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August 2006 Comparison of Sampling Schemes for Dynamic Linear Models
Edna A. Reis, Esther Salazar, Dani Gamerman
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Internat. Statist. Rev. 74(2): 203-214 (August 2006).

Abstract

Hyperparameter estimation in dynamic linear models leads to inference that is not available analytically. Recently, the most common approach is through MCMC approximations. A number of sampling schemes that have been proposed in the literature are compared. They basically differ in their blocking structure. In this paper, comparison between the most common schemes is performed in terms of different efficiency criteria, including efficiency ratio and processing time. A sample of time series was simulated to reflect different relevant features such as series length and system volatility.

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Edna A. Reis. Esther Salazar. Dani Gamerman. "Comparison of Sampling Schemes for Dynamic Linear Models." Internat. Statist. Rev. 74 (2) 203 - 214, August 2006.

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Published: August 2006
First available in Project Euclid: 24 July 2006

Keywords: Bayesian inference , blocking , MCMC , reparameterization , state space

Rights: Copyright © 2006 International Statistical Institute

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Vol.74 • No. 2 • August 2006
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