Results 21 to 30 of about 1,572 (217)
Stochastic Processes with Expected Stopping Time [PDF]
Logical Methods in Computer ScienceMarkov chains are the de facto finite-state model for stochastic dynamical systems, and Markov decision processes (MDPs) extend Markov chains by incorporating non-deterministic behaviors.
Krishnendu Chatterjee, Laurent Doyen
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Multiplex Markov chains: Convection cycles and optimality
Physical Review Research, 2020 Multiplex networks are a common modeling framework for interconnected systems and multimodal data, yet we still lack fundamental insights for how multiplexity affects stochastic processes.
Dane Taylor
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Markov Chains and reliability analysis for reinforced concrete structure service life [PDF]
Materials Research, 2014 From field studies and the literature, it was found that the degradation of concrete over time can be modelled probabilistically using homogeneous Markov Chains. To confirm this finding, this study presents an application of Markov Chains associated with
Edna Possan +1 more
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Journal of Applied Mathematics, 2014 We study the strong law of large numbers for the frequencies of occurrence of states and ordered couples of states for countable Markov chains indexed by an infinite tree with uniformly bounded degree, which extends the corresponding results of countable
Bao Wang +3 more
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Algorithms for Markov Binomial Chains [PDF]
Logical Methods in Computer ScienceWe study algorithms to analyze a particular class of Markov population processes that is often used in epidemiology. More specifically, Markov binomial chains are the model that arises from stochastic time-discretizations of classical compartmental ...
Alejandro Alarcón Gonzalez +3 more
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Polynomial Recurrence of Time-inhomogeneous Markov Chains
Austrian Journal of Statistics, 2023 This paper is devoted to establishing conditions that guarantee the existence of a p-th moment of the time it takes for a timeinhomogeneous Markov chain to hit some set C.
Vitaliy Golomoziy, Olha Moskanova
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Distributed Markov Chains [PDF]
, 2015 The formal verification of large probabilistic models is challenging. Exploiting the concurrency that is often present is one way to address this problem. Here we study a class of communicating probabilistic agents in which the synchronizations determine the probability distribution for the next moves of the participating agents.
Ratul Saha +4 more
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Matrix Analysis for Continuous-Time Markov Chains
Special Matrices, 2021 Continuous-time Markov chains have transition matrices that vary continuously in time. Classical theory of nonnegative matrices, M-matrices and matrix exponentials is used in the literature to study their dynamics, probability distributions and other ...
Le Hung V., Tsatsomeros M. J.
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Markov Chain Models for Stock Prices Forecasts and Analysis [PDF]
ITM Web of ConferencesUnder the condition of complexity and volatility of financial markets, stock price prediction remains a challenging research topic. Markov chain models, with their “memoryless” nature, provide a probabilistic framework for analyzing stock price dynamics.
Jia Henghua
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, 2018 This book covers the classical theory of Markov chains on general state-spaces as well as many recent developments. The theoretical results are illustrated by simple examples, many of which are taken from Markov Chain Monte Carlo methods. The book is self-contained, while all the results are carefully and concisely proven.
Douc, Randal +3 more
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