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Bayesian econometric methods / Gary Koop, Dale J. Poirier, Justin L. Tobias.

By: Contributor(s): Material type: TextTextSeries: Econometric exercises ; 7.Publisher: Cambridge ; New York : Cambridge University Press, 2007Description: xxi, 357 pages : illustrations ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 0521855713
  • 9780521855716
  • 0521671736
  • 9780521671736
Subject(s): DDC classification:
  • 330.01519542 22
LOC classification:
  • HB139 .K6359 2007
Contents:
1. The subjective interpretation of probability -- 2. Bayesian inference -- 3. Point estimation -- 4. Frequentist properties of bayesian estimators -- 5. Interval estimation -- 6. Hypothesis testing -- 7. Prediction -- 8. Choice of prior -- 9. Asymptotic bayes -- 10. The linear regression model -- 11. Basics of bayesian computation -- 12. Hierarchical models -- 13. The linear regression model with general covariance matrix -- 14. Latent variable models -- 15. Mixture models -- 16. Bayesian model averaging and selection -- 17. Some stationary time series models -- 18. Some nonstationary time series models.
Review: "This book is a volume in the Econometric Exercises series. It teaches principles of Bayesian econometrics by posing a series of theoretical and applied questions, and providing detailed solutions to those questions. This text is primarily suitable for graduate study in econometrics, though it can be used for advanced undergraduate courses, and should generate interest from students in related fields, including finance, marketing, agricultural economics, business economics, and other disciplines that employ statistical methods. The book provides a detailed treatment of a wide array of models commonly employed by economists and statisticians, including linear regression-based models, hierarchical models, latent variable models, mixture models, and time series models."--BOOK JACKET.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Book City Campus City Campus Main Collection 330.01519542 KOO (Browse shelf(Opens below)) 1 Available A372836B

Includes bibliographical references (pages 343-351) and index.

1. The subjective interpretation of probability -- 2. Bayesian inference -- 3. Point estimation -- 4. Frequentist properties of bayesian estimators -- 5. Interval estimation -- 6. Hypothesis testing -- 7. Prediction -- 8. Choice of prior -- 9. Asymptotic bayes -- 10. The linear regression model -- 11. Basics of bayesian computation -- 12. Hierarchical models -- 13. The linear regression model with general covariance matrix -- 14. Latent variable models -- 15. Mixture models -- 16. Bayesian model averaging and selection -- 17. Some stationary time series models -- 18. Some nonstationary time series models.

"This book is a volume in the Econometric Exercises series. It teaches principles of Bayesian econometrics by posing a series of theoretical and applied questions, and providing detailed solutions to those questions. This text is primarily suitable for graduate study in econometrics, though it can be used for advanced undergraduate courses, and should generate interest from students in related fields, including finance, marketing, agricultural economics, business economics, and other disciplines that employ statistical methods. The book provides a detailed treatment of a wide array of models commonly employed by economists and statisticians, including linear regression-based models, hierarchical models, latent variable models, mixture models, and time series models."--BOOK JACKET.

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