On Bartlett Adjustments for Approximate Bayesian Inference
推导了似然比统计量和后验比统计量的巴特利特调整因子显式公式，将卡方近似的误差从O(n⁻¹)降至O(n⁻²)，并应用于完整和右删失数据的回归模型推断。
In wide generality, the posterior distributions of the likehood ratio statistic and the posterior ratio statistic are chi-squared to error of order O(n−1), where n is sample size. The error in the chi-squared approximation can be reduced to order O(n−2) by Bartlett correction. In this paper, explicit formulae are derived for the Bartlett adjustment factors of both statistics, and the derivations are based on the Tierney. Kass & Kadane (1989) asymptotic approximation for marginal posterior probability density functions. The use of numerical differentiation to facilitate calculation of the Bartlett adjustments is also described. Some applications are considered that concern inference about regression models from both complete and right-censored data.