tnkdecontinuousfunction: The main function to calculate continuous TNKDE (with...

tnkdecontinuousfunctionR Documentation

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

Description

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

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

Usage

continuous_tnkde_cpp_arma_sparse(
  neighbour_list,
  events,
  events_time,
  weights,
  samples,
  samples_time,
  bws_net,
  bws_time,
  kernel_name,
  nodes,
  line_list,
  max_depth,
  verbose,
  div
)

continuous_tnkde_cpp_arma(
  neighbour_list,
  events,
  events_time,
  weights,
  samples,
  samples_time,
  bws_net,
  bws_time,
  kernel_name,
  nodes,
  line_list,
  max_depth,
  verbose,
  div
)

Arguments

neighbour_list

a list of the neighbours of each node

events

a numeric vector of the node id of each event

events_time

a numeric vector with the time for the events

weights

a numeric vector of the weight of each event

samples

a DataFrame of the samples (with spatial coordinates and belonging edge)

samples_time

a NumericVector indicating when to do the samples

bws_net

the network kernel bandwidths for each event

bws_time

the time 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

a string indicating how to standardize the kernel values

Value

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

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


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