{"id":"W1971333466","doi":"10.1080/10485250601046752","title":"Risk comparison of some shrinkage M-estimators in linear models","year":2006,"lang":"en","type":"article","venue":"Journal of nonparametric statistics","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Estimator; Mathematics; A priori and a posteriori; Applied mathematics; Linear regression; Linear model; Subspace topology; Asymptotic distribution; Statistics; Asymptotic analysis; Sampling (signal processing); Computer science; Mathematical analysis","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002548889,0.0002080383,0.001012003,0.001712285,0.00007267322,0.00007674727,0.0007686252,0.0001091497,0.00003633067],"category_scores_gemma":[0.0257435,0.0001652072,0.0001098351,0.002763138,0.0001962126,0.000629793,0.00009502652,0.0006977574,0.00002107783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001467503,"about_ca_system_score_gemma":0.0001690822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009389519,"about_ca_topic_score_gemma":0.00001401444,"domain_scores_codex":[0.9935289,0.000239837,0.003119872,0.0002750264,0.002481556,0.000354833],"domain_scores_gemma":[0.9827282,0.01274399,0.002831086,0.0003269945,0.001200615,0.0001690653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001279334,0.0005053839,0.165501,0.00002873615,0.00002143532,0.0001534873,0.0001740361,0.7489779,0.00003532327,0.02346959,0.002677265,0.05832794],"study_design_scores_gemma":[0.0006772426,0.0002579459,0.03953457,0.00003841974,0.00003630566,0.00001254167,0.0001825722,0.4122529,0.0002916907,0.5464171,0.0001506971,0.0001480488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1827391,0.0007834299,0.8152805,0.00001496722,0.000655853,0.00008320314,0.0002121361,0.00000633017,0.0002244837],"genre_scores_gemma":[0.5952473,0.00003104704,0.4045309,0.000005269623,0.0001191734,7.237294e-7,0.000001216532,0.00001302021,0.00005131994],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5229475,"threshold_uncertainty_score":0.9824631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09597850055443359,"score_gpt":0.435455462143716,"score_spread":0.3394769615892824,"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."}}