4.1 Article

Bias reductions for beta kernel estimation

Journal

JOURNAL OF NONPARAMETRIC STATISTICS
Volume 28, Issue 1, Pages 1-30

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/10485252.2015.1112011

Keywords

beta kernel estimator; boundary problem; nonparametric density estimator; 62G07; 62G20

Funding

  1. Japan Society for the Promotion of Science (JSPS) [15H06068]
  2. Grants-in-Aid for Scientific Research [15H06068] Funding Source: KAKEN

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The beta kernel estimator for a density with support [GRAPHICS] was discussed by Chen [(1999) 'Beta Kernel Estimators for Density Functions', Computational Statistics and Data Analysis, 31, 131-145]. In this paper, when the underlying density has a fourth-order derivative, we improve the beta kernel estimator using the bias correction techniques based on two beta kernel estimators with different smoothing parameters. As a result, we propose new bias corrected beta kernel estimators involving the digamma functions, and then establish their asymptotic properties. Simulation studies are conducted to illustrate the finite sample performance of the proposed estimators.

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