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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...

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Detalles Bibliográficos
Autores principales: Hu, Xueping, Jiang, Rong, Yu, Keming, Zhang, Tong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
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
Descripción
Sumario: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.