nndist

<code>nndist</code> determines the nearest
neighbors for a set of observations within a certain
radius.

Implements statistical methods for analyzing the counts of areal data, with a focus on the detection of spatial clusters and clustering. The package has a heavy emphasis on spatial scan methods, which were first introduced by Kulldorff and Nagarwalla (1995) <doi:10.1002/sim.4780140809> and Kulldorff (1997) <doi:10.1080/03610929708831995>.

Joshua French

smerc

Statistical Methods for Regional Counts

Mohammad Meysami

nndist function

<dl><dt>d</dt>
<dd>An \(n\times n\) square distance matrix
containing the intercentroid distance between the
\(n\) region centroids.</dd>
<dt>ubd</dt>
<dd>A proportion in (0, 1]. The distance of
potential clusters must be no more than <code>ubd * m</code>,
where <code>m</code> is the maximum intercentroid distance
between all coordinates.</dd></dl>

Arguments

Author

Determine nearest neighbors based on maximum distance — nndist

<dl>

<dt>d</dt>
<dd>An \(n\times n\) square distance matrix
containing the intercentroid distance between the
\(n\) region centroids.</dd>


<dt>ubd</dt>
<dd>A proportion in (0, 1]. The distance of
potential clusters must be no more than <code>ubd * m</code>,
where <code>m</code> is the maximum intercentroid distance
between all coordinates.</dd>

</dl>

nndist: Determine nearest neighbors based on maximum distance

Description

Usage

Value

Arguments

Author

Details

Examples