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:	1.0-0
Depends:	R (≥ 2.6)
Imports:	coda, extremefit
Published:	2022-10-03
Author:	Surya Tokdar
Maintainer:	Surya Tokdar <surya.tokdar at duke.edu>
License:	GPL-2
NeedsCompilation:	yes
CRAN checks:	sbde results

Documentation:

Reference manual:

sbde.pdf

Downloads:

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

Linking:

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