highest_concentration_candidate

Find the highest concentration for the current iteration.

internal

Provides methods for spatial concentration and radius-based risk
calculations. The package focuses on efficient determination of the sum of
observations within a given radius, identifying local concentration
hotspots, and aggregating point data to polygon geometries. These methods
are useful for applications such as insurance, urban analytics,
environmental exposure analysis, and other spatial point pattern workflows.
The underlying maximum covering problem is described by Church (1974)
<doi:10.1007/BF01942293>.

Martin Haringa

spatialrisk

Spatial Concentration and Radius-Based Risk Calculations

highest_concentration_candidate function

<dl><dt>new_candidates</dt>
<dd>highest concentrations from the current iteration.</dd>
<dt>candidate_cells</dt>
<dd>data.frame containing cell ids with focal values
selected for refinement in the current iteration.</dd>
<dt>cache</dt>
<dd>data.frame containing previously saved highest concentrations.</dd></dl>

Arguments

Author

Find the highest concentration for the current iteration — highest_concentration_candidate

<dl>

<dt>new_candidates</dt>
<dd>highest concentrations from the current iteration.</dd>


<dt>candidate_cells</dt>
<dd>data.frame containing cell ids with focal values
selected for refinement in the current iteration.</dd>


<dt>cache</dt>
<dd>data.frame containing previously saved highest concentrations.</dd>

</dl>

highest_concentration_candidate: Find the highest concentration for the current iteration

Description

Usage

Arguments

Author