Bayesian functional Linear regression with Sparse Step functions (BLiSS)

A method for the Bayesian Functional Linear Regression model (functions-on-scalar), including two estimators of the coefficient function and an estimator of its support. A representation of the posterior distribution is also available.


To install the bliss package, the easiest is to install it directly from GitHub. Open an R session and run the following commands:

install_github("pmgrollemund/bliss", build_vignettes=TRUE)


Once the package is installed on your computer, it can be loaded into a R session:



As a lot of time and effort were spent in creating the bliss method, please cite it when using it for data analysis:

Grollemund, Paul-Marie; Abraham, Christophe; Baragatti, Meïli; Pudlo, Pierre. Bayesian Functional Linear Regression with Sparse Step Functions. Bayesian Anal. 14 (2019), no. 1, 111--135. doi:10.1214/18-BA1095.

You should also cite the bliss package:


See also citation() for citing R itself.

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bliss documentation built on May 17, 2021, 5:07 p.m.