finite_differences

Estimates first-order derivatives of column vectors of a matrix

misc

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.

Rick Dale

sindyr

Sparse Identification of Nonlinear Dynamics

finite_differences function

<dl> <dt>xs</dt>
<dd>Raw data to be differentiated (matrix)</dd> <dt>S</dt>
<dd>Sample rate of data to return derivatives using raw time</dd>
</dl>

Arguments

Author

Estimate derivatives of multiple variables with finite differences — finite_differences

<dl>

 <dt>xs</dt>
<dd>Raw data to be differentiated (matrix)</dd>

 <dt>S</dt>
<dd>Sample rate of data to return derivatives using raw time</dd>


</dl>

finite_differences: Estimate derivatives of multiple variables with finite differences

Description

Value

Arguments

Author

Details