funMoDisco 1.0.0

Initial CRAN Release

Features

• Motif Discovery in Functional Data:
  • ProbKMA: Implements a probabilistic K-means algorithm that leverages local alignment and fuzzy clustering to discover recurring patterns (functional motifs) within and across curves.
    • Capable of handling diverse motifs through a family of distances and normalization techniques.
    • Learns motif lengths in a data-driven manner and supports local clustering for misaligned data.
  • FunBIalign: Provides hierarchical agglomerative clustering using the Mean Squared Residue Score for motif identification of specified lengths in functional data.
    • Offers a more deterministic approach with user-tunable parameters for control over motif detection.
• Simulation Tools: Includes functions to simulate functional data embedded with motifs, enabling users to create benchmark datasets for validating and comparing motif discovery methods.

Additional Notes

• Authors: Marzia Angela Cremona, Francesca Chiaromonte, Jacopo Di Iorio, Niccolo Feresini, Riccardo Lazzarini.
• License: GPL (>= 2).
• System Requirements: C++20.