{"id":"W4309998789","doi":"10.1002/cjs.11736","title":"A hyperbolic divergence based nonparametric test for two‐sample multivariate distributions","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Science and Technology Cooperation Programme; National Natural Science Foundation of China","keywords":"Mathematics; Test statistic; Nonparametric statistics; Divergence (linguistics); Resampling; Hypersphere; Statistical hypothesis testing; Multivariate statistics; Sample space; Null distribution; Statistics; Sample size determination; Multivariate normal distribution; Applied mathematics; Geometry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02600513,0.0005457956,0.001549231,0.003003652,0.001108333,0.002378249,0.002819082,0.001753937,0.004343772],"category_scores_gemma":[0.1149659,0.000371966,0.001110424,0.00254576,0.004323606,0.003299234,0.003611772,0.0031192,0.0004276172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001765794,"about_ca_system_score_gemma":0.002453327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001912248,"about_ca_topic_score_gemma":0.001011571,"domain_scores_codex":[0.9823443,0.01150022,0.0008536048,0.001793695,0.003097996,0.0004102812],"domain_scores_gemma":[0.847476,0.1328553,0.004901859,0.006986128,0.006264979,0.001515795],"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":[0.001505327,0.0005523834,0.08050548,0.0005888531,0.000937801,0.001396713,0.001213984,0.1535934,0.01123258,0.4322453,0.00535406,0.3108741],"study_design_scores_gemma":[0.0001830967,0.000507233,0.01781,0.00009628073,0.00006969948,0.0006041159,0.0003956629,0.8021522,0.004595049,0.17057,0.002860456,0.0001562169],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09047486,0.0001448273,0.9057402,0.0004470577,0.00006489504,0.0001950513,0.0002655089,0.0003270872,0.00234045],"genre_scores_gemma":[0.7550499,0.00008274367,0.2419579,0.0003094865,0.00007577136,0.0004531908,0.0006091385,0.0001325373,0.001329317],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02600513,"threshold_uncertainty_score":0.1375299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1096872526930947,"score_gpt":0.3794951379342598,"score_spread":0.2698078852411651,"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."}}