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M.D.I. estimation via unconstrained convex programming

 

作者: P. L. Brockett,   A. Charnes,   W. W Cooper,  

 

期刊: Communications in Statistics - Simulation and Computation  （Taylor Available online 1980）
卷期: Volume 9, issue 3  

页码: 223-234

 

ISSN:0361-0918

 

年代: 1980

 

DOI:10.1080/03610918008812151

 

出版商: Marcel Dekker, Inc.

 

关键词: minimum discrimination information estimation;information theory;unconstrained dual geometric program;contingency tables

 

数据来源: Taylor

 

摘要:

A method is presented for obtaining minimum discrimination information (M.D.I.) estimates of probability distributions. This involves using an extremal principle of Charnes and Cooper (1974) and, viewing M.D.I, estimation in a dual convex programming framework. The resulting dual convex program is unconstrained and involves only exponential and linear terms, and hence is easily

 

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