{"id":"W2055208440","doi":"10.1016/j.jmva.2004.02.018","title":"Minimax multivariate empirical Bayes estimators under multicollinearity","year":2004,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multicollinearity; Mathematics; Estimator; Minimax estimator; Statistics; Minimax; Variance inflation factor; Shrinkage estimator; Multivariate statistics; Multivariate normal distribution; Bayes' theorem; Applied mathematics; Econometrics; Linear regression; Mathematical optimization; Minimum-variance unbiased estimator; Bayesian probability","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":[0.02354024,0.001485324,0.003662207,0.001862637,0.0008972235,0.003032818,0.003275788,0.002809326,0.003684056],"category_scores_gemma":[0.1037232,0.001893971,0.001117141,0.002187358,0.002652077,0.005156291,0.003348588,0.004030701,0.0006899228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001170415,"about_ca_system_score_gemma":0.001939125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008575521,"about_ca_topic_score_gemma":0.0008569775,"domain_scores_codex":[0.9911637,0.006565242,0.0003361639,0.0007973239,0.0009117256,0.0002258268],"domain_scores_gemma":[0.9194025,0.07090603,0.003386401,0.003476252,0.002342933,0.000485903],"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":[0.0003515274,0.0001273687,0.002730519,0.0005635158,0.0004583584,0.0001669506,0.0003525682,0.1970774,0.00118352,0.6618493,0.004582063,0.130557],"study_design_scores_gemma":[0.00009178484,0.00006185736,0.0006916075,0.0001187609,0.00006350927,0.0001396285,0.00002847544,0.4370483,0.0005903644,0.5592666,0.001868433,0.00003060147],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006036691,0.0006849655,0.991943,0.0004808995,0.00004128795,0.00002743279,0.00004969887,0.0001025369,0.0006334183],"genre_scores_gemma":[0.2522973,0.002620085,0.7359821,0.0006337165,0.0009911784,0.0006311325,0.0005600345,0.0003477914,0.005936645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02354024,"threshold_uncertainty_score":0.1244942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1553428282528146,"score_gpt":0.4838001558763431,"score_spread":0.3284573276235285,"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."}}