{"id":"W4224244396","doi":"10.1080/03610926.2022.2064503","title":"Efficient estimation method for generalized ARFIMA models","year":2022,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg; University of Regina","funders":"","keywords":"Estimator; Covariate; Mathematics; Shrinkage estimator; Statistics; Shrinkage; Econometrics; Efficient estimator; Minimum-variance unbiased estimator","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007397768,0.0001518201,0.0002833901,0.0001301344,0.000689225,0.00004100764,0.0002968583,0.0000477134,0.0002701707],"category_scores_gemma":[0.003333189,0.0001644578,0.00004292997,0.000293308,0.0001333082,0.00004249909,0.0002081156,0.0002340684,0.000001796727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001225257,"about_ca_system_score_gemma":0.00005485956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001205416,"about_ca_topic_score_gemma":0.000002636715,"domain_scores_codex":[0.995155,0.003614405,0.000587085,0.0002710959,0.0001711512,0.0002011991],"domain_scores_gemma":[0.9865671,0.0123725,0.0002473735,0.0005861034,0.0001452654,0.00008169674],"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":[0.0001041013,0.0001566864,0.000001042895,0.00005908691,0.00001276313,1.759204e-7,0.0007298448,0.02668476,0.00015764,0.9110436,0.0007068547,0.06034343],"study_design_scores_gemma":[0.0004701725,0.00001724892,0.00004229222,0.000007013682,0.00003678201,0.000003950218,0.0002458544,0.4825593,0.0000676969,0.5158799,0.0005751659,0.00009467162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004610939,0.0002534945,0.9960807,0.0003529047,0.00005814049,0.0008277622,0.001187148,0.0000763899,0.0007023675],"genre_scores_gemma":[0.04920886,0.00002406588,0.947973,0.0002260188,0.000006999295,0.001866995,0.0004274694,0.00002408993,0.000242471],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4558745,"threshold_uncertainty_score":0.6706395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1350916912304896,"score_gpt":0.5117099661457954,"score_spread":0.3766182749153059,"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."}}