{"id":"W2156755705","doi":"10.1080/03610920903324882","title":"Generalized Kernel Estimators for the Weibull-Tail Coefficient","year":2010,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Waterloo","keywords":"Estimator; Weibull distribution; Mathematics; Asymptotic distribution; Statistics; Order statistic; Kernel (algebra); Transformation (genetics); Sequence (biology); Distribution (mathematics); Kernel density estimation; Applied mathematics; Mathematical analysis; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0076952,0.0001068414,0.0002447925,0.00007957092,0.0003360621,0.00006219252,0.0003471436,0.00008852164,0.00007157662],"category_scores_gemma":[0.002916997,0.00009753769,0.000039729,0.000113763,0.0002342098,0.00006146718,0.000104133,0.0002847588,0.000007920364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001783552,"about_ca_system_score_gemma":0.00002106446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001289724,"about_ca_topic_score_gemma":0.00007577068,"domain_scores_codex":[0.9988558,0.0002492326,0.0004955548,0.0002084493,0.00002009934,0.000170869],"domain_scores_gemma":[0.9956225,0.003409744,0.0002052397,0.0006659362,0.00005395609,0.0000426252],"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":[0.00005089251,0.00003235678,0.001988037,0.0000159846,0.000008507022,5.923383e-8,0.0009557305,0.0002875626,0.00004968918,0.9575399,0.0001225788,0.03894866],"study_design_scores_gemma":[0.0003863808,0.0000144481,0.005457019,0.000008179314,0.000008320904,8.794518e-7,0.0001006721,0.2358214,0.00005671367,0.7269234,0.03110964,0.0001128921],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0288909,0.004077553,0.9653182,0.0002598133,0.0003440915,0.0003177383,0.0001878117,0.0000173111,0.000586585],"genre_scores_gemma":[0.4041204,0.0007682357,0.5945621,0.0001457421,0.00002390537,0.0001128685,0.00002245546,0.00001447539,0.0002298932],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3752295,"threshold_uncertainty_score":0.3977472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05605670135521534,"score_gpt":0.3702811237317607,"score_spread":0.3142244223765454,"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."}}