search for: region1

..., I cannot use it for 2 and get the message “Erreur dans regcalibrate.survey.design2(design, formula, population, aggregate.stage = aggregate.stage, : Population and sample totals are not the same length.” Here is the format I use as a data.frame: ecodiaMG[1:10, 71:73] age_cl1 sexe1 region1 1 MG_54 MG_H MG_NE 2 MG_54 MG_H MG_NE 3 MG_54 MG_H MG_NE 4 MG_54 MG_H MG_NE 5 MG_54 MG_H MG_NE 6 MG_54 MG_H MG_NE 7 MG_54 MG_H MG_NE 8 MG_54 MG_H MG_NE 9 MG_54 MG_H MG_NE 10 MG_54 MG_H MG_NE … My program is: grap<-svydesi...

Hi, Alan Really very excited to receive your email and sorry to be slow replying, it has been exceptionally busy over the last few days ;( Your explanation made the problem clear to me. So gcov branch coverage should be called condition coverage and clang region coverage is branch coverage in fact(also known as *decision/C1*), right? And llvm/clang will support all the following coverage

...y that clang region coverage is branch coverage(‘aka > decision coverage’). I would say that it may be possible to extrapolate > branch decision coverage based on region coverage. For example, consider > the following: > > > > [region0] > > if (decision) { > > [region1] > > } > > > > Region coverage will tell you that whether [region1] was executed, and > this will be enough to tell you that the branch decision evaluated to True > at least once. However, this will not tell you how many times the decision > evaluated to False, which is...

...0){ wd1<-paste(wd,wd0,"Input\\.", sep = "\\") d<-read.table(choose.files(default = wd1, caption = "Escolher o Ficheiro de Input - *.txt ", multi = FALSE), head=T,sep="\t",dec=".") return(d)} reg<-"Region1" import(reg) reg<-"Region2" import(reg) export<-function(wd0,var1,trim){ wd1<-paste(wd,wd0,trim,"Output\\.", sep = "\\") d<- write.table(var1,"C:/Teste/Region/Trim/Output/var1.txt",sep="\t",dec=&qu...

...out_150.txt", header=TRUE )) colnames(datain) <- c("geogid","long","lat","cluster") #Set up screen device #split 2x2 - permits 1 map per section par(bg="white") split.screen(c(2,2)) #Load maps once only w <- read.shape("c:\\data\\region1.shp", dbf.data = TRUE) x <- read.shape("c:\\data\\region2.shp", dbf.data = TRUE) y <- read.shape("c:\\data\\region3.shp", dbf.data = TRUE) z <- read.shape("c:\\data\\region4.shp", dbf.data = TRUE) #Loop through the clusters and produce maps of each regio...

On Wed, 2 Aug 2000 p.dalgaard@biostat.ku.dk wrote: > Martin Maechler <maechler@stat.math.ethz.ch> writes: > > > (from R-help) > > PD> Stephen Eglen <stephen@cogsci.ed.ac.uk> writes: > > > > > > > generated by R into a latex document. Specifically, the latex package > > > > > graphicsx allow you to specify the

Sarah et. al.: As a matter of aesthetics (i.e. my personal ocd-ness) I prefer using the public API of an object, i.e. *not* to makes use of the representation of a factor as essentially an integer vector with labels, but rather to use its documented behavior. (Feel free to ignore this remark!) Anyway, >cumsum(!duplicated(dat1$B)) [1] 1 1 1 2 2 3 3 3 3 3 4 4 will do it. This is very