == 'Seasonal Differences (s=12)'){
+ (n <- n - 12)
+ x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
+ for (i in 1:n) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+12,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par3 == 'First and Seasonal Differences (s=12)'){
+ (n <- n -1)
+ x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ (n <- n - 12)
+ x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B12)',colnames(x),sep='')))
+ for (i in 1:n) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+12,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if(par4 > 0) {
+ x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep='')))
+ for (i in 1:(n-par4)) {
+ for (j in 1:par4) {
+ x2[i,j] <- x[i+par4-j,par1]
+ }
+ }
+ x <- cbind(x[(par4+1):n,], x2)
+ n <- n - par4
+ }
> if(par5 > 0) {
+ x2 <- array(0, dim=c(n-par5*12,par5), dimnames=list(1:(n-par5*12), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep='')))
+ for (i in 1:(n-par5*12)) {
+ for (j in 1:par5) {
+ x2[i,j] <- x[i+par5*12-j*12,par1]
+ }
+ }
+ x <- cbind(x[(par5*12+1):n,], x2)
+ n <- n - par5*12
+ }
> 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[n,]))
[1] 2
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
dch cr
1 0.916 1.5
2 0.900 3.5
3 0.898 3.1
4 0.894 4.1
5 -0.305 5.0
6 -0.300 3.7
7 -0.299 3.6
8 -0.298 1.8
9 5.395 -2.5
10 5.300 -1.4
11 5.627 -2.3
12 5.981 -1.5
13 -0.527 4.2
14 -0.700 2.8
15 -1.600 4.4
16 -2.177 5.0
17 -1.648 2.8
18 -1.666 3.5
19 -1.335 2.6
20 -1.394 2.7
21 -1.300 2.7
22 -1.134 2.1
23 -0.602 2.3
24 -0.370 2.3
25 -0.151 1.8
26 0.400 1.1
27 0.238 0.4
28 0.441 0.3
> (k <- length(x[n,]))
[1] 2
> head(x)
dch cr
1 0.916 1.5
2 0.900 3.5
3 0.898 3.1
4 0.894 4.1
5 -0.305 5.0
6 -0.300 3.7
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) cr
2.3762 -0.9287
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.7668 -1.0441 -0.2715 1.0267 2.3255
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.3762 0.3609 6.584 5.55e-07 ***
cr -0.9287 0.1226 -7.573 4.87e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.319 on 26 degrees of freedom
Multiple R-squared: 0.6881, Adjusted R-squared: 0.6761
F-statistic: 57.36 on 1 and 26 DF, p-value: 4.866e-08
> 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,] 0.08387572 0.1677514479 0.9161242760
[2,] 0.10510912 0.2102182469 0.8948908765
[3,] 0.10003494 0.2000698797 0.8999650601
[4,] 0.12184291 0.2436858277 0.8781570861
[5,] 0.38352051 0.7670410199 0.6164794901
[6,] 0.45801425 0.9160284982 0.5419857509
[7,] 0.42040734 0.8408146863 0.5795926569
[8,] 0.99342586 0.0131482702 0.0065741351
[9,] 0.99905005 0.0018999023 0.0009499511
[10,] 0.99931199 0.0013760135 0.0006880068
[11,] 0.99922395 0.0015520976 0.0007760488
[12,] 0.99918495 0.0016301075 0.0008150538
[13,] 0.99956321 0.0008735723 0.0004367862
[14,] 0.99892098 0.0021580418 0.0010790209
[15,] 0.99825167 0.0034966626 0.0017483313
[16,] 0.99695623 0.0060875472 0.0030437736
[17,] 0.99417803 0.0116439447 0.0058219723
[18,] 0.99888908 0.0022218416 0.0011109208
[19,] 0.99613042 0.0077391686 0.0038695843
> postscript(file="/var/wessaorg/rcomp/tmp/1eoom1458028191.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2wuf71458028191.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/34fa21458028191.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4gn9e1458028191.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5qjnw1458028191.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 = 28
Frequency = 1
1 2 3 4 5 6
-0.06718696 1.77422609 1.40074348 2.32545000 1.96228587 0.75996739
7 8 9 10 11 12
0.66809674 -1.00257500 0.69698696 1.62356413 1.11472826 2.21169348
13 14 15 16 17 18
0.99732065 -0.47586848 0.11006196 0.09028587 -1.42386848 -0.79177391
19 20 21 22 23 24
-1.29660978 -1.26273913 -1.16873913 -1.55996304 -0.84222174 -0.61022174
25 26 27 28
-0.85557500 -0.95466957 -1.76676413 -1.65663478
> postscript(file="/var/wessaorg/rcomp/tmp/6ypni1458028191.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 = 28
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.06718696 NA
1 1.77422609 -0.06718696
2 1.40074348 1.77422609
3 2.32545000 1.40074348
4 1.96228587 2.32545000
5 0.75996739 1.96228587
6 0.66809674 0.75996739
7 -1.00257500 0.66809674
8 0.69698696 -1.00257500
9 1.62356413 0.69698696
10 1.11472826 1.62356413
11 2.21169348 1.11472826
12 0.99732065 2.21169348
13 -0.47586848 0.99732065
14 0.11006196 -0.47586848
15 0.09028587 0.11006196
16 -1.42386848 0.09028587
17 -0.79177391 -1.42386848
18 -1.29660978 -0.79177391
19 -1.26273913 -1.29660978
20 -1.16873913 -1.26273913
21 -1.55996304 -1.16873913
22 -0.84222174 -1.55996304
23 -0.61022174 -0.84222174
24 -0.85557500 -0.61022174
25 -0.95466957 -0.85557500
26 -1.76676413 -0.95466957
27 -1.65663478 -1.76676413
28 NA -1.65663478
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.77422609 -0.06718696
