sim_nsprocess

Simulation of the Neyman-Scott process. Only applicable if the intensity was estimated
for an appropriately enlarged window.
More details in <code>sim_nsppp</code>.

Functions for determining and evaluating high-risk zones and
simulating and thinning point process data, as described in 'Determining
high risk zones using point process methodology - Realization by building
an R package' Seibold (2012) <http://highriskzone.r-forge.r-project.org/Bachelorarbeit.pdf>
and 'Determining high-risk zones for unexploded World War II bombs by using point
process methodology', Mahling et al. (2013) <doi:10.1111/j.1467-9876.2012.01055.x>.

Rickmer Schulte

highriskzone

Determining and Evaluating High-Risk Zones

sim_nsprocess function

<dl><dt>ppdata</dt>
<dd>observed point pattern whose estimated intensity (adjusted for
thinning and divided by "clustering") is used for simulating the
parent process</dd>
<dt>intens</dt>
<dd>estimated intensity</dd>
<dt>radius</dt>
<dd>radius of the circles around the parent points in which the cluster
points are located (Maximum radius of a random cluster)</dd>
<dt>clustering</dt>
<dd>a value larger or equal 1 which describes the amount of clustering; the
adjusted estimated intensity of the observed pattern is divided by
this value; it is also the parameter of the Poisson distribution
for the number of points per cluster</dd>
<dt>thinning</dt>
<dd>constant thinning probability (in case the observed pattern is a
thinned version of a full pattern); usually equal to the probability of having
unobserved events</dd></dl>

Arguments

Simulation of the Neyman-Scott process. — sim_nsprocess

<dl>

<dt>ppdata</dt>
<dd>observed point pattern whose estimated intensity (adjusted for
thinning and divided by "clustering") is used for simulating the
parent process</dd>


<dt>intens</dt>
<dd>estimated intensity</dd>


<dt>radius</dt>
<dd>radius of the circles around the parent points in which the cluster
points are located (Maximum radius of a random cluster)</dd>


<dt>clustering</dt>
<dd>a value larger or equal 1 which describes the amount of clustering; the
adjusted estimated intensity of the observed pattern is divided by
this value; it is also the parameter of the Poisson distribution
for the number of points per cluster</dd>


<dt>thinning</dt>
<dd>constant thinning probability (in case the observed pattern is a
thinned version of a full pattern); usually equal to the probability of having
unobserved events</dd>

</dl>

sim_nsprocess: Simulation of the Neyman-Scott process.

Description

Usage

Value

Arguments