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Sampling from a multivariate gaussian distribution truncated on a simplex: a review

Altmann, Yoann and McLaughlin, Steve and Dobigeon, Nicolas Sampling from a multivariate gaussian distribution truncated on a simplex: a review. (2014) In: 2014 IEEE Workshop on Statistical Signal Processing (SSP), 29 June 2014 - 2 July 2014 (Gold Coast, Australia).

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Official URL: http://dx.doi.org/10.1109/SSP.2014.6884588

Abstract

In many Bayesian models, the posterior distribution of interest is a multivariate Gaussian distribution restricted to a specific domain. In particular, when the unknown parameters to be estimated can be considered as proportions or probabilities, they must satisfy positivity and sum-to-one constraints. This paper reviews recent Monte Carlo methods for sampling from multivariate Gaussian distributions restricted to the standard simplex. First, a classical Gibbs sampler is presented. Then, two Hamiltonian Monte Carlo methods are described and analyzed. In a similar fashion to the Gibbs sampler, the first method has a acceptance rate equal to one whereas the second requires an accept/reject procedure. The performance of the three methods are compared through the use of a few examples.

Item Type:Conference or Workshop Item (Paper)
Additional Information:ISBN : 978-1-4799-4975-5
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Heriot-Watt University (UNITED KINGDOM)
Laboratory name:
Statistics:download
Deposited By: IRIT IRIT
Deposited On:18 Feb 2015 08:42

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