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: 1.0.4
Depends: R (≥ 3.3.0)
Imports: Rcpp, RcppArmadillo, MASS
LinkingTo: Rcpp, RcppArmadillo
Suggests: rmarkdown, knitr, RColorBrewer
Published: 2022-02-16
Author: Paul-Marie Grollemund [aut, cre], Isabelle Sanchez [ctr], Meili Baragatti [ctr]
Maintainer: Paul-Marie Grollemund <paul.marie.grollemund at>
License: GPL-3
NeedsCompilation: yes
Citation: bliss citation info
Materials: README NEWS
CRAN checks: bliss results


Reference manual: bliss.pdf
Vignettes: Introduction to BliSS method


Package source: bliss_1.0.4.tar.gz
Windows binaries: r-prerel:, r-release:, r-oldrel:
macOS binaries: r-prerel (arm64): bliss_1.0.4.tgz, r-release (arm64): bliss_1.0.4.tgz, r-oldrel (arm64): bliss_1.0.4.tgz, r-prerel (x86_64): bliss_1.0.4.tgz, r-release (x86_64): bliss_1.0.4.tgz
Old sources: bliss archive


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