{"id":"W2604241187","doi":"10.1002/cjs.11315","title":"Depth‐weighted robust multivariate regression with application to sparse data","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multivariate statistics; Mahalanobis distance; Mathematics; Estimator; Robust regression; Robust statistics; Statistics; Affine transformation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.007225819,0.001259563,0.001701557,0.001830079,0.0003940509,0.0009465669,0.001938553,0.001095706,0.001873549],"category_scores_gemma":[0.0328413,0.000706104,0.001364214,0.002271243,0.001078063,0.001680795,0.003038928,0.002052892,0.0004258541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008023278,"about_ca_system_score_gemma":0.001095778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004236964,"about_ca_topic_score_gemma":0.003629023,"domain_scores_codex":[0.995932,0.002367051,0.0001702491,0.0005582014,0.0008062914,0.0001662181],"domain_scores_gemma":[0.9829454,0.01180439,0.001756873,0.001735872,0.001511863,0.0002456809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002119111,0.00006611577,0.00227036,0.000278927,0.0002513353,0.000169489,0.0001348593,0.7555234,0.006451129,0.06397503,0.001929731,0.1687378],"study_design_scores_gemma":[0.00001217277,0.00002917168,0.0003686019,0.00001176278,0.00001277283,0.00002648442,0.000008450653,0.9843013,0.0009751814,0.01336783,0.0008707622,0.00001555838],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003382561,0.0001415812,0.9960323,0.00007780577,0.00001074143,0.00001603003,0.00004619491,0.0001428392,0.0001498806],"genre_scores_gemma":[0.1937999,0.0006916935,0.802735,0.000175039,0.0001786317,0.000199604,0.0004525182,0.0003344591,0.00143314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007225819,"threshold_uncertainty_score":0.03821427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2503253772044177,"score_gpt":0.4105006008252451,"score_spread":0.1601752236208275,"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."}}