Generalized and robustified empirical depths for multivariate data

DOI10.1016/j.spl.2018.10.018zbMath1407.62176OpenAlexW2901436077MaRDI QIDQ1726846

Jafer Rahman, Shi Hua Luo, Xiao Hui Liu

Publication date: 20 February 2019

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2018.10.018

zbMATH Keywords

weighted meanzonoid depthgeneral empirical depthweighted zonoid depth

Mathematics Subject Classification ID

Nonparametric robustness (62G35) Nonparametric estimation (62G05) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (1)

K-sign depth: from asymptotics to efficient implementation

Uses Software

• CompPD

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Fast nonparametric classification based on data depth
• Weighted-mean trimming of multivariate data
• Empirical likelihood ratio confidence regions
• Computing projection depth and its associated estimators
• Computing zonoid trimmed regions of dimension \(d>2\)
• Multivariate risks and depth-trimmed regions
• Zonoid trimming for multivariate distributions
• Projection-based depth functions and associated medians
• General notions of statistical depth function.
• Influence function and maximum bias of projection depth based estimators.
• An empirical depth function for multivariate data
• Computing zonoid trimmed regions of bivariate data sets
• Empirical likelihood ratio confidence intervals for a single functional
• Robustness and Complex Data Structures

This page was built for publication: Generalized and robustified empirical depths for multivariate data