One-step jackknife for \(M\)-estimators computed using Newton's method

DOI10.1007/BF00053398zbMath0772.62016OpenAlexW2021666659MaRDI QIDQ1260724

Jun Shao

Publication date: 25 August 1993

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00053398

zbMATH Keywords

consistencyasymptotic variancesimulation studyasymptotic equivalenceNewton's iterative methodfinite sample propertiesregression estimatorsdispersion estimatordispersion of \(M\)-estimatorsone-step jackknife estimators

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Probabilistic methods, stochastic differential equations (65C99)

Cites Work

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• Heteroscedasticity-robustness of jackknife variance estimators in linear models
• Jackknifing maximum likelihood estimates
• An unbalanced jackknife
• Approximation Theorems of Mathematical Statistics
• Jackknifing fixed points of iterations
• Jackknifing in Nonlinear Regression
• The Asymptotic Behaviour of Tukey's General Method of Setting Approximate Confidence Limits (The Jackknife) When Applied to Maximum Likelihood Estimates
• Robust Statistics

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