Joint reconstruction and prediction\break of random dynamical systems under\break borrowing of strength

DOI10.1063/1.5054656zbMath1414.62394arXiv1811.07625OpenAlexW2900907928WikidataQ92054485 ScholiaQ92054485MaRDI QIDQ4627644

Christos Merkatas, Spyridon J. Hatjispyros

Publication date: 11 March 2019

Published in: Chaos: An Interdisciplinary Journal of Nonlinear Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1811.07625

zbMATH Keywords

predictionrandom dynamical systemsreconstructionMarkov chain Monte Carlo methodsstochastic dynamical systemsBayesian nonparametric model

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Density estimation (62G07) Monte Carlo methods (65C05) Generation, random and stochastic difference and differential equations (37H10)

Related Items (2)

System identification using autoregressive Bayesian neural networks with nonparametric noise models ⋮ A Bayesian nonparametric approach to the approximation of the global stable manifold

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