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Differentiated logdensity approximants

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dc.contributor.authorProvost, Serge B.-
dc.contributor.authorHa, Hyung-Tae-
dc.date.available2020-02-28T08:42:03Z-
dc.date.created2020-02-06-
dc.date.issued2015-09-
dc.identifier.issn1572-3127-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/10163-
dc.description.abstractA moment-based density approximation technique whereby the derivative of the logarithm of a density approximant is expressed as a rational function is introduced in this paper. Guidelines for the selection of the polynomial orders of the numerator and denominator are proposed. The coefficients are then determined by solving a system of linear equations. The resulting density approximation, referred to as a differentiated logdensity approximant or DLA, satisfies a differential equation whose explicit solution is provided. It is shown that a unique solution exists when a polynomial is utilized in lieu of a rational function. The proposed methodology is successfully applied to two test statistics and several distributions. It is also explained that the same moment-matching technique can yield density estimates on the basis of sample moments. An example involving a widely analyzed data set illustrates this approach. (C) 2015 Elsevier B.V. All rights reserved.-
dc.language영어-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE BV-
dc.relation.isPartOfSTATISTICAL METHODOLOGY-
dc.subjectCOVARIANCE MATRICES-
dc.subjectSPHERICITY TEST-
dc.subjectDISTRIBUTIONS-
dc.subjectEDGEWORTH-
dc.titleDifferentiated logdensity approximants-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000357353000004-
dc.identifier.doi10.1016/j.stamet.2015.02.005-
dc.identifier.bibliographicCitationSTATISTICAL METHODOLOGY, v.26, pp.61 - 71-
dc.identifier.scopusid2-s2.0-84926157261-
dc.citation.endPage71-
dc.citation.startPage61-
dc.citation.titleSTATISTICAL METHODOLOGY-
dc.citation.volume26-
dc.contributor.affiliatedAuthorHa, Hyung-Tae-
dc.type.docTypeArticle-
dc.subject.keywordAuthorDensity approximation-
dc.subject.keywordAuthorMoments-
dc.subject.keywordAuthorRational functions-
dc.subject.keywordAuthorLogdensity-
dc.subject.keywordPlusCOVARIANCE MATRICES-
dc.subject.keywordPlusSPHERICITY TEST-
dc.subject.keywordPlusDISTRIBUTIONS-
dc.subject.keywordPlusEDGEWORTH-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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