Estimation of parameters in mean-reverting stochastic systems
Stochastic differential equation (SDE) is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as p...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Gordon and Breach
2014
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| Online Access: | http://hdl.handle.net/20.500.11937/31895 |
| _version_ | 1848753511004635136 |
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| author | Tian, T. Zhou, Y. Wu, Yong Hong Ge, X. |
| author_facet | Tian, T. Zhou, Y. Wu, Yong Hong Ge, X. |
| author_sort | Tian, T. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Stochastic differential equation (SDE) is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as physical sciences. Since a SDE can generate unlimited numbers of trajectories, it is difficult to estimate model parameters based on experimental observations which may represent only one trajectory of the stochastic model. Although substantial research efforts have been made to develop effective methods, it is still a challenge to infer unknown parameters in SDE models from observations that may have large variations. Using an interest rate model as a test problem, in this work we use the Bayesian inference and Markov Chain Monte Carlo method to estimate unknown parameters in SDE models. |
| first_indexed | 2025-11-14T08:25:40Z |
| format | Journal Article |
| id | curtin-20.500.11937-31895 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:25:40Z |
| publishDate | 2014 |
| publisher | Gordon and Breach |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-318952017-09-13T16:07:20Z Estimation of parameters in mean-reverting stochastic systems Tian, T. Zhou, Y. Wu, Yong Hong Ge, X. mathematical tools inference engines - Bayesian inference dynamic property Bayesian networks estimation physical science stochastic differential equations estimation of parameters Markov chain Monte Carlo method interest rate models Stochastic differential equation (SDE) is a very important mathematical tool to describe complex systems in which noise plays an important role. SDE models have been widely used to study the dynamic properties of various nonlinear systems in biology, engineering, finance, and economics, as well as physical sciences. Since a SDE can generate unlimited numbers of trajectories, it is difficult to estimate model parameters based on experimental observations which may represent only one trajectory of the stochastic model. Although substantial research efforts have been made to develop effective methods, it is still a challenge to infer unknown parameters in SDE models from observations that may have large variations. Using an interest rate model as a test problem, in this work we use the Bayesian inference and Markov Chain Monte Carlo method to estimate unknown parameters in SDE models. 2014 Journal Article http://hdl.handle.net/20.500.11937/31895 10.1155/2014/317059 Gordon and Breach fulltext |
| spellingShingle | mathematical tools inference engines - Bayesian inference dynamic property Bayesian networks estimation physical science stochastic differential equations estimation of parameters Markov chain Monte Carlo method interest rate models Tian, T. Zhou, Y. Wu, Yong Hong Ge, X. Estimation of parameters in mean-reverting stochastic systems |
| title | Estimation of parameters in mean-reverting stochastic systems |
| title_full | Estimation of parameters in mean-reverting stochastic systems |
| title_fullStr | Estimation of parameters in mean-reverting stochastic systems |
| title_full_unstemmed | Estimation of parameters in mean-reverting stochastic systems |
| title_short | Estimation of parameters in mean-reverting stochastic systems |
| title_sort | estimation of parameters in mean-reverting stochastic systems |
| topic | mathematical tools inference engines - Bayesian inference dynamic property Bayesian networks estimation physical science stochastic differential equations estimation of parameters Markov chain Monte Carlo method interest rate models |
| url | http://hdl.handle.net/20.500.11937/31895 |