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A class of Birnbaum–Saunders type kernel density estimators for nonnegative data

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  • Kakizawa, Yoshihide

Abstract

Nonparametric density estimation using a class of deformed skew Birnbaum–Saunder (BS) type kernels is suggested for nonnegative data. A remarkable feature of new skew BS type kernel density estimators lies in its general formulation via asymmetry parameter as well as density generator. Mean integrated squared errors of the proposed estimators are investigated, together with strong consistency and asymptotic normality. Simulation studies and applications to real data sets are presented.

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  • Kakizawa, Yoshihide, 2021. "A class of Birnbaum–Saunders type kernel density estimators for nonnegative data," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    • Handle: RePEc:eee:csdana:v:161:y:2021:i:c:s0167947321000839
    DOI: 10.1016/j.csda.2021.107249
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    Cited by:

    1. Ouimet, Frédéric & Tolosana-Delgado, Raimon, 2022. "Asymptotic properties of Dirichlet kernel density estimators," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
    2. Kakizawa, Yoshihide, 2022. "Multivariate elliptical-based Birnbaum–Saunders kernel density estimation for nonnegative data," Journal of Multivariate Analysis, Elsevier, vol. 187(C).

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