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Bayesian non- and semi-parametric methods and applications / Peter E. Rossi.

By: Material type: TextTextSeries: The Econometric and Tinbergen Institutes lecturesPublication details: Princeton : Princeton University Press, c2014.Description: xiii, 202 p. : illustrations ; 22 cmISBN:
  • 9780691145327 (hardcover : alk. paper)
Subject(s): DDC classification:
  • 000SB:330 23 R833
Contents:
1. Mixtures of normals-- 2. Dirichlet process prior and density estimation-- 3. Non-parametric regression-- 4. Semi-parametric approaches-- 5. Random coefficient models-- 6. Conclusions and directions for future research-- Bibliography-- Index.
Summary: 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.
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Includes bibliographical references (p. 195-200) and index.

1. Mixtures of normals--
2. Dirichlet process prior and density estimation--
3. Non-parametric regression--
4. Semi-parametric approaches--
5. Random coefficient models--
6. Conclusions and directions for future research--

Bibliography--
Index.

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.

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