A Comprehensive Exploration of Complete Cross-Validation for Circular Data

• Autorzy: Kamila Hasilová , Ivana Horová , David Vališ , Stanislav Zámečník
• Języki publikacji: EN

Abstrakty

EN

Kernel density estimation of circular data has recently received considerable attention for its ability to model and analyse distributions on unit circles and other periodic domains. Our aim is to contribute to the literature on data-driven bandwidth selectors in circular kernel density estimation. We propose a novel circular-specific method that is based on a crossvalidation procedure with a von Mises density used as a kernel function. Using simulated data as well as real-world circular datasets, we evaluate and validate the proposed method and compare it with the existing methods. (original abstract)

Słowa kluczowe

EN

Estimation; Data analysis; Statistics

PL

Estymacja; Analiza danych; Statystyka

• Czasopismo: Statistics in Transition
• Rocznik: 2024
• Tom: 25
• Numer: nr 3
• Strony: 1--12

Twórcy

autor

Kamila Hasilová

• University of Defence, Brno, Czech Republic

autor

Ivana Horová

• Masaryk University, Brno, Czech Republic

autor

David Vališ

• University of Defence, Brno, Czech Republic

autor

Stanislav Zámečník

• Masaryk University, Brno, Czech Republic

Bibliografia

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Identyfikatory

DOI

10.59170/stattrans-2024-024