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2022•Brazilian Journal of Probability and StatisticsRequires access

Consistency of nearest neighbor estimator of density function for m-END samples

Wei Wang, Yi Wu

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Abstract

In this paper, we mainly study the consistency of the nearest neighbor estimator of the density function based on m-extended negatively dependent samples. The weak consistency, strong consistency, uniformly strong consistency and the convergence rate are established under some mild conditions. The results obtained in this paper extend and improve some existing ones in the literature.

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What this paper is about

In this paper, we mainly study the consistency of the nearest neighbor estimator of the density function based on m-extended negatively dependent samples. The weak consistency, strong consistency, uniformly strong consistency and the convergence rate are established under some mild conditions. The results obtained in this paper extend and improve some existing ones in the literature.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper, we mainly study the consistency of the nearest neighbor estimator of the density function based on m-extended negatively dependent samples. The weak consistency, strong consistency, uniformly strong consistency and the convergence rate are established under some mild conditions. The results obtained in this paper extend and improve some existing ones in the literature.

Key concepts: Consistency (knowledge bases), Mathematics, Estimator, Strong consistency, Weak consistency, k-nearest neighbors algorithm, Statistics, Function (biology)

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