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

Yoshihide Kakizawa

Computational Statistics & Data Analysis, 2021, vol. 161, issue C

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.

Keywords: Birnbaum–Saunder distribution; Azzalini's type skew distribution; Epsilon-skew-symmetric distribution; Nonparametric density estimation; Boundary bias problem (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:161:y:2021:i:c:s0167947321000839

DOI: 10.1016/j.csda.2021.107249

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