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Residuals in Generalized Linear Models

 

作者: DonaldA. Pierce,   DanielW. Schafer,  

 

期刊: Journal of the American Statistical Association  （Taylor Available online 1986）
卷期: Volume 81, issue 396  

页码: 977-986

 

ISSN:0162-1459

 

年代: 1986

 

DOI:10.1080/01621459.1986.10478361

 

出版商: Taylor & Francis Group

 

关键词: Asymptotic theory;Binomial regression;Deviance;Goodness-of-fit tests;Poisson regression;Saddlepoint approximations

 

数据来源: Taylor

 

摘要:

Generalized linear models are regression-type models for data not normally distributed, appropriately fitted by maximum likelihood rather than least squares. Typical examples are models for binomial or Poisson data, with a linear regression model for a given, ordinarily nonlinear, function of the expected values of the observations. Use of such models has become very common in recent years, and there is a clear need to study the issue of appropriate residuals to be used for diagnostic purposes.

 

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