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.