Abstract
A generic method for the estimation of parameters for Stochastic Ordinary Differential Equations (SODEs) is introduced and developed. This algorithm, called the GePERs method, utilises a genetic optimisation algorithm to minimise a stochastic objective function based on the Kolmogorov-Smirnov statistic. Numerical simulations are utilised to form the KS statistic. Further, the examination of some of the factors that improve the precision of the estimates is conducted. This method is used to estimate parameters of diffusion equations and jump-diffusion equations. It is also applied to the problem of model selection for the Queensland electricity market.
Original language | English |
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Pages (from-to) | 255-275 |
Number of pages | 21 |
Journal | Computational Statistics and Data Analysis |
Volume | 47 |
Issue number | 2 SPEC. ISS. |
DOIs | |
Publication status | Published - 1 Sept 2004 |
Keywords
- Genetic algorithms
- Jump-diffusion equations
- Parameter estimation
- Stochastic ordinary differential equations
ASJC Scopus subject areas
- Statistics and Probability
- Computational Mathematics
- Computational Theory and Mathematics
- Applied Mathematics