Minimum distance method for directional data and outlier detection

DOI10.1007/s11634-017-0287-9zbMath1416.62175OpenAlexW2621080226MaRDI QIDQ1630878

Mercedes Fernandez Sau, Daniela Rodriguez

Publication date: 5 December 2018

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/11336/55569

zbMATH Keywords

asymptotic propertiesrobust estimationdirectional dataoutlier detection

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items

Robust estimation for multivariate wrapped models ⋮ Recent advances in directional statistics

Uses Software

• wle
• CircStats
• circular
• movMF

Cites Work

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• Kernel estimators of density function of directional data
• Kernel density estimation with spherical data
• Exact risk improvement of bandwidth selectors for kernel density estimation with directional data
• Minimum distance density-based estimation
• Robust estimation for circular data
• Automatic bandwidth selection for circular density estimation
• Robustness of estimators for directional data
• Exponential models for directional data
• Robust estimation of the concentration parameter of the von Mises-Fisher distribution
• Central limit theorem for integrated square error of kernel estimators of spherical density
• Minimum disparity estimation for continuous models: Efficiency, distributions and robustness
• Robust \(M\)-estimators on spheres
• On semiparametric \(M\)-estimation in single-index regression
• Topics in Circular Statistics
• The Identification of Multiple Outliers
• Outliers in Circular Data
• Powering Up With Space-Time Wind Forecasting
• A General Qualitative Definition of Robustness

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