{"id":"W2921485947","doi":"10.1002/env.2494","title":"The new family of Fisher copulas to model upper tail dependence and radial asymmetry: Properties and application to high‐dimensional rainfall data","year":2018,"lang":"en","type":"article","venue":"Environmetrics","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tail dependence; Copula (linguistics); Asymmetry; Mathematics; Multivariate statistics; Parametric statistics; Statistics; Econometrics; Multivariate normal distribution; Statistical physics; Marginal distribution; Physics; Random variable","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":[0.002575899,0.0009689913,0.0005585348,0.0009169504,0.0003004645,0.0005611773,0.0009731097,0.0005885577,0.001164319],"category_scores_gemma":[0.009338824,0.000333716,0.001101887,0.001036726,0.0006875582,0.001329477,0.0007961448,0.001318816,0.0003079426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004996634,"about_ca_system_score_gemma":0.0008507067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004170884,"about_ca_topic_score_gemma":0.003367333,"domain_scores_codex":[0.9993683,0.0002946882,0.00003759809,0.00008579459,0.0001613301,0.00005235982],"domain_scores_gemma":[0.9973122,0.001690143,0.000261527,0.0003235466,0.0003452996,0.00006734239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006092167,0.00006484478,0.006604666,0.000147422,0.0001869161,0.0003977221,0.0002041375,0.6990557,0.005511079,0.1180397,0.004674931,0.165052],"study_design_scores_gemma":[0.000004504091,0.00002546614,0.001394193,0.00001200979,0.00001431365,0.0001829217,0.00001498001,0.9772764,0.0005332456,0.01886359,0.001656866,0.00002158797],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009646038,0.0002703848,0.9890103,0.00008899431,0.00003105219,0.00003222988,0.0001154621,0.0001732294,0.0006323655],"genre_scores_gemma":[0.5162332,0.002341414,0.4759704,0.0002145528,0.0001809454,0.000320359,0.000800275,0.0002667058,0.003672218],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004170884,"threshold_uncertainty_score":0.01362282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02150674003429712,"score_gpt":0.2249035603368164,"score_spread":0.2033968203025192,"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."}}