A Bayesian approach to flexible modeling of multivariable response functions

David M. Steinberg

Journal of Multivariate Analysis, 1990, vol. 34, issue 2, 157-172

Abstract: This paper presents a Bayesian approach to empirical regression modeling in which the response function is represented by a power series expansion in Hermite polynomials. The common belief that terms of low degree will reasonably approximate the response function is reflected by assigning prior distributions that exponentially downweight the coefficients of high-degree terms. The model thus includes the complete series expansion. A useful property of the Hermite expansion is that it can be easily extended to handle models with several explanatory variables.

Keywords: Bayesian; linear; model; empirical; modeling; Hermite; polynomials; polynomial; regression; smoothing (search for similar items in EconPapers)
Date: 1990
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