Title :
Estimation of Mixtures of Symmetric Alpha Stable Distributions With an Unknown Number of Components
Author :
Salas-González, D. ; Kuruoglu, E.E. ; Ruiz, D.P.
Author_Institution :
Dept. of Appl. Phys., Granada Univ.
Abstract :
In this work, we study the estimation of mixtures of symmetric alpha-stable distributions using Bayesian inference. We utilise numerical Bayesian sampling techniques such as Markov chain Monte Carlo (MCMC). Our estimation technique is capable of estimating also the number of alpha-stable components in the mixture in addition to the component parameters and mixing coefficients which is accomplished by using the reversible jump MCMC (RJMCMC) algorithm
Keywords :
Markov processes; Monte Carlo methods; inference mechanisms; signal sampling; Bayesian inference; Markov chain Monte Carlo; numerical Bayesian sampling techniques; symmetric alpha stable distributions; Bayesian methods; Gaussian processes; Inference algorithms; Monte Carlo methods; Parameter estimation; Physics; Probability distribution; Random variables; Sampling methods; Signal processing algorithms;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
Print_ISBN :
1-4244-0469-X
DOI :
10.1109/ICASSP.2006.1661333
