Calculation of simplicial depth estimators for polynomial regression with applications

DOI10.1016/J.CSDA.2006.10.015zbMath1162.62368OpenAlexW2087157772WikidataQ60432761 ScholiaQ60432761MaRDI QIDQ1020170

Christine H. Müller, Robin Wellmann, Stanislav Katina

Publication date: 29 May 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.10.015

zbMATH Keywords

polynomial regressionsimplicial depthshape analysistwo-sample testsdistribution free testsmaximum depth estimatorone-sample tests

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Estimation in multivariate analysis (62H12) General nonlinear regression (62J02)

Related Items (5)

Depth notions for orthogonal regression ⋮ Data depth for simple orthogonal regression with application to crack orientation ⋮ Consistency and robustness of tests and estimators based on depth ⋮ Tests for multiple regression based on simplicial depth ⋮ Distribution-free tests for polynomial regression based on simplicial depth

Cites Work

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• High breakdown-point and high efficiency robust estimates for regression
• Multivariate dispersion, central regions and depth. The lift zonoid approach
• On a notion of data depth based on random simplices
• The catline for deep regression
• The deepest regression method
• On depth and deep points: A calculus.
• Least Median of Squares Regression
• On a notion of simplicial depth
• Regression Depth

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