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Adaptive Metropolis-Hastings Sampling using Reversible Dependent Mixture Proposals
Ergodic convergence Markov Chain Monte Carlo Metropolis-within Gibbs composite sampling Multivariatet mixtures Simulated annealing Variational Approx-imation
2013/6/14
This article develops a general-purpose adaptive sampler that approximates the target density by a mixture of multivariate t densities. The adaptive sampler is based on reversible proposal distributio...
Exact recording of Metropolis-Hastings-class Monte Carlo simulations using one bit per sample
Markov chain Monte Carlo Metropolis-Hastings information theory data representation
2011/6/21
The Metropolis-Hastings (MH) algorithm is the prototype for a class of Markov chain Monte Carlo methods
that propose transitions between states and then accept or reject the proposal. These methods g...
Using parallel computation to improve Independent Metropolis--Hastings based estimation
MCMC algorithm independent Metropolis{Hastings
2010/10/19
In this paper, we consider the implications of the fact that parallel raw-power can be exploited by a generic Metropolis--Hastings algorithm if the proposed values are independent. In particular, we p...
On the Stability and Ergodicity of an Adaptive Scaling Metropolis Algorithm
Adaptive Markov chain Monte Carlo ergodicity Metropolis algorithm stability stochastic approximation
2010/3/19
This paper considers the stability and ergodicity of an adaptive random
walk Metropolis algorithm. The algorithm adjusts the scale of the symmetric
proposal distribution continuously, based on the o...
Variable-at-a-time Implementations of Metropolis-Hastings
Variable-at-a-time Implementations Metropolis-Hastings
2010/3/18
It is common practice in Markov chain Monte Carlo to update a high-dimensional
chain one variable (or sub-block of variables) at a time, rather than conduct a single block
update. While this modific...
Metropolis algorithm and equienergy sampling for two mean field spin systems
asymptotic variance Chain decomposition theorem fast/slowly mixingchain mean-field Ising model Metropolis
2010/4/28
In this paper we study the Metropolis algorithm in connection
with two mean–field spin systems, the so called mean–field Ising model and
the Blume–Emery–Griffiths model. In both this examples the na...