Full Product Details
Author: Arnaud Doucet ,
A. Smith ,
Nando de Freitas ,
Neil Gordon
Publisher: Springer-Verlag New York Inc.
Imprint: Springer-Verlag New York Inc.
Edition: 1st ed. Softcover of orig. ed. 2001
Dimensions:
Width: 15.50cm
, Height: 3.10cm
, Length: 23.50cm
Weight: 1.870kg
ISBN: 9781441928870
ISBN 10: 1441928871
Pages: 582
Publication Date: 01 December 2010
Audience:
Professional and scholarly
,
Professional and scholarly
,
Professional & Vocational
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: In Print
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Reviews
From the reviews: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION ...a remarkable, successful effort at making these ideas available to statisticians. It gives an overview, presents available theory, gives a splendid development of various bells and whistles important in practical implementation, and finally gives a large number of detailed examples and case studies...The authors and editors have been careful to write in a unified, readable way...I find it remarkable that the editors and authors have combined to produce an accessible bible that will be studied and used for years to come. Usually, very few volumes edited from papers contributed by many different authors result in books which can serve as either good textbooks or as useful reference. However, in the case of this book, it is enough to read the foreword by Adrian Smith to realize that this particular volume is quite different. ... it is a good reference book for SMC. (Mohan Delampady, Sankhya: Indian Journal of Statistics, Vol. 64 (A), 2002) In this book the authors present sequential Monte Carlo (SMC) methods ... . Over the last few years several closely related algorithms have appeared under the names `boostrap filters', `particle filters', `Monte Carlo filters', and `survival of the fittest'. The book under review brings together many of these algorithms and presents theoretical developments ... . This book will be of great value to advanced students, researchers, and practitioners who want to learn about sequential Monte Carlo methods for the computational problems of Bayesian Statistics. (E. Novak, Metrika, May, 2003) This book provides a very good overview of the sequential Monte Carlo methods and contains many ideas on further research on methodologies and newer areas of application. ... It will be certainly a valuable reference book for students and researchers working in the area of on-line data analysis. ... the techniques discussed in this book are of great relevance to practitioners dealing with real time data. (Pradipta Sarkar, Technometrics, Vol. 45 (1), 2003)
From the reviews: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION !a remarkable, successful effort at making these ideas available to statisticians. It gives an overview, presents available theory, gives a splendid development of various bells and whistles important in practical implementation, and finally gives a large number of detailed examples and case studies!The authors and editors have been careful to write in a unified, readable way!I find it remarkable that the editors and authors have combined to produce an accessible bible that will be studied and used for years to come. Usually, very few volumes edited from papers contributed by many different authors result in books which can serve as either good textbooks or as useful reference. However, in the case of this book, it is enough to read the foreword by Adrian Smith to realize that this particular volume is quite different. ! it is a good reference book for SMC. (Mohan Delampady, Sankhya: Indian Journal of Statistics, Vol. 64 (A), 2002) In this book the authors present sequential Monte Carlo (SMC) methods ! . Over the last few years several closely related algorithms have appeared under the names 'boostrap filters', 'particle filters', 'Monte Carlo filters', and 'survival of the fittest'. The book under review brings together many of these algorithms and presents theoretical developments ! . This book will be of great value to advanced students, researchers, and practitioners who want to learn about sequential Monte Carlo methods for the computational problems of Bayesian Statistics. (E. Novak, Metrika, May, 2003) This book provides a very good overview of the sequential Monte Carlo methods and contains many ideas on further research on methodologies and newer areas of application. ! It will be certainly a valuable reference book for students and researchers working in the area of on-line data analysis. ! the techniques discussed in this book are of great relevance to practitioners dealing with real time data. (Pradipta Sarkar, Technometrics, Vol. 45 (1), 2003)
From the reviews: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION ...a remarkable, successful effort at making these ideas available to statisticians. It gives an overview, presents available theory, gives a splendid development of various bells and whistles important in practical implementation, and finally gives a large number of detailed examples and case studies...The authors and editors have been careful to write in a unified, readable way...I find it remarkable that the editors and authors have combined to produce an accessible bible that will be studied and used for years to come. Usually, very few volumes edited from papers contributed by many different authors result in books which can serve as either good textbooks or as useful reference. However, in the case of this book, it is enough to read the foreword by Adrian Smith to realize that this particular volume is quite different. ... it is a good reference book for SMC. (Mohan Delampady, Sankhya: Indian Journal of Statistics, Vol. 64 (A), 2002) In this book the authors present sequential Monte Carlo (SMC) methods ... . Over the last few years several closely related algorithms have appeared under the names 'boostrap filters,, 'particle filters,, 'Monte Carlo filters,, and 'survival of the fittest,. The book under review brings together many of these algorithms and presents theoretical developments ... . This book will be of great value to advanced students, researchers, and practitioners who want to learn about sequential Monte Carlo methods for the computational problems of Bayesian Statistics. (E. Novak, Metrika, May, 2003) This book provides a very good overview of the sequential Monte Carlo methods and contains many ideas on further research on methodologies and newer areas of application. ... It will be certainly a valuable reference book for students and researchers working in the area of on-line data analysis. ... the techniques discussed in this book are of great relevance to practitioners dealing with real time data. (Pradipta Sarkar, Technometrics, Vol. 45 (1), 2003)
