[R] Constrained Poisson model / Bayesian Poisson model
dwinsemius at comcast.net
Fri Jan 22 18:40:53 CET 2016
> On Jan 22, 2016, at 7:01 AM, mara.pfleiderer at 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().
Alameda, CA, USA
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