Performance different uninformative efficiency of priors for binomial model

Abstract

The current paper studies the performance efficiency of two uninformative priors, namely Bayes-Laplace (Uniform) prior and Jeffrey’s prior for Binomial model. Several performance measures, such as the Bayes estimators under different loss functions, the posterior distribution skewness coefficient, the Bayesian point estimates, and the posterior variance, are used for comparison. Using these two uninformative priors, we conducted numerical simulation which showed that they perform extreme similarly.