sindyr: Sparse Identification of Nonlinear Dynamics

This implements the Brunton et al (2016; PNAS <doi:10.1073/pnas.1517384113>) sparse identification algorithm for finding ordinary differential equations for a measured system from raw data (SINDy). The package includes a set of additional tools for working with raw data, with an emphasis on cognitive science applications (Dale and Bhat, in press <doi:10.1016/j.cogsys.2018.06.020>).

Version: 0.2.3
Depends: R (≥ 3.4), arrangements, matrixStats, igraph, graphics, grDevices
Imports: crqa, plot3D, pracma
Published: 2020-06-09
Author: Rick Dale and Harish S. Bhat
Maintainer: Rick Dale <racdale at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: sindyr results

Documentation:

Reference manual: sindyr.pdf

Downloads:

Package source: sindyr_0.2.3.tar.gz
Windows binaries: r-devel: sindyr_0.2.3.zip, r-release: sindyr_0.2.3.zip, r-oldrel: sindyr_0.2.3.zip
macOS binaries: r-release (arm64): sindyr_0.2.3.tgz, r-oldrel (arm64): sindyr_0.2.3.tgz, r-release (x86_64): sindyr_0.2.3.tgz, r-oldrel (x86_64): sindyr_0.2.3.tgz
Old sources: sindyr archive

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