Package: sbde 1.0-1
Surya Tokdar
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>.
Authors:
sbde_1.0-1.tar.gz
sbde_1.0-1.tar.gz(r-4.5-noble)sbde_1.0-1.tar.gz(r-4.4-noble)
sbde_1.0-1.tgz(r-4.4-emscripten)sbde_1.0-1.tgz(r-4.3-emscripten)
sbde.pdf |sbde.html✨
sbde/json (API)
| # Install 'sbde' in R: |
| install.packages('sbde', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 10 months agofrom:488fb2a5f3. Checks:OK: 1 NOTE: 1. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 13 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 13 2024 |
Exports:sbde
Dependencies:codaextremefitlattice
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Coefficient Extraction from sbde Model Fit | coef.sbde |
| Posterior predictive Summary for Semiparametric Density Estimation | predict.sbde |
| Bayesian Semiparametric Density Estimation | sbde update.sbde |
| Summary Method for Semiparametric Density Estimation | summary.sbde |