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Activity Number: 297 - Advances in Nonparametric Testing
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract #323354
Title: On the Likelihood Ratio Test for Gaussian Mixtures Based on the Nonparametric Maximum Likelihood Estimator
Author(s): Wenhua Jiang* and Cun-Hui Zhang
Companies: Fudan University and Rutgers University
Keywords: nonparametric maximum likelihood estimator ; likelihood ratio test ; Gaussian mixture ; nonparametric empirical Bayes

We study a likelihood ratio test for Gaussian mixtures. The test is based on the nonparametric maximum likelihood estimator in the context of demixing (Kiefer and Wolfowitz, 1956). We prove that when the mixing distribution is supported in [-M_n,M_n] with M_n^2\le\log n/\log9, the test is of equal or smaller order than M_n^2.

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

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