{"package":"deconvolveR","ecosystem":"cran","latest_version":"1.2-1","description":"Empirical Bayes Estimation Strategies. Empirical Bayes methods for learning prior distributions from data. An unknown prior distribution (g) has yielded (unobservable) parameters, each of which produces a data point from a parametric exponential family (f). The goal is to estimate the unknown prior (\"g-modeling\") by deconvolution and Emp","license":"GPL (>= 2)","license_risk":"unknown","commercial_use_notes":"verify manually — license not parseable / not declared.","homepage":"https://bnaras.github.io/deconvolveR/","repository":"https://CRAN.R-project.org/package=deconvolveR","downloads_weekly":762,"health":{"score":42,"risk":"high","breakdown":{"maintenance":0,"popularity":3,"security":25,"maturity":12,"community":2},"deprecated":false,"max_score":100},"vulnerabilities":{"count":0,"critical":0,"high":0,"medium":0,"low":0,"details":[]},"versions":{"latest":"1.2-1","total_count":0,"recent":[]},"metadata":{"deprecated":false,"deprecated_message":null,"maintainers_count":1,"first_published":"2020-08-30 01:50:32","last_published":"2020-08-30T00:00:26+00:00","dependencies_count":2,"dependencies":["splines","stats"]},"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":"1.2-1","version_hint":null,"summary":"deconvolveR@1.2-1 is safe to use (health: 42/100)"},"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}}