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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>.

Versions across snapshots

VersionRepositoryFileSize
1.0-2 rolling linux/jammy R-4.5 sbde_1.0-2.tar.gz 93.7 KiB
1.0-2 rolling linux/noble R-4.5 sbde_1.0-2.tar.gz 94.2 KiB
1.0-2 rolling source/ R- sbde_1.0-2.tar.gz 20.5 KiB
1.0-2 latest linux/jammy R-4.5 sbde_1.0-2.tar.gz 93.7 KiB
1.0-2 latest linux/noble R-4.5 sbde_1.0-2.tar.gz 94.2 KiB
1.0-2 latest source/ R- sbde_1.0-2.tar.gz 20.5 KiB
1.0-2 2026-04-26 source/ R- sbde_1.0-2.tar.gz 20.5 KiB
1.0-2 2026-04-23 source/ R- sbde_1.0-2.tar.gz 20.5 KiB
1.0-2 2026-04-09 windows/windows R-4.5 sbde_1.0-2.zip 100.4 KiB
1.0-1 2025-04-20 source/ R- sbde_1.0-1.tar.gz 20.6 KiB

Dependencies (latest)

Imports