{"id":"W2766235828","doi":"10.1016/j.jmva.2017.10.006","title":"Extreme-value limit of the convolution of exponential and multivariate normal distributions: Link to the Hüsler–Reiß distribution","year":2017,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia; King Abdullah University of Science and Technology","keywords":"Mathematics; Multivariate statistics; Copula (linguistics); Multivariate normal distribution; Convolution (computer science); Exponential function; Applied mathematics; Multivariate random variable; Limit (mathematics); Random variable; Statistics; Mathematical analysis; Econometrics; Computer science","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":[0.01143777,0.001426581,0.002097711,0.003174354,0.001035452,0.003554108,0.002993827,0.002494865,0.004719516],"category_scores_gemma":[0.05402931,0.0008726419,0.001753602,0.002086075,0.008058895,0.008765095,0.003429909,0.004558895,0.0007814376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001828465,"about_ca_system_score_gemma":0.002055448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001852331,"about_ca_topic_score_gemma":0.001053537,"domain_scores_codex":[0.9968382,0.001390238,0.0001728717,0.0006025716,0.0006599044,0.0003361612],"domain_scores_gemma":[0.962276,0.02540829,0.003469023,0.002190767,0.004382472,0.002273547],"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":[0.00008308343,0.00005658707,0.001574763,0.0001119971,0.00006324139,0.0002350989,0.0002635827,0.02183476,0.001224317,0.9660845,0.0009787272,0.007489523],"study_design_scores_gemma":[0.0000242787,0.00005480774,0.00123204,0.00005777379,0.00003632852,0.0004326651,0.00009933527,0.2822675,0.0008598297,0.7136154,0.001240407,0.00007967173],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07811823,0.001763075,0.9120614,0.001328369,0.0001409979,0.00003585635,0.0001326869,0.0001938618,0.006225634],"genre_scores_gemma":[0.8873363,0.003469372,0.09481163,0.0005855229,0.0008436553,0.0002256828,0.0004231971,0.0002541876,0.01205038],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01143777,"threshold_uncertainty_score":0.06048936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07240964380968566,"score_gpt":0.3601203292356547,"score_spread":0.287710685425969,"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."}}