Algebraic methods for evaluating integrals In Bayesian statistics

Algebraic methods for evaluating integrals In Bayesian statistics The accurate evaluation of marginal likelihood integrals is a difficult fundamental problem in Bayesian inference that has important applications in machine learning and computational biology. Following the recent success of algebraic statistics in frequentist inference and inspired by Watanabe's foundational approach to singular le