# Cross-validation score for a specified bandwidth for basic GWR

### Description

This function finds the cross-validation score for a specified bandwidth for basic GWR

### Usage

1 2 |

### Arguments

`bw` |
bandwidth used in the weighting function;fixed (distance) or adaptive bandwidth(number of nearest neighbours) |

`X` |
a numeric matrix of the independent data with an extra column of “ones” for the 1st column |

`Y` |
a column vector of the dependent data |

`kernel` |
function chosen as follows: gaussian: wgt = exp(-.5*(vdist/bw)^2); exponential: wgt = exp(-vdist/bw); bisquare: wgt = (1-(vdist/bw)^2)^2 if vdist < bw, wgt=0 otherwise; tricube: wgt = (1-(vdist/bw)^3)^3 if vdist < bw, wgt=0 otherwise; boxcar: wgt=1 if dist < bw, wgt=0 otherwise |

`adaptive` |
if TRUE calculate an adaptive kernel where the bandwidth (bw) corresponds to the number of nearest neighbours (i.e. adaptive distance); default is FALSE, where a fixed kernel is found (bandwidth is a fixed distance) |

`dp.locat` |
a two-column numeric array of observation coordinates |

`p` |
the power of the Minkowski distance, default is 2, i.e. the Euclidean distance |

`theta` |
an angle in radians to rotate the coordinate system, default is 0 |

`longlat` |
if TRUE, great circle distances will be calculated |

`dMat` |
a pre-specified distance matrix, it can be calculated by the function |

`verbose` |
if TRUE (default), reports the progress of search for bandwidth |

### Value

`CV.score` |
cross-validation score |

### Author(s)

Binbin Lu binbinlu@whu.edu.cn

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