Functional approach to the asymptotic normality of the nonlinear least squares estimator

DOI10.1016/S0167-7152(99)00034-6zbMath0939.62061OpenAlexW2061718616MaRDI QIDQ1962140

M. B. Malyutov, Rostislav S. Protassov

Publication date: 30 March 2000

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-7152(99)00034-6

zbMATH Keywords

asymptotic normalitysum of squared residuals

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Design of statistical experiments (62K99) General nonlinear regression (62J02)

Related Items (2)

Some probability inequalities of least-squares estimator in non linear regression model with strong mixing errors ⋮ Large deviation for a least squares estimator in a nonlinear regression model

Cites Work

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• Asymptotic theory of nonlinear least squares estimation
• An Asymptotic Expansion for the Distribution of the Least Squares Estimator of the Non-Linear Regression Parameter
• Regression problems with controllable variables subject to error
• Asymptotic Properties of Non-Linear Least Squares Estimators
• The Consistency of Nonlinear Regressions
• LAN, LAM and convergence of iterative ML estimates; optimal design in Gaussian one-way mixed model

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