fitlandr

fitlandr-package

<img src="figures/logo.png?package=fitlandr&version=0.1.1" style="float: right" alt="logo" width="120">
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 &amp; Moloche (2018) tools:::Rd_expr_doi("10.1017/S0266466617000305") and the Sparse Vector Field Consensus (SparseVFC) algorithm by Ma et al. (2013) tools:::Rd_expr_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) tools:::Rd_expr_doi("10.31234/osf.io/pzva3"), or the Bhattacharya et al. (2011) method for path integration tools:::Rd_expr_doi("10.1186/1752-0509-5-85").

internal

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

Fit Vector Fields and Potential Landscapes from Intensive
Longitudinal Data

fitlandr-package function

Maintainer: Jingmeng Cui <a href="/link/jingmeng.cui%40outlook.com?package=fitlandr&version=0.1.1" data-mini-rdoc="fitlandr::jingmeng.cui@outlook.com">jingmeng.cui@outlook.com</a> (<a href="https://orcid.org/0000-0003-3421-8457">ORCID</a>)

Author

<img src='figures/logo.png' style='float: right' alt='logo' width='120' />
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 &amp; Moloche (2018) tools:::Rd_expr_doi("10.1017/S0266466617000305") and the Sparse Vector Field Consensus (SparseVFC) algorithm by Ma et al. (2013) tools:::Rd_expr_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) tools:::Rd_expr_doi("10.31234/osf.io/pzva3"), or the Bhattacharya et al. (2011) method for path integration tools:::Rd_expr_doi("10.1186/1752-0509-5-85").

fitlandr: Fit Vector Fields and Potential Landscapes from Intensive Longitudinal Data — fitlandr-package

Maintainer: Jingmeng Cui <a href='mailto:jingmeng.cui@outlook.com'>jingmeng.cui@outlook.com</a> (<a href='https://orcid.org/0000-0003-3421-8457'>ORCID</a>)

fitlandr-package: fitlandr: Fit Vector Fields and Potential Landscapes from Intensive Longitudinal Data

Description

Arguments

Author

See Also