{"id":"W2011416863","doi":"10.1080/07350015.2012.738955","title":"Optimal Bandwidth Selection for Nonparametric Conditional Distribution and Quantile Functions","year":2012,"lang":"en","type":"article","venue":"Journal of Business and Economic Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; North Dakota State University; North Dakota Humanities Council","keywords":"Nonparametric statistics; Quantile; Selection (genetic algorithm); Conditional probability distribution; Econometrics; Bandwidth (computing); Computer science; Mathematics; Statistics; Artificial intelligence; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01798048,0.001115519,0.001587929,0.001908086,0.0007224349,0.001459072,0.003071716,0.002088851,0.001802039],"category_scores_gemma":[0.06274544,0.0009869655,0.0009888366,0.001424249,0.001772115,0.001875427,0.002762752,0.002556359,0.0006844981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124599,"about_ca_system_score_gemma":0.002531017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004471312,"about_ca_topic_score_gemma":0.003400561,"domain_scores_codex":[0.9930323,0.00493102,0.000232735,0.0005975523,0.0008942678,0.0003120749],"domain_scores_gemma":[0.9782091,0.0164113,0.001030779,0.001751617,0.002271767,0.0003254974],"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":[0.0003084509,0.000249185,0.005221071,0.0001931375,0.0001894012,0.0001629309,0.0003514126,0.7216157,0.005783814,0.1027745,0.00231594,0.1608344],"study_design_scores_gemma":[0.00002481058,0.00001582485,0.0004200652,0.00001817497,0.000009949263,0.00001657452,0.00001143879,0.979362,0.0009256186,0.01882462,0.0003563558,0.00001448341],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007425614,0.00008744839,0.991932,0.00009097314,0.000008090496,0.00002099476,0.00001979739,0.0002401653,0.0001751045],"genre_scores_gemma":[0.3716327,0.0002697929,0.6253197,0.0002188065,0.00006615609,0.0004977055,0.000526647,0.0004359813,0.001032451],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01798048,"threshold_uncertainty_score":0.09509104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06748716992492598,"score_gpt":0.3348235636902627,"score_spread":0.2673363937653367,"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."}}