Emmanuel Charpentier wrote: > > I do not understand the problem as stated. if x[i] and n[i] are known, > and unless sum(n)=0, your dataset reduces to a set of nrow(dataset) > independent linear equations with nrow(dataset) unknowns (the beta[i]), > whose solution is trivially beta[i]=log(x[i]/n[i])-log(sum(x)/sum(n), > except when n[i]=0 in which case your equation has no solution. > Could you try to re-express your problem ? >
This is taken from this article: "Methods for confidence interval estimation of a ratio parameter with application to location quotients". The authors argue that it's not the solution to find beta that they're after but the side effect of having the profile-likelihood confidence intervals in the estimation process. Those guys say they used the SAS "Genmod" procedure. I thought I could use glm in R and find the profile-likelihood CIs using "confint" on the glm results. -- View this message in context: http://www.nabble.com/User-defined-GLM--tp24150859p24154447.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
