Results 221 to 230 of about 23,325 (286)

Markov Chain Monte Carlo Methods: Computation and Inference

, 2001
Abstract This chapter reviews the recent developments in Markov chain Monte Carlo simulation methods. These methods, which are concerned with the simulation of high dimensional probability distributions, have gained enormous prominence and revolutionized Bayesian statistics.
Siddhartha Chib
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Numerical Methods for Computing Stationary Distributions of Finite Irreducible Markov Chains

2000
In this chapter our attention will be devoted to computational methods for computing stationary distributions of finite irreducible Markov chains. We let q ij denote the rate at which an n-state Markov chain moves from state i to state j. The n × n matrix Q whose off-diagonal elements are q ij and whose i th diagonal element is given by \( - \sum ...
W. Stewart
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Computational complexity of Markov chain Monte Carlo methods for finite Markov random fields

Biometrika, 1997
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Arnoldo Frigessi
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Predicting transient particle transport in enclosed environments with the combined computational fluid dynamics and Markov chain method

Indoor Air, 2013
To quickly obtain information about airborne infectious disease transmission in enclosed environments is critical in reducing the infection risk to the occupants. This study developed a combined computational fluid dynamics (CFD) and Markov chain method for quickly predicting transient particle transport in enclosed environments.
Chun Chen, Chao‐Hsin Lin, Zhengwei Long, Qingyan Chen   +3 more
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Computation of atomic many-electron integrals using a Markov chain generated Monte Carlo method

The Journal of Chemical Physics, 1975
A Monte Carlo method for evaluating complicated many-electron integrals is described. The process utilizes a Markov chain which properly chooses configurations of electrons in accordance with the form of Ψ chosen. The method inherently reduces the variance compared to the classical Monte Carlo method.
R. L. Gibbs, T. M. Dunn
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Iterative aggregation/disaggregation methods for computing some characteristics of Markov chains. II. Fast convergence

Applied Numerical Mathematics, 2003
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Ivo Marek
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Markov chains computational method for determination of the copolymer composition and microstructure as a function of the conversion

Polymer Bulletin, 1983
A computational method is proposed for determination of the copolymer composition and microstructure dependence on the conversion on the basis of finite Markov's chains. The method is valuable because of its easy numeric realization and the possibility for a more profound characterization of the multi-component copolymers.
George Georgiev
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Numerical Method for Bounds Computations of Discrete-Time Markov Chains with Different State Spaces

, 2009
In this paper, we propose a numerical method for bounds computations of discrete-time Markov chains with different state spaces. This method is based on the necessary and sufficient conditions for the comparison of one-dimensional (also known as the point-wise comparison) of discrete-time Markov chains given in our previous work [3].
Mourad Ahmane, Laurent Truffet
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An Enhanced Method for the Computation of the Distribution of the Proportion of Time that a Continuous-Time Markov Chain is in a Subset of States in a Time Interval

Methodology and Computing in Applied Probability
We develop a new numerical method for the computation of the complementary probability distribution of the proportion of time in a time interval that a continuous-time Markov chain (CTMC) is in a subset of states. The new method is an enhanced version of a method developed by the second author (method C) based on a uniformization construct with a ...
Vı́ctor Suñé, Juan A. Carrasco
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Computational efficiency study of a micro-macro Markov chain Monte Carlo method for molecular dynamics

Applied Mathematics and Computation
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Hannes Vandecasteele, Giovanni Samaey
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