Nothing
blapsr: 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) <doi:10.1016/j.csda.2018.02.007>). The Laplace-P-spline methodology can also be implemented for inference in (generalized) additive models (Gressani, O. and Lambert, P. (2021) <doi:10.1016/j.csda.2020.107088>). See the associated website for more information and examples.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Oswaldo Gressani [aut, cre] (Author), Philippe Lambert [aut, ths] (Co-author and thesis advisor) |
| Maintainer | Oswaldo Gressani <oswaldo_gressani@hotmail.fr> |
| License | GPL-3 |
| Version | 0.6.1 |
| URL | <https://www.blapsr-project.org/> |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the blapsr package in your browser
Any scripts or data that you put into this service are public.
