normalize_predict_f

Return a normalized prediction function

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

normalize_predict_f function

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

Arguments

Return a normalized prediction function — normalize_predict_f

<dl>

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

</dl>

normalize_predict_f: Return a normalized prediction function

Description

Usage

Value

Arguments