{"package":"bayeslm","ecosystem":"cran","latest_version":"2.0","description":"Efficient Sampling for Gaussian Linear Regression with Arbitrary Priors. Efficient sampling for Gaussian linear regression with arbitrary priors, Hahn, He and Lopes (2018) <doi:10.48550/arXiv.1806.05738>.","license":"LGPL (>= 2)","license_risk":"unknown","commercial_use_notes":"verify manually — license not parseable / not declared.","homepage":"https://github.com/JingyuHe/bayeslm","repository":"https://github.com/JingyuHe/bayeslm","downloads_weekly":134,"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","total_count":0,"recent":[]},"metadata":{"deprecated":false,"deprecated_message":null,"maintainers_count":1,"first_published":"2026-04-03 22:02:32","last_published":"2026-04-03T20:50:26+00:00","dependencies_count":7,"dependencies":["Rcpp","stats","graphics","grDevices","coda","methods","RcppParallel"]},"github_stats":null,"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","version_hint":null,"summary":"bayeslm@2.0 is safe to use (health: 55/100)"},"version_scoped":null,"requested_version":null,"_cache":"miss","_response_ms":792,"_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},"version_history_summary":{"total_versions":1,"first_release_age_days":27,"last_release_days_ago":27,"avg_days_between_releases":null,"release_velocity":"active"}}