corrfactor_continuous

A function to calculate the necessary information to apply the
Diggle correction factor with a continuous method

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

corrfactor_continuous function

<dl><dt>neighbour_list</dt>
<dd>a list of the neighbours of each node</dd>
<dt>events</dt>
<dd>a numeric vector of the node id of each event</dd>
<dt>line_list</dt>
<dd>a DataFrame representing the lines of the graph</dd>
<dt>bws</dt>
<dd>the kernel bandwidth for each event</dd>
<dt>max_depth</dt>
<dd>the maximum recursion depth (after which recursion is stopped)</dd></dl>

Arguments

A function to calculate the necessary information to apply the
Diggle correction factor with a continuous method — corrfactor_continuous

<dl>

<dt>neighbour_list</dt>
<dd>a list of the neighbours of each node</dd>


<dt>events</dt>
<dd>a numeric vector of the node id of each event</dd>


<dt>line_list</dt>
<dd>a DataFrame representing the lines of the graph</dd>


<dt>bws</dt>
<dd>the kernel bandwidth for each event</dd>


<dt>max_depth</dt>
<dd>the maximum recursion depth (after which recursion is stopped)</dd>

</dl>

corrfactor_continuous: A function to calculate the necessary information to apply the Diggle correction factor with a continuous method

Description

Usage

Value

Arguments