JSM 2005 - Toronto

Abstract #304627

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 70
Type: Contributed
Date/Time: Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Computing
Abstract - #304627
Title: Estimating Mixtures of Normals Using UNMIX
Author(s): Hasan Hamdan*+
Companies: James Madison University
Address: MSC 7803, Harrisonburg, VA, 22807, United States
Keywords: mixture ; UNMIX ; minimize ; smoothing
Abstract:

In this paper, a new method for estimating the parameters of mixtures of normals is introduced and evaluated. The new method is called UNMIX and is based on minimizing the weighted square distance between exact values of the density of the mixture and the estimated values using kernel smoothing techniques over a specified grid of x-values, a grid of potential scale values, and a grid of mean values. The method is compared with the EM algorithm through simulated examples. It also is used to fit the density of real data. The method can be extended to include other mixtures such as mixtures of exponentials and Poissons.

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