BIROn - Birkbeck Institutional Research Online

    GWmodel: an R package for exploring spatial heterogeneity using geographically weighted models

    Gollini, Isabella and Lu, B. and Charlton, M. and Brunsdon, C. and Harris, P. (2015) GWmodel: an R package for exploring spatial heterogeneity using geographically weighted models. Journal of Statistical Software 63 (17), ISSN 1548-7660.

    [img]
    Preview
    Text
    v63i17.pdf - Published Version of Record
    Available under License Creative Commons Attribution.

    Download (3MB) | Preview

    Abstract

    Spatial statistics is a growing discipline providing important analytical techniques in a wide range of disciplines in the natural and social sciences. In the R package GWmodel we present techniques from a particular branch of spatial statistics, termed geographically weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localized calibration provides a better description. The approach uses a moving window weighting technique, where localized models are found at target locations. Outputs are mapped to provide a useful exploratory tool into the nature of the data spatial heterogeneity. Currently, GWmodel includes functions for: GW summary statistics, GW principal components analysis, GW regression, and GW discriminant analysis; some of which are provided in basic and robust forms.

    Metadata

    Item Type: Article
    Keyword(s) / Subject(s): geographically weighted regression, geographically weighted principal components analysis, spatial prediction, robust, R package
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Economics, Mathematics and Statistics
    Depositing User: Isabella Gollini
    Date Deposited: 27 Oct 2015 11:30
    Last Modified: 27 Oct 2015 11:30
    URI: http://eprints.bbk.ac.uk/id/eprint/13189

    Statistics

    Downloads
    Activity Overview
    145Downloads
    135Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item