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

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

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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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 13/97.

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Length: 42 pages
Date of creation: 1997
Date of revision:
Handle: RePEc:msh:ebswps:1997-13
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Web page: http://www.buseco.monash.edu.au/depts/ebs/
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  1. Smith, M. & Kohn, R., . "Nonparametric Regression using Bayesian Variable Selection," Statistics Working Paper _009, Australian Graduate School of Management.
  2. Smith, M. & Sheather S. & Kohn, R., . "Finite sample performance of robust Bayesian regression," Statistics Working Paper _011, Australian Graduate School of Management.
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