Mixture estimation with state-space components and Markov model of switching

The paper proposes a recursive algorithm for estimation of mixtures with state-space components and a dynamic model of switching. Bayesian methodology is adopted. The main features of the presented approach are: (i) recursiveness that enables a real-time performance of the algorithm; (ii) one-pass e...

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Veröffentlicht in:	Applied mathematical modelling 2013-12, Vol.37 (24), p.9970-9984
Hauptverfasser:	Nagy, Ivan, Suzdaleva, Evgenia
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayesian analysis Bayesian dynamic decision making under uncertainty Dynamical systems Exploitation Kerridge inaccuracy Markov models Mathematical analysis Mathematical models Probabilistic dynamic mixtures Probability density function Recursive mixture estimation State-space models Switching
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