adaptive_bw_tnkde: Adaptive bandwidth for TNDE

In spNetwork: Spatial Analysis on Network

Adaptive bandwidth for TNDE

Description

Function to calculate Adaptive bandwidths according to Abramson’s smoothing regimen for TNKDE with a space-time interaction.

Usage

adaptive_bw_tnkde(
  grid,
  events_loc,
  events,
  lines,
  bw_net,
  bw_time,
  trim_bw_net,
  trim_bw_time,
  method,
  kernel_name,
  max_depth,
  div,
  tol,
  digits,
  sparse,
  verbose
)

Arguments

grid	A spatial grid to split the data within
events	A feature collection of points representing the events points
lines	A feature collection of linestrings representing the network
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.
trim_bw_net	The maximum size of local bandwidths for network dimension. Must be a vector if bw_net is a vector
trim_bw_time	The maximum size of local bandwidths for time dimension. Must be a vector if bw_net is a vector
method	The method to use when calculating the NKDE
kernel_name	The name of the kernel to use
max_depth	The maximum recursion depth
div	The divisor to use for kernels
tol	A float indicating the spatial tolerance when snapping events on lines
digits	The number of digits to keep
sparse	A Boolean indicating if sparse matrix should be used
verbose	A Boolean indicating if update messages should be printed

Value

A vector with the local bandwidths, or an array if bw_time and bw_net are vectors. In that case, the array has the following dimensions : length(bw_net) X length(bw_time) X nrow(events)

Examples

#This is an internal function, no example provided

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