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Bayesian Inference in Dynamic Econometric Models$
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Luc Bauwens, Michel Lubrano, and Jean-François Richard

Print publication date: 2000

Print ISBN-13: 9780198773122

Published to Oxford Scholarship Online: September 2011

DOI: 10.1093/acprof:oso/9780198773122.001.0001

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Methods of Numerical Integration

Methods of Numerical Integration

Chapter:
(p.65) 3 Methods of Numerical Integration
Source:
Bayesian Inference in Dynamic Econometric Models
Author(s):

Luc Bauwens

Michel Lubrano

Jean-François Richard

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198773122.003.0003

This chapter examines the application of numerical methods in econometrics and provides some methods useful for Bayesian inference in econometrics. It presents the general principle of Bayesian analysis of models for which partly analytical results are available. It explains the general principle of partially linear models and discusses the computing principles for the Bayesian analysis of econometric models for which fully analytical posterior or predictive results are not available.

Keywords:   numerical methods, econometrics, Bayesian inference, linear models, econometric models

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