R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-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.
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(5.029
+ ,4.768
+ ,4.812
+ ,5.302
+ ,5.562
+ ,5.307
+ ,5.350
+ ,5.372
+ ,5.199
+ ,5.070
+ ,4.552
+ ,24.994
+ ,23.191
+ ,22.269
+ ,23.291
+ ,24.151
+ ,24.046
+ ,25.278
+ ,25.919
+ ,26.277
+ ,25.048
+ ,24.926
+ ,6.639
+ ,6.100
+ ,6.054
+ ,6.321
+ ,6.702
+ ,6.671
+ ,7.101
+ ,7.353
+ ,7.320
+ ,7.117
+ ,6.999
+ ,3.451
+ ,3.099
+ ,2.936
+ ,3.116
+ ,3.286
+ ,3.398
+ ,3.435
+ ,3.657
+ ,3.699
+ ,3.526
+ ,3.493
+ ,5.844
+ ,5.409
+ ,5.263
+ ,5.391
+ ,5.609
+ ,5.429
+ ,5.835
+ ,5.995
+ ,6.234
+ ,5.812
+ ,5.874
+ ,3.954
+ ,3.603
+ ,3.587
+ ,3.765
+ ,3.842
+ ,3.834
+ ,4.039
+ ,3.977
+ ,4.065
+ ,3.907
+ ,3.881
+ ,5.106
+ ,4.980
+ ,4.429
+ ,4.698
+ ,4.712
+ ,4.714
+ ,4.868
+ ,4.937
+ ,4.959
+ ,4.686
+ ,4.679
+ ,15.100
+ ,14.151
+ ,13.353
+ ,13.184
+ ,13.583
+ ,13.788
+ ,14.185
+ ,14.270
+ ,14.137
+ ,13.185
+ ,12.681
+ ,279
+ ,274
+ ,277
+ ,266
+ ,279
+ ,256
+ ,283
+ ,328
+ ,335
+ ,282
+ ,287
+ ,1.567
+ ,1.451
+ ,1.439
+ ,1.441
+ ,1.562
+ ,1.532
+ ,1.616
+ ,1.497
+ ,1.578
+ ,1.430
+ ,1.411
+ ,5.616
+ ,5.082
+ ,4.801
+ ,4.676
+ ,4.826
+ ,4.851
+ ,4.990
+ ,5.149
+ ,4.934
+ ,4.728
+ ,4.524
+ ,4.560
+ ,4.425
+ ,4.182
+ ,4.170
+ ,4.321
+ ,4.318
+ ,4.429
+ ,4.518
+ ,4.441
+ ,4.063
+ ,3.946
+ ,1.262
+ ,1.277
+ ,1.158
+ ,1.121
+ ,1.102
+ ,1.209
+ ,1.212
+ ,1.253
+ ,1.229
+ ,1.133
+ ,1.141
+ ,2.095
+ ,1.916
+ ,1.773
+ ,1.776
+ ,1.772
+ ,1.878
+ ,1.938
+ ,1.853
+ ,1.955
+ ,1.831
+ ,1.659)
+ ,dim=c(11
+ ,14)
+ ,dimnames=list(c('2000'
+ ,'2001'
+ ,'2002'
+ ,'2003'
+ ,'2004'
+ ,'2005'
+ ,'2006'
+ ,'2007'
+ ,'2008'
+ ,'2009'
+ ,'2010')
+ ,1:14))
> y <- array(NA,dim=c(11,14),dimnames=list(c('2000','2001','2002','2003','2004','2005','2006','2007','2008','2009','2010'),1:14))
> 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'
> 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, 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
2000 2001 2002 2003 2004 2005 2006 2007 2008
1 5.029 4.768 4.812 5.302 5.562 5.307 5.350 5.372 5.199
2 24.994 23.191 22.269 23.291 24.151 24.046 25.278 25.919 26.277
3 6.639 6.100 6.054 6.321 6.702 6.671 7.101 7.353 7.320
4 3.451 3.099 2.936 3.116 3.286 3.398 3.435 3.657 3.699
5 5.844 5.409 5.263 5.391 5.609 5.429 5.835 5.995 6.234
6 3.954 3.603 3.587 3.765 3.842 3.834 4.039 3.977 4.065
7 5.106 4.980 4.429 4.698 4.712 4.714 4.868 4.937 4.959
8 15.100 14.151 13.353 13.184 13.583 13.788 14.185 14.270 14.137
9 279.000 274.000 277.000 266.000 279.000 256.000 283.000 328.000 335.000
10 1.567 1.451 1.439 1.441 1.562 1.532 1.616 1.497 1.578
11 5.616 5.082 4.801 4.676 4.826 4.851 4.990 5.149 4.934
12 4.560 4.425 4.182 4.170 4.321 4.318 4.429 4.518 4.441
13 1.262 1.277 1.158 1.121 1.102 1.209 1.212 1.253 1.229
14 2.095 1.916 1.773 1.776 1.772 1.878 1.938 1.853 1.955
2009 2010
1 5.070 4.552
2 25.048 24.926
3 7.117 6.999
4 3.526 3.493
5 5.812 5.874
6 3.907 3.881
7 4.686 4.679
8 13.185 12.681
9 282.000 287.000
10 1.430 1.411
11 4.728 4.524
12 4.063 3.946
13 1.133 1.141
14 1.831 1.659
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `2001` `2002` `2003` `2004` `2005`
-0.003798 0.744621 1.469476 -1.106998 0.445419 0.705384
`2006` `2007` `2008` `2009` `2010`
-1.593076 -0.850059 -0.290292 1.657276 0.059580
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
1 2 3 4 5 6 7 8
-0.015163 0.003544 -0.013063 0.024701 -0.054450 0.044969 0.016578 -0.011290
9 10 11 12 13 14
0.000274 0.045625 0.039152 -0.013952 -0.082427 0.015502
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.003798 0.032571 -0.117 0.9145
`2001` 0.744621 0.301762 2.468 0.0903 .
