{"id":"W2021091247","doi":"10.1198/073500107000000250","title":"Nonparametric Estimation of Conditional CDF and Quantile Functions With Mixed Categorical and Continuous Data","year":2008,"lang":"en","type":"article","venue":"Journal of Business and Economic Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":254,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Estimator; Nonparametric statistics; Conditional probability distribution; Kernel regression; Quantile; Categorical variable; Kernel density estimation; Quantile function; Cumulative distribution function; Mathematics; Econometrics; Quantile regression; Statistics; Kernel (algebra); Conditional expectation; Regular conditional probability; Probability density function; Probability mass function","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":[0.0002721739,0.00009632648,0.0003868731,0.0001116796,0.00008123978,0.00002936259,0.00006361857,0.00003970157,0.00005047485],"category_scores_gemma":[0.00110674,0.00007421487,0.00000800518,0.00007755326,0.0002569104,0.0001602309,0.00004519131,0.00009290197,8.254639e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001528074,"about_ca_system_score_gemma":0.0001076485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005650355,"about_ca_topic_score_gemma":0.0000112517,"domain_scores_codex":[0.9991952,0.00003232526,0.0004678119,0.000123448,0.00009084634,0.00009038495],"domain_scores_gemma":[0.997431,0.001732145,0.0004413418,0.0001145644,0.0001982745,0.0000827046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0007235888,0.0005526273,0.06955954,0.001000559,0.000512552,0.0002047209,0.0004758999,0.00115571,0.00008183238,0.7888867,0.02754964,0.1092967],"study_design_scores_gemma":[0.002302582,0.0005997412,0.6006346,0.00009189729,0.0003803477,0.003030771,0.0002423215,0.1615078,0.00002222163,0.2305824,0.0003179297,0.0002873589],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3300787,0.0001071631,0.6690909,0.00004367694,0.0000802867,0.0000435483,0.0005152543,0.000002033731,0.00003844796],"genre_scores_gemma":[0.6344638,0.0002680009,0.3651792,0.000007902583,0.0000351415,7.487987e-7,0.00002260088,0.000006679682,0.00001583161],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5583043,"threshold_uncertainty_score":0.3026395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1067694690153859,"score_gpt":0.3248579928145062,"score_spread":0.2180885237991204,"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."}}