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fitlandr: Fit Vector Fields and Potential Landscapes from IntensiveLongitudinal 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 CuiORCID iD [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:

Reference manual:fitlandr.html ,fitlandr.pdf

Downloads:

Package source: fitlandr_0.1.0.tar.gz
Windows binaries: r-devel:fitlandr_0.1.0.zip, r-release:fitlandr_0.1.0.zip, r-oldrel:fitlandr_0.1.0.zip
macOS binaries: r-release (arm64):fitlandr_0.1.0.tgz, r-oldrel (arm64):fitlandr_0.1.0.tgz, r-release (x86_64):fitlandr_0.1.0.tgz, r-oldrel (x86_64):fitlandr_0.1.0.tgz

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