Forecasting with the Fokker-Planck model: Bayesian setting of parameter

DOI10.1016/J.PHYSA.2016.12.005zbMath1400.82196OpenAlexW2563966295MaRDI QIDQ1620462

Chris Montagnon

Publication date: 13 November 2018

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physa.2016.12.005

zbMATH Keywords

Fokker-Planck equationprobability distributionBayesian parameter selectionstock reduction

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics (82C31)

Related Items (1)

Forecasting by splitting a time series using singular value decomposition then using both ARMA and A Fokker Planck equation

Cites Work

• Handbook of economic forecasting. Volume 1
• Time series: theory and methods.
• The Fokker-Planck equation. Methods of solutions and applications.
• A note on estimating drift and diffusion parameters from time series

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