Hi, Im carrying out some Bayesian analysis using a binomial response variable (proportion: 0 to 1), but most of my observations have a value of 0 and many have very small values (i.e. 0.001). I'm having troubles getting my MCMC algorithm to converge, so I have decided to try normalising my response variable to see if this helps.
I want it to stay between 0 and 1 but to have a larger range of values, or just for them all to be slightly higher. Does anyone know the best way to acheive this? I could just add a value to each observation (say 10 to increase the proportion a bit, but ensuring it would still be between 0 and 1) - would that be ok? Or is there a better way to stretch the values up? Sorry - i know its not really an R specific question, but I have never found a forum with as many stats litterate people as this one :-) Cheers - any advice much appreciated! nicola -- View this message in context: http://www.nabble.com/%27stretching%27-a-binomial-variable-tp22740114p22740114.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.