Statistical Methods for Stochastic Differential Equations

Author:   Mathieu Kessler ,  Alexander Lindner ,  Michael Sorensen
Publisher:   Taylor & Francis Inc
Volume:   No. 124
ISBN:  

9781439849408


Pages:   508
Publication Date:   17 May 2012
Format:   Hardback
Availability:   In Print   Availability explained
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Statistical Methods for Stochastic Differential Equations


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Author:   Mathieu Kessler ,  Alexander Lindner ,  Michael Sorensen
Publisher:   Taylor & Francis Inc
Imprint:   Chapman & Hall/CRC
Volume:   No. 124
Dimensions:   Width: 15.60cm , Height: 3.30cm , Length: 23.40cm
Weight:   0.839kg
ISBN:  

9781439849408


ISBN 10:   1439849404
Pages:   508
Publication Date:   17 May 2012
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Estimating functions for diffusion-type processes. The econometrics of high frequency data. Statistics and high frequency data. Importance sampling techniques for estimation of diffusion models. Non parametric estimation of the coefficients of ergodic diffusion processes based on high frequency data. Ornstein–Uhlenbeck related models driven by Lévy processes. Parameter estimation for multiscale diffusions: an overview.

Reviews

"""… an excellent resource for anyone currently active in research in this area, interested in getting into research in the area, or just interested in the topic. I cannot think of another source that provides detailed yet accessible introductions of this quality and timeliness to the major issues of interest in this area. … As noted in the preface, the idea is to get young researchers ‘quickly to the forefront of knowledge and research.’ … The book succeeds in delivering on this goal. A careful reading of the chapters of this book would go a long way toward putting one in a position to begin contributing to the large and rapidly growing body of research in this important area of statistics. It would certainly be an excellent resource for teaching advanced Ph.D. courses. … This is a wonderful book for anyone interested in SDEs. I highly recommend it and am happy to have it on my bookshelf."" —Garland B. Durham, Journal of the American Statistical Association, March 2014 ""The contributors are all renowned specialists in the field … the last four chapters are generally well written, informative, and cover a wide range of different aspects of statistics for SDE … the first three chapters … constitute an original and very useful contribution in a field that too often has the reputation of being technical and somehow austere. … I strongly recommend the book for anyone interested in the wide topic of statistical methods for SDE, whether she or he is a specialist or a student starting in the field."" —Marc Hoffmann, Université Paris–Dauphine Sørensen, CHANCE, 26.3 ""… a good collection of useful and interesting articles … [I have] no hesitation in recommending the book."" —Tusheng Zhang, Journal of Time Series Analysis, 2013"


... a good collection of useful and interesting articles ... [I have] no hesitation in recommending the book. -Tusheng Zhang, Journal of Time Series Analysis, 2013


Author Information

Matthieu Kessler, Department of Applied Mathematics and Statistics, University of Cartagena, Spain Alexander Lindner, Institute of Mathematics and Statistics, TU Braunschweig, Germany Michael Sorensen, Department of Mathematical Sciences, University of Copenhagen, Denmark

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