B1182
Title: Kernel density estimation for stochastic process with values in a Riemannian manifold
Authors: Wiem Nefzi - Universite El Manar - Laboratoire M2AHTP (Tunisia)
Salah Khardani - Universite El Manar - Laboratoire M2AHTP (Tunisia)
Papa Alioune Meissa Mbaye - University of Clermont Auvergne (France)
Anne Francoise Yao - Universite Clermont Auvergne/LMBP (France)
Mohamed Abdillahi Isman - University Clermont Auvergne (France) [presenting]
Abstract: The purpose is to study the behavior of the kernel density estimator for the Riemannian manifold value proposed in a former study where the observations are generated from a mixing process. Namely, the weak and strong consistency of the estimator is studied. A central-limit theorem, probability and almost sure rate of convergence are also given. The purpose is illustrated through some simulations and a real data application.
