{"id":"W2952373856","doi":"10.48550/arxiv.1405.2105","title":"Hybrid Copula Estimators","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ruhr-Universität Bochum; Fédération Wallonie-Bruxelles; McGill University","keywords":"Copula (linguistics); Estimator; Marginal distribution; Mathematics; Empirical distribution function; Cumulative distribution function; Joint probability distribution; Econometrics; Statistics; Applied mathematics; Probability density function; Random variable","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005351415,0.001189309,0.001422433,0.002810517,0.0004094152,0.00214716,0.002061394,0.001408447,0.004329354],"category_scores_gemma":[0.01633915,0.0005699312,0.001250802,0.002476148,0.0008571334,0.002947239,0.002610111,0.001451451,0.001281337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006631647,"about_ca_system_score_gemma":0.0005760238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008014457,"about_ca_topic_score_gemma":0.0006319161,"domain_scores_codex":[0.9971806,0.001284614,0.0001253974,0.0005135848,0.0007440675,0.000151815],"domain_scores_gemma":[0.993439,0.003531632,0.0005694045,0.001201612,0.001091904,0.0001663979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001699011,0.0001421743,0.004773116,0.0003666209,0.000534882,0.0002991903,0.0001785699,0.2399176,0.007010307,0.4177133,0.006277338,0.322617],"study_design_scores_gemma":[0.00001915444,0.00005542303,0.001030385,0.00005110378,0.00006016968,0.0002390598,0.00002244174,0.8713026,0.001742945,0.1191029,0.006340874,0.0000329053],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002963802,0.0003264418,0.9953152,0.00005225256,0.00003048097,0.00002007659,0.00004824416,0.0001696495,0.001073802],"genre_scores_gemma":[0.2830889,0.0009287988,0.7091461,0.0002385008,0.0002769348,0.0002466404,0.0004861562,0.000336087,0.005251864],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005351415,"threshold_uncertainty_score":0.0283013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1521070751415411,"score_gpt":0.2630957524177751,"score_spread":0.110988677276234,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}