Markov Chain Monte Carlo and Numerical Differential Equations

DOI10.1007/978-3-319-01300-8_2zbMath1318.65007OpenAlexW12587120MaRDI QIDQ5261579

Jesús María Sanz-Serna

Publication date: 6 July 2015

Published in: Lecture Notes in Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-01300-8_2

zbMATH Keywords

numerical exampleFokker-Planck equationstochastic differential equationsnumerical experimentHamiltonian dynamicsMarkov chain Monte Carlo methodsMetropolis adjusted Langevin algorithmMetropolis random-walk algorithm

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Sums of independent random variables; random walks (60G50) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Numerical analysis or methods applied to Markov chains (65C40) Ordinary differential equations and systems with randomness (34F05) Stochastic partial differential equations (aspects of stochastic analysis) (60H15) PDEs with randomness, stochastic partial differential equations (35R60) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30) Fokker-Planck equations (35Q84)

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