worker_adaptive_bw_tnkde: Worker function for adaptive bandwidth for TNDE

In spNetwork: Spatial Analysis on Network

Worker function for adaptive bandwidth for TNDE

Description

The worker function to calculate Adaptive bandwidths according to Abramson’s smoothing regimen for TNKDE with a space-time interaction (INTERNAL).

Usage

worker_adaptive_bw_tnkde(
  lines,
  quad_events,
  events_loc,
  events,
  w,
  kernel_name,
  bw_net,
  bw_time,
  method,
  div,
  digits,
  tol,
  sparse,
  max_depth,
  verbose = FALSE
)

Arguments

lines	A feature collection of linestrings representing the underlying network
quad_events	a feature collection of points indicating for which events the densities must be calculated
events_loc	A feature collection of points representing the location of the events
events	A feature collection of points representing the events. Multiple events can share the same location. They are linked by the goid column
w	A numeric vector with the weight of the events
kernel_name	The name of the kernel to use (string)
bw_net	The fixed kernel bandwidth for the network dimension. Can also be a vector if several bandwidth must be used.
bw_time	The fixed kernel bandwidth for the time dimension. Can also be a vector if several bandwidth must be used.
method	The type of NKDE to use (string)
div	The divisor to use for the kernel. Must be "n" (the number of events within the radius around each sampling point), "bw" (the bandwidth) "none" (the simple sum).
digits	The number of digits to retain from the spatial coordinates. It ensures that topology is good when building the network. Default is 3. Too high a precision (high number of digits) might break some connections
tol	A float indicating the minimum distance between the events and the lines' extremities when adding the point to the network. When points are closer, they are added at the extremity of the lines.
sparse	A Boolean indicating if sparse or regular matrices should be used by the Rcpp functions. These matrices are used to store edge indices between two nodes in a graph. Regular matrices are faster, but require more memory, in particular with multiprocessing. Sparse matrices are slower (a bit), but require much less memory.
max_depth	An integer, the maximum depth to reach for continuous and discontinuous NKDE
verbose	A Boolean, indicating if the function should print messages about the process.

Value

A vector with the local bandwidths or an array if bw_net and bw_time are vectors

Examples

#This is an internal function, no example provided

spNetwork documentation built on June 22, 2024, 9:40 a.m.