Minimum distance method for directional data and outlier detection

Mercedes Fernandez Sau and Daniela Rodriguez ()
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Mercedes Fernandez Sau: Universidad de Buenos Aires
Daniela Rodriguez: Universidad de Buenos Aires

Advances in Data Analysis and Classification, 2018, vol. 12, issue 3, No 7, 587-603

Abstract: Abstract In this paper, we propose estimators based on the minimum distance for the unknown parameters of a parametric density on the unit sphere. We show that these estimators are consistent and asymptotically normally distributed. Also, we apply our proposal to develop a method that allows us to detect potential atypical values. The behavior under small samples of the proposed estimators is studied using Monte Carlo simulations. Two applications of our procedure are illustrated with real data sets.

Keywords: Directional data; Robust estimation; Outlier detection; Asymptotic properties; Primary 62F35; Secondary 62G05 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11634-017-0287-9

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