[R] Bayesian logistic regression with a beta prior (MCMClogit)

[francogrex]

Hi, yes but I realized afterwards that it's the logfun argument that had to
be put to logfun=F and the logpriorfun function had to be log=F
logpriorfun <- function(beta,shape1,shape2){
sum(dbeta(beta,shape1,shape2,log=F)) }

But that's just for that particular example. I find I am having problems
still even after adjusting for that. Using other data it is not accepting
the estimation of beta.start with maximum likelihood
("user.prior.density(beta.start) <= 0") and it is obliging me to specify it
giving me a very narrow range, and hence the acceptance rate of the output
is very mediocre (0.01)... I don't know I am missing something here maybe.
What I want to say is that it is a very good package, noone get me wrong
please, it's just me, I am having difficulty using it like I should.


Cody_Hamilton wrote:
> 
> Dear Franco,
> 
> Have you tried using the beta.start option in MCMClogit?  (The problem may
> be where you are starting your chain.)
> 
> Regards,
>    -Cody                                                        
>         

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