Asymptotic theory for description of regions in which Newton-Raphson iterations converge to location M-estimators

DOI10.1016/0378-3758(86)90086-8zbMath0657.62049OpenAlexW2074339725MaRDI QIDQ1110951

S. H. Smith

Publication date: 1986

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

Full work available at URL: https://doi.org/10.1016/0378-3758(86)90086-8

zbMATH Keywords

Newton-Raphson iterationscontaminated normal distributionCauchy location familylocation M-estimatorsmaximum likelihood equation

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05)

Related Items (2)

On the convergence of Newton's method when estimating higher dimensional parameters ⋮ On consistency of redescending M-kernel smoothers

Cites Work

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• Uniqueness and Fréchet differentiability of functional solutions to maximum likelihood type equations
• Robust estimation of a location parameter in the presence of asymmetry
• On Estimating Variances of Robust Estimators when the Errors are Asymmetric
• Statistical inference for Markov processes when the model is incorrect
• A Robust Method for Multiple Linear Regression
• The Influence Curve and Its Role in Robust Estimation
• The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data
• Robust Estimation of a Location Parameter
• Evaluation of the maximum-likelihood estimator where the likelihood equation has multiple roots
• Robust Estimates of Location: Survey and Advances
• Convergence de la répartition empirique vers la répartition théorique
• Robust Statistics

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