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Minimization technique for a convex function with application to multiple regression model

 

作者: Wansoo T. Rhee,   K. Anthony Rhee,  

 

期刊: Optimization  （Taylor Available online 1988）
卷期: Volume 19, issue 2  

页码: 253-267

 

ISSN:0233-1934

 

年代: 1988

 

DOI:10.1080/02331938808843342

 

出版商: Akademic-Verlag

 

关键词: Maximum Likelihood Estimator;Convex function;Simplex Method;Primary:65 K 10;Secondary:65 D 10

 

数据来源: Taylor

 

摘要:

This paper develops an algorithm for estimating the parameters in a general multiple regression model, The estimator coincides with the maximum likelihood estimator when the errors have a probability density function of the typef(t) =C1exp ( −φ(t)), where φ is a convex and symmetric function but not necessarily differentiable. Even in the special case corresponding tol1-estimation, this algorithm is as efficient as the algorithms developed to this date.

 

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