{"id":"W1519898186","doi":"","title":"Time Series of Correlated Count Data usingMultifractal Process","year":2013,"lang":"en","type":"article","venue":"","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Count data; Series (stratigraphy); Multifractal system; Property (philosophy); Econometrics; Poisson distribution; Mathematics; Term (time); Process (computing); Statistics; Applied mathematics; Statistical physics; Computer science; Fractal; Mathematical analysis; Physics","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":[0.007191183,0.001100483,0.001691996,0.003089118,0.0008316015,0.002369793,0.002825011,0.002402007,0.003625927],"category_scores_gemma":[0.02222325,0.0008680575,0.002120713,0.003782632,0.001740957,0.004371776,0.001959163,0.002253699,0.0006666651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001736891,"about_ca_system_score_gemma":0.000852862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008138639,"about_ca_topic_score_gemma":0.004999492,"domain_scores_codex":[0.9963773,0.001184072,0.0002610499,0.0010587,0.0008278651,0.0002910007],"domain_scores_gemma":[0.9881167,0.006114298,0.002872482,0.00144281,0.001158003,0.0002956629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001693094,0.000144748,0.02914054,0.000363321,0.0004173506,0.001551732,0.0008230498,0.439264,0.003387222,0.4806608,0.002519648,0.04155833],"study_design_scores_gemma":[0.0000152729,0.00003294645,0.003687429,0.00002570239,0.00004929578,0.0001736622,0.00004598511,0.9557579,0.000331333,0.03858434,0.001250701,0.00004539288],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1390645,0.001054169,0.855971,0.0008344503,0.0001768821,0.0001383444,0.0008639849,0.0003350922,0.001561606],"genre_scores_gemma":[0.9158494,0.001899763,0.07202687,0.0002472929,0.0004396747,0.0003500128,0.002149026,0.0001054322,0.006932584],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008138639,"threshold_uncertainty_score":0.03803104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0501894301175398,"score_gpt":0.2411424770339112,"score_spread":0.1909530469163714,"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."}}