tkde

Calculate the Temporal kernel density estimate based on sampling points in
time and events

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

tkde function

<dl><dt>events</dt>
<dd>A numeric vector representing the moments of occurrence of events</dd>
<dt>w</dt>
<dd>The weight of the events</dd>
<dt>samples</dt>
<dd>A numeric vector representing the moments to sample</dd>
<dt>bw</dt>
<dd>A float, the bandwidth to use</dd>
<dt>kernel_name</dt>
<dd>The name of the kernel to use</dd>
<dt>adaptive</dt>
<dd>Boolean</dd></dl>

Arguments

Temporal Kernel density estimate — tkde

<dl>

<dt>events</dt>
<dd>A numeric vector representing the moments of occurrence of events</dd>


<dt>w</dt>
<dd>The weight of the events</dd>


<dt>samples</dt>
<dd>A numeric vector representing the moments to sample</dd>


<dt>bw</dt>
<dd>A float, the bandwidth to use</dd>


<dt>kernel_name</dt>
<dd>The name of the kernel to use</dd>


<dt>adaptive</dt>
<dd>Boolean</dd>

</dl>

tkde: Temporal Kernel density estimate

Description

Usage

Value

Arguments

Examples