Sequential Monte Carlo Methods in Practice (Statistics for Engineering and Information Science)

Doucet, Arnaud [Editor]; Freitas, Nando de [Editor]; Gordon, Neil [Editor]; Smith, A. [Foreword];

ISBN 10: 0387951466 / ISBN 13: 9780387951461

Editore: Springer, 2001

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Dati bibliografici

• Titolo: Sequential Monte Carlo Methods in Practice (Statistics for Engineering and Information Science)
• Editore: Springer
• Data di pubblicazione: 2001
• Lingua: Inglese
• ISBN 10: 0387951466
• ISBN 13: 9780387951461
• Rilegatura: hardcover
• Condizione: New

Descrizione articolo

Riassunto

Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques.

Recensione

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)