bliss: Bayesian Functional Linear Regression with Sparse Step Functions
A method for the Bayesian functional linear regression model (scalar-on-function),
including two estimators of the coefficient function and an estimator of its support.
A representation of the posterior distribution is also available. Grollemund P-M., Abraham C.,
Baragatti M., Pudlo P. (2019) <doi:10.1214/18-BA1095>.
| Version: |
1.1.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp, MASS, ggplot2, RcppArmadillo |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppProgress |
| Suggests: |
rmarkdown, knitr, RColorBrewer |
| Published: |
2024-07-17 |
| DOI: |
10.32614/CRAN.package.bliss |
| Author: |
Paul-Marie Grollemund [aut, cre],
Isabelle Sanchez [ctr],
Meili Baragatti [ctr] |
| Maintainer: |
Paul-Marie Grollemund <paul_marie.grollemund at uca.fr> |
| BugReports: |
https://github.com/pmgrollemund/bliss/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/pmgrollemund/bliss |
| NeedsCompilation: |
yes |
| Citation: |
bliss citation info |
| Materials: |
README NEWS |
| CRAN checks: |
bliss results |
Documentation:
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