p_prob

Generates an <code>n</code> probability
values in accordance with a specified
proportional ratios.

Generates artificial point patterns marked by their
spatial and temporal signatures. The resulting point cloud
may exhibit inherent interactions between both signatures.
The simulation integrates microsimulation
(Holm, E., (2017)<doi:10.1002/9781118786352.wbieg0320>)
and agent-based models (Bonabeau, E., (2002)<doi:10.1073/pnas.082080899>),
beginning with the configuration of movement characteristics for
the specified agents (referred to as 'walkers') and their interactions
within the simulation environment. These interactions
(Quaglietta, L. and Porto, M., (2019)<doi:10.1186/s40462-019-0154-8>)
result in specific spatiotemporal patterns that can be visualized,
analyzed, and used for various analytical purposes.
Given the growing scarcity of detailed spatiotemporal data
across many domains, this package provides an alternative data source
for applications in social and life sciences.

Monsuru Adepeju

stppSim

Spatiotemporal Point Patterns Simulation

p_prob function

<dl><dt>n</dt>
<dd>a number of data points.</dd>
<dt>p_ratio</dt>
<dd>the smaller of the
terms of specified proportional ratios. For instance, for a
<code>30:70</code> ratio, <code>p_ratio</code> is equal to <code>30</code>.
Default value is set as
<code>20</code>. Valid <code>p_ratio</code> values
are: (<code>5, 10, 20, 30, 40</code>).</dd></dl>

Arguments

Proportional (probability) distribution — p_prob

<dl>

<dt>n</dt>
<dd>a number of data points.</dd>


<dt>p_ratio</dt>
<dd>the smaller of the
terms of specified proportional ratios. For instance, for a
<code>30:70</code> ratio, <code>p_ratio</code> is equal to <code>30</code>.
Default value is set as
<code>20</code>. Valid <code>p_ratio</code> values
are: (<code>5, 10, 20, 30, 40</code>).</dd>

</dl>

p_prob: Proportional (probability) distribution

Description

Usage

Value

Arguments

Details

Examples