Frequentist Validity of Posterior Quantiles in the Presence of a Nuisance Parameter: Higher Order Asymptotics
研究了当分布依赖于未知参数θ=(θ1,θ2)时，将θ2视为多余参数，后验分位数在频率学派意义下达到o(n^{-1})阶有效性的条件，并提出通过匹配后验和频率覆盖概率来优化先验选择。
Given a random sample from a distribution with density function that depends on an unknown parameter θ = (θ1, θ2), we are concerned with frequentist validity, up to o(n−1), of posterior quantiles of θ1, treating θ2 as a nuisance parameter. We propose to make the best choice of the prior on θ by matching, as far as practicable, the posterior and frequentist coverage probabilities up to o(n−1).