Parameter estimation in nonlinear stochastic dierential equations
نویسنده
چکیده
We discuss the problem of parameter estimation in nonlinear stochastic dierential equations (SDEs) based on sampled time series. A central message from the theory of integrating SDEs is that there exist in general two time scales, i.e. that of integrating these equations and that of sampling. We argue that therefore, maximum likelihood estimation is computationally extremely expensive. We discuss the relation between maximum likelihood and quasi maximum likelihood estimation. In a simulation study, we compare the quasi maximum likelihood method with an approach for parameter estimation in nonlinear SDEs that disregards the existence of the two time scales. Ó 2000 Elsevier Science Ltd. All rights reserved.
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