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 |
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