Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/18152
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dc.contributor.authorJiang, R-
dc.contributor.authorYu, K-
dc.contributor.authorZhang, T-
dc.date.accessioned2019-05-21T12:11:19Z-
dc.date.available2018-01-01-
dc.date.available2019-05-21T12:11:19Z-
dc.date.issued2018-07-28-
dc.identifier.citationJournal of Inequalities and Applications, 2018, 2018en_US
dc.identifier.issn1025-5834-
dc.identifier.issnhttp://dx.doi.org/10.1186/s13660-018-1788-6-
dc.identifier.issn1029-242X-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/18152-
dc.description.abstractIn 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 O(n^−1/4 logn) 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.en_US
dc.description.sponsorshipNNSF (China); Natural Science Foundation of Anhui Province Ministry of Education; Fundamental Research Funds for the Central Universitiesen_US
dc.language.isoenen_US
dc.publisherSpringerOpenen_US
dc.subjectSample quantileen_US
dc.subjectAsymptotic normalityen_US
dc.subjectLinearly negative quadrant dependent sequenceen_US
dc.titleUniformly asymptotic normality of sample quantiles estimator for linearly negative quadrant dependent samplesen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1186/s13660-018-1788-6-
dc.relation.isPartOfJournal of Inequalities and Applications-
pubs.publication-statusPublished-
pubs.volume2018-
dc.identifier.eissn1029-242X-
Appears in Collections:Dept of Mathematics Research Papers

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