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: 1.0.2
Depends: R (≥ 3.3.0)
Imports: Rcpp, MASS, rockchalk
LinkingTo: Rcpp, RcppArmadillo
Suggests: rmarkdown, knitr, RColorBrewer
Published: 2021-05-17
Author: Paul-Marie Grollemund [aut, cre], Isabelle Sanchez [ctr], Meili Baragatti [ctr]
Maintainer: Paul-Marie Grollemund <paul.marie.grollemund at gmail.com>
License: GPL-3
NeedsCompilation: yes
Citation: bliss citation info
Materials: README
CRAN checks: bliss results

Downloads:

Reference manual: bliss.pdf
Vignettes: Introduction to BliSS method
Package source: bliss_1.0.2.tar.gz
Windows binaries: r-devel: bliss_1.0.2.zip, r-devel-UCRT: bliss_1.0.2.zip, r-release: bliss_1.0.2.zip, r-oldrel: bliss_1.0.2.zip
macOS binaries: r-release (arm64): bliss_1.0.2.tgz, r-release (x86_64): bliss_1.0.2.tgz, r-oldrel: bliss_1.0.2.tgz
Old sources: bliss archive

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