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    SOME NEW DEVELOPMENTS ON TWO SEPARATE TOPICS: STATISTICAL CROSS VALIDATION AND FLOODPLAIN MAPPING

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    Issue Date
    2008-08-06
    Author
    Kastens, Jude Heathcliff
    Publisher
    University of Kansas
    Format
    191 pages
    Type
    Dissertation
    Degree Level
    PH.D.
    Discipline
    Mathematics
    Rights
    This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
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    Abstract
    This dissertation describes two unrelated threads of research. The first is a study of cross validation (CV), which is a data resampling method. CV is used for model ranking in model selection and for estimating expected prediction error of a model. A review of three resampling methods is provided in Chapter 1. Chapter 2 contains results from simulations that examine various properties of CV, in particular the use of CV for model selection in small sample settings as well as the expected value of the delete-d cross validation statistic. The second research thread is described in Chapter 3, where a new, physically-based computational model (called FLDPLN, or "Floodplain") for mapping potential inundation extents (floodplains) using gridded topographic data is introduced. Due to the parametric economy of FLDPLN, this model has significant advantages over existing methods such as hydrodynamic models. The model is validated using imagery from an actual flood event.
    URI
    http://hdl.handle.net/1808/5354
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    • Dissertations [4454]
    • Mathematics Dissertations and Theses [179]

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    785-864-8983
    KU Libraries
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    785-864-8983

    KU Libraries
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    Lawrence, KS 66045
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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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