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Multinomial and empirical likelihood under convex constraints

  1. TitleMultinomial and empirical likelihood under convex constraints
    Subtitledirections of recession, Fenchel duality, the PP algorithm
    Author infoMarian Grendár, Vladimír Špitalský
    Author Grendár Marian 1969- (50%)
    Co-authors Špitalský Vladimír 1973- (50%) UMBFP10 - Katedra matematiky
    Source document Electronic Journal of Statistics. Vol. 11, no. 1 (2017), pp. 2547-2612. - [Shaker Heights] : Institute of Mathematical Statistics, 2017
    Keywords contingency tables   lineárne modely - linear models   estimating equations  
    LanguageEnglish
    CountryUnited States of America
    systematics 51
    AnnotationThe primal problem of multinomial likelihood maximization restricted to a convex closed subset of the probability simplex is studied. A solution of this problem may assign a positive mass to an outcome with zero count. Such a solution cannot be obtained by the widely used, simplified Lagrange and Fenchel duals. Related flaws in the simplified dual problems, which arise because the recession directions are ignored, are identified and the correct Lagrange and Fenchel duals are developed.
    Public work category ADC
    No. of Archival Copy40086
    Catal.org.BB301 - Univerzitná knižnica Univerzity Mateja Bela v Banskej Bystrici
    Databasexpca - PUBLIKAČNÁ ČINNOSŤ
    ReferencesPERIODIKÁ-Súborný záznam periodika
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