A Bayesian Semiparametric Approach for Solving the Discrete Calibration Problem

Paz Casanova, Maria; Iglesias, Pilar; Bolfarine, Heleno

A Bayesian Semiparametric Approach for Solving the Discrete Calibration Problem

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2024-05-08. A Bayesian Semiparametric Approach for Solving the Discrete Calibration Problem.pdf(2.31 KB)

Date

2010

Authors

Paz Casanova, Maria

Iglesias, Pilar

Bolfarine, Heleno

Publisher

TAYLOR & FRANCIS INC

Abstract

In this article, we introduce a semi-parametric Bayesian approach based on Dirichlet process priors for the discrete calibration problem in binomial regression models. An interesting topic is the dosimetry problem related to the dose-response model. A hierarchical formulation is provided so that a Markov chain Monte Carlo approach is developed. The methodology is applied to simulated and real data.

Keywords

Binary regression, Dirichlet process, Dosimetry problem, MCMC, Posterior distribution, NONPARAMETRIC-INFERENCE, BINARY REGRESSION, RESPONSE DATA, MODELS, BIOASSAY, LINK, DOSIMETRY

URI

https://doi.org/10.1080/03610910903453427
https://repositorio.uc.cl/handle/11534/75677

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