{"id":"W2998698044","doi":"10.1016/j.jmva.2019.104586","title":"On moments of doubly truncated multivariate normal mean–variance mixture distributions with application to multivariate tail conditional expectation","year":2020,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Kurtosis; Mathematics; Multivariate statistics; Multivariate stable distribution; Normal-Wishart distribution; Multivariate analysis of variance; Multivariate normal distribution; Skewness; Statistics; Matrix t-distribution; Multivariate t-distribution; Multivariate analysis; Conditional probability distribution; Conditional variance; Normal distribution; Elliptical distribution; Econometrics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.008609929,0.001590621,0.001948999,0.002698842,0.0007257648,0.002622689,0.00262014,0.00226327,0.003732148],"category_scores_gemma":[0.04440535,0.001356676,0.002573521,0.003177852,0.003330153,0.004961494,0.003576064,0.004431118,0.000768766],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001584067,"about_ca_system_score_gemma":0.001848177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002974161,"about_ca_topic_score_gemma":0.002633636,"domain_scores_codex":[0.9978147,0.001146029,0.0001232341,0.0002573563,0.0004764771,0.0001821831],"domain_scores_gemma":[0.976075,0.01974005,0.001213008,0.0009125351,0.001542735,0.0005166354],"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":[0.0001283349,0.00007259069,0.001387367,0.0002524273,0.0001224764,0.0003481493,0.0003850595,0.2475325,0.002626188,0.7069302,0.002107825,0.03810697],"study_design_scores_gemma":[0.000008455777,0.00002031411,0.0005039583,0.00005361092,0.0000307489,0.0001518035,0.00003347168,0.8035622,0.0005542061,0.1939241,0.001114613,0.00004250739],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004847538,0.0004849276,0.9932327,0.0001760841,0.00005654213,0.00002050007,0.00004218944,0.00009466994,0.001044979],"genre_scores_gemma":[0.4404623,0.00727136,0.53734,0.0005393213,0.001180554,0.000403175,0.0007295702,0.0008042503,0.01126939],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008609929,"threshold_uncertainty_score":0.04553425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03332112765358988,"score_gpt":0.3375746618629803,"score_spread":0.3042535342093904,"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."}}