{"id":"W2338903144","doi":"10.7202/1036915ar","title":"Finite-Sample Sign-Based Inference in Linear and Nonlinear Regression Models with Applications in Finance","year":2016,"lang":"en","type":"article","venue":"L Actualité économique","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Durham University","keywords":"Heteroscedasticity; Sign (mathematics); Predictability; Econometrics; Inference; Nonlinear system; Variable (mathematics); Context (archaeology); Computer science; Variables; Statistical hypothesis testing; Orthogonality; Linear regression; Mathematics; Statistics; 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":[0.01656408,0.00153343,0.002715565,0.002678489,0.0005881551,0.002146053,0.002626369,0.002594114,0.004323803],"category_scores_gemma":[0.1182931,0.001040833,0.001882103,0.00291711,0.00418456,0.004201639,0.002290085,0.003687911,0.001057855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009794879,"about_ca_system_score_gemma":0.001430735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002081773,"about_ca_topic_score_gemma":0.001773554,"domain_scores_codex":[0.9922948,0.005463883,0.0003537099,0.0007501939,0.0009412753,0.0001961895],"domain_scores_gemma":[0.8859368,0.1052247,0.003625593,0.002777944,0.001963242,0.0004717156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001494107,0.0001484341,0.006700703,0.001037258,0.0003213858,0.0005426296,0.000203767,0.2148495,0.001296466,0.5802597,0.004228586,0.1902623],"study_design_scores_gemma":[0.00003753586,0.00008249683,0.0008361352,0.0001301123,0.0000440855,0.000126129,0.00002507084,0.5579754,0.0006429245,0.4368667,0.003183814,0.00004947386],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003205956,0.003637771,0.9910358,0.0006179736,0.0001216229,0.00002252957,0.00009937613,0.000224188,0.00103473],"genre_scores_gemma":[0.2781281,0.01511027,0.6970027,0.001047327,0.001896642,0.0005455003,0.0008852272,0.000436922,0.004947254],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01656408,"threshold_uncertainty_score":0.08760029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1304836509379759,"score_gpt":0.3824764910962395,"score_spread":0.2519928401582636,"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."}}