Description: Bayesian Inference in Dynamic Econometric Models, Paperback by Bauwens, Luc; Lubrano, Michel; Richard, Jean-Francois, ISBN 0198773137, ISBN-13 9780198773139, Brand New, Free shipping in the US 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 Series Advanced 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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Book Title: Bayesian Inference in Dynamic Econometric Models
Number of Pages: 366 Pages
Publication Name: Bayesian Inference in Dynamic Econometric Models
Language: English
Publisher: Oxford University Press, Incorporated
Subject: Econometrics
Publication Year: 2000
Item Height: 0.8 in
Item Weight: 18.9 Oz
Type: Textbook
Item Length: 9.3 in
Author: Michel Lubrano, Jean-François Richard, Luc Bauwens
Subject Area: Business & Economics
Series: Advanced Texts in Econometrics Ser.
Item Width: 6.1 in
Format: Trade Paperback
