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Bayesian Estimation of State-Space Model Using the Hybrid Monte Carlo within Gibbs Sampler
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 Title & Authors
Bayesian Estimation of State-Space Model Using the Hybrid Monte Carlo within Gibbs Sampler
Park, Ilsu;
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 Abstract
In a standard Metropolis-type Monte Carlo simulation, the proposal distribution cannot be easily adapted to "local dynamics" of the target distribution. To overcome some of these difficulties, Duane et al. (1987) introduced the method of hybrid Monte Carlo(HMC) which combines the basic idea of molecular dynamics and the Metropolis acceptance-rejection rule to produce Monte Carlo samples from a given target distribution. In this paper, using the HMC within Gibbs sampler, an asymptotical estimate of the smoothing mean and a general solution to state space modeling in Bayesian framework is obtaineds obtained
 Keywords
Hybrid Monte Carlo;Gibbs sampler;State-space model;
 Language
English
 Cited by
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