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Continuous time Markov chain approaches for analyzing transtheoretical models of health behavioral change: A case study and comparison of model estimations. [PDF]
Stat Methods Med Res, 2018 Ma J, Chan W, Tilley BC.
europepmc +4 more sources
A continuous-time Markov chain model of fibrosis progression in NAFLD and NASH [PDF]
Frontiers in Medicine, 2023 The specific pathways, timescales, and dynamics driving the progression of fibrosis in NAFLD and NASH are not yet fully understood. Hence, a mechanistic model of the pathogenesis and treatment of fibrosis in NASH will necessarily have significant ...
Lyndsey F. Meyer +2 more
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Computer-Aided Civil and Infrastructure Engineering, 2023 Markov chains have been widely used to characterize performance deterioration of infrastructure assets, to model maintenance effectiveness, and to find the optimal intervention strategies.
D. Mizutani, Xian-Xun Yuan
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Maximum likelihood estimation of diffusions by continuous time Markov chain [PDF]
Computational Statistics & Data Analysis, 2021 In this paper we present a novel method for estimating the parameters of a parametric diffusion processes. Our approach is based on a closed-form Maximum Likelihood estimator for an approximating Continuous Time Markov Chain (CTMC) of the diffusion ...
J. Kirkby +3 more
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Information diffusion model with homogeneous continuous time Markov chain on Indonesian Twitter users [PDF]
International Journal of Data and Network Science, 2022 In this paper, a homogeneous continuous time Markov chain (CTMC) is used to model information diffusion or dissemination, also to determine influencers on Twitter dynamically. The tweeting process can be modeled with a homogeneous CTMC since the
Firdaniza Firdaniza +3 more
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Non-homogeneous continuous time Markov chain model for information dissemination on Indonesian Twitter users [PDF]
International Journal of Data and Network Science, 2023 Nonhomogeneous Continuous-Time Markov Chain (NH-CTMC) is a stochastic process that can be used to model problems where the future state depends only on the current state and is independent of the past.
Firdaniza Firdaniza +3 more
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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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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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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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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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