Bayesian Inference for Stochastic Processes - Couverture rigide

Broemeling, Lyle D.

Couverture rigide

ISBN 10 : 1138196134 ISBN 13 : 9781138196131

Editeur : CRC Press, 2017

A propos du livre

Présentation de l'éditeur

The book is designed to introduce Bayesian inference methods for stochastic processes. It is well-known that the Bayesian approach has certain advantages compared to non-Bayesian, among which is the optimal use of prior information via data from previous similar experiments. The book begins with a brief review of Bayesian inference and uses many examples relevant to the analysis of stochastic processes, including the four major types, i.e. discrete time, discete state space, continuous time and continuous state space. Examples taken from a variety of fields including biology, economics, and astronomy will reinforce the basic concepts of the subject. R and WinBUGS will be used to implement the analyses.

Biographie de l'auteur

Lyle D. Broemeling, Ph.D., is Director of Broemeling and Associates Inc., and is a consulting biostatistician. He has been involved with academic health science centers for about 20 years and has taught and been a consultant at the University of Texas Medical Branch in Galveston, The University of Texas MD Anderson Cancer Center and the University of Texas School of Public Health. His main interest is in developing Bayesian methods for use in medical and biological problems and in authoring textbooks in statistics. His previous books are Bayesian Biostatistics and Diagnostic Medicine, and Bayesian Methods for Agreement

Détails de l'édition

• Éditeur: CRC Press
• Date d'édition: 2017
• ISBN 10: 1138196134
• ISBN 13: 9781138196131
• Reliure: Relié
• Langue: anglais
• Nombre de pages: 448