randomize_distmatrix2

Randomize location of points on a network.

internal

Perform spatial analysis on network.
Implement several methods for spatial analysis on network: Network Kernel Density estimation,
building of spatial matrices based on network distance ('listw' objects from 'spdep' package), K functions estimation
for point pattern analysis on network, k nearest neighbours on network, reachable area calculation, and graph generation
References: Okabe et al (2019) <doi:10.1080/13658810802475491>;
Okabe et al (2012, ISBN:978-0470770818);Baddeley et al (2015, ISBN:9781482210200).

Jeremy Gelb

spNetwork

Spatial Analysis on Network

Philippe Apparicio

randomize_distmatrix2 function

<dl><dt>graph</dt>
<dd>An graph object from igraph</dd>
<dt>edge_df</dt>
<dd>A DataFrame describing the edges</dd>
<dt>n</dt>
<dd>The number of point</dd>
<dt>resolution</dt>
<dd>The maximum size of the network edges</dd>
<dt>nsim</dt>
<dd>The number of distance matrices to generate</dd>
<dt>start_vert</dt>
<dd>The vertices from which the distances will be calculated.
if null, then the distances are calculated from the generated locations.</dd></dl>

Arguments

Points on network randomization simplified — randomize_distmatrix2

<dl>

<dt>graph</dt>
<dd>An graph object from igraph</dd>


<dt>edge_df</dt>
<dd>A DataFrame describing the edges</dd>


<dt>n</dt>
<dd>The number of point</dd>


<dt>resolution</dt>
<dd>The maximum size of the network edges</dd>


<dt>nsim</dt>
<dd>The number of distance matrices to generate</dd>


<dt>start_vert</dt>
<dd>The vertices from which the distances will be calculated.
if null, then the distances are calculated from the generated locations.</dd>

</dl>

randomize_distmatrix2: Points on network randomization simplified

Description

Usage

Value

Arguments

Examples