Package: LongituRF
Title: Random Forests for Longitudinal Data
Version: 0.9
Authors@R: person(given = "Louis",
           family = "Capitaine",
           role = c("aut", "cre"),
           email = "Louis.capitaine@u-bordeaux.fr",comment = c(ORCID = "0000-0001-6800-2342"))
Description: Random forests are a statistical learning method widely used in many areas of scientific research essentially for its ability to learn complex relationships between input and output variables and also its capacity to handle high-dimensional data. However, current random forests approaches are not flexible enough to handle longitudinal data.  In this package, we propose a general approach of random forests for high-dimensional longitudinal data. It includes a flexible stochastic model which allows the covariance structure to vary over time. Furthermore, we introduce a new method which takes intra-individual covariance into consideration to build random forests. The method is fully detailled in Capitaine et.al. (2020) <doi:10.1177/0962280220946080> Random forests for high-dimensional longitudinal data.
License: GPL-2
Imports: stats, randomForest, rpart, mvtnorm, latex2exp
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-08-25 22:24:05 UTC; capitainelouis
Author: Louis Capitaine [aut, cre] (<https://orcid.org/0000-0001-6800-2342>)
Maintainer: Louis Capitaine <Louis.capitaine@u-bordeaux.fr>
Repository: CRAN
Date/Publication: 2020-08-31 09:10:07 UTC
Built: R 4.6.0; ; 2025-10-14 02:15:59 UTC; windows
