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    Statistical downscaling of rainfall data using sparse variable selection methods

    Access Status
    Fulltext not available
    Authors
    Phatak, Aloke
    Bates, B.
    Charles, S.
    Date
    2011
    Type
    Journal Article
    
    Metadata
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    Citation
    Phatak, A. and Bates, B. and Charles, S. 2011. Statistical downscaling of rainfall data using sparse variable selection methods. Environmental Modelling and Software. 26 (11): pp. 1363-1371.
    Source Title
    Environmental Modelling and Software
    DOI
    10.1016/j.envsoft.2011.05.007
    ISSN
    1364-8152
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/47407
    Collection
    • Curtin Research Publications
    Abstract

    In many statistical downscaling methods, atmospheric variables are chosen by using a combination of expert knowledge with empirical measures such as correlations and partial correlations. In this short communication, we describe the use of a fast, sparse variable selection method, known as RaVE, for selecting atmospheric predictors, and illustrate its use on rainfall occurrence at stations in South Australia. We show that RaVE generates parsimonious models that are both sensible and interpretable, and whose results compare favourably to those obtained by a non-homogeneous hidden Markov model (Hughes et al., 1999). © 2011.

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