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Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data

  • Smith, Michael
  • Kohn, Robert
  • Mathur, Sharat K.

A new regression based approach is proposed for modeling marketing databases. The approach is Bayesian and provides a number of significant improvements over current methods. Independent variables can enter into the model in either a parametric or nonparametric manner, significant variables can be identified from a large number of potential regressors and an appropriate transformation of the dependent variable can be automatically selected from a discrete set of pre-specified candidate transformations.

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File URL: http://www.sciencedirect.com/science/article/B6V7S-4105CV8-2/2/5bc8359c1c4777836c49e1e0584d54ff
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Article provided by Elsevier in its journal Journal of Business Research.

Volume (Year): 49 (2000)
Issue (Month): 3 (September)
Pages: 229-244

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Handle: RePEc:eee:jbrese:v:49:y:2000:i:3:p:229-244
Contact details of provider: Web page: http://www.elsevier.com/locate/jbusres

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  1. Smith, M. & Sheather S. & Kohn, R., . "Finite sample performance of robust Bayesian regression," Statistics Working Paper _011, Australian Graduate School of Management.
  2. Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
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