In this paper we study the effects of infinitesimal perturbations to a fixed sampling distribution function, known up to a finite-dimensional parameter, on the Bayes factor comparing the given parametric model against a nonparametric alternative. We consider the Bayes factor as a non ratio-linear functional defined on a set of sampling distributions functions and maximize its first von Mises derivative over this set. In particular mixture and density bounded sets are considered.
Local robustness and Bayes factors for nonparametric alternatives
CAROTA, Cinzia
1996-01-01
Abstract
In this paper we study the effects of infinitesimal perturbations to a fixed sampling distribution function, known up to a finite-dimensional parameter, on the Bayes factor comparing the given parametric model against a nonparametric alternative. We consider the Bayes factor as a non ratio-linear functional defined on a set of sampling distributions functions and maximize its first von Mises derivative over this set. In particular mixture and density bounded sets are considered.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
