S-estimation of hidden Markov models

Alessio Farcomeni and Luca Greco ()

Computational Statistics, 2015, vol. 30, issue 1, 57-80

Abstract: 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. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Bisquare; EM; HMM; Mahalanobis distance; Mixture; Robust distance; S-estimation (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:30:y:2015:i:1:p:57-80

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DOI: 10.1007/s00180-014-0521-2

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