Bayesian Model Comparison
Published on 21. November 2014
Book
Hardback
390 pages
978-1-78441-185-5 (ISBN)
Description
The volume contains articles that should appeal to readers with computational, modeling, theoretical, and applied interests. Methodological issues include parallel computation, Hamiltonian Monte Carlo, dynamic model selection, small sample comparison of structural models, Bayesian thresholding methods in hierarchical graphical models, adaptive reversible jump MCMC, LASSO estimators, parameter expansion algorithms, the implementation of parameter and non-parameter-based approaches to variable selection, a survey of key results in objective Bayesian model selection methodology, and a careful look at the modeling of endogeneity in discrete data settings. Important contemporary questions are examined in applications in macroeconomics, finance, banking, labor economics, industrial organization, and transportation, among others, in which model uncertainty is a central consideration.
More details
Series
Language
English
Place of publication
Bingley
United Kingdom
Publishing group
Emerald Publishing Limited
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 24 mm
Weight
675 gr
ISBN-13
978-1-78441-185-5 (9781784411855)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Ivan Jeliazkov | Dale J. Poirier
Bayesian Model Comparison
E-Book
11/2014
Emerald Publishing Limited
€134.99
Available for download
Content
Adaptive Sequential Posterior Simulators for Massively Parallel Computing Environments.
Model Switching and Model Averaging in Time-Varying Parameter Regression Models.
Assessing Bayesian Model Comparison in Small Samples.
Bayesian Selection of Systemic Risk Networks.
Parallel Constrained Hamiltonian Monte Carlo for BEKK Model Comparison.
Factor Selection in Dynamic Hedge Fund Replication Models: A Bayesian Approach.
Determining the Proper Specification for Endogenous Covariates in Discrete Data Settings.
Variable Selection in Bayesian Models: Using Parameter Estimation and Non Parameter Estimation Methods.
Intrinsic Priors for Objective Bayesian Model Selection.
Copyright page.
Bayesian Model Comparison.
List of Contributors.
Preface.
Advances in Econometrics.
Bayesian Model Comparison.
Demand Estimation with High-Dimensional Product Characteristics.
Copula Analysis of Correlated Counts.
Model Switching and Model Averaging in Time-Varying Parameter Regression Models.
Assessing Bayesian Model Comparison in Small Samples.
Bayesian Selection of Systemic Risk Networks.
Parallel Constrained Hamiltonian Monte Carlo for BEKK Model Comparison.
Factor Selection in Dynamic Hedge Fund Replication Models: A Bayesian Approach.
Determining the Proper Specification for Endogenous Covariates in Discrete Data Settings.
Variable Selection in Bayesian Models: Using Parameter Estimation and Non Parameter Estimation Methods.
Intrinsic Priors for Objective Bayesian Model Selection.
Copyright page.
Bayesian Model Comparison.
List of Contributors.
Preface.
Advances in Econometrics.
Bayesian Model Comparison.
Demand Estimation with High-Dimensional Product Characteristics.
Copula Analysis of Correlated Counts.