MixMashNet: An R Package for Single and Multilayer Networks

TL;DR

MixMashNet is an R package that enables comprehensive estimation, analysis, and visualization of single and multilayer networks with mixed data types, including tools for stability and community analysis.

Contribution

It introduces an integrated framework for multilayer network analysis with mixed data types, including stability assessment and interactive visualization tools.

Findings

Provides bootstrap-based uncertainty quantification for network edges.

Includes tools for community stability and scoring.

Supports multilayer networks with different variable types.

Abstract

The R package MixMashNet provides an integrated framework for estimating and analyzing single and multilayer networks using Mixed Graphical Models (MGMs), accommodating continuous, count, and categorical variables. In the multilayer setting, layers may comprise different types and numbers of variables, and users can explicitly impose a predefined multilayer topology. Bootstrap procedures are implemented to quantify sampling uncertainty for edge weights and node-level centrality indices. In addition, the package includes tools to assess the stability of node community membership and to compute community scores that summarize the latent dimensions identified through network clustering. MixMashNet also offers interactive Shiny applications to support exploration, visualization, and interpretation of the estimated networks.