Bayesian Non- and Semi-parametric Methods and Applications
Title | Bayesian Non- and Semi-parametric Methods and Applications PDF eBook |
Author | Peter Rossi |
Publisher | Princeton University Press |
Pages | 218 |
Release | 2014-04-27 |
Genre | Business & Economics |
ISBN | 0691145326 |
This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distributional assumptions. As more data becomes available, a natural desire to provide methods that relax these assumptions arises. Peter Rossi advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. The Bayesian approach can use either a large but fixed number of normal components in the mixture or an infinite number bounded only by the sample size. By using flexible distributional approximations instead of fixed parametric models, the Bayesian approach can reap the advantages of an efficient method that models all of the structure in the data while retaining desirable smoothing properties. Non-Bayesian non-parametric methods often require additional ad hoc rules to avoid "overfitting," in which resulting density approximates are nonsmooth. With proper priors, the Bayesian approach largely avoids overfitting, while retaining flexibility. This book provides methods for assessing informative priors that require only simple data normalizations. The book also applies the mixture of the normals approximation method to a number of important models in microeconometrics and marketing, including the non-parametric and semi-parametric regression models, instrumental variables problems, and models of heterogeneity. In addition, the author has written a free online software package in R, "bayesm," which implements all of the non-parametric models discussed in the book.
Bayesian Semi-Parametric and Non-Parametric Methods in Marketing and Micro-Econometrics
Title | Bayesian Semi-Parametric and Non-Parametric Methods in Marketing and Micro-Econometrics PDF eBook |
Author | Peter E. Rossi |
Publisher | |
Pages | 214 |
Release | 2013 |
Genre | |
ISBN |
I review and develop Bayesian non-parametric and semi-parametric methods based on finite and infinite mixtures of normals. Applications include regression, IV methods, and random coefficient models.
Practical Nonparametric and Semiparametric Bayesian Statistics
Title | Practical Nonparametric and Semiparametric Bayesian Statistics PDF eBook |
Author | Dipak D. Dey |
Publisher | Springer Science & Business Media |
Pages | 376 |
Release | 2012-12-06 |
Genre | Mathematics |
ISBN | 1461217326 |
A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies.
Applied Bayesian Semiparametric Methods with Special Application to the Accelerated Failure Time Model and to Hierarchical Models for Screening
Title | Applied Bayesian Semiparametric Methods with Special Application to the Accelerated Failure Time Model and to Hierarchical Models for Screening PDF eBook |
Author | Timothy Edward Hanson |
Publisher | |
Pages | 268 |
Release | 2000 |
Genre | |
ISBN |
Bayesian Nonparametrics
Title | Bayesian Nonparametrics PDF eBook |
Author | J.K. Ghosh |
Publisher | Springer Science & Business Media |
Pages | 311 |
Release | 2006-05-11 |
Genre | Mathematics |
ISBN | 0387226540 |
This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian non-parametrics.
Bayesian Nonparametric and Semiparametric Modeling Using Dirichlet Process Mixing
Title | Bayesian Nonparametric and Semiparametric Modeling Using Dirichlet Process Mixing PDF eBook |
Author | Athanasios Kottas |
Publisher | |
Pages | 294 |
Release | 2000 |
Genre | |
ISBN |
Nonparametric and Semiparametric Models
Title | Nonparametric and Semiparametric Models PDF eBook |
Author | Wolfgang Karl Härdle |
Publisher | Springer Science & Business Media |
Pages | 317 |
Release | 2012-08-27 |
Genre | Mathematics |
ISBN | 364217146X |
The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.