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Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples
In the present article, by utilizing some inequalities for linearly negative quadrant dependent random variables, we discuss the uniformly asymptotic normality of sample quantiles for linearly negative quadrant dependent samples under mild conditions. The rate of uniform asymptotic normality is pres...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6096958/ https://www.ncbi.nlm.nih.gov/pubmed/30839555 http://dx.doi.org/10.1186/s13660-018-1788-6 |
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author | Hu, Xueping Jiang, Rong Yu, Keming Zhang, Tong |
author_facet | Hu, Xueping Jiang, Rong Yu, Keming Zhang, Tong |
author_sort | Hu, Xueping |
collection | PubMed |
description | In the present article, by utilizing some inequalities for linearly negative quadrant dependent random variables, we discuss the uniformly asymptotic normality of sample quantiles for linearly negative quadrant dependent samples under mild conditions. The rate of uniform asymptotic normality is presented and the rate of convergence is near [Formula: see text] when the third moment is finite, which extends and improves the corresponding results of Yang et al. (J. Inequal. Appl. 2011:83, 2011) and Liu et al. (J. Inequal. Appl. 2014:79, 2014) under negatively associated random samples in some sense. |
format | Online Article Text |
id | pubmed-6096958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-60969582018-08-24 Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples Hu, Xueping Jiang, Rong Yu, Keming Zhang, Tong J Inequal Appl Research In the present article, by utilizing some inequalities for linearly negative quadrant dependent random variables, we discuss the uniformly asymptotic normality of sample quantiles for linearly negative quadrant dependent samples under mild conditions. The rate of uniform asymptotic normality is presented and the rate of convergence is near [Formula: see text] when the third moment is finite, which extends and improves the corresponding results of Yang et al. (J. Inequal. Appl. 2011:83, 2011) and Liu et al. (J. Inequal. Appl. 2014:79, 2014) under negatively associated random samples in some sense. Springer International Publishing 2018-07-28 2018 /pmc/articles/PMC6096958/ /pubmed/30839555 http://dx.doi.org/10.1186/s13660-018-1788-6 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Hu, Xueping Jiang, Rong Yu, Keming Zhang, Tong Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples |
title | Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples |
title_full | Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples |
title_fullStr | Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples |
title_full_unstemmed | Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples |
title_short | Uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples |
title_sort | uniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samples |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6096958/ https://www.ncbi.nlm.nih.gov/pubmed/30839555 http://dx.doi.org/10.1186/s13660-018-1788-6 |
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