{"id":"W4377015802","doi":"10.1016/j.cam.2023.115329","title":"Ergodic estimators of double exponential Ornstein–Uhlenbeck processes","year":2023,"lang":"en","type":"article","venue":"Journal of Computational and Applied Mathematics","topic":"Stochastic processes and financial applications","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Ornstein–Uhlenbeck process; Mathematics; Ergodic theory; Estimator; Uniqueness; Applied mathematics; Asymptotic distribution; Exponential function; Consistency (knowledge bases); Double exponential function; Function (biology); Mathematical analysis; Stochastic process; Statistics; Discrete mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00600899,0.0007375896,0.001067063,0.001846568,0.0003828464,0.002054687,0.001501317,0.001332566,0.002296015],"category_scores_gemma":[0.03295325,0.0005814443,0.0007837035,0.0008633969,0.001230998,0.003391812,0.00197093,0.001549108,0.0004528176],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007973581,"about_ca_system_score_gemma":0.0009839283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008514893,"about_ca_topic_score_gemma":0.0008470939,"domain_scores_codex":[0.9987391,0.0004939419,0.00009794551,0.0002356995,0.0002941056,0.0001392308],"domain_scores_gemma":[0.9887241,0.007505914,0.001029229,0.0012609,0.001053727,0.0004261343],"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":[0.0003193718,0.0001745866,0.007333271,0.0002082495,0.0003111357,0.0001558685,0.0001815126,0.3546451,0.005882621,0.5314627,0.001585916,0.09773958],"study_design_scores_gemma":[0.00001758277,0.00003218008,0.0008413449,0.00002840933,0.00002812163,0.00007011515,0.00002026862,0.9258566,0.001733082,0.07057175,0.0007716018,0.00002893903],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05306691,0.000458716,0.9448843,0.0001044305,0.0001191956,0.00002309759,0.00006005098,0.0001638814,0.001119439],"genre_scores_gemma":[0.8312374,0.000886966,0.1623735,0.0001235124,0.0002878541,0.00008854485,0.0005361691,0.000151903,0.004314124],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00600899,"threshold_uncertainty_score":0.03177899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03446275133410923,"score_gpt":0.2421684066426671,"score_spread":0.2077056553085579,"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."}}