Posterior inference on parameters of stochastic differential equations via non-linear Gaussian filtering and adaptive MCMC

DOI10.1007/s11222-013-9441-1zbMath1331.65021OpenAlexW2000454092MaRDI QIDQ5962749

Jouni Hartikainen, Heikki Haario, Isambi Sailon Mbalawata, Simo Särkkä

Publication date: 23 February 2016

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-013-9441-1

zbMATH Keywords

stochastic differential equationparameter estimationadaptive Markov chain Monte CarloGaussian approximationnon-linear Kalman filter

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Estimation and detection in stochastic control theory (93E10) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (2)

Contrast estimation for noisy observations of diffusion processes via closed-form density expansions ⋮ Generative Ensemble Regression: Learning Particle Dynamics from Observations of Ensembles with Physics-informed Deep Generative Models

Uses Software

• BayesDA
• ramcmc

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