Tools for Additive and Multiplicative Effects (AME) models for both cross-sectional and longitudinal network analysis. The package provides two main functions: 'ame()' for cross-sectional networks and 'lame()' for longitudinal networks. Package supports unipartite (square) and bipartite (rectangular) network structures. Key features include: (1) Cross-sectional network analysis via 'ame()' with support for various data types (binary, continuous, ordinal, count); (2) Longitudinal network analysis via 'lame()' with dynamic effects modeling where both additive (sender/receiver) and multiplicative (latent factor) effects can be chosen to evolve over time via AR(1) processes (Sewell & Chen 2015 <doi:10.1080/01621459.2014.988214>, Durante & Dunson 2014 <doi:10.1093/biomet/asu040>); (3) Handling of changing actor compositions across time periods in longitudinal models; (4) Performance improvements through C++ implementations via Rcpp and RcppArmadillo.