{"id":"W3122586527","doi":"","title":"Asymptotic properties of the Bernstein density copula estimator for alpha-mixing data","year":2010,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Copula (linguistics); Estimator; Mathematics; Asymptotic distribution; Nonparametric statistics; Density estimation; Econometrics; Applied mathematics; Parametric statistics; Strong consistency; Bernstein polynomial; Statistics; Statistical physics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01507424,0.0009072748,0.001265593,0.001916999,0.0005478752,0.001624894,0.00185921,0.00128897,0.002881925],"category_scores_gemma":[0.1084696,0.0006810682,0.001215377,0.001599873,0.002505592,0.004273048,0.002374907,0.002840825,0.0007636041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001398705,"about_ca_system_score_gemma":0.00226039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00398409,"about_ca_topic_score_gemma":0.001978545,"domain_scores_codex":[0.995828,0.002254424,0.0001579484,0.0005263605,0.0009978238,0.0002354762],"domain_scores_gemma":[0.9535547,0.03691377,0.001953371,0.003015405,0.003899533,0.000663157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001454239,0.0001107068,0.01273187,0.0003160425,0.0001918391,0.0003846142,0.0006964255,0.185201,0.006453605,0.6966864,0.003283414,0.09379871],"study_design_scores_gemma":[0.00002172052,0.00007707257,0.003678903,0.00009266287,0.0000352567,0.0004086104,0.0001335733,0.8067523,0.001742104,0.1848549,0.002143018,0.00005986109],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01442445,0.0004378076,0.9829141,0.0002894874,0.00002501722,0.00004878508,0.00009452699,0.0001656412,0.001600167],"genre_scores_gemma":[0.6645805,0.003307011,0.3260983,0.0004203695,0.0002783891,0.0005114535,0.001144399,0.0003327145,0.003326896],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01507424,"threshold_uncertainty_score":0.07972115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1273282790717306,"score_gpt":0.315083904521141,"score_spread":0.1877556254494104,"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."}}