rpoistlpp

This function simulates realisations of a spatio-temporal Poisson point process on a linear network.

Statistical analysis of spatio-temporal point processes on linear networks. This packages provides tools to visualise and analyse spatio-temporal point patterns on linear networks using first- and second-order summary statistics.

Mehdi Moradi

stlnpp

Spatio-Temporal Analysis of Point Patterns on Linear Networks

Ottmar Cronie

Jorge Mateu

rpoistlpp function

<dl><dt>lambda</dt>
<dd>intensity of the point process. it can be either a number, function of location and time, or an abject of class <code>stlppint</code></dd>
<dt>a</dt>
<dd>lower bound of time period</dd>
<dt>b</dt>
<dd>upper bound of time period</dd>
<dt>L</dt>
<dd>a linear network</dd>
<dt>check</dt>
<dd>logical value indicating whether to check that all the (x,y) points lie inside the specified window. see <code>ppp</code></dd>
<dt>lmax</dt>
<dd>upper bound for the values of <code>labmda</code>. this is optional</dd>
<dt>nsim</dt>
<dd>number of simulated patterns to generate</dd></dl>

Arguments

Mehdi Moradi &lt;m2.moradi@yahoo.com&gt;

Author

Simulating spatio-temporal Poisson point processes on a linear network — rpoistlpp

<dl>

<dt>lambda</dt>
<dd>intensity of the point process. it can be either a number, function of location and time, or an abject of class <code>stlppint</code></dd>


<dt>a</dt>
<dd>lower bound of time period</dd>


<dt>b</dt>
<dd>upper bound of time period</dd>


<dt>L</dt>
<dd>a linear network</dd>


<dt>check</dt>
<dd>logical value indicating whether to check that all the (x,y) points lie inside the specified window. see <code>ppp</code></dd>


<dt>lmax</dt>
<dd>upper bound for the values of <code>labmda</code>. this is optional</dd>


<dt>nsim</dt>
<dd>number of simulated patterns to generate</dd>

</dl>

rpoistlpp: Simulating spatio-temporal Poisson point processes on a linear network

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples