Orthogonal projections and the geometry of estimating functions.

DOI10.1016/S0378-3758(97)00118-3zbMath1067.62517WikidataQ127217884 ScholiaQ127217884MaRDI QIDQ1299394

Schultz Chan, Malay Ghosh

Publication date: 1998

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Mathematics Subject Classification ID

Point estimation (62F10) Generalized linear models (logistic models) (62J12)

Cites Work

• Longitudinal data analysis using generalized linear models
• Unbiased statistical estimation functions for parameters in presence of nuisance parameters
• Estimation in the presence of infinitely many nuisance parameters - Geometry of estimating functions
• An \(E\)-ancillarity projection property of Cox's partial score function
• Linear Bayes and optimal estimation
• An extension of quasi-likelihood estimation
• Generalizations of ancillarity, completeness and sufficiency in an inference function space
• The foundations of finite sample estimation in stochastic processes
• Projected score methods for approximating conditional scores
• Estimating equations in the presence of prior knowledge
• A projected likelihood function for semiparametric models
• Projection as a method for increasing sensitivity and eliminating nuisance parameters
• Projected partial likelihood and its application to longitudinal data
• An Optimum Property of Regular Maximum Likelihood Estimation
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