fitlandr: Fit Vector Fields and Potential Landscapes from Intensive
Longitudinal Data
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>.
| Version: |
0.1.0 |
| Imports: |
cli, dplyr, furrr, future.apply, ggplot2, glue, grDevices, grid, magrittr, MASS, numDeriv, plotly, R.utils, Rfast, rlang, rootSolve, simlandr (≥ 0.3.0), SparseVFC, tidyr |
| Suggests: |
akima, colorRamps, future |
| Published: |
2023-02-10 |
| DOI: |
10.32614/CRAN.package.fitlandr |
| Author: |
Jingmeng Cui 
[aut, cre] |
| Maintainer: |
Jingmeng Cui <jingmeng.cui at outlook.com> |
| BugReports: |
https://github.com/Sciurus365/fitlandr/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://sciurus365.github.io/fitlandr/,
https://github.com/Sciurus365/fitlandr |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| In views: |
Psychometrics |
| CRAN checks: |
fitlandr results |
Documentation:
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