Elsa_categorical_matrix_window

method described here : https://doi.org/10.1016/j.spasta.2018.10.001

internal

Provides functions to apply spatial fuzzy unsupervised classification, visualize and interpret results. This method is well suited when the user wants to analyze data with a fuzzy clustering algorithm and to account for the spatial dimension of the dataset. In addition, indexes for estimating the spatial consistency and classification quality are proposed.
The methods were originally proposed in the field of brain imagery (seed Cai and al. 2007 <doi:10.1016/j.patcog.2006.07.011> and Zaho and al. 2013 <doi:10.1016/j.dsp.2012.09.016>) and recently applied in geography (see Gelb and Apparicio <doi:10.4000/cybergeo.36414>).

Jeremy Gelb

geocmeans

Implementing Methods for Spatial Fuzzy Unsupervised
Classification

Philippe Apparicio

Elsa_categorical_matrix_window function

<dl><dt>mat</dt>
<dd>an IntegerMatrix, must be filled with integer, -1 indicates NA values, categories must start at 0</dd>
<dt>window</dt>
<dd>the window to use to define neighbours. 0 can be used to indicate that a cell is not a neighbour</dd>
<dt>dist</dt>
<dd>a distance matrix between the categories</dd></dl>

Arguments

Elsa statistic calculated on a matrix with a given window — Elsa_categorical_matrix_window

<dl>

<dt>mat</dt>
<dd>an IntegerMatrix, must be filled with integer, -1 indicates NA values, categories must start at 0</dd>


<dt>window</dt>
<dd>the window to use to define neighbours. 0 can be used to indicate that a cell is not a neighbour</dd>


<dt>dist</dt>
<dd>a distance matrix between the categories</dd>

</dl>

Elsa_categorical_matrix_window: Elsa statistic calculated on a matrix with a given window

Description

Usage

Value

Arguments