{"id":"W3165547170","doi":"10.1002/cjs.11616","title":"Quantile function regression and variable selection for sparse models","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quantile regression; Quantile; Estimator; Quantile function; Mathematics; Statistics; Binomial regression; Feature selection; Econometrics; Linear regression; Regression analysis; Computer science; Cumulative distribution function; Probability density function; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009667573,0.001531763,0.002375151,0.001866593,0.0006506422,0.001427829,0.001898506,0.001635147,0.002888084],"category_scores_gemma":[0.02447203,0.0007794615,0.001765169,0.002723341,0.001768959,0.001627851,0.00200444,0.002908834,0.0007786464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00103749,"about_ca_system_score_gemma":0.001565651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004062973,"about_ca_topic_score_gemma":0.00274664,"domain_scores_codex":[0.9936535,0.004393835,0.0001569325,0.0008287317,0.0007320975,0.0002348164],"domain_scores_gemma":[0.9893004,0.008449011,0.0008217054,0.0006555006,0.0006510107,0.0001223199],"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":[0.0001313374,0.00009412479,0.004242537,0.0004807237,0.0003867874,0.000287447,0.0001505832,0.6953692,0.001541847,0.177874,0.003999312,0.115442],"study_design_scores_gemma":[0.00002097542,0.00004254173,0.0006596064,0.00003652681,0.00002917617,0.00004790573,0.0000157252,0.9494705,0.0003550022,0.04726782,0.002037858,0.00001637273],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003238516,0.0007245564,0.9950837,0.0002531341,0.00003481049,0.00002847411,0.00007602108,0.0001206812,0.0004402321],"genre_scores_gemma":[0.4733337,0.006262913,0.5081031,0.0007463651,0.001065419,0.000903803,0.00173072,0.0003704596,0.007483554],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009667573,"threshold_uncertainty_score":0.05112761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1383965863067766,"score_gpt":0.3316610625230124,"score_spread":0.1932644762162358,"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."}}