Statistics – Methodology
Scientific paper
2007-09-21
Statistics
Methodology
31 pages, 10 figures
Scientific paper
A nonparametric and locally adaptive Bayesian estimator is proposed for estimating a binary regression. Flexibility is obtained by modeling the binary regression as a mixture of probit regressions with the argument of each probit regression having a thin plate spline prior with its own smoothing parameter and with the mixture weights depending on the covariates. The estimator is compared to a single spline estimator and to a recently proposed locally adaptive estimator. The methodology is illustrated by applying it to both simulated and real examples.
Cottet Remy
Jiang Wenxin
Kohn Robert
Tanner Martin
Wood Sally
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