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   *                       Package   GWmodel                             *
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   Call:
   gwda(formula = gwdaformula, data = spdata, predict.data = sppred, 
    kernel = kernel, adaptive = adaptive, bw = bw, dMat = dMat)

   Grouping factor:  y  with the following groups: 

    high low
    Discriminators:  x1 x2 x3 x4
    Prediction: Ordinary prediction is made with given prediction data
    Meams: Localised mean is used for GW discriminant analysis
    Variance-covariance: Localised variance-covariance matrix is used for GW discriminant analysis
    Localised prior probability is used for GW discriminant analysis
    Adaptive bandwidth: 50 (number of nearest neighbours)
    Distance metric: Euclidean distance metric is used.
    The correct ratio is validated as  0.981
    The number of points for prediction is  1000
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