JSIAM Letters
Online ISSN : 1883-0617
Print ISSN : 1883-0609
ISSN-L : 1883-0617
Articles
Hamiltonian Monte Carlo with explicit, reversible, and volume-preserving adaptive step size control
Michiko OkudoHideyuki Suzuki
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2017 Volume 9 Pages 33-36

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Abstract

Hamiltonian Monte Carlo is a Markov chain Monte Carlo method that uses Hamiltonian dynamics to efficiently produce distant samples. It employs geometric numerical integration to simulate Hamiltonian dynamics, which is a key of its high performance. We present a Hamiltonian Monte Carlo method with adaptive step size control to further enhance the efficiency. We propose a new explicit, reversible, and volume-preserving integration method to adaptively set the step sizes, which does not violate the detailed balance condition or require a large increase in computational time.

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© 2017, The Japan Society for Industrial and Applied Mathematics
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