Changes in version 1.0.0 (2025-04-15)                  

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.