{"id":"W4387140126","doi":"10.1007/s11222-023-10297-1","title":"Testing symmetry for bivariate copulas using Bernstein polynomials","year":2023,"lang":"en","type":"article","venue":"Statistics and Computing","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bivariate analysis; Copula (linguistics); Bernstein polynomial; Mathematics; Multiplier (economics); Applied mathematics; Symmetry (geometry); Econometrics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02559985,0.0009734172,0.001576431,0.001268677,0.0009816067,0.002290757,0.001941456,0.001291734,0.007244957],"category_scores_gemma":[0.2278478,0.0005799709,0.00269388,0.001493758,0.003218017,0.006868941,0.003044145,0.00301992,0.0007245367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007630236,"about_ca_system_score_gemma":0.003691543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003000075,"about_ca_topic_score_gemma":0.001249902,"domain_scores_codex":[0.9752473,0.01574985,0.00111743,0.003420532,0.002720861,0.001743964],"domain_scores_gemma":[0.6809503,0.28129,0.00891566,0.01766191,0.007303837,0.003878325],"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":[0.00444413,0.001281677,0.1218845,0.0004378999,0.001600207,0.001208049,0.001734491,0.1403942,0.01342869,0.5045712,0.006341747,0.2026733],"study_design_scores_gemma":[0.0004702361,0.001368663,0.01595282,0.0000713592,0.0001686718,0.0005818126,0.001054397,0.5842617,0.004601391,0.3900975,0.001262936,0.0001084929],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4242665,0.0002171747,0.5709438,0.0006668388,0.0001172001,0.0001105102,0.0003783822,0.0003949164,0.002904685],"genre_scores_gemma":[0.9700629,0.0001008094,0.02901771,0.00007380692,0.0000540441,0.00005690936,0.0003469895,0.00006624224,0.0002206298],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02559985,"threshold_uncertainty_score":0.1353866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1081812010776814,"score_gpt":0.2943661963261016,"score_spread":0.1861849952484202,"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."}}