The empirical Bayes approach: estimating the prior distribution

Abstract
There is a random variable A distributed according to a specific but unknown prior distribution G from an appropriate class GP. The random variable Λ = λ is unobrvable but another random variable X = x, distributed with known conditional distribution function F(x∣λ), is observable. We construct estimators Gn(λ) of G(λ) such that lim E[{Gn(λ) − G(λ)}2]=0 and we use Gn(λ) to estimate the posterior distribution G(λ∣x) and hence to construct consistent estimators of posterior confidence intervals.

This publication has 0 references indexed in Scilit: