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Bayesian Inference in Dynamic Econometric Models (Advanced Texts in Econometrics)
Luc Bauwens
(Author)
·
Michel Lubrano
(Author)
·
Jean-François Richard
(Author)
·
Oxford University Press, USA
· Hardcover
Bayesian Inference in Dynamic Econometric Models (Advanced Texts in Econometrics) - Bauwens, Luc ; Lubrano, Michel ; Richard, Jean-François
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Synopsis "Bayesian Inference in Dynamic Econometric Models (Advanced Texts in Econometrics)"
This book offers an up-to-date coverage of the basic principles and tools of Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations, and the long available analytical results of Bayesian inference for linear regression models. About the SeriesAdvanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.
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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.
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