Robust cluster-based multivariate outlier diagnostics and parameter estimation in regression analysis

DOI10.1080/03610918.2014.960093zbMath1359.62230OpenAlexW2077740951MaRDI QIDQ2965569

Ekele Alih, Hong Choon Ong

Publication date: 3 March 2017

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2014.960093

zbMATH Keywords

similarity metricsbounded influence regressionaddition-point Least squares regressionDFFITS-statisticminimum Mahalanobis distancePivot point

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05)

Related Items (2)

An automated robust algorithm for clustering multivariate data ⋮ Back propagation neural networks and multiple regressions in the case of heteroskedasticity

Uses Software

• robustbase

Cites Work

• Unnamed Item
• High breakdown-point and high efficiency robust estimates for regression
• Small sample corrections for LTS and MCD
• New tools for residual analysis
• Robust diagnostic regression analysis
• BACON: blocked adaptive computationally efficient outlier nominators.
• A class of robust and fully efficient regression estimators
• A Re-Weighted Least Squares Method for Robust Regression Estimation
• Robust regression:a weighted least squares approach
• Inconsistency of Resampling Algorithms for High-Breakdown Regression Estimators and a New Algorithm
• Robust Statistics

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