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Multi-strategy evolutionary games: A Markov chain approach. [PDF]
PLoS ONE, 2022 Interacting strategies in evolutionary games is studied analytically in a well-mixed population using a Markov chain method. By establishing a correspondence between an evolutionary game and Markov chain dynamics, we show that results obtained from the ...
Mahdi Hajihashemi +1 more
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Affects affect affects: A Markov Chain [PDF]
Frontiers in Psychology, 2023 Pietro Cipresso +3 more
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SHS Web of Conferences, 2023 In this paper, Markov chain is used to model the reproduction of the fixed finite population, and use binomial distribution to discuss the probability of gen inheritance between generations population genes and establish transfer matrix ,using ...
Zhai Qian
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Open Markov Type Population Models: From Discrete to Continuous Time
Mathematics, 2021 We address the problem of finding a natural continuous time Markov type process—in open populations—that best captures the information provided by an open Markov chain in discrete time which is usually the sole possible observation from data.
Manuel L. Esquível +2 more
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Markov chains and applications
Selecciones Matemáticas, 2022 This work has three important purposes: first it is the study of Markov Chains, the second is to show that Markov chains have different applications and finally it is to model a process of this behaves. Throughout this work we will describe what a Markov
Mississippi Valenzuela
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Handbook of Markov Chain Monte Carlo [PDF]
, 2011 Foreword Stephen P. Brooks, Andrew Gelman, Galin L. Jones, and Xiao-Li Meng Introduction to MCMC, Charles J. Geyer A short history of Markov chain Monte Carlo: Subjective recollections from in-complete data, Christian Robert and George Casella Reversible
Radford M. Neal
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Barekeng, 2023 Markov chain is a stochastic process to describe a phenomenon in the future based on a previous state. In practice, Markov chains are distinguished by time into two, namely discrete-time Markov chain and continuous-time Markov Chain.
Putri Monika +3 more
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Analysis and Application of Grey-Markov Chain Model in Tax Forecasting
Journal of Mathematics, 2021 Tax data is a typical time series data, which is subject to the interaction and influence of economic and political factors and has dynamic and highly nonlinear characteristics.
Huidi Zhang, Yimao Chen
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A rapidly mixing Markov chain from any gapped quantum many-body system [PDF]
Quantum, 2023 We consider the computational task of sampling a bit string $x$ from a distribution $\pi(x)=|\langle x|\psi\rangle|^2$, where $\psi$ is the unique ground state of a local Hamiltonian $H$.
Sergey Bravyi +3 more
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Convergence Diagnostics for Markov Chain Monte Carlo [PDF]
Annual Review of Statistics and Its Application, 2019 Markov chain Monte Carlo (MCMC) is one of the most useful approaches to scientific computing because of its flexible construction, ease of use, and generality. Indeed, MCMC is indispensable for performing Bayesian analysis.
Vivekananda Roy
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