`2002` 1.469476 0.460860 3.189 0.0498 *
`2003` -1.106998 0.560290 -1.976 0.1426
`2004` 0.445419 0.639927 0.696 0.5365
`2005` 0.705384 0.477564 1.477 0.2362
`2006` -1.593076 0.705436 -2.258 0.1091
`2007` -0.850059 0.348086 -2.442 0.0923 .
`2008` -0.290292 0.300657 -0.966 0.4055
`2009` 1.657276 0.551187 3.007 0.0574 .
`2010` 0.059580 0.353018 0.169 0.8767
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.07584 on 3 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 1.207e+06 on 10 and 3 DF, p-value: 1.118e-09
> 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
+ }
> postscript(file="/var/wessaorg/rcomp/tmp/1rthx1351937036.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2t4bi1351937036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3sbfy1351937036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4nxlt1351937036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/52g1i1351937036.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 = 14
Frequency = 1
1 2 3 4 5
-0.0151632313 0.0035440906 -0.0130629655 0.0247013658 -0.0544504894
6 7 8 9 10
0.0449688611 0.0165779142 -0.0112900597 0.0002739783 0.0456248471
11 12 13 14
0.0391520250 -0.0139516965 -0.0824270917 0.0155024520
> postscript(file="/var/wessaorg/rcomp/tmp/65qit1351937036.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 = 14
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.0151632313 NA
1 0.0035440906 -0.0151632313
2 -0.0130629655 0.0035440906
3 0.0247013658 -0.0130629655
4 -0.0544504894 0.0247013658
5 0.0449688611 -0.0544504894
6 0.0165779142 0.0449688611
7 -0.0112900597 0.0165779142
8 0.0002739783 -0.0112900597
9 0.0456248471 0.0002739783
10 0.0391520250 0.0456248471
11 -0.0139516965 0.0391520250
12 -0.0824270917 -0.0139516965
13 0.0155024520 -0.0824270917
14 NA 0.0155024520
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.0035440906 -0.0151632313
[2,] -0.0130629655 0.0035440906
[3,] 0.0247013658 -0.0130629655
[4,] -0.0544504894 0.0247013658
[5,] 0.0449688611 -0.0544504894
[6,] 0.0165779142 0.0449688611
[7,] -0.0112900597 0.0165779142
[8,] 0.0002739783 -0.0112900597
[9,] 0.0456248471 0.0002739783
[10,] 0.0391520250 0.0456248471
[11,] -0.0139516965 0.0391520250
[12,] -0.0824270917 -0.0139516965
[13,] 0.0155024520 -0.0824270917
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.0035440906 -0.0151632313
2 -0.0130629655 0.0035440906
3 0.0247013658 -0.0130629655
4 -0.0544504894 0.0247013658
5 0.0449688611 -0.0544504894
6 0.0165779142 0.0449688611
7 -0.0112900597 0.0165779142
8 0.0002739783 -0.0112900597
9 0.0456248471 0.0002739783
10 0.0391520250 0.0456248471
11 -0.0139516965 0.0391520250
12 -0.0824270917 -0.0139516965
13 0.0155024520 -0.0824270917
> 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/7zi501351937036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/833xw1351937036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9bpmw1351937036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
2: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/1003qn1351937036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11cm2a1351937036.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/12c1il1351937036.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/13k4951351937036.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/14iiz91351937036.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/15azft1351937036.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/168fov1351937036.tab")
+ }
>
> try(system("convert tmp/1rthx1351937036.ps tmp/1rthx1351937036.png",intern=TRUE))
character(0)
> try(system("convert tmp/2t4bi1351937036.ps tmp/2t4bi1351937036.png",intern=TRUE))
character(0)
> try(system("convert tmp/3sbfy1351937036.ps tmp/3sbfy1351937036.png",intern=TRUE))
character(0)
> try(system("convert tmp/4nxlt1351937036.ps tmp/4nxlt1351937036.png",intern=TRUE))
character(0)
> try(system("convert tmp/52g1i1351937036.ps tmp/52g1i1351937036.png",intern=TRUE))
character(0)
> try(system("convert tmp/65qit1351937036.ps tmp/65qit1351937036.png",intern=TRUE))
character(0)
> try(system("convert tmp/7zi501351937036.ps tmp/7zi501351937036.png",intern=TRUE))
character(0)
> try(system("convert tmp/833xw1351937036.ps tmp/833xw1351937036.png",intern=TRUE))
character(0)
> try(system("convert tmp/9bpmw1351937036.ps tmp/9bpmw1351937036.png",intern=TRUE))
character(0)
> try(system("convert tmp/1003qn1351937036.ps tmp/1003qn1351937036.png",intern=TRUE))
convert: unable to open image `tmp/1003qn1351937036.ps': @ error/blob.c/OpenBlob/2587.
convert: missing an image filename `tmp/1003qn1351937036.png' @ error/convert.c/ConvertImageCommand/3011.
character(0)
attr(,"status")
[1] 1
Warning message:
running command 'convert tmp/1003qn1351937036.ps tmp/1003qn1351937036.png' had status 1
>
>
> proc.time()
user system elapsed
5.063 1.004 6.160