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BSCB  

Bayesian Simultaneous Credible Bands for Polynomial Regression
View on CRAN: Click here


Download and install BSCB package within the R console
Install from CRAN:
install.packages("BSCB")

Install from Github:
library("remotes")
install_github("cran/BSCB")

Install by package version:
library("remotes")
install_version("BSCB", "1.0.1")



Attach the package and use:
library("BSCB")
Maintained by
Fei Yang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-13
Latest Update: 2026-07-13
Description:
Provides functions to construct two-sided Bayesian simultaneous credible bands (BSCBs) for the regression curve in univariate polynomial regression over a finite covariate interval. Six methods are implemented, including Normal-Gamma conjugate priors (with empirical Bayes, unit-information, and g-prior hyperparameter specifications), non-conjugate priors fitted via Hamiltonian Monte Carlo (HMC) using 'cmdstanr', and a non-informative independent Jeffreys prior approach. Also includes functions for computing the empirical simultaneous coverage rate (ESCR) and posterior simultaneous coverage probability (PSCP), enabling performance comparison across methods. The methodology is described in: Yang, F., Han, Y., Liu, W., & Hall, I. (2026). "Bayesian simultaneous credible bands for polynomial regression" <doi:10.48550/arXiv.2606.28015>.
How to cite:
Fei Yang (2026). BSCB: Bayesian Simultaneous Credible Bands for Polynomial Regression. R package version 1.0.1, https://cran.r-project.org/web/packages/BSCB. Accessed 29 Sep. 2026.
Previous versions and publish date:
1.0.0 (2026-07-10 22:10), 1.0.1 (2026-07-13 09:10), (2026-07-23 18:50)
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Complete documentation for BSCB
Functions, R codes and Examples using the BSCB R package
Full BSCB package functions and examples
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