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A Simple Justification of the Iterative Fitting Procedure for Generalized Linear Models

 

作者: StephenL. Hillis,   CharlesS. Davis,  

 

期刊: The American Statistician  （Taylor Available online 1994）
卷期: Volume 48, issue 4  

页码: 288-289

 

ISSN:0003-1305

 

年代: 1994

 

DOI:10.1080/00031305.1994.10476082

 

出版商: Taylor & Francis Group

 

关键词: Fisher scoring;Iteratively reweighted least squares

 

数据来源: Taylor

 

摘要:

The extension of classical linear models to generalized linear models has had an important unifying impact on the exposition, teaching, and practice of statistical modeling. This article gives a new and simple justification of the commonly used iteratively reweighted least squares procedure for obtaining maximum likelihood parameter estimates.

 

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