Package: UpDown
Type: Package
Title: Detecting Group Disturbances from Longitudinal Observations
Version: 1.2.3
Description: Provides an algorithm to detect and characterize
        disturbances (start, end dates, intensity) that can occur at
        different hierarchical levels by studying the dynamics of
        longitudinal observations at the unit level and group level
        based on Nadaraya-Watson's smoothing curves, but also a shiny
        app which allows to visualize the observations and the detected
        disturbances. Finally the package provides a dataframe
        mimicking a pig farming system subsected to disturbances
        simulated according to Le et al.(2022)
        <doi:10.1016/j.animal.2022.100496>.
Authors@R: c(
    person("Tom", "Rohmer",, "tom.rohmer@inrae.fr", role = c("aut", "cre")),
    person("Vincent", "Le",, "giang-nam.le@inrae.fr", role = "aut"),
    person("Ingrid", "David",, "Ingrid.david@inrae.fr",role = "aut")
    )
License: GPL (>=3)
Encoding: UTF-8
LazyDataCompression: xz
Imports: stats, mixtools, mclust, dplyr,tidyr, ggplot2, shiny
Depends: R (>= 4.0.0)
LazyData: true
Author: Tom Rohmer [aut, cre], Vincent Le [aut], Ingrid David [aut]
Maintainer: Tom Rohmer <tom.rohmer@inrae.fr>
RoxygenNote: 7.3.2
Config/pak/sysreqs: cmake make libicu-dev libuv1-dev libssl-dev
        zlib1g-dev
Repository: https://tomrohmer.r-universe.dev
Date/Publication: 2025-08-28 13:47:44 UTC
RemoteUrl: https://github.com/tomrohmer/updown
RemoteRef: HEAD
RemoteSha: 3d8f71042ded9460992fe67ac0eaddc01f8369ab
NeedsCompilation: no
Packaged: 2026-07-16 04:57:38 UTC; root