Expectation propagation for estimating the parameters of the beta distribution
2010 (English)In: 2010 IEEE International Conference On Acoustics, Speech, And Signal Processing, 2010, 2082-2085 p.Conference paper (Refereed)
Parameter estimation for the beta distribution is analytically intractable due to the integration expression in the normalization constant. For maximum likelihood estimation, numerical methods can be used to calculate the parameters. For Bayesian estimation, we can utilize different approximations to the posterior parameter distribution. A method based on the variational inference (VI) framework reported the posterior mean of the parameters analytically but the approximating distribution violated the correlation between the parameters. We now propose a method via the expectation propagation (EP) framework to approximate the posterior distribution analytically and capture the correlation between the parameters. Compared to the method based on VI, the EP based algorithm performs better with small amounts of data and is more stable.
Place, publisher, year, edition, pages
2010. 2082-2085 p.
, International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Beta Distribution, Expectation Propagation, Variational Inference, Importance Sampling, Laplace Approximation
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-32255DOI: 10.1109/ICASSP.2010.5495085ISI: 000287096002016ScopusID: 2-s2.0-78049387838ISBN: 978-1-4244-4296-6OAI: oai:DiVA.org:kth-32255DiVA: diva2:411459
2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010; Dallas, TX; 14 March 2010 through 19 March 2010
QC 201104182011-04-182011-04-112011-11-15Bibliographically approved