continuousfunction: The main function to calculate continuous NKDE (with ARMADILO...

In spNetwork: Spatial Analysis on Network

The main function to calculate continuous NKDE (with ARMADILO and sparse matrix)

Description

The main function to calculate continuous NKDE (with ARMADILO and sparse matrix)

The main function to calculate continuous NKDE (with ARMADILO and integer matrix)

Usage

continuous_nkde_cpp_arma_sparse(
  neighbour_list,
  events,
  weights,
  samples,
  bws,
  kernel_name,
  nodes,
  line_list,
  max_depth,
  verbose,
  div = "bw"
)

continuous_nkde_cpp_arma(
  neighbour_list,
  events,
  weights,
  samples,
  bws,
  kernel_name,
  nodes,
  line_list,
  max_depth,
  verbose,
  div = "bw"
)

Arguments

neighbour_list	a list of the neighbours of each node
events	a numeric vector of the node id of each event
weights	a numeric vector of the weight of each event
samples	a DataFrame of the samples (with spatial coordinates and belonging edge)
bws	the kernel bandwidths for each event
kernel_name	the name of the kernel to use
nodes	a DataFrame representing the nodes of the graph (with spatial coordinates)
line_list	a DataFrame representing the lines of the graph
max_depth	the maximum recursion depth (after which recursion is stopped)
verbose	a boolean indicating if the function must print its progress
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).

Value

a DataFrame with two columns : the kernel values (sum_k) and the number of events for each sample (n)

a DataFrame with two columns : the kernel values (sum_k) and the number of events for each sample (n)

spNetwork documentation built on Aug. 24, 2023, 5:10 p.m.