> 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

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