Can I Use the loo function to help me choose between a Poisson and Bernouilli distribution in bayesian I have two models exactly similar, but I’m using a Poisson distribution for one and a Bernoulli distribution for the other. Can I trust the information coming out of loo to help me choose?
The Bernoulli model comes on top.
rbpa <- brm(status ~ ... , family = poisson(), prior = 
            set_prior('normal(0, 4)', class = 'b'),  
            cores = 6, iter = 4000)

rbba <- brm(status ~ ... , family = bernoulli, 
            prior(normal(0, 4), class = b), cores = 6, 
            iter = 4000)

loo(rbpa,rbba)


Methods for model selection like loo have nothing to do with the problem. Bernoulli distribution is a distribution for the binary variable (0's or 1's) while Poisson distribution can take any non-negative integers like counts. You can't use Bernoulli distribution instead of Poisson or the other way around.
