Bahadur representation of \(M_m\) estimates
DOI10.1214/aos/1028144859zbMath0929.62019OpenAlexW1989810336MaRDI QIDQ1807083
Publication date: 9 November 1999
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aos/1028144859
asymptotic normalityBahadur representationgeneralized order statisticsOja medianHodges-Lehmann estimatemeasures of location\(M\) estimates\(U\) statisticsmeasures of dispersion
Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05) Order statistics; empirical distribution functions (62G30)
Related Items (8)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Concavity and estimation
- On a notion of data depth based on random simplices
- Cube root asymptotics
- Descriptive statistics for multivariate distributions
- Generalized order statistics, Bahadur representations, and sequential nonparametric fixed-width confidence intervals
- Multivariate location estimation using extension of \(R\)-estimates through \(U\)-statistics type approach
- Asymptotics for \(M\)-estimators defined by convex minimization
- The asymptotics of Rousseeuw's minimum volume ellipsoid estimator
- A location estimator based on a U-statistic
- Asymptotic relations of M-estimates and R-estimates in linear regression model
- A general Bahadur representation of \(M\)-estimators and its application to linear regression with nonstochastic designs
- Estimators related to \(U\)-processes with applications to multivariate medians: Asymptotic normality
- The Bahadur-Kiefer representation for \(U\)-quantiles
- On a Geometric Notion of Quantiles for Multivariate Data
- Asymptotic normality ofr-estimates in the linear model
- Law of the Iterated Logarithm and Invariance Principle for M-Estimators
- Robust Estimation of a Location Parameter
- A Note on Quantiles in Large Samples
- On Bahadur's Representation of Sample Quantiles
This page was built for publication: Bahadur representation of \(M_m\) estimates