{"id":"W2963283068","doi":"10.48550/arxiv.1511.04903","title":"The tail empirical process of regularly varying functions of geometrically ergodic Markov chains","year":2015,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Labex","keywords":"Mathematics; Ergodic theory; Stationary ergodic process; Markov chain; Counterexample; Series (stratigraphy); Ergodicity; Estimator; Weak convergence; Markov process; Applied mathematics; Convergence (economics); Statistical physics; Mathematical analysis; Discrete mathematics; Statistics; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.004971611,0.0009959599,0.0008740349,0.002023119,0.0007944908,0.001697868,0.002151216,0.001591605,0.003297659],"category_scores_gemma":[0.0228457,0.0005758442,0.0009437878,0.001010545,0.004212556,0.003266246,0.001748089,0.002137892,0.0005277055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001802443,"about_ca_system_score_gemma":0.001087665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004327882,"about_ca_topic_score_gemma":0.002797768,"domain_scores_codex":[0.9991085,0.0003538335,0.00002844915,0.0001948811,0.0001646376,0.0001497031],"domain_scores_gemma":[0.989916,0.006833843,0.001332149,0.0006618407,0.0007364519,0.0005195776],"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":[0.00009024209,0.00005823284,0.004757783,0.00009159687,0.00005276983,0.0003473253,0.0003967186,0.1866632,0.003815126,0.7955791,0.0009341107,0.007213775],"study_design_scores_gemma":[0.00001134755,0.00002733225,0.001093482,0.00002300201,0.00001822885,0.00005855481,0.00005255592,0.8548129,0.001024054,0.1424656,0.000376716,0.00003620575],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3632287,0.0005557659,0.6305608,0.0008767857,0.00006802424,0.0000608238,0.0001904877,0.0003133099,0.004145395],"genre_scores_gemma":[0.9700509,0.000774967,0.02232125,0.0001407905,0.0001161823,0.0001179328,0.0002691876,0.0001167453,0.00609202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004971611,"threshold_uncertainty_score":0.02629268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2356702024121475,"score_gpt":0.291762896224996,"score_spread":0.05609269381284857,"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."}}