Statistical methods for stochastic differential equations [electronic resource] / edited by Mathieu Kessler, Alexander Lindner, Michael S�rensen.

"A Chapman & Hall book."

Includes bibliographical references (p. 471-472) and index.

1. Estimating functions for diffusion-type processes / Michael S�rensen -- 2. The econometrics of high-frequency data / Per A. Mykland and Lan Zhang -- 3. Statistics and high-frequency data / Jean Jacod -- 4. Importance sampling techniques for estimation of diffusion models / Omiros Papaspiliopoulos and Gareth Roberts -- 5. Non-parametric estimation of the coefficients of ergodic diffusion processes based on high-frequency data / Fabienne Comte, Valentine Genon-Catalot, and Yves Rozenholc -- 6. Ornstein-Uhlenbeck related models driven by L�evy processes / Peter J. Brockwell and Alexander Lindner -- 7. Parameter estimation for multiscale diffusions : an overview / Grigorios A. Pavliotis, Yvo Pokern, and Andrew M. Stuart.

"Preface The chapters of this volume represent the revised versions of the main papers given at the seventh S�eminaire Europ�een de Statistique on "Statistics for Stochastic Differential Equations Models", held at La Manga del Mar Menor, Cartagena, Spain, May 7th-12th, 2007. The aim of the S�eminaire Europ�een de Statistique is to provide talented young researchers with an opportunity to get quickly to the forefront of knowledge and research in areas of statistical science which are of major current interest. As a consequence, this volume is tutorial, following the tradition of the books based on the previous seminars in the series entitled: Networks and Chaos - Statistical and Probabilistic Aspects. Time Series Models in Econometrics, Finance and Other Fields. Stochastic Geometry: Likelihood and Computation. Complex Stochastic Systems. Extreme Values in Finance, Telecommunications and the Environment. Statistics of Spatio-temporal Systems. About 40 young scientists from 15 different nationalities mainly from European countries participated. More than half presented their recent work in short communications; an additional poster session was organized, all contributions being of high quality. The importance of stochastic differential equations as the modeling basis for phenomena ranging from finance to neurosciences has increased dramatically in recent years. Effective and well behaved statistical methods for these models are therefore of great interest. However the mathematical complexity of the involved objects raise theoretical but also computational challenges. The S�eminaire and the present book present recent developments that address, on one hand, properties of the statistical structure of the corresponding models and,"-- Provided by publisher.

Also available in print edition.

Mode of access: World Wide Web.