Data Representation: Bayesian Approach That's Sparse

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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.1.4 by Gabrielle Weinrott, 8 months ago

Browse source code at

Authors: Gabrielle Weinrott [aut, cre], Brigitte Charnomordic [aut], Benedicte Fontez [aut], Nadine Hilgert [aut], Susan Holmes [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports ade4, coda, MASS, Matrix, rstan, sde

Suggests fda, ggplot2, knitr, parallel, rmarkdown, testthat

See at CRAN