Bias of LS estimators in nonlinear regression models with constraints. I: General case.

DOI10.1023/A:1023092911235zbMath1059.62557OpenAlexW103943717MaRDI QIDQ1775170

Jean-Baptiste Denis, Andrej Pázman

Publication date: 4 May 2005

Published in: Applications of Mathematics (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/32523

zbMATH Keywords

asymptotic biasmaximum likelihoodnonlinear least squaresnonlinear constraints

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Parametric inference under constraints (62F30) General nonlinear regression (62J02)

Related Items

A third-order bias corrected estimate in generalized linear models ⋮ Birnbaum-Saunders nonlinear regression models ⋮ Bias of LS estimators in nonlinear regression models with constraints. II: Biadditive models. ⋮ Regularised PCA to denoise and visualise data ⋮ Improved maximum-likelihood estimation in a regression model with general parametrization

Cites Work

• Bias of LS estimators in nonlinear regression models with constraints. II: Biadditive models.
• The Lagrangian Multiplier Test
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