estimate_k_max {GeoThinneR} | R Documentation |
Estimate Maximum Neighbors for kd-Tree Thinning
Description
This function estimates the maximum value of k (the number of nearest neighbors) for kd-tree-based thinning by evaluating the densest regions of a spatial dataset. The function uses a histogram-based binning approach for efficiency and low memory usage.
Usage
estimate_k_max(coordinates, thin_dist, distance = c("haversine", "euclidean"))
Arguments
coordinates |
A matrix of spatial coordinates with two columns for longitude and latitude. |
thin_dist |
A positive numeric value representing the thinning distance in kilometers. This defines the resolution of the grid used for density calculations. |
distance |
Distance metric used 'c("haversine", "euclidean")'. |
Details
The function divides the spatial domain into grid cells based on the specified thinning distance. Grid cell sizes are determined assuming approximately 111.32 km per degree (latitude/longitude). The function identifies the densest grid cells and their immediate neighbors to compute the maximum k value.
Value
A numeric value representing the maximum k (number of nearest neighbors) required for the densest regions in the dataset.
Examples
# Generate sample data
set.seed(123)
coordinates <- matrix(runif(200, min = -10, max = 10), ncol = 2)
# Estimate k for kd-tree thinning
k_max <- estimate_k_max(coordinates, thin_dist = 50)
print(k_max)