{"id":"W2073882261","doi":"10.1007/s13171-013-0047-7","title":"On Generalized Wishart Distributions - I: Likelihood Ratio Test for Homogeneity of Covariance Matrices","year":2014,"lang":"en","type":"article","venue":"Sankhya A","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Wishart distribution; Likelihood-ratio test; Mathematics; Covariance; Applied mathematics; Statistic; Covariance matrix; Homogeneity (statistics); Gaussian; Estimation of covariance matrices; Multivariate normal distribution; Inverse-Wishart distribution; Statistics; Generalized normal distribution; Test statistic; Normal-Wishart distribution; Scatter matrix; Normal distribution; Statistical hypothesis testing; Multivariate statistics; Physics","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":[0.0164352,0.001611477,0.002680759,0.003277321,0.0009563745,0.003175379,0.003704916,0.003158704,0.005755371],"category_scores_gemma":[0.1237613,0.001183523,0.002271359,0.003274392,0.005221366,0.006056204,0.004812739,0.003360216,0.001484764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007467553,"about_ca_system_score_gemma":0.002024487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001099456,"about_ca_topic_score_gemma":0.0004604602,"domain_scores_codex":[0.982403,0.01278085,0.0005595863,0.002107053,0.001639202,0.0005103032],"domain_scores_gemma":[0.8670321,0.1185779,0.003399603,0.006323243,0.003520709,0.001146641],"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":[0.001084788,0.0001970384,0.008790613,0.0009074501,0.000682314,0.001241578,0.0007530577,0.1156622,0.0106362,0.6759685,0.006594924,0.1774813],"study_design_scores_gemma":[0.0001464105,0.0004951218,0.003785347,0.0001415224,0.0001808517,0.001522441,0.0002731792,0.4692955,0.006910378,0.5132833,0.003780868,0.0001850527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01081538,0.0002765437,0.9870444,0.0001719878,0.00004362956,0.00006189761,0.0001545676,0.0003094057,0.00112205],"genre_scores_gemma":[0.4687315,0.001290514,0.520497,0.0006136635,0.0008315498,0.001051358,0.002144044,0.0008324448,0.00400798],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0164352,"threshold_uncertainty_score":0.08691865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06878410913642044,"score_gpt":0.3929434937247834,"score_spread":0.324159384588363,"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."}}