spdep_skater

SKATER forms clusters by spatially partitioning data that has similar values for features of interest.

Wrapping and supplementing commonly used functions in the R ecosystem related to spatial data science,
while serving as a basis for other packages maintained by Wenbo Lv.

Wenbo Lv

sdsfun

Spatial Data Science Complementary Features

spdep_skater function

<dl><dt>sfj</dt>
<dd>An <code>sf</code> object of observation data. Please ensure that the attribute columns are included
in the SKATER analysis.</dd>
<dt>k</dt>
<dd>(optional) The number of clusters. Default is <code>6</code>.</dd>
<dt>nb</dt>
<dd>(optional) A neighbours list with class nb. If the input <code>nb</code> is NULL, it will be constructed
automatically using <code>spdep_nb()</code>.</dd>
<dt>ini</dt>
<dd>(optional) The initial node in the minimal spanning tree. Defaul is <code>5</code>.</dd>
<dt>...</dt>
<dd>(optional) Other parameters passed to spdep::skater().</dd></dl>

Arguments

spatial c(k)luster analysis by tree edge removal — spdep_skater

<dl>

<dt>sfj</dt>
<dd>An <code>sf</code> object of observation data. Please ensure that the attribute columns are included
in the SKATER analysis.</dd>


<dt>k</dt>
<dd>(optional) The number of clusters. Default is <code>6</code>.</dd>


<dt>nb</dt>
<dd>(optional) A neighbours list with class nb. If the input <code>nb</code> is NULL, it will be constructed
automatically using <code>spdep_nb()</code>.</dd>


<dt>ini</dt>
<dd>(optional) The initial node in the minimal spanning tree. Defaul is <code>5</code>.</dd>


<dt>...</dt>
<dd>(optional) Other parameters passed to spdep::skater().</dd>

</dl>

spdep_skater: spatial c(k)luster analysis by tree edge removal

Description

Usage

Value

Arguments

Examples