{"id":"W2059296920","doi":"10.1016/j.jmva.2013.12.013","title":"Multivariate Archimax copulas","year":2014,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Multivariate statistics; Copula (linguistics); Bivariate analysis; Mathematics; Multivariate analysis; Econometrics; Univariate; 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":[0.002188947,0.001324773,0.001398618,0.001386035,0.0006877207,0.002849005,0.001114845,0.001127054,0.008018158],"category_scores_gemma":[0.009444422,0.0007939897,0.001535835,0.001560553,0.001383187,0.003481785,0.00160038,0.002863502,0.001363385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000870321,"about_ca_system_score_gemma":0.0008838443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001175075,"about_ca_topic_score_gemma":0.001228584,"domain_scores_codex":[0.9991639,0.0003400737,0.0000421748,0.0001343765,0.0002190911,0.0001004997],"domain_scores_gemma":[0.9970219,0.001219717,0.0004687691,0.0004677644,0.0005649115,0.0002570052],"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":[0.00003028674,0.0000351254,0.000951148,0.00005004051,0.00008150762,0.0001203564,0.00008279821,0.04423667,0.001310993,0.9350674,0.004130223,0.01390352],"study_design_scores_gemma":[0.00001132476,0.00002525267,0.001615889,0.0000308974,0.00005356713,0.0002459205,0.0000397978,0.4081524,0.0005080503,0.5838658,0.005409936,0.00004123547],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05574148,0.003261755,0.9067807,0.001655446,0.0004340157,0.000040058,0.0004402647,0.0004353952,0.03121092],"genre_scores_gemma":[0.8600142,0.004744272,0.07840226,0.0005572588,0.001255258,0.0001178632,0.0007129557,0.0004548868,0.05374094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008018158,"threshold_uncertainty_score":0.02682346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03275809156087462,"score_gpt":0.2604514471476593,"score_spread":0.2276933555867847,"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."}}