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    Nonparametric estimation of the dependence of a spatial point process on spatial covariates

    Access Status
    Fulltext not available
    Authors
    Baddeley, Adrian
    Chang, Y.
    Song, Y.
    Turner, R.
    Date
    2012
    Type
    Journal Article
    
    Metadata
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    Citation
    Baddeley, A. and Chang, Y. and Song, Y. and Turner, R. 2012. Nonparametric estimation of the dependence of a spatial point process on spatial covariates. Statistics and its Interface. 5 (2): pp. 221-236.
    Source Title
    Statistics and its Interface
    DOI
    10.4310/SII.2012.v5.n2.a7
    ISSN
    1938-7989
    School
    Department of Mathematics and Statistics
    URI
    http://hdl.handle.net/20.500.11937/44007
    Collection
    • Curtin Research Publications
    Abstract

    In the statistical analysis of spatial point patterns, it is often important to investigate whether the point pattern depends on spatial covariates. This paper describes nonparametric (kernel and local likelihood) methods for estimating the effect of spatial covariates on the point process intensity. Variance estimates and confidence intervals are provided in the case of a Poisson point process. Techniques are demonstrated with simulated examples and with applications to exploration geology and forest ecology.

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