Fitting generalized linear models and their nonlinear extensions with least squares calculations

DOI10.1016/0167-9473(88)90059-XzbMath0633.65149OpenAlexW2081578556MaRDI QIDQ1096376

W. Douglas Stirling

Publication date: 1988

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-9473(88)90059-x

zbMATH Keywords

fittinggeneralized linear modelsiteratively reweighted least squaresGLIMdelta algorithmmaximum likelihood algorithmsNRL algorithms

Mathematics Subject Classification ID

Numerical smoothing, curve fitting (65D10) Linear regression; mixed models (62J05) Foundations and philosophical topics in statistics (62A01) General nonlinear regression (62J02) Probabilistic methods, stochastic differential equations (65C99)

Related Items

Maximum likelihood estimation in models with two systematic parts ⋮ Applied regression analysis bibliography update 1988-89

Uses Software

• AS 216

Cites Work

• Maximum likelihood estimation in models with two systematic parts
• Maximum likelihood estimation and large-sample inference for generalized linear and nonlinear regression models
• Iteratively Reweighted Least Squares for Models with a Linear Part
• The Delta Algorithm and GLIM
• Fitting nonlinear models: numerical techniques
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