Locally Adaptive Nonparametric Binary Regression

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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.
31 pages, 10 figures

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Methodology

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http://salesiana.dossiersoluciones.com/handle/123456789/138564

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0709.3545
 http://arxiv.org/abs/0709.3545

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arXiv