Description Usage Arguments Details Value Author(s) References Examples

This function uses a non-parametric approach to test whether local spatial autocorrelation (characterised by ELSA) is significant. It generates a p-value at each spatial location (a raster cell or spatial point/polygon) that can be used to infer the significancy of local spatial autocorrelation.

1 |

`x` |
A Raster or Spatial* dataset |

`d` |
the local distance, or an object of class neighbours created by dneigh function |

`n` |
number of simulation, default is 999 for small datasets, and 99 for large datasets |

`null` |
Optional, a null distribution of data (a Raster if x is Raster or a numerical vector if x is either Raster or Spatial dataset ); if not provided, a null distribution is generated by the function |

`method` |
resampling method for nonparametric simulation, can be either 'boot' (bootstraping; default) or 'perm' (permutation) |

`nc` |
number of classes (only if x is a continuous variable); if not specified, it is estimated using nclass function |

`categorical` |
logical, specifies whether x is a categorical; if not specified, it is guessed by the function |

`dif` |
the level of dissimilarities between different categories (only if x is a categorical variable); see |

`classes` |
Optional, only when |

`...` |
Aditional arguments passed to writeRaster function (applied only when x is Raster) |

This function test how significant the local spatial autocorrelation is at each location, so it generates a p-value at each location through a Monte Carlo simulation and a non-parametric approach. See the reference for the details about the method.

If `null`

distribution is not provided, the function generates a null distribution by randomly shuffling the values in the dataset.

An object same as the input (`x`

)

Babak Naimi naimi.b@gmail.com

Naimi, B., Hamm, N. A., Groen, T. A., Skidmore, A. K., Toxopeus, A. G., & Alibakhshi, S. (2019). ELSA: Entropy-based local indicator of spatial association. Spatial statistics, 29, 66-88.

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