Statistical Inference for Ergodic Diffusion Processes (Springer Series in Statistics)

Kutoyants, Yury A.

ISBN 10: 184996906X / ISBN 13: 9781849969062

Published by Springer, 2010

About this Item

Like New. Seller Inventory # D8F0-0-M-184996906X-6

Bibliographic Details

Title: Statistical Inference for Ergodic Diffusion ...

Publisher: Springer

Publication Date: 2010

Binding: Paperback

Condition: Like New

Book Type: book

About this title

Synopsis:

The first book in inference for stochastic processes from a statistical, rather than a probabilistic, perspective. It provides a systematic exposition of theoretical results from over ten years of mathematical literature and presents, for the first time in book form, many new techniques and approaches.

 

Review:

From the reviews:

"This book is very much in the Springer mould of graduate mathematical statistics books, giving rapid access to the latest literature...It presents a strong discussion of nonparametric and semiparametric results, from both classical and Bayesian standpoints...I have no doubt that it will come to be regarded as a classic text." Journal of the Royal Statistical Society, Series A, v. 167

"This book is an amazing collection of results and examples of inference problems in the setup considered. Each chapter also considers historical remarks and starts with a very focused introduction explaining in a few lines the content of the chapter. ... The book is well written ... . This book will be useful to both Ph.D. students in mathematical statistics and young researchers. Experts in the field will also find this collection of results valuable. A must have!" (Stefano Maria Iacus, Mathematical Reviews, 2006 b)

"The author has done a thorough job of presenting all that is known in the area of large sample theory of estimation in diffusions processes. Many deep and technically difficult results of the authors and his collaborators appear in the book. A must have for anyone interested in inference in diffusions." (Arup Bose, Sankhya: The Indian Journal of Statistics, Vol. 67 (1), 2005)

"This book is very much in the Springer mould of graduate mathematical statistics books, giving rapid access to the latest literature. ... It presents a strong discussion of nonparametric and semiparametric results, from both classical and Bayesian standpoints. The book will be of greatest use to mathematical statisticians, and as a reference work for those highly mathematical financial analysts who are involved in pricing, monitoring and trading derivatives. ... I have no doubt that it will come to be regarded as a classic text." (Mohamed Afzal Norat, Journal of the Royal Statistical Society, Vol. 167 (4), 2004)

"This work is a continuation of the study of large sample theory of continuous time stochastic processes investigated by the author ... . The book is written in a very clear style and is of use for research workers in the area of stochastic processes." (B. L. S. Prakasa Rao, Zentralblatt MATH, Vol. 1038 (13), 2004)