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Activity Number: 187 - Contributed Poster Presentations: Section on Nonparametric Statistics
Type: Contributed
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract #304336
Title: Strong Consistency of the Non-Parametric Maximum Likelihood Estimator of Correlated Normal Random Variables
Author(s): Xiangjie Xue*
Companies: University of Auckland
Keywords: Non-parametric Maximum Likelihood Estimate; Correlated Variables

The strong consistency of the non-parametric maximum likelihood estimator (NPMLE) of a mixing distribution was established in 1956 under the independence assumption. We consider the special yet important problem of estimating the distribution function of location parameters of weakly correlated normal random variables and show that under certain conditions, the almost-sure convergence can be established if the likelihood function for the independent variables is used as the likelihood function for the weakly correlated variables. Simulation studies with different correlation structures and mean patterns will also be presented to complement the proofs.

Authors who are presenting talks have a * after their name.

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