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: | 1.0-1 |
Depends: | R (≥ 2.6) |
Imports: | coda, extremefit |
Published: | 2024-02-16 |
DOI: | 10.32614/CRAN.package.sbde |
Author: | Surya Tokdar |
Maintainer: | Surya Tokdar <surya.tokdar at duke.edu> |
License: | GPL-2 |
NeedsCompilation: | yes |
CRAN checks: | sbde results |
Reference manual: | sbde.pdf |
Package source: | sbde_1.0-1.tar.gz |
Windows binaries: | r-devel: sbde_1.0-1.zip, r-release: sbde_1.0-1.zip, r-oldrel: sbde_1.0-1.zip |
macOS binaries: | r-devel (arm64): sbde_1.0-1.tgz, r-release (arm64): sbde_1.0-1.tgz, r-oldrel (arm64): sbde_1.0-1.tgz, r-devel (x86_64): sbde_1.0-1.tgz, r-release (x86_64): sbde_1.0-1.tgz, r-oldrel (x86_64): sbde_1.0-1.tgz |
Old sources: | sbde archive |
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