{"id":"W2081434932","doi":"10.1007/s13369-011-0106-0","title":"Shrinkage Estimation Using Ranked Set Samples","year":2011,"lang":"en","type":"article","venue":"Arabian Journal for Science and Engineering","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Estimator; Shrinkage; RSS; Statistics; Monte Carlo method; Sample (material); Mathematics; Set (abstract data type); Estimation; Shrinkage estimator; Population; Sampling (signal processing); Estimation theory; Computer science; Econometrics; Algorithm; Engineering; Bias of an estimator","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008764846,0.001332889,0.002749228,0.001646233,0.0009526863,0.001811286,0.002315611,0.002269154,0.003248969],"category_scores_gemma":[0.02649678,0.001428376,0.002083495,0.001177501,0.001114842,0.002508191,0.002107112,0.002426622,0.001869721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006449795,"about_ca_system_score_gemma":0.001510955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002012077,"about_ca_topic_score_gemma":0.003187155,"domain_scores_codex":[0.9951921,0.002688042,0.0002310032,0.0005605033,0.001080388,0.0002480218],"domain_scores_gemma":[0.9826649,0.0123291,0.0007341106,0.001921092,0.002113173,0.0002377072],"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":[0.001058195,0.0003272262,0.003051442,0.0006282312,0.0005613518,0.0002960717,0.0002412705,0.4764612,0.01371341,0.03711728,0.007329034,0.4592153],"study_design_scores_gemma":[0.00004052749,0.00009497454,0.0004540792,0.00002661,0.00005455094,0.00007073851,0.00001908459,0.982883,0.002974426,0.0125184,0.0008386391,0.00002498057],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009884574,0.0002208624,0.9887673,0.00009363593,0.00003059601,0.00005107353,0.00006890277,0.000350104,0.0005328815],"genre_scores_gemma":[0.3664317,0.0006322714,0.6228964,0.0002836023,0.000282087,0.0004461952,0.001763322,0.0003332335,0.006931113],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008764846,"threshold_uncertainty_score":0.04635352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2346127213472306,"score_gpt":0.3513971008261586,"score_spread":0.116784379478928,"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."}}