Results 1 to 10 of about 35,404 (160)
Practical guidelines for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC). [PDF]
Open Res Eur, 2023 Phylogenetic estimation is, and has always been, a complex endeavor. Estimating a phylogenetic tree involves evaluating many possible solutions and possible evolutionary histories that could explain a set of observed data, typically by using a model of evolution.
Barido-Sottani J +4 more
europepmc +5 more sources
MCMC-ODPR: Primer design optimization using Markov Chain Monte Carlo sampling [PDF]
BMC Bioinformatics, 2012 Background Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly.
Kitchen James L +3 more
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On the Markov Chain Monte Carlo (MCMC) method
Sadhana - Academy Proceedings in Engineering Sciences, 2006 Let \(f(x)\) be a density of a distribution of some random variable \(X.\) We are interested in computing the integral \(\int\limits g(x) f(x)\,dx = E g(X)\) for a given function \(g.\) If we can generate a random sample \(x_1, \ldots, x_n\) of size \(n\) from this distribution and compute \(a_n ={1\over n} \sum_{i=1}^n g(x_i)\), then by the law of ...
Rajeeva L Karandikar +1 more
exaly +4 more sources
MONTE CARLO MARKOV CHAIN (MCMC) STOCHASTIC MODELING OF SUPPLY CHAIN
Annals: Series on engineering sciences (Academy of Romanian Scientists)Effective inventory management in multi-echelon supply chains is challenged by stochastic demand and uncertain lead times, which amplify variability and increase operational costs.
Marcel ILIE, Augustin SEMENESCU
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A Markov chain Monte Carlo (MCMC) methodology with bootstrap percentile estimates for predicting presidential election results in Ghana. [PDF]
Springerplus, 2015 Although, there exists numerous literature on the procedure for forecasting or predicting election results, in Ghana only opinion poll strategies have been used. To fill this gap, the paper develops Markov chain models for forecasting the 2016 presidential election results at the Regional, Zonal (i.e.
Nortey EN +3 more
europepmc +4 more sources
Quantum annealing enhanced Markov-Chain Monte Carlo [PDF]
Scientific ReportsIn this study, we propose quantum annealing-enhanced Markov Chain Monte Carlo (QAEMCMC), where QA is integrated into the MCMC subroutine. QA efficiently explores low-energy configurations and overcomes local minima, enabling the generation of proposal ...
Shunta Arai, Tadashi Kadowaki
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Mixed Path HMC Sampling Methods for Molecular Tree Spaces [PDF]
Jisuanji kexue, 2023 With the increasing abundance of modern molecular sequence data and the dramatic expansion of the tree-like topological space describing historical relationships between species,reliable inference of phylogenetic trees continues to face enormous ...
LI Xiaopeng, LING Cheng, GAO Jingyang
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Markov Chain Monte Carlo Methods for Estimating Systemic Risk Allocations
Risks, 2020 In this paper, we propose a novel framework for estimating systemic risk measures and risk allocations based on Markov Chain Monte Carlo (MCMC) methods. We consider a class of allocations whose jth component can be written as some risk measure of the jth
Takaaki Koike, Marius Hofert
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Data-Centric Engineering, 2021 Monte Carlo algorithms simulates some prescribed number of samples, taking some random real time to complete the computations necessary. This work considers the converse: to impose a real-time budget on the computation, which results in the number of ...
Lawrence M. Murray +2 more
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Markov Chain Monte Carlo Solution of Poisson’s Equation in Axisymmetric Regions
Advanced Electromagnetics, 2019 The advent of the Monte Carlo methods to the field of EM have seen floating random walk, fixed random walk and Exodus methods deployed to solve Poisson’s equation in rectangular coordinate and axisymmetric solution regions.
A. E. Shadare +2 more
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