{"package":"varbvs","ecosystem":"cran","latest_version":"2.6-10","description":"Large-Scale Bayesian Variable Selection Using Variational Methods. Fast algorithms for fitting Bayesian variable selection models and computing Bayes factors, in which the outcome (or response variable) is modeled using a linear regression or a logistic regression. The algorithms are based on the variational approximations described in \"Scalable variational inferen","license":"GPL (>= 3)","license_risk":"unknown","commercial_use_notes":"verify manually — license not parseable / not declared.","homepage":"https://github.com/pcarbo/varbvs","repository":"https://github.com/pcarbo/varbvs","downloads_weekly":99,"health":{"score":34,"risk":"critical","breakdown":{"maintenance":0,"popularity":0,"security":25,"maturity":6,"community":3},"deprecated":false,"max_score":100},"vulnerabilities":{"count":0,"critical":0,"high":0,"medium":0,"low":0,"details":[]},"versions":{"latest":"2.6-10","total_count":0,"recent":[]},"metadata":{"deprecated":false,"deprecated_message":null,"maintainers_count":1,"first_published":"2023-05-31 19:09:23","last_published":"2023-05-31T17:30:02+00:00","dependencies_count":8,"dependencies":["methods","Matrix","stats","graphics","lattice","latticeExtra","Rcpp","nor1mix"]},"bundle":null,"typescript":null,"known_issues":{"bugs_count":0,"bugs_severity":{},"status_breakdown":{},"link":null,"scope":"none"},"historical_compromise":null,"recommendation":{"action":"use_with_caution","issues":["Low health score (34/100)"],"use_version":"2.6-10","version_hint":null,"summary":"varbvs@2.6-10 low health (34/100) — consider alternatives"},"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}}