{"id":"W2007738022","doi":"10.1007/s003620100073","title":"On the comparison of the pre-test and shrinkage estimators for the univariate normal mean","year":2001,"lang":"en","type":"article","venue":"Statistical Papers","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Estimator; Univariate; Statistics; Shrinkage estimator; Mathematics; Mean squared error; Shrinkage; Sample (material); Variance (accounting); Sample size determination; Population; Population mean; Econometrics; Minimum-variance unbiased estimator; Efficient estimator; Multivariate statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004816729,0.0001581829,0.0002543722,0.00001115746,0.000332628,0.0000248305,0.0002481462,0.00004892052,0.0001137351],"category_scores_gemma":[0.00674384,0.00006855711,0.00005518655,0.00008806195,0.0004915152,0.00002505907,0.00007823539,0.0002259565,0.000001542334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001896053,"about_ca_system_score_gemma":0.00002521928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002419408,"about_ca_topic_score_gemma":0.00005204671,"domain_scores_codex":[0.9988176,0.0001433082,0.0003220654,0.000196368,0.0002541954,0.0002665256],"domain_scores_gemma":[0.9677932,0.03161969,0.0001176545,0.0003483913,0.00004670567,0.00007437698],"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":[0.00007306818,0.00008153197,0.0001998624,0.00004146481,0.00002823163,0.00000110264,0.0004477443,0.0001501419,0.0001850825,0.9861851,0.0007505658,0.01185605],"study_design_scores_gemma":[0.000422801,0.0002371016,0.004245364,0.00004797341,0.0001523554,0.000004104102,0.0003872472,0.06991538,0.0001639081,0.9223415,0.001941723,0.0001405468],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00660265,0.00002309506,0.9860842,0.001226111,0.0001082816,0.0006820629,0.000322886,0.00002185645,0.00492892],"genre_scores_gemma":[0.8161298,0.000009497046,0.18319,0.0002278468,0.00002733041,0.00004332388,0.00000235354,0.00002261496,0.0003471939],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8095272,"threshold_uncertainty_score":0.8073494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0796369323591667,"score_gpt":0.4147179015500356,"score_spread":0.3350809691908689,"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."}}