Zigzag path connects two Monte Carlo samplers: Hamiltonian counterpart to a piecewise deterministic Markov process. [PDF]
J Am Stat Assoc, 2021 Zigzag and other piecewise deterministic Markov process samplers have attracted significant interest for their non-reversibility and other appealing properties for Bayesian posterior computation.
Nishimura A, Zhang Z, Suchard MA.
europepmc +3 more sources
Variability and singularity arising from a Piecewise-Deterministic Markov Process applied to model poor patient compliance in the multi-IV case. [PDF]
J Appl Stat, 2020 We propose a Piecewise-Deterministic Markov Process (PDMP) to model the drug concentration in the case of multiple intravenous-bolus (multi-IV) doses and poor patient adherence situation: the scheduled time and doses of drug administration are not ...
Fermín LJ, Lévy-Véhel J.
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Piecewise deterministic Markov process - recent results [PDF]
ESAIM: Proceedings, 2013 We give a short overview of recent results on a specific class of Markov process: the Piecewise Deterministic Markov Processes (PDMPs). We first recall the definition of these processes and give some general results.
Romain Azais +4 more
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Markov modeling of performance deterioration in irradiated resistive plate chambers [PDF]
European Physical Journal C: Particles and FieldsThis work presents a piecewise deterministic Markov process model for describing performance deterioration in resistive plate chambers (RPC) under uniform background irradiation.
Dario Stocco +2 more
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HYPE with stochastic events [PDF]
Electronic Proceedings in Theoretical Computer Science, 2011 The process algebra HYPE was recently proposed as a fine-grained modelling approach for capturing the behaviour of hybrid systems. In the original proposal, each flow or influence affecting a variable is modelled separately and the overall behaviour of ...
Luca Bortolussi +2 more
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Hypocoercivity of piecewise deterministic Markov process-Monte Carlo [PDF]
The Annals of Applied Probability, 2018 In this work, we establish $\mathrm{L}^2$-exponential convergence for a broad class of Piecewise Deterministic Markov Processes recently proposed in the context of Markov Process Monte Carlo methods and covering in particular the Randomized Hamiltonian ...
C. Andrieu +3 more
semanticscholar +8 more sources
A Monte-Carlo planning strategy for medical follow-up optimization: Illustration on multiple myeloma data. [PDF]
PLoS ONEDesigning patient-specific follow-up strategies is key to personalized cancer care. Tools to assist doctors in treatment decisions and scheduling follow-ups based on patient preferences and medical data would be highly beneficial.
Benoîte de Saporta +3 more
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Recent advances in the long-time analysis of killed degenerate processes and their particle approximation [PDF]
ESAIM: Proceedings and Surveys, 2023 We review some recent results of quantitative long-time convergence for the law of a killed Markov process conditioned to survival toward a quasi-stationary distribution, and on the analogous question for the particle systems used in practice to sample ...
Cloez Bertrand +4 more
doaj +1 more source
Piecewise deterministic Markov process for condition-based imperfect maintenance models [PDF]
Reliability Engineering & System Safety, 2022 In this paper, a condition-based imperfect maintenance model based on piecewise deterministic Markov process (PDMP) is constructed. The degradation of the system includes two types: natural degradation and random shocks.
Weikai Wang, Xian-Li Chen
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Adaptive Importance Sampling Based on Fault Tree Analysis for Piecewise Deterministic Markov Process [PDF]
SIAM/ASA J. Uncertain. Quantification, 2022 Piecewise deterministic Markov processes (PDMPs) can be used to model complex dynamical industrial systems. The counterpart of this modeling capability is their simulation cost, which makes reliability assessment untractable with standard Monte Carlo ...
G. Chennetier +3 more
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