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  "Title": "Geometric Analysis of Configurations in High-Dimensional Spaces",
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  "Description": "Tools for analysing the geometry of configurations in\nhigh-dimensional spaces using the Average Membership Degree\n(AMD) framework and synthetic configuration generation. The\npackage supports a domain-agnostic approach to studying the\nshape, dispersion, and internal structure of point clouds, with\napplications across biological and ecological datasets,\nincluding those derived from deep-time records. The AMD\nframework builds on the idea that strongly coupled systems may\noccupy a limited set of recurrent regimes in state space,\nproducing high-occupancy regions separated by sparsely\npopulated transitional configurations. The package focuses on\ndetecting these concentration patterns and quantifying their\ngeometric definition without assuming any underlying dynamical\nmodel. It provides AMD curve computation, cluster assignment,\nand sigma-equivalent estimation, together with S3 methods for\nplotting, printing, and summarising AMD and sigma-equivalent\nobjects. Mendoza (2025)\n<https://mmendoza1967.github.io/AMDconfigurations/>.",
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  "URL": "https://github.com/mmendoza1967/AMDconfigurations,\nhttps://mmendoza1967.github.io/AMDconfigurations/",
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