Bayesian Inference with Laplace Approximations and P-Splines.
Approximate Bayesian inference with blapsr
Purpose
The blapsr package consists in a set of routines that can be used for analysis in survival models and (generalized) additive models. The methodology is based on the combination of Bayesian P-splines for flexible estimation of smooth functions and Laplace approximations to (selected) posterior distributions.
Version
First version (0.5.1) was published on CRAN 2020-07-13.
This is version 0.6.1 (submitted to CRAN on 2022-08-20).
Website
A website is dedicated to the package: https://www.blapsr-project.org. The link to the CRAN page is https://cran.r-project.org/package=blapsr .
Special thanks
This package was developed during a PhD thesis at Université catholique de Louvain (Belgium) that was funded in part by the Actions de Recherche Concertées (ARC 11/16-039) grant and another grant obtained from the Luxembourgish Ministry of higher education.
We are grateful to Vincent Bremhorst for providing the function on which the simcuredata.R routine is based. The latter is used for generating survival times in the promotion time cure model (Bremhorst and Lambert, 2016).