Semiparametric Bayesian Density Estimation
Overview
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.
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 5 (1 internal)
- Examples that run
- 100%4 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 70%
- Return-value docs
- 100%
- Help pages citing references
- 40%
Downloads
Dependencies
Installing sbde adds 2 packages (0 with compiled code, 4.5 MB of source tarballs). Heaviest: extremefit 4.4 MB, coda 73 KB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 1.0-2Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- unarchivedReturned to CRAN2024-02-17
- 1.0-12024-02-17 · diff ↗
- RR 4.3.0 released · 2023-04-21
- archivedRemoved from CRAN2023-02-11issues were not corrected in time
- 1.0-02022-10-03
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-10-03
- Total releases
- 3 / 4 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 2.6
- Download size
- 21 KB
Cite
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