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.
| Version: |
0.6.1 |
| Depends: |
R (≥ 3.6.0), survival (≥ 2.44.1) |
| Imports: |
coda (≥ 0.19.3), graphics (≥ 3.6.0), MASS (≥ 7.3.51), Matrix (≥ 1.2.17), RSpectra (≥ 0.16.0), sn (≥ 1.5.4), stats, utils (≥ 3.6.0) |
| Suggests: |
knitr (≥ 1.26), rmarkdown (≥ 1.14), testthat (≥ 2.3.1) |
| Published: |
2022-08-20 |
| DOI: |
10.32614/CRAN.package.blapsr |
| Author: |
Oswaldo Gressani [aut, cre] (Author),
Philippe Lambert [aut, ths] (Co-author and thesis advisor) |
| Maintainer: |
Oswaldo Gressani <oswaldo_gressani at hotmail.fr> |
| License: |
GPL-3 |
| Copyright: |
see file COPYRIGHTS |
| URL: |
<https://www.blapsr-project.org/> |
| NeedsCompilation: |
no |
| Citation: |
blapsr citation info |
| Materials: |
README NEWS |
| CRAN checks: |
blapsr results |
Documentation:
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