dc.creator | Paz Casanova, Maria | |
dc.creator | Iglesias, Pilar | |
dc.creator | Bolfarine, Heleno | |
dc.date.accessioned | 2024-01-10T12:04:05Z | |
dc.date.available | 2024-01-10T12:04:05Z | |
dc.date.created | 2024-01-10T12:04:05Z | |
dc.date.issued | 2010 | |
dc.identifier | 10.1080/03610910903453427 | |
dc.identifier | 0361-0918 | |
dc.identifier | https://doi.org/10.1080/03610910903453427 | |
dc.identifier | https://repositorio.uc.cl/handle/11534/75677 | |
dc.identifier | WOS:000274979200010 | |
dc.description.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. | |
dc.language | en | |
dc.publisher | TAYLOR & FRANCIS INC | |
dc.rights | acceso restringido | |
dc.subject | Binary regression | |
dc.subject | Dirichlet process | |
dc.subject | Dosimetry problem | |
dc.subject | MCMC | |
dc.subject | Posterior distribution | |
dc.subject | NONPARAMETRIC-INFERENCE | |
dc.subject | BINARY REGRESSION | |
dc.subject | RESPONSE DATA | |
dc.subject | MODELS | |
dc.subject | BIOASSAY | |
dc.subject | LINK | |
dc.subject | DOSIMETRY | |
dc.title | A Bayesian Semiparametric Approach for Solving the Discrete Calibration Problem | |
dc.type | artículo | |