The metrically trimmed mean as a robust estimator of location

DOI10.1214/aos/1176348783zbMath0782.62039OpenAlexW1969463942MaRDI QIDQ1206723

Seong-Ju Kim

Publication date: 1 April 1993

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1176348783

zbMATH Keywords

asymptotic normalitymetricmediantrimmed meaninfluence curverobust estimator of locationmultivariate extensionaverage of observationsdistance from the medianmetrically trimmed meanneighborhoods of nonparametric modelsoutlying observationsvon Mises expansions

Mathematics Subject Classification ID

Nonparametric robustness (62G35) Nonparametric estimation (62G05)

Related Items (17)

Asymptotic properties of location estimators based on projection depth ⋮ Symmetric regression quantile and its application to robust estimation for the nonlinear regression model ⋮ Robust analogs of hotelling's two-sample t² ⋮ Asymptotic normality of multivariate trimmed means ⋮ Multidimensional trimming based on projection depth ⋮ Trimmed and winsorized standard deviations based on a scaled deviation ⋮ Symmetric quantile and symmetric trimmed mean for linear regression model ⋮ On the performance of bivariate robust location estimators under contamination ⋮ Trimmed and Winsorized means based on a scaled deviation ⋮ Bounding maximum likelihood estimates based on incomplete ordered data ⋮ High breakdown analogs of the trimmed mean ⋮ Symmetric quantiles and their applications ⋮ Trimmed least squares estimator as best trimmed linear conditional estimator for linear regression model ⋮ Rate of convergence of depth contours: with application to a multivariate metrically trimmed mean. ⋮ Another approach to asymptotics and bootstrap of randomly trimmed means ⋮ Robust confidence interval for the variance ⋮ Trimmed and Winsorized transformed means based on a scaled deviation

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