Bayesian Inference with Laplace Approximations and P-Splines

Laplace approximations and penalized B-splines are combined for fast Bayesian inference in latent Gaussian models. The routines can be used to fit survival models, especially proportional hazards and promotion time cure models (Gressani, O. and Lambert, P. (2018) ). The Laplace-P-spline methodology can also be implemented for inference in (generalized) additive models (Gressani, O. and Lambert, P. (2021) ). See the associated website for more information and examples.


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install.packages("blapsr")

0.5.5 by Oswaldo Gressani, 8 days ago


< https://www.blapsr-project.org/>


Browse source code at https://github.com/cran/blapsr


Authors: Oswaldo Gressani [aut, cre] (Author) , Philippe Lambert [aut, ths] (Co-author and thesis advisor)


Documentation:   PDF Manual  


GPL-3 license


Imports coda, graphics, MASS, Matrix, RSpectra, sn, stats, utils

Depends on survival

Suggests knitr, rmarkdown, testthat


See at CRAN