Event-Chain Monte-Carlo Simulations of Dense Soft Matter Systems
Frontiers in Physics, 2021 We discuss the rejection-free event-chain Monte-Carlo algorithm and several applications to dense soft matter systems. Event-chain Monte-Carlo is an alternative to standard local Markov-chain Monte-Carlo schemes, which are based on detailed balance, for ...
Tobias Alexander Kampmann +4 more
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Multilevel Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics [PDF]
, 2012 We show how to extend a recently proposed multi-level Monte Carlo approach to the continuous time Markov chain setting, thereby greatly lowering the computational complexity needed to compute expected values of functions of the state of the system to a ...
Anderson, David, Higham, Desmond
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The random walk Metropolis : linking theory and practice through a case study. [PDF]
, 2010 The random walk Metropolis (RWM) is one of the most common Markov Chain Monte Carlo algorithms in practical use today. Its theoretical properties have been extensively explored for certain classes of target, and a number of results with important ...
Fearnhead, Paul +2 more
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Markov chain Monte Carlo methods for state-space models with point process observations [PDF]
, 2012 This letter considers how a number of modern Markov chain Monte Carlo (MCMC) methods can be applied for parameter estimation and inference in state-space models with point process observations.
Niranjan, Mahesan +2 more
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A Markov Chain Monte Carlo Algorithm for Spatial Segmentation
Information, 2021 Spatial data are very often heterogeneous, which indicates that there may not be a unique simple statistical model describing the data. To overcome this issue, the data can be segmented into a number of homogeneous regions (or domains). Identifying these
Nishanthi Raveendran, Georgy Sofronov
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Statistical Inference on Simple Step-Stress Accelerated Life Testing for Gompertz Distribution Under .Progressive Type-II Censoring [PDF]
Maǧallaẗ Al-Buḥūṯ Al-TiǧāriyyaẗWe consider a simple step-stress model under the Gompertz distribution (GD) when the available data are type-II progressive censored. The cumulative exposure model is assumed when the lifetime of test units follows a Gompertz distribution.
السيد وليد شعبان عبدالمنتصر +2 more
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Markov chain Monte Carlo for integrated face image analysis [PDF]
, 2014 This PhD thesis is about the integration of different methods to fit a statistical model of human faces to a single image. I propose to take a probabilistic view on the problem and implement and evaluate an integrative framework for face image ...
Schönborn, Sandro
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A full bayesian approach for boolean genetic network inference. [PDF]
PLoS ONE, 2014 Boolean networks are a simple but efficient model for describing gene regulatory systems. A number of algorithms have been proposed to infer Boolean networks.
Shengtong Han +5 more
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IMPLEMENTASI MARKOV CHAIN MONTE CARLO PADA PENDUGAAN HYPERPARAMETER REGRESI PROSES GAUSSIAN
Media Statistika, 2011 This paper studies the implementation of Markov Chain Monte Carlo on estimating the hyperparameter of Gaussian process. Metropolish-Hasting (MH) algorithm is used to generate the random samples from the posterior distribution that can not be generated by
Moch. Abdul Mukid, Sugito Sugito
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Geodesic Monte Carlo on Embedded Manifolds [PDF]
, 2013 Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows
Simon Byrne +5 more
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