An optimal experimental design perspective on redial basis function regression

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Title: An optimal experimental design perspective on redial basis function regression
Author: Fokoue, Ernest; Goel, Prem
Abstract: This paper provides a new look at radial basis function regression that reveals striking similarities with the traditional optimal experimental design framework. We show theoreti- cally and computationally that the so-called relevant vectors derived through the relevance vector machine (RVM) and corresponding to the centers of the radial basis function net- work, are very similar and often identical to the support points obtained through various optimal experimental design criteria like D-optimality. This allows us to provide a sta- tistical meaning to the relevant centers in the context of radial basis function regression, but also opens the door to a variety of ways of approach optimal experimental design in multivariate settings.
Record URI: http://hdl.handle.net/1850/11694
Date: 2010-03-15

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