adj_to_edgelist | Converts an adjacency matrix to edgelist and edgeweight using... |
adj_to_wdnet | Creates a 'wdnet' object using an adjacency matrix |
assortcoef | Compute the assortativity coefficient(s) for a network. |
centrality | Centrality measures |
closeness_c | Closeness centrality |
clustcoef | Directed clustering coefficient |
compile_pref_func | Compile preference functions via 'RcppXPtrUtils'. |
create_wdnet | Creates a 'wdnet' object from input data. |
cvxr_control | Parameters passed to CVXR::solve(). |
degree_c | Degree-based centrality |
dprewire | Degree preserving rewiring. |
dprewire_directed | Degree preserving rewiring for directed networks |
dprewire_directed_cpp | Degree preserving rewiring process for directed networks. |
dprewire.range | Range of assortativity coefficients. |
dprewire_undirected | Degree preserving rewiring for undirected networks |
dprewire_undirected_cpp | Degree preserving rewiring process for undirected networks. |
dw_assort | Compute the assortativity coefficient of a weighted and... |
dw_feature_assort | Feature based assortativity coefficient |
edgelist_to_adj | Convert edgelist and edgeweight to adjacency matrix. |
edgelist_to_wdnet | Creates a 'wdnet' object using 'edgelist'. |
fill_weight_cpp | Fill edgeweight into the adjacency matrix. Defined for... |
find_node_cpp | Fill missing nodes in the node sequence. Defined for... |
find_node_undirected_cpp | Fill missing values in node sequence. Defined for... |
get_constr | Get the constraints for the optimization problem. This... |
get_dist | Get the node-level joint distributions and some empirical... |
get_eta_directed | Compute edge-level distributions for directed networks with... |
get_eta_undirected | Compute edge-level distribution for undirected networks with... |
get_values | Get the value of an object from the optimization problem.... |
igraph_to_wdnet | Converts an 'igraph' object to a 'wdnet' object |
is_rpacontrol | Checks whether the input is a 'rpacontrol' object |
is_wdnet | Checks if the input is a 'wdnet' object |
node_strength_cpp | Aggregate edgeweight into nodes' strength. |
plot.wdnet | Plots the input network |
plus-.rpacontrol | Add components to the control list |
print_control_details | Prints 'rpacontrol' in terminal |
print_control_edgeweight | Prints 'rpa_control_edgeweight()' in terminal |
print_control_newedge | Prints 'rpa_control_newedge()' in terminal |
print_control_preference | Prints 'rpa_control_preference()' in terminal |
print_control_reciprocal | Prints 'rpa_control_reciprocal()' in terminal |
print_control_scenario | Prints 'rpa_control_scenario()' in terminal |
print.rpacontrol | Prints 'rpacontrol' objects |
print.wdnet | Prints the input network |
rpacontrol | rpacontrol: Controls the Preferential Attachment (PA) Network... |
rpa_control_default | Default controls for 'rpanet' |
rpa_control_edgeweight | Control weight of new edges. Defined for 'rpanet'. |
rpa_control_newedge | Control new edges in each step. Defined for 'rpanet'. |
rpa_control_preference | Set preference function(s). Defined for 'rpanet'. |
rpa_control_reciprocal | Control reciprocal edges. Defined for 'rpanet'. |
rpa_control_scenario | Control edge scenarios. Defined for 'rpanet'. |
rpanet | Generate PA networks. |
rpanet_bag_cpp | Preferential attachment algorithm for simple situations,... |
rpanet_binary_directed | Preferential attachment network generation. |
rpanet_binary_undirected_cpp | Preferential attachment network generation. |
rpanet.internal | Internal functions for generating PA networks |
rpanet_linear_directed_cpp | Preferential attachment network generation. |
rpanet_linear_undirected_cpp | Preferential attachment network generation. |
sample_node_cpp | Uniformly draw a node from existing nodes for each time step.... |
wdnet-package | wdnet: Weighted and Directed Networks |
wdnet_to_igraph | Converts a 'wdnet' object to an 'igraph' object |
wpr | Weighted PageRank centrality |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.