Date: 2016-04-01

Time: 15:30-16:30

Location: BURN 1205

Abstract:

In this talk, I will describe the finite- and large-sample behavior of binned kernel density estimators for dependent and locally non-stationary random fields converging to stationary random fields. In addition to looking at the bias and asymptotic normality of the estimators, I will present results from a simulation study which shows that the kernel density estimator and the binned kernel density estimator have the same behavior and both estimate accurately the true density when the number of fields increases. This work finds applications in various fields, including the study of epidemics and mining research. My specific illustration will be concerned with the 2002 incidence rates of tuberculosis in the departments of France.

Speaker

Michel Harel is Professor of Statistics at the Université de Limoges and a member of the Institut de mathématiques de Toulouse, France.