shrinkem
cranv0.2.0Approximate Bayesian Regularization for Parsimonious Estimates. Approximate Bayesian regularization using Gaussian approximations. The input is a vector of estimates and a Gaussian error covariance matrix of the key parameters. Bayesian shrinkage is then applied to obtain parsimonious solutions. The method is described on Karimova, van Erp, Leenders, and Mulder
License GPL (>= 3)0 versions1 maintainers6 deps68 weekly dl
https://CRAN.R-project.org/package=shrinkem38
/ 100
Health
use with caution
[email protected] low health (38/100) — consider alternatives
- Low health score (38/100)
Health breakdown0 – 100
5/25
maintenance
0/20
popularity
25/25
security
6/15
maturity
2/15
community
Vulnerabilities
0
none known
Health History
Dependency Tree
License Audit
Dependencies (6)
API access
Get this data programmatically — free, no authentication.
curl https://depscope.dev/api/check/cran/shrinkemFirst published · 2024-10-05 10:47:08
Last updated · 2024-10-05T09:20:03+00:00