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Activity Number: 163
Type: Contributed
Date/Time: Monday, August 3, 2009 : 10:30 AM to 12:20 PM
Sponsor: Section for Statistical Programmers and Analysts
Abstract - #305779
Title: Recursive Sparse Estimation Using a Gaussian Sum Filter
Author(s): Michael Rotkowitz*+ and Lachlan Blackhall
Companies: The University of Melbourne and The Australian National University
Address: Dept. of Electrical & Electronic Engr., Parkville, Victoria, International, 3065, Australia
Keywords: filter ; sparse estimation ; recursive estimation
Abstract:

We develop a recursive estimator that systematically arrives at sparse parameter estimates. The algorithm is computationally feasible for moderate parameter estimation problems and leverages the Gaussian sum filter to provide both sparse parameter estimates and credible Bayesian intervals for non-zero parameters in a recursive fashion. Simulations show extremely promising accuracy, as well as a robustness to parameters not enjoyed by other sparse estimators.

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