Network Estimation, Bootstrap, and Higher-Order Analysis // Estimate, compare, and analyze dynamic and psychological networks using a unified interface. Provides transition network analysis estimation (transition, frequency, co-occurrence, attention-weighted) Saqr et al. (2025) doi:10.1145/3706468.3706513, psychological network methods (correlation, partial correlation, 'graphical lasso', 'Ising') Saqr, Beck, and Lopez-Pernas (2024) doi:10.1007/978-3-031-54464-4_19, and higher-order network methods including higher-order networks, higher-order network embedding, hyper-path anomaly, and multi-order generative model. Supports bootstrap inference, permutation testing, split-half reliability, centrality stability analysis, mixed Markov models, multi-cluster multi-layer networks and clustering.