Results 41 to 50 of about 2,583,540 (350)
Multivariate output analysis for Markov chain Monte Carlo [PDF]
Biometrika, 2015 Markov chain Monte Carlo (MCMC) produces a correlated sample for estimating expectations with respect to a target distribution. A fundamental question is when should sampling stop so that we have good estimates of the desired quantities?
Dootika Vats +2 more
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Detection of Factors Affecting State Transition Based on Non-Homogeneous Markov Chain Model
IEEE Access, 2021 The dependent and independent variables in traditional linear regression models are continuous numerical variables. When the dependent variable or independent variable is a discrete variable, the traditional linear regression model can no longer be used ...
Shen Xiujuan +3 more
doaj +1 more source
Applied Sciences, 2021 The reconstruction of optical properties for opaque mediums is highly desired for medical, atmosphere and aerosol applications. However, the modeling and reconstruction process is highly related with multiple scattering phenomena, which elevates both the
Hujie Pan +4 more
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Bounds of the stationary distribution in M/G/1 retrial queue with two-way communication and n types of outgoing calls [PDF]
Yugoslav Journal of Operations Research, 2019 In this article we analyze the M=G=1 retrial queue with two-way communication and n types of outgoing calls from a stochastic comparison viewpoint. The main idea is that given a complex Markov chain that cannot be analyzed numerically, we propose to ...
Alem Lala Maghnia +2 more
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Markov Chain Analysis of Cumulative Step-Size Adaptation on a Linear Constrained Problem [PDF]
Evolutionary Computation, 2015 This paper analyzes a -Evolution Strategy, a randomized comparison-based adaptive search algorithm optimizing a linear function with a linear constraint. The algorithm uses resampling to handle the constraint.
A. Chotard, A. Auger, N. Hansen
semanticscholar +1 more source
Variance and Covariance of Several Simultaneous Outputs of a Markov Chain [PDF]
Discrete Mathematics & Theoretical Computer Science, 2016 The partial sum of the states of a Markov chain or more generally a Markov source is asymptotically normally distributed under suitable conditions. One of these conditions is that the variance is unbounded.
Sara Kropf
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A simple introduction to Markov Chain Monte–Carlo sampling
Psychonomic Bulletin & Review, 2016 Markov Chain Monte–Carlo (MCMC) is an increasingly popular method for obtaining information about distributions, especially for estimating posterior distributions in Bayesian inference. This article provides a very basic introduction to MCMC sampling. It
D. van Ravenzwaaij +2 more
semanticscholar +1 more source
The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method [PDF]
, 2015 Many Markov chain Monte Carlo techniques currently available rely on discrete-time reversible Markov processes whose transition kernels are variations of the Metropolis–Hastings algorithm.
Alexandre Bouchard-Cot'e +2 more
semanticscholar +1 more source
Markov Chain Ontology Analysis (MCOA)
BMC Bioinformatics, 2012 Background Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research.
Frost H, McCray Alexa T
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Enabling Quantum Speedup of Markov Chains using a Multi-level Approach [PDF]
arXiv, 2022 Quantum speedup for mixing a Markov chain can be achieved based on the construction of slowly-varying $r$ Markov chains where the initial chain can be easily prepared and the spectral gaps have uniform lower bound. The overall complexity is proportional to $r$.
arxiv