A unified method to calculate the moments of the least squares estimators in nonlinear regression

DOI10.1007/BF02006010zbMath0697.62052OpenAlexW2048741587MaRDI QIDQ911188

Bo-Cheng Wei

Publication date: 1989

Published in: Acta Mathematicae Applicatae Sinica. English Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02006010

zbMATH Keywords

momentsregularity conditionscurvature measuresresidualsunified methodleast squares estimatorsstochastic expansionsfitting errorsindependent standard normal random variables

Mathematics Subject Classification ID

Linear inference, regression (62J99) General nonlinear regression (62J02)

Related Items (1)

Assessing local prior influence in Bayesian analysis

Cites Work

• Parameter transformations for improved approximate confidence regions in nonlinear least squares
• Bias in nonlinear regression
• Testing a Subset of the Parameters of a Nonlinear Regression Model
• Optimal significance procedures for simple hypotheses
• Asymptotic Properties of Non-Linear Least Squares Estimators
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