{"package":"shrinkGPR","ecosystem":"cran","latest_version":"2.0.0","description":"Scalable Gaussian Process Regression with Hierarchical Shrinkage Priors. Efficient variational inference methods for fully Bayesian univariate and multivariate Gaussian and t-process regression models. Hierarchical shrinkage priors, including the triple gamma prior, are used for effective variable selection and covariance shrinkage in high-dimensional settings. The packa","license":"GPL (>= 2)","license_risk":"unknown","commercial_use_notes":"verify manually — license not parseable / not declared.","homepage":"https://cran.r-project.org/package=shrinkGPR","repository":"https://CRAN.R-project.org/package=shrinkGPR","downloads_weekly":137,"health":{"score":55,"risk":"high","breakdown":{"maintenance":25,"popularity":3,"security":25,"maturity":0,"community":2},"deprecated":false,"max_score":100},"vulnerabilities":{"count":0,"critical":0,"high":0,"medium":0,"low":0,"details":[]},"versions":{"latest":"2.0.0","total_count":0,"recent":[]},"metadata":{"deprecated":false,"deprecated_message":null,"maintainers_count":1,"first_published":"2026-03-30 15:53:30","last_published":"2026-03-30T13:10:03+00:00","dependencies_count":7,"dependencies":["gsl","progress","rlang","utils","methods","torch","mniw"]},"bundle":null,"typescript":null,"known_issues":{"bugs_count":0,"bugs_severity":{},"status_breakdown":{},"link":null,"scope":"none"},"historical_compromise":null,"recommendation":{"action":"safe_to_use","issues":[],"use_version":"2.0.0","version_hint":null,"summary":"shrinkGPR@2.0.0 is safe to use (health: 55/100)"},"version_scoped":null,"requested_version":null,"_cache":"hit","_response_ms":0,"_powered_by":"depscope.dev — free package intelligence for AI agents","typosquat":{"is_suspected":false},"maintainer_trust":{"available":false},"malicious":{"is_malicious":false},"scorecard":{"available":false},"quality":{"available":false}}