S-estimation of hidden Markov models

被引：0
作者：
Alessio Farcomeni
Luca Greco
机构：
[1] Sapienza - University of Rome,Dipartimento di Sanitá Pubblica e Malattie Infettive
[2] University of Sannio,DEMM Department
来源：
Computational Statistics | 2015年 / 30卷
关键词：
Bisquare; EM; HMM; Mahalanobis distance; Mixture; Robust distance; S-estimation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A method for robust estimation of dynamic mixtures of multivariate distributions is proposed. The EM algorithm is modified by replacing the classical M-step with high breakdown S-estimation of location and scatter, performed by using the bisquare multivariate S-estimator. Estimates are obtained by solving a system of estimating equations that are characterized by component specific sets of weights, based on robust Mahalanobis-type distances. Convergence of the resulting algorithm is proved and its finite sample behavior is investigated by means of a brief simulation study and n application to a multivariate time series of daily returns for seven stock markets.
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页码：57 / 80
页数：23
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