sindyr: Tools for Sparse Identification of Nonlinear Dynamics with R
sindyr is an R library for inferring ordinary differential equations from raw data, based on SINDy by Brunton et al. (2016). The library also extends this method in several ways, including a sliding window tool that generates descriptive measures of a system from SINDy.
If you use the code, toss us a shout out by citing:
Dale, R. & Bhat, H. S. (2018). Equations of mind: Data science for inferring nonlinear dynamics of socio-cognitive systems. Cognitive Systems Research, 52, 275-290.
Under "dale-bhat-materials," we show several example uses of
sindyr, based on the manuscript cited above. For a quick start, consider perusing the reconstruction of the Lorenz attractor's equations using
sindyr is now available on CRAN:
On occasion this version on GitHub will go out of alignment before we do a CRAN update. If this happens you can install from the repository this way:
sindyr works with R >= 3.4.
sindyr depends on the following packages: arrangements, matrixStats, igraph, and pracma.
Brunton, S. L., Proctor, J. L., & Kutz, J. N. (2016). Discovering governing equations from data by sparse identification of nonlinear dynamical systems. Proceedings of the National Academy of Sciences, 113(15), 3932-3937.