Hello,
I'm a mathematics student at Ulm University and currently I am working
on my bachelor thesis about a Poisson regression model.
For this, I am using the function glm () in R which is working very well.
But still I have two questions to improve my model and I hope that you
could help me:
(i) Is there a possibility to set constraints on the regression
parameters in glm() or is there another function in R?
Specifically, my paramters should be constrained to be positive as
negative parameters wouldn't make sense. How can I do this in R
(preferably with glm() or similar functions)?
(ii) Is there a Bayesian version of the glm()-function where I can
specify the prior distribution for my regression parameters?
Thanks in advance!
Kind regards,
Mara Pfleiderer
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