{"id":"W2113479332","doi":"10.1080/03610926.2011.624242","title":"Selection of Variables in Multivariate Regression Models for Large Dimensions","year":2012,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Akaike information criterion; Mathematics; Covariance matrix; Statistics; Bayesian information criterion; Estimator; Scatter matrix; Dimension (graph theory); Sample size determination; Covariance; Statistic; Estimation of covariance matrices; Multivariate statistics; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009825709,0.0001349753,0.0003682131,0.0001304543,0.0001196372,0.000006920377,0.000127972,0.0001084194,0.00001950614],"category_scores_gemma":[0.007029667,0.0001170841,0.00002519483,0.0001678706,0.00008216767,0.0001984447,0.0001186778,0.0002064859,1.549201e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003790306,"about_ca_system_score_gemma":0.00002248123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001525621,"about_ca_topic_score_gemma":0.00001593534,"domain_scores_codex":[0.9954475,0.003504967,0.0005409798,0.0001602333,0.00007550941,0.0002707742],"domain_scores_gemma":[0.9796799,0.01954467,0.0002302076,0.0003584402,0.0001164821,0.00007025329],"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":[0.000187236,0.0002509805,0.0001755879,0.0001398933,0.00001043987,7.290983e-8,0.001988555,0.000104918,0.002161589,0.9676781,0.00002338755,0.02727929],"study_design_scores_gemma":[0.0007311528,0.0000308552,0.0004324108,0.0001930425,0.00003398447,0.000001373008,0.0003570761,0.08344215,0.001286837,0.9131783,0.0001957073,0.0001171163],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001318753,0.0006620232,0.9970064,0.00001782949,0.00006520075,0.0004276631,0.0001603777,0.00001731525,0.0003244038],"genre_scores_gemma":[0.2339285,0.0002498297,0.7655815,0.00001948541,0.000008197665,0.0001123602,0.00001702677,0.0000176416,0.00006551165],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2326097,"threshold_uncertainty_score":0.8415676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1651706163689602,"score_gpt":0.5250308425509028,"score_spread":0.3598602261819426,"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."}}