Overview

Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.

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9783540842767

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<p>From the reviews: <p><p> This book deals with a variety of statistical inference problems for stochastic differential equations . In each chapter the author starts with useful introductory notes clearly describing the specific models and the problems. A series of interesting and well commented examples are provided as an illustration. Among the readers who can benefit from this carefully written book are researchers and postgraduate students in stochastic modelling; especially those working in areas such as physics, engineering, biology and finance. (Jordan M. Stoyanov, Zentralblatt MATH, Vol. 1134 (12), 2008)

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