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    Maximal uniform convergence rates in parametric estimation problems

    Beckert, Walter and McFadden, D. (2004) Maximal uniform convergence rates in parametric estimation problems. Working Paper. Birkbeck, University of London, London, UK.

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    Abstract

    This paper considers parametric estimation problems with i.i.d. data. It focuses on rate-efficiency, in the sense of maximal possible convergence rates of stochastically bounded estimators, as an optimality criterion, largely unexplored in parametric estimation. Under mild conditions, the Hellinger metric, defined on the space of parametric probability measures, is shown to be an essentially universally applicable tool to determine maximal possible convergence rates.

    Metadata

    Item Type: Monograph (Working Paper)
    Additional Information: BWPEF 0405
    Keyword(s) / Subject(s): parametric estimators, uniform convergence, Hellinger distance, Locally Asymptotically Quadratic (LAQ) Families
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Economics, Mathematics and Statistics
    Depositing User: Administrator
    Date Deposited: 09 Apr 2019 12:00
    Last Modified: 27 Jul 2019 23:23
    URI: http://eprints.bbk.ac.uk/id/eprint/27107

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