{"package":"r-adaptgauss","ecosystem":"conda","latest_version":"1.6","description":"Multimodal distributions can be modelled as a mixture of components. The model is derived using the Pareto Density Estimation (PDE) for an estimation of the pdf. PDE has been designed in particular to identify groups/classes in a dataset. Precise limits for the classes can be calculated using the theorem of Bayes. Verification of the model is possible by QQ plot, Chi-squared test and Kolmogorov-Smirnov test. The package is based on the publication of Ultsch, A., Thrun, M.C., Hansen-Goos, O., Lotsch, J. (2015)  <DOI:10.3390/ijms161025897>.","license":"GPL-3.0-only","license_risk":"unknown","commercial_use_notes":"verify manually — license not parseable / not declared.","homepage":"https://www.deepbionics.org","repository":"","downloads_weekly":144,"health":{"score":49,"risk":"high","breakdown":{"maintenance":10,"popularity":3,"security":25,"maturity":9,"community":2},"deprecated":false,"max_score":100},"vulnerabilities":{"count":0,"critical":0,"high":0,"medium":0,"low":0,"details":[]},"versions":{"latest":"1.6","total_count":2,"recent":["1.5.6","1.6"]},"metadata":{"deprecated":false,"deprecated_message":null,"maintainers_count":1,"first_published":"2021-06-03 07:10:41.565000+00:00","last_published":"2025-10-01 01:18:05.266000+00:00","dependencies_count":0,"dependencies":[]},"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":"use_with_caution","issues":["Moderate health score (49/100) — verify manually"],"use_version":"1.6","version_hint":null,"summary":"r-adaptgauss@1.6 low health (49/100) — consider alternatives"},"version_scoped":null,"_meta":{"endpoint":"check","tier":"full","philosophy":"DepScope is free. Use the cheapest endpoint that answers your real question.","cheaper_alternatives":[{"endpoint":"/api/exists/conda/r-adaptgauss","tokens_estimated":12,"use_when":"you only need to know if the package exists (hallucination guard)"},{"endpoint":"/api/health/conda/r-adaptgauss","tokens_estimated":80,"use_when":"you only need a 0-100 score for go/no-go (>=70 = safe)"},{"endpoint":"/api/prompt/conda/r-adaptgauss","tokens_estimated":280,"use_when":"you want a plain-text LLM-friendly brief instead of JSON"},{"endpoint":"POST /api/check_bulk","tokens_estimated":60,"use_when":"you have 5+ packages to check; sends one round-trip instead of N"}],"docs":"https://depscope.dev/integrate"},"requested_version":null,"_cache":"miss","_response_ms":532,"_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":2,"first_release_age_days":1796,"last_release_days_ago":216,"avg_days_between_releases":1796,"release_velocity":"moderate"}}