Package: FREEtree Type: Package Title: Tree Method for High Dimensional Longitudinal Data Version: 0.1.0 Authors@R: c( person("Yuancheng", "Xu", email = "xuyuancheng0@gmail.com", role = c("aut")), person("Athanasse", "Zafirov", email = "zafirov@gmail.com", role = c("cre")), person("Christina", "Ramirez", email = "cr@ucla.edu", role = c("aut")), person("Dan", "Kojis", email = "x@xxx.edu", role = c("aut")), person("Min", "Tan", email = "xx@xxx.edu", role = c("aut")), person("Mike", "Alvarez", email = "rma@hss.caltech.edu", role = c("aut"))) Description: A tree-based method for high dimensional longitudinal data with correlated features. 'FREEtree' deals with longitudinal data by using a piecewise random effect model. It also exploits the network structure of the features, by first clustering them using Weighted Gene Co-expression Network Analysis ('WGCNA'). It then conducts a screening step within each cluster of features and a selecting step among the surviving features, which provides a relatively unbiased way to do feature selection. By using dominant principle components as regression variables at each leaf and the original features as splitting variables at splitting nodes, 'FREEtree' maintains 'interpretability' and improves computational efficiency. Depends: R (>= 3.5.0) License: GPL-3 Encoding: UTF-8 LazyData: true Imports: glmertree, pre, WGCNA, MASS RoxygenNote: 7.1.0 Suggests: knitr, rmarkdown, testthat (>= 2.1.0) Config/pak/sysreqs: cmake make libicu-dev libuv1-dev Repository: https://adzafirov.r-universe.dev Date/Publication: 2020-06-16 17:33:29 UTC RemoteUrl: https://github.com/adzafirov/freetree RemoteRef: HEAD RemoteSha: c4c0ad138de516d6b92fb287f559dc056fabb752 NeedsCompilation: no Packaged: 2026-10-20 09:51:33 UTC; root Author: Yuancheng Xu [aut], Athanasse Zafirov [cre], Christina Ramirez [aut], Dan Kojis [aut], Min Tan [aut], Mike Alvarez [aut] Maintainer: Athanasse Zafirov