DrBats: Data Representation: Bayesian Approach That's Sparse (original) (raw)
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.
| Version: | 0.1.6 |
|---|---|
| Depends: | R (≥ 3.1.0), rstan |
| Imports: | ade4, coda, MASS, Matrix, sde |
| Suggests: | fda, ggplot2, knitr, parallel, rmarkdown, testthat |
| Published: | 2022-02-13 |
| DOI: | 10.32614/CRAN.package.DrBats |
| Author: | Gabrielle Weinrott [aut], Brigitte Charnomordic [ctr], Benedicte Fontez [cre, aut], Nadine Hilgert [ctr], Susan Holmes [ctr], Isabelle Sanchez [ctr] |
| Maintainer: | Benedicte Fontez <benedicte.fontez at supagro.fr> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | DrBats results |
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