bayesreg
1.3Bayesian Regression Models with Global-Local Shrinkage Priors
Overview
Fits linear or generalized linear regression models using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Provides an efficient implementation of ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace, Student-t, Poisson or geometric distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <doi:10.48550/arXiv.1611.06649>.
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- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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29 1 exported
Complexity
10.4 avg / 63 max
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29 nodes / 26 edges
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People & History
4 releases. Pick two to compare their code metrics; R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 1.3Latest2024-09-30 · current release
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.22021-03-29 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 1.12019-06-03 · diff ↗
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- 1.02016-11-24
Package metadata
- First published
- 2016-11-24
- Total releases
- 4 / 10 yrs
- License
- GPL (>= 3) OSI
- Download size
- not tracked yet
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