RT Generic
T1 Bayesian inference for the half-normal and half-t distributions
A1 Wiper, Michael Peter
A1 Giron, F.J.
A1 Pewsey, A.
AB In this article we consider approaches to Bayesian inference for the half-normal and half-t distributions. We show that a generalized version of the normal-gamma distribution is conjugate to the half-normal likelihood and give the moments of this new distribution. The bias and coverage of the Bayesian posterior mean estimator of the halfnormal location parameter are compared with those of maximum likelihood based estimators. Inference for the half-t distribution is performed using Gibbs sampling and model comparison is carried out using Bayes factors. A real data example is presented which demonstrates the fitting of the half-normal and half-t models.
YR 2005
FD 2005-07
LK https://hdl.handle.net/10016/229
UL https://hdl.handle.net/10016/229
LA eng
LA eng
DS e-Archivo
RD 27 jul. 2024