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.
(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...
Thanks in advance!
Best,
Mara
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