Stochastic differential equations as a tool to regularize the parameter estimation problem for continuous time dynamical systems given discrete time measurements-Reference-Cited by-同舟云学术

Stochastic differential equations as a tool to regularize the parameter estimation problem for continuous time dynamical systems given discrete time measurements

Published:2014-05 Issue: Volume:251 Page:54-62
ISSN:0025-5564
Container-title:Mathematical Biosciences
language:en
Short-container-title:Mathematical Biosciences

Author:

Leander Jacob,Lundh Torbjörn,Jirstrand Mats

Publisher

Elsevier BV

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine,Statistics and Probability

Reference35 articles.

1. Scientific Computing with Ordinary Differential Equations;Deuflhard,2002

2. Numerical Data Fitting in Dynamical Systems – A Practical Introduction with Applications and Software;Schittkowsky,2002

3. Issues in nonlinear stochastic grey box identification;Bohlin;Int. J. Adapt. Control Signal Process.,1995

4. Parameter estimation in stochastic differential equations with Markov chain Monte Carlo and non-linear Kalman filtering;Mbalawata;Comput. Stat.,2012

5. Parameter estimation in stochastic grey-box models;Kristensen;Automatica,2004

Cited by 27 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Parameter Estimation for Geometric Lévy Processes with Constant Volatility;Annals of Data Science;2024-01-30

2. Introduction;SpringerBriefs on PDEs and Data Science;2024

3. Kinematic motion models based vessel state estimation to support advanced ship predictors;Ocean Engineering;2023-10

4. Identifiability analysis for stochastic differential equation models in systems biology;Journal of The Royal Society Interface;2020-12

5. Differential equations in data analysis;WIREs Computational Statistics;2020-11-30