Generation of optimal designs for nonlinear models when the design points are incidental parameters

Martijn P.F. Berger

    Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

    Abstract

    This paper considers the problem of finding D-optimal designs for nonlinear exponential models when the design points are not known, and have to be approximated or estimated. The procedure in this paper not only deals with this problem, but also handles the problem that for nonlinear models the information of the parameters is a function of the values of these parameters. The results will be discussed and illustrated for item response theory models that are frequently used in psychometric research.
    Original languageEnglish
    Title of host publicationComputational statistics
    EditorsYadolah Dodge, Joe Whittaker
    Place of PublicationHeidelberg
    PublisherPhysica-Verlag
    Pages202-208
    Number of pages7
    Volume2: Proceedings of the 10th Symposium on Computational Statistics, COMPSTAT, Neuchâtel, Switzerland, August 1992
    ISBN (Electronic)978-3-642-48678-4
    ISBN (Print)978-3-642-48680-7
    DOIs
    Publication statusPublished - 1992
    Event10th Symposium on Computational Statistics, COMPSTAT 1992 - Neuchâtel, Switzerland
    Duration: 24 Aug 199228 Aug 1992
    Conference number: 10

    Conference

    Conference10th Symposium on Computational Statistics, COMPSTAT 1992
    Abbreviated titleCOMPSTAT
    CountrySwitzerland
    CityNeuchâtel
    Period24/08/9228/08/92

    Keywords

    • Rang
    • Statistical computing
    • Neural networks
    • Statistics

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