{"id":"W3123357942","doi":"10.2139/ssrn.3133077","title":"Negative Binomial Autoregressive Process","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; Center for Interuniversity Research and Analysis on Organizations; University of Toronto","funders":"","keywords":"Autoregressive model; Mathematics; Univariate; SETAR; Negative binomial distribution; STAR model; Bivariate analysis; Estimator; Econometrics; Statistics; Wishart distribution; Overdispersion; Autoregressive integrated moving average; Applied mathematics; Time series; Multivariate statistics; Poisson distribution","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":[0.0004453277,0.0001136755,0.00012999,0.00005202469,0.0003735474,0.0000486767,0.0001920793,0.00005472811,0.0003613829],"category_scores_gemma":[0.00095984,0.00009333251,0.00005385703,0.0001687236,0.0001778518,0.000114399,0.00001557881,0.0006835739,0.0002361912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004249293,"about_ca_system_score_gemma":0.001161596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004358763,"about_ca_topic_score_gemma":0.00006549805,"domain_scores_codex":[0.998323,0.00004737195,0.0002580235,0.0001449701,0.0002201953,0.001006422],"domain_scores_gemma":[0.9990336,0.000182303,0.0001950636,0.0001210402,0.0003707685,0.00009717483],"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":[0.00002069152,0.00006086437,0.00003427607,0.000003558815,0.00003894901,5.646378e-7,0.000210296,6.926472e-7,0.00004307723,0.9933152,0.00128882,0.004983061],"study_design_scores_gemma":[0.0004545687,0.0001390392,0.0004021283,0.0000138723,0.00003056205,0.0001247601,0.0008082248,0.0009309381,0.0006465645,0.9958513,0.0004827894,0.0001152428],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06789052,0.00003677279,0.9232279,0.001344817,0.0001318175,0.0002030497,0.00003507481,0.0001005681,0.007029485],"genre_scores_gemma":[0.9962729,0.00002369286,0.002027422,0.00008375003,0.0004472678,0.00002126084,0.000006751823,0.0000150955,0.001101907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9283823,"threshold_uncertainty_score":0.3956889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03146420695060119,"score_gpt":0.3717411777322929,"score_spread":0.3402769707816917,"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."}}