In the present study, Bayesian method of estimating Pickands dependence function bivariate extreme-value copulas is proposed. Initially, cubic B-spline regression used to model function. Then, estimator obtained by approach. Through estimation process, prior and posterior distributions parameter vectors are provided. The sampling algorithm presented in order approximate distribution. We give a ...

In this article we study function estimation via wavelet shrinkage for data with long-range dependence. We propose a fractional Gaussian noise model to approximate nonparametric regression with long-range dependence and establish asymp-totics for minimax risks. Because of long-range dependence, the minimax risk and the minimax linear risk converge to zero at rates that diier from those for data...

We consider the case in which the available knowledge does not allow to specify a precise probabilistic model for the prior and/or likelihood in statistical estimation. We assume that this imprecision can be represented by belief functions. Thus, we exploit the mathematical structure of belief functions and their equivalent representation in terms of closed convex sets of probability measures t...