{"id":"W2764305583","doi":"10.1002/jae.2685","title":"Bayesian parametric and semiparametric factor models for large realized covariance matrices","year":2019,"lang":"en","type":"article","venue":"Journal of Applied Econometrics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Parametric statistics; Wishart distribution; Covariance; Dirichlet process; Factor analysis; Dirichlet distribution; Nonparametric statistics; Inverse; Computer science; Applied mathematics; Semiparametric model; Mathematics; Bayesian probability; Econometrics; Statistics","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":[0.007174049,0.0007164393,0.00111977,0.001081569,0.0003926486,0.002247486,0.001685351,0.00131089,0.004031932],"category_scores_gemma":[0.02388329,0.001029662,0.001376684,0.001210638,0.001890637,0.002963494,0.001687409,0.002359122,0.000726797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001239565,"about_ca_system_score_gemma":0.001331423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006041856,"about_ca_topic_score_gemma":0.00592525,"domain_scores_codex":[0.9970722,0.001672173,0.0001107029,0.0004538517,0.0004836573,0.0002074055],"domain_scores_gemma":[0.9901108,0.006831089,0.001005616,0.001199414,0.0006574838,0.000195618],"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":[0.00006728795,0.00004733775,0.002009542,0.00005760627,0.00009368853,0.0001073383,0.0001847337,0.3489775,0.0006591941,0.6174573,0.001841441,0.02849714],"study_design_scores_gemma":[0.000009364791,0.000008481404,0.00067629,0.00001649767,0.00001186998,0.00002675031,0.00002167974,0.7443269,0.0001201015,0.2536927,0.00106594,0.0000234285],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0175462,0.0001918762,0.9799023,0.0003046298,0.00002372831,0.0000185435,0.0001362324,0.0001645735,0.001712037],"genre_scores_gemma":[0.7758121,0.0008128273,0.2133627,0.000152935,0.0001352955,0.0002800667,0.0006767152,0.0002288036,0.008538443],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007174049,"threshold_uncertainty_score":0.03794044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02775264564314967,"score_gpt":0.2603599612005525,"score_spread":0.2326073155574029,"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."}}