On almost sure convergence rates for the kernel estimator of a covariance operator under negative association

It is suppose that $\{X_n,~n\geq 1\}$ is a strictly stationary sequence of negatively associated random variables with continuous distribution function F. The aim of this paper is to estimate the distribution of $(X_1,X_{k+1})$ for $k\in I\!\!N_0$ using kernel type estimators. We also estimate the c...

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Main Author: Hadi Jabbari
Format: Article
Language:English
Published: Shahid Bahonar University of Kerman 2024-08-01
Series:Journal of Mahani Mathematical Research
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Online Access:https://jmmrc.uk.ac.ir/article_4398_7c14a7723fcf637c41d7e2c9ce039b0a.pdf
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author Hadi Jabbari
author_facet Hadi Jabbari
author_sort Hadi Jabbari
collection DOAJ
description It is suppose that $\{X_n,~n\geq 1\}$ is a strictly stationary sequence of negatively associated random variables with continuous distribution function F. The aim of this paper is to estimate the distribution of $(X_1,X_{k+1})$ for $k\in I\!\!N_0$ using kernel type estimators. We also estimate the covariance function of the limit empirical process induced by the sequence $\{X_n,~n\geq 1\}$. Then, we obtain uniform strong convergence rates for the kernel estimator of the distribution function of $(X_1,X_{k+1})$. These rates, which do not require any condition on the covariance structure of the variables, were not already found. Furthermore, we show that the covariance function of the limit empirical process based on kernel type estimators has uniform strong convergence rates assuming a convenient decrease rate of covariances $Cov(X_1,X_{n+1}),~n\geq 1$. Finally, the convergence rates obtained here are empirically compared with corresponding results already achieved by some authors.
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publishDate 2024-08-01
publisher Shahid Bahonar University of Kerman
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spelling doaj-art-9a28ec0809bd4dfcb8109a4284e2f28a2025-01-04T19:29:35ZengShahid Bahonar University of KermanJournal of Mahani Mathematical Research2251-79522645-45052024-08-011339110410.22103/jmmr.2024.22733.15614398On almost sure convergence rates for the kernel estimator of a covariance operator under negative associationHadi Jabbari0Department of Statistics, Ordered Data, Reliability and Dependency Center of Excellence, Ferdowsi University of Mashhad, Mashhad, IranIt is suppose that $\{X_n,~n\geq 1\}$ is a strictly stationary sequence of negatively associated random variables with continuous distribution function F. The aim of this paper is to estimate the distribution of $(X_1,X_{k+1})$ for $k\in I\!\!N_0$ using kernel type estimators. We also estimate the covariance function of the limit empirical process induced by the sequence $\{X_n,~n\geq 1\}$. Then, we obtain uniform strong convergence rates for the kernel estimator of the distribution function of $(X_1,X_{k+1})$. These rates, which do not require any condition on the covariance structure of the variables, were not already found. Furthermore, we show that the covariance function of the limit empirical process based on kernel type estimators has uniform strong convergence rates assuming a convenient decrease rate of covariances $Cov(X_1,X_{n+1}),~n\geq 1$. Finally, the convergence rates obtained here are empirically compared with corresponding results already achieved by some authors.https://jmmrc.uk.ac.ir/article_4398_7c14a7723fcf637c41d7e2c9ce039b0a.pdfalmost sure convergence ratebivariate distribution functionempirical processkernel estimation
spellingShingle Hadi Jabbari
On almost sure convergence rates for the kernel estimator of a covariance operator under negative association
Journal of Mahani Mathematical Research
almost sure convergence rate
bivariate distribution function
empirical process
kernel estimation
title On almost sure convergence rates for the kernel estimator of a covariance operator under negative association
title_full On almost sure convergence rates for the kernel estimator of a covariance operator under negative association
title_fullStr On almost sure convergence rates for the kernel estimator of a covariance operator under negative association
title_full_unstemmed On almost sure convergence rates for the kernel estimator of a covariance operator under negative association
title_short On almost sure convergence rates for the kernel estimator of a covariance operator under negative association
title_sort on almost sure convergence rates for the kernel estimator of a covariance operator under negative association
topic almost sure convergence rate
bivariate distribution function
empirical process
kernel estimation
url https://jmmrc.uk.ac.ir/article_4398_7c14a7723fcf637c41d7e2c9ce039b0a.pdf
work_keys_str_mv AT hadijabbari onalmostsureconvergenceratesforthekernelestimatorofacovarianceoperatorundernegativeassociation