Copyright © 2012 Salim Bouzebda and Mohamed Cherfi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
A general notion of bootstrapped ϕ-divergence estimates constructed
by exchangeably weighting sample is introduced. Asymptotic properties of these
generalized bootstrapped ϕ-divergence estimates are obtained, by means of the
empirical process theory, which are applied to construct the bootstrap confidence
set with asymptotically correct coverage probability. Some of practical problems
are discussed, including, in particular, the choice of escort parameter, and several
examples of divergences are investigated. Simulation results are provided to illustrate
the finite sample performance of the proposed estimators.