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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, 2018 <doi:10.1016/j.cogsys.2018.06.020>). See <https://github.com/racdale/sindyr> for examples and updates.
Package details |
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Author | Rick Dale and Harish S. Bhat |
Maintainer | Rick Dale <racdale@gmail.com> |
License | GPL (>= 2) |
Version | 0.2.4 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
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