Acceleration of the EM Algorithm Using the Vector Aitken Method and Its Steffensen Form

作     者：Xu GUO Qiu-yue LI Wang-li XU 

作者机构：School of StatisticsBeijing Normal University College of ScienceChina Agricultural University Center for Applied StatisticsSchool of StatisticsRenmin University of China 

出 版 物：《Acta Mathematicae Applicatae Sinica》 (应用数学学报（英文版）)

年 卷 期：2017年第33卷第1期

页      面：175-182页

核心收录：

学科分类：07[理学] 070102[理学-计算数学] 0701[理学-数学] 

基　　金：Supported by the National Natural Science Foundation of China(No.11071253 11471335 11626130) 

主　　题：EM algorithm VA-accelerated EM algorithm convergence rate Steffensen iterative 

摘      要：Based on Vector Aitken （VA） method, we propose an acceleration Expectation-Maximization （EM） algorithm, VA-accelerated EM algorithm, whose convergence speed is faster than that of EM algorithm. The VA-accelerated EM algorithm does not use the information matrix but only uses the sequence of estimates obtained from iterations of the EM algorithm, thus it keeps the flexibility and simplicity of the EM algorithm. Considering Steffensen iterative process, we have also given the Steffensen form of the VA-accelerated EM algorithm. It can be proved that the reform process is quadratic convergence. Numerical analysis illustrate the proposed methods are efficient and faster than EM algorithm.