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

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

Abstract

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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Suggested Citation

  • Smith, Michael & Kohn, Robert & Mathur, Sharat K., 2000. "Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data," Journal of Business Research, Elsevier, vol. 49(3), pages 229-244, September.
  • Handle: RePEc:eee:jbrese:v:49:y:2000:i:3:p:229-244
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    References listed on IDEAS

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    1. Smith, M. & Sheather S. & Kohn, R., "undated". "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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    Cited by:

    1. Peter J. Danaher & Michael S. Smith, 2011. "Modeling Multivariate Distributions Using Copulas: Applications in Marketing," Marketing Science, INFORMS, vol. 30(1), pages 4-21, 01-02.
    2. Danaher, Peter J. & Dagger, Tracey S. & Smith, Michael S., 2011. "Forecasting television ratings," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1215-1240, October.
    3. Huhmann, Bruce A. & Franke, George R. & Mothersbaugh, David L., 2012. "Print advertising: Executional factors and the RPB Grid," Journal of Business Research, Elsevier, vol. 65(6), pages 849-854.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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