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

Michael Smith (), S.K. Mathur and Robert Kohn ()

No 13/97, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

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.

Keywords: ECONOMETRICS (search for similar items in EconPapers)
JEL-codes: C11 C14 (search for similar items in EconPapers)
Pages: 42 pages
Date: 1997
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Related works:
Journal Article: Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data (2000)
Working Paper: Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data
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