Detail publikačního výsledku

Approximate Bayesian inference methods for mixture filtering with known model of switching

PAPEŽ, M.

Originální název

Approximate Bayesian inference methods for mixture filtering with known model of switching

Anglický název

Approximate Bayesian inference methods for mixture filtering with known model of switching

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

Bayesian inference has proven itself to be a practically useful tool for many scientific fields. The exact Bayesian inference is, however, possible in only a narrow class of probabilistic models enjoying the conjugacy principle. It is rather typical that the principle does not hold, and therefore the approximate Bayesian inference methods are taken into account. The present paper compares some of these techniques on a mixture filtering problem. The methods are presented in a generic way, considering that the mixture components are members of the exponential family of probability distributions and that the Markov model of switching between the mixture components is known. A particular instance of the methods is given for a mixture of normal linear state space models, and experiments evaluating the estimation precision and computational time are performed.

Anglický abstrakt

Bayesian inference has proven itself to be a practically useful tool for many scientific fields. The exact Bayesian inference is, however, possible in only a narrow class of probabilistic models enjoying the conjugacy principle. It is rather typical that the principle does not hold, and therefore the approximate Bayesian inference methods are taken into account. The present paper compares some of these techniques on a mixture filtering problem. The methods are presented in a generic way, considering that the mixture components are members of the exponential family of probability distributions and that the Markov model of switching between the mixture components is known. A particular instance of the methods is given for a mixture of normal linear state space models, and experiments evaluating the estimation precision and computational time are performed.

Klíčová slova

Approximate Bayesian inference methods, decision-making theory, probabilistic mixtures, computational statistics

Klíčová slova v angličtině

Approximate Bayesian inference methods, decision-making theory, probabilistic mixtures, computational statistics

Autoři

PAPEŽ, M.

Rok RIV

2017

Vydáno

30.06.2016

Nakladatel

Institute of Electrical and Electronics Engineers

Místo

Tatranska Lomnica

ISBN

978-1-4673-8606-7

Kniha

Proceedings of the 17th International Carpathian Control Conference, ICCC 2016

Strany od

545

Strany do

551

Strany počet

7

URL

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7501157&isnumber=7501055

BibTex

@inproceedings{BUT127522,
  author="Milan {Papež}",
  title="Approximate Bayesian inference methods for mixture filtering with known model of switching",
  booktitle="Proceedings of the 17th International Carpathian Control Conference, ICCC 2016",
  year="2016",
  pages="545--551",
  publisher="Institute of Electrical and Electronics Engineers",
  address="Tatranska Lomnica",
  doi="10.1109/CarpathianCC.2016.7501157",
  isbn="978-1-4673-8606-7",
  url="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7501157&isnumber=7501055"
}