This repository contains the source codes of the FMM R package which implements the core of the FMM approach.
The FMM (Frequency Modulated Möbius) model is a nonlinear parametric regression model designed to analyze nearly periodic, non-sinusoidal physiological time series, extracting key features encoded in time-varying oscillatory morphology. This method decomposes signals into harmonic functions, known as Möbius waves, which are characterized by four physiologically interpretable parameters: amplitude ( $A$ ), location ( $\alpha$ ), width/sharpness ( $\omega$ ), and direction/symmetry ( $\beta$ ).
The FMM approach has demonstrated its effectiveness across various fields, including cardiology, neuroscience, and circadian biology, among many others. Readers may refer to [1-3] for further details.
The FMM R package provides a collection of well-documented functions to fit and explore single, multi-component, and restricted FMM models in the programming language R.
# Can be installed directly from CRAN
install.packages("FMM")
# Or the development version from GitHub:
# install.packages("devtools")
devtools::install_github("FMMGroupVa/FMM")
To get acquainted with some of the important functions, read the vignette:
# Overview of the package
vignette("FMMVignette", package = "FMM")
[1] Rueda, C., Larriba, Y., & Peddada, S. D. (2019). Frequency modulated möbius model accurately predicts rhythmic signals in biological and physical sciences. Scientific reports, 9(1), 18701.
[2] Rueda, C., Rodríguez-Collado, A., & Larriba, Y. (2021). A novel wave decomposition for oscillatory signals. IEEE Transactions on Signal Processing, 69, 960-972.
[3] Rueda, C., Larriba, Y., & Lamela, A. (2021). The hidden waves in the ECG uncovered revealing a sound automated interpretation method. Scientific reports, 11(1), 3724.
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