AMDconfigurations: Geometric Analysis of Configurations in High-Dimensional Spaces
Tools for analysing the geometry of configurations in high-dimensional
spaces using the Average Membership Degree (AMD) framework and synthetic
configuration generation. The package supports a domain-agnostic approach
to studying the shape, dispersion, and internal structure of point clouds,
with applications across biological and ecological datasets, including
those derived from deep-time records. The AMD framework builds on the idea
that strongly coupled systems may occupy a limited set of recurrent regimes
in state space, producing high-occupancy regions separated by sparsely
populated transitional configurations. The package focuses on detecting
these concentration patterns and quantifying their geometric definition
without assuming any underlying dynamical model. It provides AMD curve
computation, cluster assignment, and sigma-equivalent estimation, together
with S3 methods for plotting, printing, and summarising AMD and
sigma-equivalent objects. Mendoza (2025) <https://mmendoza1967.github.io/AMDconfigurations/>.
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