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.
Department of Statistics and Operations Research
Department of Statistics and Operations Research
Department of Statistics and Operations Research
Department of Statistics and Operations Research
June 20, 2022
Sep 6, 2021
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2022-015.zip
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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}
}