Activity Number:

614
 Statistical Methods for Longitudinal and Other Dependent Data

Type:

Contributed

Date/Time:

Thursday, August 1, 2019 : 8:30 AM to 10:20 AM

Sponsor:

Section on Nonparametric Statistics

Abstract #303091

Presentation

Title:

Estimation of a StarShaped Distribution Function

Author(s):

Ganesh Malla*

Companies:

University of CincinnatiClermont

Keywords:

StarShaped Distribution;
convex distribution function;
nonparametric maximum likelihood estimation;
uniformly strongly consistent;
convergence in distribution;
arg max theorem

Abstract:

A life distribution function F is said to be starshaped if F(x)/x is nondecreasing on its support. This generalizes the model of a convex distribution function, even allowing for jumps. The nonparametric maximum likelihood estimation is known to be inconsistent. We provide a uniformly strongly consistent least squares estimator. We also derive the convergence in distribution of the estimator at a point where F(x)/x is increasing using the arg max theorem.
