Approximate Predictive Likelihood
提出一种近似预测似然，通过后验似然展开同时逼近贝叶斯和最大似然预测推断，适用于缺乏先验信息或无法获得精确预测似然的情形，并应用于广义极值分布的极端值预测。
A predictive likelihood is given which approximates both Bayes and maximum likelihood predictive inference by expansion of a posterior likelihood. This synthesizes and extends previous results and is widely applicable. The approximation usually differs from exact Bayes posterior predictive density by Op(n–2), and from exact predictive likelihood by Op(n–2) but does not depend on the availability of prior information and is applicable when exact predictive likelihood cannot be found. The results are applied to the prediction of extremes using the generalized extreme-value distribution.