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: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=fitlandr to link to this page.
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