Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data
AbstractA 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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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Business Research.
Volume (Year): 49 (2000)
Issue (Month): 3 (September)
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Web page: http://www.elsevier.com/locate/jbusres
Other versions of this item:
- Smith, M. & Mathur, S.K. & Kohn, R., 1997. "Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data," Monash Econometrics and Business Statistics Working Papers 13/97, Monash University, Department of Econometrics and Business Statistics.
- Smith, M. & Mathur, S. & Kohn, R., . "Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data," Statistics Working Paper _010, Australian Graduate School of Management.
- 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
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Smith, Michael & Kohn, Robert, 1996.
"Nonparametric regression using Bayesian variable selection,"
Journal of Econometrics,
Elsevier, vol. 75(2), pages 317-343, December.
- Smith, M. & Kohn, R., . "Nonparametric Regression using Bayesian Variable Selection," Statistics Working Paper _009, Australian Graduate School of Management.
- Smith, M. & Sheather S. & Kohn, R., . "Finite sample performance of robust Bayesian regression," Statistics Working Paper _011, Australian Graduate School of Management.
- 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.
- 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.
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