continuousfunction | R Documentation |

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

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

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" )

`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). |

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)

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