Bayesian Inference for Stochastic Processes

Lingua: inglese

Editore: Chapman And Hall/CRC Jun 2020, 2020

0367572435 / 9780367572433

Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

Venditore con 5 stelle

Venditore AbeBooks dal 11 gennaio 2012

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This item is printed on demand - it takes 3-4 days longer - Neuware -This is the first book designed to introduce Bayesian inference procedures for stochastic processes. There are clear advantages to the Bayesian approach (including the optimal use of prior information). Initially, 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, namely those with discrete time and discrete state space and continuous time and continuous state space. The elements necessary to understanding stochastic processes are then introduced, followed by chapters devoted to the Bayesian analysis of such processes. It is important that a chapter devoted to the fundamental concepts in stochastic processes is included. Bayesian inference (estimation, testing hypotheses, and prediction) for discrete time Markov chains, for Markov jump processes, for normal processes (e.g. Brownian motion and the Ornstein-Uhlenbeck process), for traditional time series, and, lastly, for point and spatial processes are described in detail. Heavy emphasis is placed on many examples taken from biology and other scientific disciplines. In order analyses of stochastic processes, it will use R and WinBUGS.Features:Uses the Bayesian approach to make statistical Inferences about stochastic processesThe R package is used to simulate realizations from different types of processesBased on realizations from stochastic processes, the WinBUGS package will provide the Bayesian analysis (estimation, testing hypotheses, and prediction) for the unknown parameters of stochastic processesTo illustrate the Bayesian inference, many examples taken from biology, economics, and astronomy will reinforce the basic concepts of the subjectA practical approach is implemented by considering realistic examples of interest to the scientific communityWinBUGS and R code are provided in the text, allowing the reader to easily verify the results of the inferential procedures found in the many examples of the book Readers with a good background in two areas, probability theory and statistical inference, should be able to master the essential ideas of this book. 450 pp. Englisch.…

Codice articolo 9780367572433

Titolo
Bayesian Inference for Stochastic Processes
Autore
Lyle D. Broemeling
Editore
Chapman And Hall/CRC Jun 2020
Anno di pubblicazione
2020
Condizione
Neu
Rilegatura
Taschenbuch
Lingua
inglese
ISBN 10
0367572435
ISBN 13
9780367572433
Peso dell'articolo
840 grammi
Dimensioni
254x178x24 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 11 gennaio 2012

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 5 a 15 giorni lavorativiDa 5 a 15 giorni lavorativi
Primo articoloEUR 23,00EUR 23,00
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BuchWeltWeit Ludwig Meier e.K.

Germania