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

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0.1.5 by Anne Bisson, a year ago

Browse source code at

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

Documentation:   PDF Manual  

GPL-3 license

Imports ade4, coda, MASS, Matrix, sde

Depends on rstan

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

See at CRAN