R: Fit, Simulate, and Diagnose Hierarchical Exponential-Family Models for Big Networks

# Fit, Simulate, and Diagnose Hierarchical Exponential-Family Models for Big Networks

## Documentation for package ‘bigergm’ version 1.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

compute_multiplied_feature_matrices | Get a list of sparse feature adjacency matrix from a formula.
compute_yule_coef | Compute Yule's Phi-coefficient
draw_between_block_connection | Draw between-block connections.
draw_within_block_connection | Draw within-block connections
estimate_between_param | Estimate between-block parameters by logit
estimate_within_params | Estimate a within-block network model.
get_list_sparse_feature_adjmat | Get a list of sparse feature adjacency matrix from a formula
gof_bigergm | Goodness of fit statistics for HERGM
hergm | Hierarchical exponential-family random graph models (HERGMs) with local dependence
install_python_dependencies | Install optional Python dependencies
simulate_hergm | Simulate a network
simulate_hergm_within | Sample within cluster networks
toyNet | A toy network to play 'bigergm' with.