JSM 2004 - Toronto

Abstract #302123

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Activity Number: 404
Type: Contributed
Date/Time: Thursday, August 12, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #302123
Title: Maximum Likelihood Estimation from Local Moments
Author(s): Masahiko Sagae*+ and Atsuyuki Kogure
Companies: Gifu University and Keio University
Address: 1-1 Yanagido, Gifu-shi, Gifu-ken, International, 501-1193, Japan
Keywords: local moment ; likelihood ; Sheppard's correction ; maximum entropy density ; polynomial histogram
Abstract:

Observations should cause somewhat loss of information under data aggregation such as grouping. For example, the maximum likelihood (m.l.) estimate under grouping has bias depending on binwidth, which corresponds to Sheppard's correction for a specific case. We consider the m.l. estimates of parameters of continuous distribution from local moments. The local moments extended grouping was introduced in our previous works. The theoretical property of m.l. estimate under local moments is investigated. It is shown that the m.l. estimate from local moments does not cause loss of information in a specific case. As this result, we constitute specific local moments so that the m.l. estimates have no loss of information or so that local moments diminish loss of information with respect to m.l. estimation, compared with grouping.

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