Bayesian Inference for Stochastic Processes
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"Readers with a good background in the two areas, probability theory and statistical inference, should be able to master the essential ideas of this book."~ Ludwig Paditz, Dresden
". . .All three important types of Bayesian inferences such are estimation, hypothesis testing and forecasting are considered and many examples are worked through using R and WinBUGS codes. . . It will prove useful for students and scientists who want to learn about Bayesian analysis in stochastic processes." ~Miroslav M. Ristic, Stat Papers
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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). Les mer
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Features:
Uses the Bayesian approach to make statistical Inferences about stochastic processes
The R package is used to simulate realizations from different types of processes
Based on realizations from stochastic processes, the WinBUGS package will provide the Bayesian analysis (estimation, testing hypotheses, and prediction) for the unknown parameters of stochastic processes
To illustrate the Bayesian inference, many examples taken from biology, economics, and astronomy will reinforce the basic concepts of the subject
A practical approach is implemented by considering realistic examples of interest to the scientific community
WinBUGS 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.
Detaljer
- Forlag
- CRC Press
- Innbinding
- Innbundet
- Språk
- Engelsk
- Sider
- 448
- ISBN
- 9781138196131
- Utgivelsesår
- 2017
- Format
- 25 x 18 cm
Anmeldelser
«
"Readers with a good background in the two areas, probability theory and statistical inference, should be able to master the essential ideas of this book."~ Ludwig Paditz, Dresden
". . .All three important types of Bayesian inferences such are estimation, hypothesis testing and forecasting are considered and many examples are worked through using R and WinBUGS codes. . . It will prove useful for students and scientists who want to learn about Bayesian analysis in stochastic processes." ~Miroslav M. Ristic, Stat Papers
»
«
"Readers with a good background in the two areas, probability theory and statistical inference, should be able to master the essential ideas of this book."~ Ludwig Paditz, Dresden
". . .All three important types of Bayesian inferences such are estimation, hypothesis testing and forecasting are considered and many examples are worked through using R and WinBUGS codes. . . It will prove useful for students and scientists who want to learn about Bayesian analysis in stochastic processes." ~Miroslav M. Ristic, Stat Papers
»