Detailed Information

Cited 3 time in webofscience Cited 3 time in scopus
Metadata Downloads

Distribution approximation and modelling via orthogonal polynomial sequences

Full metadata record
DC Field Value Language
dc.contributor.authorProvost, Serge B.-
dc.contributor.authorHa, Hyung-Tae-
dc.date.available2020-02-28T06:43:49Z-
dc.date.created2020-02-06-
dc.date.issued2016-
dc.identifier.issn0233-1888-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/9726-
dc.description.abstractA general methodology is developed for approximating the distribution of a random variable on the basis of its exact moments. More specifically, a probability density function is approximated by the product of a suitable weight function and a linear combination of its associated orthogonal polynomials. A technique for generating a sequence of orthogonal polynomials from a given weight function is provided and the coefficients of the linear combination are explicitly expressed in terms of the moments of the target distribution. On applying this approach to several test statistics, we observed that the resulting percentiles are consistently in excellent agreement with the tabulated values. As well, it is explained that the same moment-matching technique can be utilized to produce density estimates on the basis of the sample moments obtained from a given set of observations. An example involving a well-known data set illustrates the density estimation methodology advocated herein.-
dc.language영어-
dc.language.isoen-
dc.publisherTAYLOR & FRANCIS LTD-
dc.relation.isPartOfSTATISTICS-
dc.titleDistribution approximation and modelling via orthogonal polynomial sequences-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000377453900013-
dc.identifier.doi10.1080/02331888.2015.1053809-
dc.identifier.bibliographicCitationSTATISTICS, v.50, no.2, pp.454 - 470-
dc.identifier.scopusid2-s2.0-84955686407-
dc.citation.endPage470-
dc.citation.startPage454-
dc.citation.titleSTATISTICS-
dc.citation.volume50-
dc.citation.number2-
dc.contributor.affiliatedAuthorHa, Hyung-Tae-
dc.type.docTypeArticle-
dc.subject.keywordAuthorapproximate distributions-
dc.subject.keywordAuthormoment-matching techniques-
dc.subject.keywordAuthororthogonal polynomials-
dc.subject.keywordAuthorpercentiles-
dc.subject.keywordAuthortest statistics-
dc.subject.keywordAuthordata modelling-
dc.subject.keywordAuthordensity estimation-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
Files in This Item
There are no files associated with this item.
Appears in
Collections
사회과학대학 > 응용통계학과 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Ha, Hyung Tae photo

Ha, Hyung Tae
Social Sciences (Department of Applied Statistics)
Read more

Altmetrics

Total Views & Downloads

BROWSE