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Kernel Density Estimation for Compositional Data

Author

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  • J. Aitchison
  • I. J. Lauder

Abstract

Although rich parametric families of distributions over the simplex now exist for describing patterns of variability of compositional data, there remain problems where such descriptions fail. For such cases this paper suggests two main kernel methods of density estimation and compares their performance on real and simulated data sets.

Suggested Citation

  • J. Aitchison & I. J. Lauder, 1985. "Kernel Density Estimation for Compositional Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 34(2), pages 129-137, June.
    • Handle: RePEc:bla:jorssc:v:34:y:1985:i:2:p:129-137
    DOI: 10.2307/2347365
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    Cited by:

    1. Tsagris, Michail, 2015. "Regression analysis with compositional data containing zero values," MPRA Paper 67868, University Library of Munich, Germany.
    2. Ouimet, Frédéric, 2021. "Asymptotic properties of Bernstein estimators on the simplex," Journal of Multivariate Analysis, Elsevier, vol. 185(C).
    3. Ouimet, Frédéric & Tolosana-Delgado, Raimon, 2022. "Asymptotic properties of Dirichlet kernel density estimators," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
    4. Frédéric Ouimet, 2021. "General Formulas for the Central and Non-Central Moments of the Multinomial Distribution," Stats, MDPI, vol. 4(1), pages 1-10, January.
    5. Bertin, Karine & Genest, Christian & Klutchnikoff, Nicolas & Ouimet, Frédéric, 2023. "Minimax properties of Dirichlet kernel density estimators," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    6. Ouimet, Frédéric, 2022. "A symmetric matrix-variate normal local approximation for the Wishart distribution and some applications," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    7. Pierre Lafaye de Micheaux & Frédéric Ouimet, 2021. "A Study of Seven Asymmetric Kernels for the Estimation of Cumulative Distribution Functions," Mathematics, MDPI, vol. 9(20), pages 1-35, October.

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