sim.void

Generates points from a void point process using parameters provided by the user.

Functions to fit point process models using the Palm likelihood. First proposed by Tanaka, Ogata, and Stoyan (2008) <DOI:10.1002/bimj.200610339>, maximisation of the Palm likelihood can provide computationally efficient parameter estimation for point process models in situations where the full likelihood is intractable. This package is chiefly focused on Neyman-Scott point processes, but can also fit the void processes proposed by Jones-Todd et al. (2019) <DOI:10.1002/sim.8046>. The development of this package was motivated by the analysis of capture-recapture surveys on which individuals cannot be identified---the data from which can conceptually be seen as a clustered point process (Stevenson, Borchers, and Fewster, 2019 <DOI:10.1111/biom.12983>). As such, some of the functions in this package are specifically for the estimation of cetacean density from two-camera aerial surveys.

Ben Stevenson

palm

Fitting Point Process Models via the Palm Likelihood

sim.void function

<dl><dt>pars</dt>
<dd>A named vector containing the values of the parameters
of the process that generates the points.</dd>
<dt>lims</dt>
<dd>A matrix or list of matrices with two columns,
corresponding to the upper and lower limits of each dimension,
respectively. If a list, then each matrix provides the limits
for the corresponding pattern in <code>points</code>.</dd>
<dt>parents</dt>
<dd>An optional matrix containing locations of
parents. If this is provided, then the parameter <code>D</code> is
not required in <code>pars</code>. If this is not provided, then
parents are generated from a homogeneous Poisson point process
with intensity <code>Dp</code>.</dd></dl>

Arguments

Simulating points from a void point process. — sim.void

<dl>

<dt>pars</dt>
<dd>A named vector containing the values of the parameters
of the process that generates the points.</dd>


<dt>lims</dt>
<dd>A matrix or list of matrices with two columns,
corresponding to the upper and lower limits of each dimension,
respectively. If a list, then each matrix provides the limits
for the corresponding pattern in <code>points</code>.</dd>


<dt>parents</dt>
<dd>An optional matrix containing locations of
parents. If this is provided, then the parameter <code>D</code> is
not required in <code>pars</code>. If this is not provided, then
parents are generated from a homogeneous Poisson point process
with intensity <code>Dp</code>.</dd>

</dl>

sim.void: Simulating points from a void point process.

Description

Usage

Value

Arguments

Details

Examples