[2,] 1.40074348 1.77422609
[3,] 2.32545000 1.40074348
[4,] 1.96228587 2.32545000
[5,] 0.75996739 1.96228587
[6,] 0.66809674 0.75996739
[7,] -1.00257500 0.66809674
[8,] 0.69698696 -1.00257500
[9,] 1.62356413 0.69698696
[10,] 1.11472826 1.62356413
[11,] 2.21169348 1.11472826
[12,] 0.99732065 2.21169348
[13,] -0.47586848 0.99732065
[14,] 0.11006196 -0.47586848
[15,] 0.09028587 0.11006196
[16,] -1.42386848 0.09028587
[17,] -0.79177391 -1.42386848
[18,] -1.29660978 -0.79177391
[19,] -1.26273913 -1.29660978
[20,] -1.16873913 -1.26273913
[21,] -1.55996304 -1.16873913
[22,] -0.84222174 -1.55996304
[23,] -0.61022174 -0.84222174
[24,] -0.85557500 -0.61022174
[25,] -0.95466957 -0.85557500
[26,] -1.76676413 -0.95466957
[27,] -1.65663478 -1.76676413
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.77422609 -0.06718696
2 1.40074348 1.77422609
3 2.32545000 1.40074348
4 1.96228587 2.32545000
5 0.75996739 1.96228587
6 0.66809674 0.75996739
7 -1.00257500 0.66809674
8 0.69698696 -1.00257500
9 1.62356413 0.69698696
10 1.11472826 1.62356413
11 2.21169348 1.11472826
12 0.99732065 2.21169348
13 -0.47586848 0.99732065
14 0.11006196 -0.47586848
15 0.09028587 0.11006196
16 -1.42386848 0.09028587
17 -0.79177391 -1.42386848
18 -1.29660978 -0.79177391
19 -1.26273913 -1.29660978
20 -1.16873913 -1.26273913
21 -1.55996304 -1.16873913
22 -0.84222174 -1.55996304
23 -0.61022174 -0.84222174
24 -0.85557500 -0.61022174
25 -0.95466957 -0.85557500
26 -1.76676413 -0.95466957
27 -1.65663478 -1.76676413
> 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/7h4tx1458028191.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8k4eu1458028191.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9506r1458028191.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10w4921458028191.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
+ if (rownames(mysum$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.row.start(a)
> a<-table.element(a, mywarning)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/115rjv1458028191.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$coefficients)[i],header=TRUE)
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+'))
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+'))
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' '))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12hxoq1458028191.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,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[2],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, signif(mysum$fstatistic[3],6))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a,formatC(signif(mysum$sigma,6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' '))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13nhy41458028191.tab")
> if(n < 200) {
+ 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,formatC(signif(x[i],6),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' '))
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/14uniy1458028191.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,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' '))
+ a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' '))
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/15bkoo1458028191.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,signif(numsignificant1,6))
+ a<-table.element(a,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' '))
+ 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,signif(numsignificant5,6))
+ a<-table.element(a,signif(numsignificant5/numgqtests,6))
+ 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,signif(numsignificant10,6))
+ a<-table.element(a,signif(numsignificant10/numgqtests,6))
+ 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/16jxu11458028191.tab")
+ }
+ }
>
> try(system("convert tmp/1eoom1458028191.ps tmp/1eoom1458028191.png",intern=TRUE))
character(0)
> try(system("convert tmp/2wuf71458028191.ps tmp/2wuf71458028191.png",intern=TRUE))
character(0)
> try(system("convert tmp/34fa21458028191.ps tmp/34fa21458028191.png",intern=TRUE))
character(0)
> try(system("convert tmp/4gn9e1458028191.ps tmp/4gn9e1458028191.png",intern=TRUE))
character(0)
> try(system("convert tmp/5qjnw1458028191.ps tmp/5qjnw1458028191.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ypni1458028191.ps tmp/6ypni1458028191.png",intern=TRUE))
character(0)
> try(system("convert tmp/7h4tx1458028191.ps tmp/7h4tx1458028191.png",intern=TRUE))
character(0)
> try(system("convert tmp/8k4eu1458028191.ps tmp/8k4eu1458028191.png",intern=TRUE))
character(0)
> try(system("convert tmp/9506r1458028191.ps tmp/9506r1458028191.png",intern=TRUE))
character(0)
> try(system("convert tmp/10w4921458028191.ps tmp/10w4921458028191.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.652 0.648 4.349