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Activity Number: 181
Type: Contributed
Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract #316050 View Presentation
Title: Bernstein Polynomial Model for Grouped Data
Author(s): Zhong Guan*
Companies: Indiana University South Bend
Keywords: Bernstein Polynomial ; Density estimation ; Mixture model ; EM algorithm ; Grouped data ; Nonparametric model
Abstract:

Grouped data are commonly used in applications. It is proposed that the Bernstein polynomial model is used to estimate a univariate density function based on grouped data. The coefficients are interpreted as mixture proportions of beta distributions and can estimated using an EM algorithm. The optimal degree of the Bernstein polynomial can be determined using a change-point estimation method. The proposed method is compared with some existing methods in a simulation study and is applied to a real dataset.


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

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