Far East Journal of Theoretical Statistics

The Far East Journal of Theoretical Statistics publishes original research papers and survey articles in the field of theoretical statistics, covering topics such as Bayesian analysis, multivariate analysis, and stochastic processes.

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ON ASYMPTOTIC NORMALITY OF THE KERNEL ESTIMATOR FOR NEGATIVELY DEPENDENT RANDOM VARIABLES

Authors

  • Aminata GNING
  • Mouhamed Mar
  • Saliou DIOUF

Keywords:

density, negatively dependent, weighted sums, asymptotic normality, kernel estimator

DOI:

https://doi.org/10.17654/0972086324020

Abstract

In this paper, we establish the asymptotic normality of the kernel estimator for negatively dependent random variables. The kernel estimator has been widely applied for independent data. However, in practice, the data are most often dependent.

Received: August 23, 2024
Revised: October 3, 2024
Accepted: October 10, 2024

References

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J. L. Doob, Stochastic Processes, John Wiley & Sons, Inc., New York, Chapman & Hall, Limited, London, 1953.

Y. Kolani, A. Gning and S. Diouf, Complete convergence for weighted sums of sequences of negatively dependent random variables, Journal of Computer Science and Applied Mathematics 6 (2024), 1-11.

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Q. Wu, A strong limit theorem for weighted sums of sequences of negatively dependent random variables, J. Inequal. Appl. (2010), Art. ID 383805, 8 pp.

Y. Li, Y. Zhou and C. Li, On the convergence rates of kernel estimator and hazard estimator for widely dependent samples, J. Inequal. Appl. (2018), Paper No. 71, 10 pp.

J. Zhou, J. Yan and D. Cheng, Complete convergence for maximum of weighted sums of WOD random variables and its application, Comm. Statist. Theory Methods 52 (2023), 8184-8206.

Published

2024-10-17

Issue

Section

Articles

How to Cite

ON ASYMPTOTIC NORMALITY OF THE KERNEL ESTIMATOR FOR NEGATIVELY DEPENDENT RANDOM VARIABLES. (2024). Far East Journal of Theoretical Statistics , 68(3), 373-383. https://doi.org/10.17654/0972086324020

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