On the Adequacy of Variational Lower Bound Functions for Likelihood-based Inference in Markovian Models with Missing Values
含缺失值马尔可夫模型中变分似然下界的推断适用性
Summary Variational methods have been proposed for obtaining deterministic lower bounds for log-likelihoods within missing data problems, but with little formal justification or investigation of the worth of the lower bound surfaces as tools for inference. We provide, within a general Markovian context, sufficient conditions under which estimators from the variational approximations are asymptotically equivalent to maximum likelihood estimators, and we show empirically, for…