Results 61 to 70 of about 29,218,928 (220)
LISA Data Analysis using MCMC methods
, 2005 14 pages, 7 ...
Cornish, Neil J., Crowder, Jeff
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A stable manifold MCMC method for high dimensions [PDF]
Statistics & Probability Letters, 2014 We combine two important recent advancements of MCMC algorithms: first, methods utilizing the intrinsic manifold structure of the parameter space; then, algorithms effective for targets in infinite-dimensions with the critical property that their mixing time is robust to mesh refinement.
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IMPLEMENTASI METODE MARKOV CHAIN MONTE CARLO DALAM PENENTUAN HARGA KONTRAK BERJANGKA KOMODITAS
E-Jurnal Matematika, 2015 The aim of the research is to implement Markov Chain Monte Carlo (MCMC) simulation method to price the futures contract of cocoa commodities. The result shows that MCMC is more flexible than Standard Monte Carlo (SMC) simulation method because MCMC ...
PUTU AMANDA SETIAWANI +2 more
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Efficient Markov chain Monte Carlo sampling for electrical impedance tomography
Computer Assisted Methods in Engineering and Science, 2017 This paper studies electrical impedance tomography (EIT) using Bayesian inference [1]. The resulting posterior distribution is sampled by Markov chain Monte Carlo (MCMC) [2]. This paper studies a toy model of EIT as the one presented in [3], and focuses
Erfang Ma
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Variational Hamiltonian Monte Carlo via Score Matching
, 2017 Traditionally, the field of computational Bayesian statistics has been divided into two main subfields: variational methods and Markov chain Monte Carlo (MCMC).
Shahbaba, Babak +2 more
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Advanced MCMC methods for sampling on diffusion pathspace
Stochastic Processes and their Applications, 2013 The need to calibrate increasingly complex statistical models requires a persistent effort for further advances on available, computationally intensive Monte Carlo methods. We study here an advanced version of familiar Markov Chain Monte Carlo (MCMC) algorithms that sample from target distributions defined as change of measures from Gaussian laws on ...
Beskos, Alexandros +2 more
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Eigenvalue analysis of an irreversible random walk with skew detailed balance conditions
, 2015 An irreversible Markov-chain Monte Carlo (MCMC) algorithm with skew detailed balance conditions originally proposed by Turitsyn et al. is extended to general discrete systems on the basis of the Metropolis-Hastings scheme.
Hukushima, Koji, Sakai, Yuji
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To MCMC or not to MCMC: Evaluating non-MCMC methods for Bayesian penalized regression
Markov Chain Monte Carlo (MCMC) sampling is computationally expensive, especially for complex models. Alternative methods make simplifying assumptions about the posterior to reduce computational burden, but their impact on predictive performance remains unclear.
van Leeuwen, Florian D., van Erp, Sara
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Application of Markov chain Monte carlo method in Bayesian statistics
MATEC Web of Conferences, 2016 In statistical inference methods, bayesian method is a method of great influence. This paper introduces the basic idea of the bayesian method. However, the widespread popularity of MCMC samplers is largely due to their impact on solving statistical ...
Zhao Qi
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Parallel and interacting Markov chains Monte Carlo method [PDF]
, 2006 In many situations it is important to be able to propose $N$ independent realizations of a given distribution law. We propose a strategy for making $N$ parallel Monte Carlo Markov Chains (MCMC) interact in order to get an approximation of an independent $
Campillo, Fabien, Rossi, Vivien
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