Bayesian Missing Data Problems
Автор
Ming T. Tan
, Ng, Kai Wang
, Tian, Guo-Liang
Presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors, based on the inverse Bayes formulae. This work focuses on exact numerical solutions, a conditional sampling approach via data augmentation, and a noniterative sampling approach via EM-type algorithms.