discontinuousfunction {spNetwork} | R Documentation |
The main function to calculate discontinuous NKDE (ARMA and sparse matrix)
Description
The main function to calculate discontinuous NKDE (ARMA and sparse matrix)
The main function to calculate discontinuous NKDE (ARMA and Integer matrix)
Usage
discontinuous_nkde_cpp_arma_sparse(
neighbour_list,
events,
weights,
samples,
bws,
kernel_name,
nodes,
line_list,
max_depth,
verbose,
div = "bw"
)
discontinuous_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 bandwidth for each event |
kernel_name |
the name of the kernel function 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)