Fit Vector Fields and Potential Landscapes from Intensive Longitudinal Data R package fitlandr version 0.1.1 CRAN Task View: Psychometrics (https://CRAN.R-project.org/view=Psychometrics) 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>. Software Imports: cli, dplyr, furrr, future.apply, ggplot2, glue, grDevices, grid, magrittr, MASS, numDeriv, plotly, purrr, R.utils, Rfast, rlang, rootSolve, simlandr (>= 0.3.0), SparseVFC, tidyr Suggests: akima, colorRamps, future, knitr Jingmeng Cui <jingmeng.cui@outlook.com> Comprehensive R Archive Network (CRAN) Jingmeng Cui [aut, cre] (ORCID: <https://orcid.org/0000-0003-3421-8457>) GPL (>= 3) 2026-01-29 application/tgz https://CRAN.R-project.org/package=fitlandr doi:10.32614/CRAN.package.fitlandr