Package: DrBats
Type: Package
Title: Data Representation: Bayesian Approach That's Sparse
Version: 0.1.5
Date: 2019-11-15
Authors@R: c(person("Anne", "Bisson", email = "anne.bisson@inra.fr", role = "cre"), person("Gabrielle", "Weinrott", email = "gabrielle.weinrott@supagro.inra.fr", role = "aut"), person("Brigitte", "Charnomordic", email = "bch@supagro.inra.fr", role = "aut"), person("Benedicte", "Fontez", email = "benedicte.fontez@supagro.fr", role = "aut"), person("Nadine", "Hilgert", email = "nadine.hilgert@supagro.inra.fr", role = "aut"), person("Susan", "Holmes", email = "susan@stat.stanford.edu", role = "aut"))
Maintainer: Anne Bisson <anne.bisson@inra.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
LazyData: TRUE
Suggests: fda, ggplot2, knitr, parallel, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 7.0.1
NeedsCompilation: no
Packaged: 2019-11-27 13:35:48 UTC; bissonan
Author: Anne Bisson [cre],
  Gabrielle Weinrott [aut],
  Brigitte Charnomordic [aut],
  Benedicte Fontez [aut],
  Nadine Hilgert [aut],
  Susan Holmes [aut]
Repository: CRAN
Date/Publication: 2019-11-27 15:20:13 UTC
Built: R 4.0.0; ; 2020-04-10 12:16:06 UTC; windows
