Algorithms and Programs of Dynamic Mixture Estimation

Beschreibung

This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.

Presents and explains the theory of the recursive Bayesian estimation algorithms for dynamic mixture models 
Develops a unified scheme for constructing the estimation algorithm of dynamic mixtures with reproducible statistics
Includes open source programs that can be easily modified or extended by readers

Presents and explains the theory of the recursive Bayesian estimation algorithms for dynamic mixture models Develops a unified scheme for constructing the estimation algorithm of dynamic mixtures with reproducible statistics Includes open source programs that can be easily modified or extended by readers Includes supplementary material: sn.pub/extras

Autor*in

Ivan Nagy

Themen in »Algorithms and Programs of Dynamic Mixture Estimation«

mixture models Markov switching models dynamic mixtures recursive Bayesian estimation mixture estimation algorithms mixtures of various distributions open source programs mixture prediction

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“The book presents and discusses dynamic mixture models and their use in estimation and prediction. ... Mixture models have applications in several domains such as industry, engineering, social science, medicine, transportation etc. The book therefore can be of interest to researchers and PhD students in many diverse fields.” (Christina Diakaki, zbMATH 1383.62005, 2018)
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