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

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  • Smith, M.
  • Mathur, S.
  • Kohn, R.

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, M. & Mathur, S. & Kohn, R., "undated". "Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data," Statistics Working Paper _010, Australian Graduate School of Management.
    • Handle: RePEc:wop:agsmst:_010
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    as
    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.
    4. Andi Tenri Ampa & I Nyoman Budiantara & Ismaini Zain, 2022. "Modeling the Level of Drinking Water Clarity in Surabaya City Drinking Water Regional Company Using Combined Estimation of Multivariable Fourier Series and Kernel," Sustainability, MDPI, vol. 14(20), pages 1-12, October.

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    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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