Open Access
VOL. 8 | 2012 A nonparametric Bayesian method for estimating a response function
Scott Brown, Glen Meeden

Editor(s) Dominique Fourdrinier, Éric Marchand, Andrew L. Rukhin

Inst. Math. Stat. (IMS) Collect., 2012: 190-199 (2012) DOI: 10.1214/11-IMSCOLL813


Consider the problem of estimating a response function which depends upon a non-stochastic independent variable under our control. The data are independent Bernoulli random variables where the probabilities of success are given by the response function at the chosen values of the independent variable. Here we present a nonparametric Bayesian method for estimating the response function. The only prior information assumed is that the response function can be well approximated by a mixture of step functions.


Published: 1 January 2012
First available in Project Euclid: 14 March 2012

zbMATH: 1326.62016
MathSciNet: MR3202511

Digital Object Identifier: 10.1214/11-IMSCOLL813

Primary: 62C10 , 62C15
Secondary: 62G05

Keywords: binary regression , nonparametric Bayes , stepwise Bayes

Rights: Copyright © 2012, Institute of Mathematical Statistics

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