On parameter identification in stochastic differential equations by penalized maximum likelihood

DOI10.1088/0266-5611/30/9/095001zbMath1341.60052arXiv1404.0651OpenAlexW2021483911MaRDI QIDQ2924857

Fabian Dunker, Thorsten Hohage

Publication date: 17 October 2014

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1404.0651

zbMATH Keywords

stochastic differential equationsparameter identificationMonte-Carlo simulationsvariational regularizationpenalized maximum likelihood estimators

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Monte Carlo methods (65C05) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Ordinary differential equations and systems with randomness (34F05) Stochastic methods (Fokker-Planck, Langevin, etc.) applied to problems in time-dependent statistical mechanics (82C31) 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)

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Parameter estimation in SDEs via the Fokker-Planck equation: likelihood function and adjoint based gradient computation ⋮ On the Asymptotical Regularization for Linear Inverse Problems in Presence of White Noise ⋮ A Fokker-Planck control framework for stochastic systems ⋮ Parameter identification and uncertainty quantification in stochastic state space models and its application to texture analysis ⋮ The Tangential Cone Condition for Some Coefficient Identification Model Problems in Parabolic PDEs

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