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On bayesian estimation of model parameters

Author: Vanhonacker, Wilfried R. INSEAD Area: MarketingIn: Marketing Science, vol. 9, no. 1, winter 1990 Language: EnglishDescription: p. 54-56.Type of document: INSEAD ArticleNote: Please ask us for this itemAbstract: Bayesian estimation procedures have received limited attention in the marketing science community despite the fact that prior information building, estimating, testing and using models are typically used. The work by Lenk and Rao (1989) re-emphasises the importance and appropriateness of the Bayesian approach to solving marketing problems. For years, attempts have been made to obtain reliable and valid forecasts of the diffusion process of product innovations early into their market cycle. Lenk and Raos (1989) useful introduction to Hierarchical Bayes (HB) procedures and their usefulness in early (and adaptive) forecasting is timely and appropriate. The purpose of this comment is to position the contribution in a broader framework of Bayesian approaches to the problem, highlight a key assumption of HB, and provide some directions for further research on this important problem
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Bayesian estimation procedures have received limited attention in the marketing science community despite the fact that prior information building, estimating, testing and using models are typically used. The work by Lenk and Rao (1989) re-emphasises the importance and appropriateness of the Bayesian approach to solving marketing problems. For years, attempts have been made to obtain reliable and valid forecasts of the diffusion process of product innovations early into their market cycle. Lenk and Raos (1989) useful introduction to Hierarchical Bayes (HB) procedures and their usefulness in early (and adaptive) forecasting is timely and appropriate. The purpose of this comment is to position the contribution in a broader framework of Bayesian approaches to the problem, highlight a key assumption of HB, and provide some directions for further research on this important problem

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