Package: DrBats
Type: Package
Title: Data Representation: Bayesian Approach That's Sparse
Version: 0.1.6
Authors@R: c(
  person("Gabrielle", "Weinrott", email = "gabrielle.weinrott@supagro.inra.fr", role = "aut"),
  person("Brigitte", "Charnomordic", email = "bch@supagro.inra.fr", role = "ctr"),
  person("Benedicte", "Fontez", email = "benedicte.fontez@supagro.fr", role = c("cre", "aut")),
  person("Nadine", "Hilgert", email = "nadine.hilgert@inrae.fr", role = "ctr"),
  person("Susan", "Holmes", email = "susan@stat.stanford.edu", role = "ctr"),
  person("Isabelle", "Sanchez", email = "isabelle.sanchez@inrae.fr", role = "ctr"))
Maintainer: Benedicte Fontez <benedicte.fontez@supagro.fr>
Description: Feed longitudinal data into a Bayesian Latent Factor Model
        to obtain a low-rank representation. Parameters are estimated
        using a Hamiltonian Monte Carlo algorithm with STAN. See G.
        Weinrott, B. Fontez, N. Hilgert and S. Holmes, "Bayesian Latent
        Factor Model for Functional Data Analysis", Actes des JdS 2016.
Depends: R (>= 3.1.0), rstan
Imports: ade4, coda, MASS, Matrix, sde
License: GPL-3
Encoding: UTF-8
LazyData: TRUE
Suggests: fda, ggplot2, knitr, parallel, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Author: Gabrielle Weinrott [aut], Brigitte Charnomordic [ctr],
        Benedicte Fontez [cre, aut], Nadine Hilgert [ctr], Susan Holmes
        [ctr], Isabelle Sanchez [ctr]
RoxygenNote: 7.1.2
Packaged: 2026-07-16 08:16:48 UTC; root
Config/pak/sysreqs: make
Repository: https://bfontez.r-universe.dev
Date/Publication: 2022-02-13 18:00:12 UTC
RemoteUrl: https://github.com/cran/DrBats
RemoteRef: HEAD
RemoteSha: 3a09e1e0e1ec581a00bb59cd3a0891be499d030e