Bayesian nonparametric binary regression via random tessellations - Archive ouverte HAL Access content directly
Journal Articles Statistics and Probability Letters Year : 2009

Bayesian nonparametric binary regression via random tessellations

Lorenzo Trippa
  • Function : Correspondent author
  • PersonId : 898436

Connectez-vous pour contacter l'auteur
Pietro Muliere
  • Function : Author

Abstract

A Bayesian nonparametric model for binary random variables is introduced. The characterization of the probability model is based on the Dirichlet process and on the Poisson hyperplane tessellation model. These two stochastic models are combined in order to adapt, under the hypothesis of partial exchangeability, the reinforcement mechanism of the Pólya urn scheme. A Gibbs sampling algorithm for implementing predictive inference is illustrated and an application of the inferential procedure is discussed.

Keywords

Fichier principal
Vignette du fichier
PEER_stage2_10.1016%2Fj.spl.2009.07.026.pdf (510.1 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-00582597 , version 1 (02-04-2011)

Identifiers

Cite

Lorenzo Trippa, Pietro Muliere. Bayesian nonparametric binary regression via random tessellations. Statistics and Probability Letters, 2009, 79 (21), pp.2273. ⟨10.1016/j.spl.2009.07.026⟩. ⟨hal-00582597⟩

Collections

PEER
18 View
111 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More