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Peter Rossi - Bayesian Non- and Semi-parametric Methods and Applications - 9780691145327 - V9780691145327
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Bayesian Non- and Semi-parametric Methods and Applications

€ 65.82
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Description for Bayesian Non- and Semi-parametric Methods and Applications Hardback. Reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. This book advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. Series: The Econometric and Tinbergen Institutes Lectures. Num Pages: 224 pages, 66 line illus. BIC Classification: PBTB. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 151 x 217 x 22. Weight in Grams: 412.
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.

Product Details

Publisher
Princeton University Press United States
Number of pages
272
Format
Hardback
Publication date
2014
Series
The Econometric and Tinbergen Institutes Lectures
Condition
New
Weight
411g
Number of Pages
224
Place of Publication
New Jersey, United States
ISBN
9780691145327
SKU
V9780691145327
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Peter Rossi
Peter E. Rossi is the James Collins Professor of Marketing, Economics, and Statistics at UCLA's Anderson School of Management. He has published widely in marketing, economics, statistics, and econometrics and is a coauthor of Bayesian Statistics and Marketing.

Reviews for Bayesian Non- and Semi-parametric Methods and Applications
"As the creator of bayesm (R software for Bayesian inference) and lead author of Bayesian Statistics and Marketing, Rossi has deep knowledge of the book's titular methods."
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Goodreads reviews for Bayesian Non- and Semi-parametric Methods and Applications


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