{"id":"W3131901145","doi":"10.1080/03610918.2021.1884715","title":"New quantile based ridge M-estimator for linear regression models with multicollinearity and outliers","year":2021,"lang":"en","type":"article","venue":"Communications in Statistics - Simulation and Computation","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Infection and Immunity","keywords":"Multicollinearity; Estimator; Quantile; Variance inflation factor; Outlier; Statistics; Ordinary least squares; Mean squared error; Mathematics; Minimum-variance unbiased estimator; Quantile regression; Ridge; Linear regression","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.004594363,0.0007729509,0.001480144,0.001158877,0.0004053289,0.0009531202,0.001935606,0.001224614,0.001478245],"category_scores_gemma":[0.01328548,0.0005199163,0.001306641,0.001737086,0.0005777359,0.001394561,0.001221971,0.002125734,0.0008036359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004141742,"about_ca_system_score_gemma":0.001138799,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001553267,"about_ca_topic_score_gemma":0.001563419,"domain_scores_codex":[0.9979103,0.001080196,0.0001040434,0.0003378234,0.0004353067,0.0001322672],"domain_scores_gemma":[0.9957979,0.002349347,0.0004949211,0.0004750867,0.0007988021,0.00008400272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000340811,0.0001928148,0.02325851,0.0008148678,0.0005817816,0.000473711,0.0002912629,0.3502072,0.01301553,0.06243803,0.008996424,0.539389],"study_design_scores_gemma":[0.00002857436,0.0000769879,0.002466887,0.0000536368,0.00005645855,0.0002260344,0.00004410011,0.9724865,0.002612231,0.01721339,0.004700478,0.00003466336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002911802,0.000420881,0.9961889,0.00005454272,0.00001873296,0.0000139425,0.00004230307,0.0001786306,0.0001702414],"genre_scores_gemma":[0.1801751,0.00139829,0.8146347,0.0002388711,0.0001658487,0.0002282636,0.0006413673,0.0002570903,0.002260542],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004594363,"threshold_uncertainty_score":0.0242976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3686744299763938,"score_gpt":0.5423827098270539,"score_spread":0.1737082798506601,"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."}}