sbde: Semiparametric Bayesian Density Estimation

Offers Bayesian semiparametric density estimation and tail-index estimation for heavy tailed data, by using a parametric, tail-respecting transformation of the data to the unit interval and then modeling the transformed data with a purely nonparametric logistic Gaussian process density prior. Based on Tokdar et al. (2022) <doi:10.1080/01621459.2022.2104727>.

Version: 1.0-2
Depends: R (≥ 2.6)
Imports: coda, extremefit
Published: 2025-09-24
DOI: 10.32614/CRAN.package.sbde
Author: Surya Tokdar [aut, cre]
Maintainer: Surya Tokdar <surya.tokdar at duke.edu>
License: GPL-2
NeedsCompilation: yes
CRAN checks: sbde results

Documentation:

Reference manual: sbde.html , sbde.pdf

Downloads:

Package source: sbde_1.0-2.tar.gz
Windows binaries: r-devel: sbde_1.0-2.zip, r-release: sbde_1.0-2.zip, r-oldrel: sbde_1.0-2.zip
macOS binaries: r-release (arm64): sbde_1.0-2.tgz, r-oldrel (arm64): sbde_1.0-2.tgz, r-release (x86_64): sbde_1.0-2.tgz, r-oldrel (x86_64): sbde_1.0-2.tgz
Old sources: sbde archive

Linking:

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