Abstract Details
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Activity Number:
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305
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Type:
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Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #308969 |
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Title:
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Parameterization and Smoothing Using Bernstein Polynomials: Another Look at Beta Mixture
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Author(s):
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Zhong Guan*+
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Companies:
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Indiana University South Bend
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Keywords:
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Iterated Bernstein polynomials ;
Beta Mixture ;
Density estimation ;
Parametrization ;
Smoothing ;
Nonparametric model
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Abstract:
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Method of parameterizing and smoothing the unknown underling distributions in non-parametric models using iterated Bernstein polynomials is proposed, verified and investigated. Methods of choosing optimal degree of the Bernstein polynomials is also presented. The method is applied to estimate the density function and the cumulative distribution function. Simulation study shows that one can benefit from both the smoothness and the accuracy by using the proposed method.
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Authors who are presenting talks have a * after their name.
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