{"id":"W4236454640","doi":"10.1002/9780470012505.tam015","title":"Maximum Likelihood","year":2004,"lang":"en","type":"other","venue":"Encyclopedia of Actuarial Science","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Inference; Maximum likelihood; Series (stratigraphy); Estimation; Indirect Inference; Econometrics; Computer science; Mathematics; Statistics; Applied mathematics; Artificial intelligence; Economics; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005288907,0.001429359,0.001779021,0.002635426,0.0009823126,0.005515616,0.003300383,0.002774144,0.04001473],"category_scores_gemma":[0.03639565,0.001048496,0.001758135,0.003321412,0.00169219,0.004782411,0.003426836,0.002760149,0.01718023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001429853,"about_ca_system_score_gemma":0.002166257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002011129,"about_ca_topic_score_gemma":0.001686883,"domain_scores_codex":[0.9932597,0.00428126,0.0002874708,0.000807557,0.001108721,0.0002551973],"domain_scores_gemma":[0.9894549,0.007048416,0.0005021371,0.001838263,0.0009965379,0.0001596087],"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":[0.00009114251,0.0000816887,0.001923989,0.000575531,0.0002412912,0.0003034516,0.0002462653,0.07511304,0.0006798916,0.511019,0.04819229,0.3615324],"study_design_scores_gemma":[0.00003757642,0.00003028994,0.0004693544,0.0002401956,0.00004566114,0.000352918,0.0000751202,0.2134005,0.0009292181,0.6960549,0.08831506,0.00004916491],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000875158,0.001500718,0.9764394,0.001427402,0.0001933003,0.0001119173,0.0009322061,0.0008055528,0.01771428],"genre_scores_gemma":[0.1057452,0.004441029,0.8488785,0.001573156,0.001099374,0.0008249323,0.004668626,0.001244771,0.03152441],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04001473,"threshold_uncertainty_score":0.1338627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01472873843419075,"score_gpt":0.2252184925882939,"score_spread":0.2104897541541031,"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."}}