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: 1.1.0
Depends: R (≥ 3.5.0)
Imports: Rcpp, MASS, ggplot2
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: rmarkdown, knitr, RColorBrewer
Published: 2024-05-14
DOI: NA
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:

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

Downloads:

Package source: bliss_1.1.0.tar.gz
Windows binaries: r-devel: bliss_1.1.0.zip, r-release: bliss_1.1.0.zip, r-oldrel: bliss_1.1.0.zip
macOS binaries: r-release (arm64): bliss_1.1.0.tgz, r-oldrel (arm64): bliss_1.1.0.tgz, r-release (x86_64): bliss_1.1.0.tgz, r-oldrel (x86_64): bliss_1.1.0.tgz
Old sources: bliss archive

Linking:

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