Acceleration of the EM algorithm using the Vector Aitken method and its Steffensen form

被引:0
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作者
Xu Guo
Qiu-yue Li
Wang-li Xu
机构
[1] Beijing Normal University,School of Statistics
[2] China Agricultural University,College of Science
[3] Renmin University of China,Center for Applied Statistics, School of Statistics
关键词
EM algorithm; VA-accelerated EM algorithm; convergence rate; Steffensen iterative; 65B05;
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学科分类号
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.
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页码:175 / 182
页数:7
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