FMM: An R Package for Modeling Rhythmic Patterns in Oscillatory Systems

This paper is dedicated to the R package FMM which implements a novel approach to describe rhythmic patterns in oscillatory signals. The frequency modulated Möbius (FMM) model is defined as a parametric signal plus a Gaussian noise, where the signal can be described as a single or a sum of waves. The FMM approach is flexible enough to describe a great variety of rhythmic patterns. The FMM package includes all required functions to fit and explore single and multi-wave FMM models, as well as a restricted version that allows equality constraints between parameters representing a priori knowledge about the shape to be included. Moreover, the FMM package can generate synthetic data and visualize the results of the fitting process. The potential of this methodology is illustrated with examples of such biological oscillations as the circadian rhythm in gene expression, the electrical activity of the heartbeat and the neuronal activity.

Itziar Fernández (Department of Statistics and Operations Research) , Alejandro Rodríguez-Collado (Department of Statistics and Operations Research) , Yolanda Larriba (Department of Statistics and Operations Research) , Adrián Lamela (Department of Statistics and Operations Research) , Christian Canedo (Department of Statistics and Operations Research) , Cristina Rueda (Department of Statistics and Operations Research)
2022-06-21

Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2022-015.zip

References

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Citation

For attribution, please cite this work as

Fernández, et al., "The R Journal: FMM: An R Package for Modeling Rhythmic Patterns in Oscillatory Systems", The R Journal, 2022

BibTeX citation

@article{RJ-2022-015,
  author = {Fernández, Itziar and Rodríguez-Collado, Alejandro and Larriba, Yolanda and Lamela, Adrián and Canedo, Christian and Rueda, Cristina},
  title = {The R Journal: FMM: An R Package for Modeling Rhythmic Patterns in Oscillatory Systems},
  journal = {The R Journal},
  year = {2022},
  note = {https://doi.org/10.32614/RJ-2022-015},
  doi = {10.32614/RJ-2022-015},
  volume = {14},
  issue = {1},
  issn = {2073-4859},
  pages = {361-380}
}