> On Jan 22, 2016, at 7:01 AM, mara.pfleide...@uni-ulm.de wrote: > > Hi all, > > I am dealing with a problem about my linear Poisson regression model (link > function=identity). > > I am using the glm()-function which results in negative coefficients, but a > negative influence of the regressors wouldn't make sense.
Negative coefficients merely indicate a lower relative rate. You need to be more specific about the exactly data and model output before you can raise our concern to a level where further comment can be made. > > (i) Is there a possibility to set constraints on the regression parameters in > glm() such that all coefficients are positive? Or is there another function > in R for which this is possible? > > (ii) Is there a Bayesian version of the glm()-function where I can specify > the prior distribution for my regression parameters? (e.g. a Dirichlet prior > s.t. the parameters are positive) > > All this with respect to the linear Poisson model... As I implied above, the word "linear" means something different than "additive" when the link is log(). -- David Winsemius Alameda, CA, USA ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
