RT Generic
T1 Bayesian marginal equivalence of elliptical regression models
A1 Osiewalski, Jacek
A1 Steel, Mark F.J.
A2 Universidad Carlos III de Madrid. Departamento de Economía, 
AB The use of proper prior densities in regression models with multivariate non-Normal elliptical error distributions is examined when the scale matrix is known up to a precision factor T, treated as a nuisance parameter. Marginally equivalent models preserve the convenient predictive and posterior results on the parameter of interest B obtained in the reference case of the Normal model and its conditionally natural conjugate gamma prior. Prior densities inducing this property are derived for two special cases of non-Normal elliptical densities representing very different patterns of tail behavior. In a linear framework, so-called semi-conjugate prior structures are defined as leading to marginal equivalence to a Normal data density with a fully natural conjugate prior.
SN 2340-5031
YR 1992
FD 1992-02
LK https://hdl.handle.net/10016/10950
UL https://hdl.handle.net/10016/10950
LA eng
DS e-Archivo
RD 4 jun. 2024