Abstract #301920

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JSM 2003 Abstract #301920
Activity Number: 331
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics
Abstract - #301920
Title: A Local Maximum Entropy Density Estimator
Author(s): Masahiko Sagae*+ and Atsuyuki Kogure
Companies: Gifu University and Keio University
Address: 1-1 Yanagido, Gifu-ken 501-11, , 501 1193, Japan
Keywords: maximum entropy principle ; method of local moments ; histogram
Abstract:

A ocal log-polynomial density function is proposed based on the maximum entropy principle and is estimated by the method of local moments. We call this density function the "Maximum Entropy Density (MED)." The MED is a "Bona Fide" density function, that is, non-negative everywhere with integral equal to one. We show that the MED can achieve the higher order convergence rates parallel to the results for the polynomial histogram by Sagae and Scott (1997). Our method can be seen as a way for estimating the continuous density function from aggregated dataset and may provide a wide range of applications in fields such as economics where it is often the case that the first data available are prebinned or rounded prior to the data analysis.

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