Function reference • spNetwork

Network Kernel Density Functions to perform Network Kernel Density estimation.
`nkde()`	Network Kernel density estimate
`nkde.mc()`	Network Kernel density estimate (multicore)
`bw_cvl_calc()`	Bandwidth selection by Cronie and Van Lieshout's Criterion
`bw_cvl_calc.mc()`	Bandwidth selection by Cronie and Van Lieshout's Criterion (multicore version)
`bw_cv_likelihood_calc()`	Bandwidth selection by likelihood cross validation
`bw_cv_likelihood_calc.mc()`	Bandwidth selection by likelihood cross validation (multicore)
`tricube_kernel()`	Tricube kernel
`triweight_kernel()`	Triweight kernel
`uniform_kernel()`	Uniform kernel
`cosine_kernel()`	Cosine kernel
`epanechnikov_kernel()`	Epanechnikov kernel
`gaussian_kernel()`	Gaussian kernel
`gaussian_kernel_scaled()`	Scaled gaussian kernel
`quartic_kernel()`	Quartic kernel
`triangle_kernel()`	triangle kernel
Temporal Network Kernel Density Functions to perform Temporal Network Kernel Density estimation.
`tnkde()`	Temporal Network Kernel density estimate
`tnkde.mc()`	Temporal Network Kernel density estimate (multicore)
`bw_tnkde_cv_likelihood_calc()`	Bandwidth selection by likelihood cross validation for temporal NKDE
`bw_tnkde_cv_likelihood_calc.mc()`	Bandwidth selection by likelihood cross validation for temporal NKDE (multicore)
`tkde()`	Temporal Kernel density estimate
`bw_cv_likelihood_calc_tkde()`	Bandwidth selection for Temporal Kernel density estimate by likelihood cross validation
Spatial weight matrices on networks Functions to calculate spatial weight matrices on networks.
`network_listw()`	Network distance listw
`network_listw.mc()`	Network distance listw (multicore)
K functions on networks Functions to calculate K and G functions on networks.
`kfunctions()`	Network k and g functions (maturing)
`kfunctions.mc()`	Network k and g functions (multicore, maturing)
`cross_kfunctions()`	Network cross k and g functions (maturing)
`cross_kfunctions.mc()`	Network cross k and g functions (multicore, maturing)
`k_nt_functions()`	Network k and g functions for spatio-temporal data (experimental, NOT READY FOR USE)
`k_nt_functions.mc()`	Network k and g functions for spatio-temporal data (multicore, experimental, NOT READY FOR USE)
Knn functions on networks Functions to calculate K nearest neighbours on networks.
`network_knn()`	K-nearest points on network
`network_knn.mc()`	K-nearest points on network (multicore version)
Network building Functions to build graphs.
`build_graph()`	Network generation
`build_graph_directed()`	Directed network generation
`graph_checking()`	Topological error
`simplify_network()`	Simplify a network
`split_graph_components()`	Split graph components
Isochrones Functions to calculate isochrones.
`calc_isochrones()`	Isochrones calculation
Geometrical functions Functions to perform geometric operations.
`build_quadtree()`	Build a quadtree
`spatial_request()`	Spatial request
`closest_points()`	Find closest points
`lines_center()`	Centre points of lines
`lines_extremities()`	Get lines extremities
`lines_direction()`	Unify lines direction
`lines_points_along()`	Points along lines
`lixelize_lines()`	Cut lines into lixels
`lixelize_lines.mc()`	Cut lines into lixels (multicore)
`split_lines_at_vertex()`	Split lines at vertices in a feature collection of linestrings
`simple_lines()`	LineString to simple Line
`st_bbox_by_feature()`	Obtain all the bounding boxes of a feature collection
Spatial data cleaning Functions to clean data before spatial analysis
`aggregate_points()`	Events aggregation
Spatial functions Functions used for specific spatial tasks
`simple_lines()`	LineString to simple Line
`spatial_index`	An object (c++ pointer) to do some spatial query of rectanlges (internal)
`st_bbox_by_feature()`	Obtain all the bounding boxes of a feature collection
Data Some datasets provided with the package
`bike_accidents`	Road accidents including a bicyle in Montreal in 2016
`mtl_network`	Road network of Montreal
`main_network_mtl`	Primary road network of Montreal
`small_mtl_network`	Smaller subset road network of Montreal
`mtl_libraries`	Libraries of Montreal
`mtl_theatres`	Theatres of Montreal
`spNetwork` `spNetwork-package`	spNetwork: Spatial Analysis on Network
`adaptive_bw_tnkde_cpp()`	The exposed function to calculate adaptive bandwidth with space-time interaction for TNKDE (INTERNAL)
`adaptive_bw_tnkde_cpp2()`	The exposed function to calculate adaptive bandwidth with space-time interaction for TNKDE (INTERNAL)
`cross_gfunc_cpp()`	c++ cross g function
`cross_kfunc_cpp()`	c++ cross k function
`esc_kernel_loo_nkde`	The worker function to calculate continuous TNKDE likelihood cv
`esc_kernel_loo_tnkde`	The worker function to calculate continuous TNKDE likelihood cv
`esd_kernel_loo_nkde`	The worker function to calculate discontinuous TNKDE likelihood cv
`esd_kernel_loo_tnkde`	The worker function to calculate discontinuous TNKDE likelihood cv
`esc_kernel_loo_tnkde_adpt`	The worker function to calculate continuous TNKDE likelihood cv (adaptive case)
`gfunc_cpp()`	c++ g function
`kfunc_cpp()`	c++ k function
`nkde_get_loo_values()`	The exposed function to calculate NKDE likelihood cv
`tnkde_get_loo_values()`	The exposed function to calculate TNKDE likelihood cv
`tnkde_get_loo_values2()`	The exposed function to calculate TNKDE likelihood cv
`tnkde_worker_bw_sel()`	Worker function fo Bandwidth selection by likelihood cross validation for temporal NKDE
`worker_adaptive_bw_tnkde()`	Worker function for adaptive bandwidth for TNDE
`bw_cv_likelihood_calc_tkde()`	Bandwidth selection for Temporal Kernel density estimate by likelihood cross validation

Reference

Network Kernel Density

Temporal Network Kernel Density

Spatial weight matrices on networks

K functions on networks

Knn functions on networks

Network building

Isochrones

Geometrical functions

Spatial data cleaning

Spatial functions

Data