Adaptive Bayesian bandwidth based on LPE kernel for asymmetric kernel density

Makhloufi Sylia (), Zougab Nabil (), Ziane Yasmina () and Adjabi Smail ()
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Makhloufi Sylia: Department of Computer Science, Faculty of Exact Sciences; and Research Unit LaMOS, 210392 University of Bejaia , Bejaia, Algeria
Zougab Nabil: Department of Electrical Engineering, Faculty of Technology; and Research Unit LaMOS, 210392 University of Bejaia , Bejaia, Algeria
Ziane Yasmina: Department of Operational Research, Faculty of Exact Sciences; and Research Unit LaMOS, 210392 University of Bejaia , Bejaia, Algeria
Adjabi Smail: Department of Operational Research, Faculty of Exact Sciences; and Research Unit LaMOS, 210392 University of Bejaia , Bejaia, Algeria

Monte Carlo Methods and Applications, 2025, vol. 31, issue 1, 1-12

Abstract: In this work, we propose to estimate the probability density function for nonnegative support using an LPE kernel with the adaptive Bayesian approach for bandwidth selection. For this, we exploit the conjugality between the LPE kernel and a prior distribution to develop the explicit form of the variable bandwidth parameter. Simulation studies are realized to evaluate the performance of the proposed adaptive Bayesian LPE kernel approach, with the classical Plug-In and UCV methods. On the other hand, we have carried out a comparative study between the proposed approach and two other adaptive Bayesian approaches with BSPE and gamma kernels. Moreover, real data sets are presented to illustrate the findings.

Keywords: Adaptive Bayesian approach; bandwidth; BSPE kernel; gamma kernel; LPE kernel; prior distribution (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1515/mcma-2024-2021

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