Given a model that uses Binomial distribution for likelihood, and Beta distribution for Prior. The product of the two which generates the Posterior is also a Beta distribution.

Dec 16, 2023 · Obviously, being a conjugate prior is useful as it saves performing tricky integrals or using a simulation, but why would I want to use a beta distribution? More generally, how …

After flipping the coin 10 times out of which 8 are heads, your posterior is $\mathrm {Beta} (17,3)$. The posterior mean is $0.85$. You can use an improper prior, that is no problem. The …

Apr 10, 2020 · Then using the fact that $\Gamma (x+1) \equiv x!$, I re-worked the equations for the Beta distribution and the Binomial distribution and came to the following set of four …

Aug 17, 2017 · I am looking for uninformative priors for beta distribution to work with a binomial process (Hit/Miss). At first I thought about using $\\alpha=1, \\beta=1$ that generate an …

Feb 9, 2015 · The beta-binomial distribution is a distribution over non-negative integers less than the number of trials, while the beta distribution is a distribution on reals in the unit interval. …

Feb 11, 2021 · Do you think beta binomial would be appropriate to model (0,1) for c and y? Would you be better of modeling it as logistic regression? Binomial distribution is used to model the …

Jan 9, 2022 · I'd be grateful for any help with beta-binomial (BB) regression in the gamlss package: predictions from the fitted model of "mu" values for each observation in my data …

A Beta distribution is used to model things that have a limited range, like 0 to 1. Examples are the probability of success in an experiment having only two outcomes, like success and failure. If …

With that, it's clear that for a given set of trial probabilities, P, in a poisson binomial distribution, one cannot simply estimate the beta distribution describing that set of probabilities and plug it …