Volume no :4, Issue no: 1, September (2010)

Journal of Statistics: Advances in Theory and Applications

KERNEL DENSITY AND REGRESSION ESTIMATIONS FOR LINEAR PROCESSES WITH MIXING INNOVATIONS

Author's: Leila Hamdad, Ouafae Benrabah and Sophie Dabo-Niang
Pages: [41] - [72]
Received Date: September 29, 2010
Submitted by:

Abstract

We investigate kernel estimates of the density and regression functions of linear processes with dependent innovations. The uniform almost sure and mean square consistencies of the estimates are proved under some mixing conditions. Special attention is paid to some simulations results.

Keywords

linear process, mixing innovations, kernel estimator.