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:

Reference manual:	bliss.html , bliss.pdf
Vignettes:	Introduction to BliSS method (source, R code)

Downloads:

Package source:	bliss_1.1.1.tar.gz
Windows binaries:	r-devel: bliss_1.1.1.zip, r-release: bliss_1.1.1.zip, r-oldrel: bliss_1.1.1.zip
macOS binaries:	r-release (arm64): bliss_1.1.1.tgz, r-oldrel (arm64): bliss_1.1.1.tgz, r-release (x86_64): bliss_1.1.1.tgz, r-oldrel (x86_64): bliss_1.1.1.tgz
Old sources:	bliss archive

Linking:

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