CRAN/E | fitlandr

fitlandr

Fit Vector Fields and Potential Landscapes from Intensive Longitudinal Data

Installation

About

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.

sciurus365.github.io/fitlandr/
github.com/Sciurus365/fitlandr
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Key Metrics

Version 0.1.0
Published 2023-02-10 434 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks fitlandr results

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Maintainer

Maintainer

Jingmeng Cui

jingmeng.cui@outlook.com

Authors

Jingmeng Cui

aut / cre

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

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

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