Toward the notion of intrinsically linear models in nonlinear regression

DOI10.3103/S1055134419030064zbMath1442.62019OpenAlexW2970216110MaRDI QIDQ2190771

Yuliana Yu. Linke, I. S. Borisov

Publication date: 22 June 2020

Published in: Siberian Advances in Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3103/s1055134419030064

zbMATH Keywords

nonlinear regressionexplicit estimatorintrinsically linear model

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Point estimation (62F10) Foundations and philosophical topics in statistics (62A01) General nonlinear regression (62J02)

Cites Work

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• Constructing initial estimators in one-step estimation procedures of nonlinear regression
• Quasi-likelihood and its application. A general approach to optimal parameter estimation
• Asymptotic normality of one-step \(M\)-estimators based on non-identically distributed observations
• Applied Regression Analysis
• Numerical Methods for Nonlinear Estimating Equations
• Asymptotic Properties of One-Step Weighted $M$-Estimators with Applications to Regression
• Multiple roots of estimating functions
• Constructing Explicit Estimators in Nonlinear Regression Problems
• Asymptotic properties of one-step M-estimators
• On Existence of Explicit Asymptotically Normal Estimators in Nonlinear Regression Problems