find_eqs

Find equilibrium points for a vector field

A toolbox for estimating vector fields from intensive
longitudinal data, and construct potential landscapes thereafter. The
vector fields can be estimated with two nonparametric methods: the
Multivariate Vector Field Kernel Estimator (MVKE) by Bandi & Moloche
(2018) <doi:10.1017/S0266466617000305> and the Sparse Vector Field
Consensus (SparseVFC) algorithm by Ma et al. (2013)
<doi:10.1016/j.patcog.2013.05.017>. The potential landscapes can be
constructed with a simulation-based approach with the 'simlandr'
package (Cui et al., 2021) <doi:10.31234/osf.io/pzva3>, or the
Bhattacharya et al. (2011) method for path integration
<doi:10.1186/1752-0509-5-85>.

Jingmeng Cui

fitlandr

Fit Vector Fields and Potential Landscapes from Intensive
Longitudinal Data

find_eqs function

<dl><dt>vf</dt>
<dd>A <code>vectorfield</code> object estimated by <code>fit_2d_vf()</code>.</dd>
<dt>starts</dt>
<dd>A vector indicating the starting value for solving the equilibrium point, or a list of vectors providing multiple starting values together.</dd>
<dt>jacobian_params</dt>
<dd>Parameters passed to <code><a href="/link/numDeriv%3A%3Ajacobian()?package=fitlandr&version=0.1.1" data-mini-rdoc="fitlandr::numDeriv::jacobian()">numDeriv::jacobian()</a></code>.</dd>
<dt>...</dt>
<dd>Parameters passed to <code>rootSolve::multiroot()</code>.</dd></dl>

Arguments

Find equilibrium points for a vector field — find_eqs

<dl>

<dt>vf</dt>
<dd>A <code>vectorfield</code> object estimated by <code>fit_2d_vf()</code>.</dd>


<dt>starts</dt>
<dd>A vector indicating the starting value for solving the equilibrium point, or a list of vectors providing multiple starting values together.</dd>


<dt>jacobian_params</dt>
<dd>Parameters passed to <code><a href='https://rdrr.io/pkg/numDeriv/man/jacobian.html'>numDeriv::jacobian()</a></code>.</dd>


<dt>...</dt>
<dd>Parameters passed to <code>rootSolve::multiroot()</code>.</dd>

</dl>

find_eqs: Find equilibrium points for a vector field

Description

Usage

Value

Arguments