{"id":"W2154239282","doi":"10.1111/j.1467-9892.2007.00572.x","title":"Portmanteau tests for ARMA models with infinite variance","year":2008,"lang":"en","type":"article","venue":"Journal of Time Series Analysis","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Mathematics; Autoregressive model; Autoregressive–moving-average model; Series (stratigraphy); Applied mathematics; Variance (accounting); Randomness; Gaussian; Monte Carlo method; Statistics","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":[0.0005243201,0.0001418068,0.0007781228,0.0004949347,0.0001717462,0.00003844026,0.00019998,0.00006865216,0.0001442406],"category_scores_gemma":[0.0001032873,0.0001299597,0.0004501442,0.0007323474,0.00005858375,0.0008051961,0.00002055876,0.0001403058,0.0000171496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005009125,"about_ca_system_score_gemma":0.00006016044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009969564,"about_ca_topic_score_gemma":0.0000388452,"domain_scores_codex":[0.9985811,0.000008533624,0.0009224536,0.0001958193,0.00007205006,0.0002201204],"domain_scores_gemma":[0.9983715,0.0000562632,0.00099656,0.0002279101,0.0002606082,0.00008712016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001513143,0.0003891629,0.2330764,0.0000765162,0.005889751,0.0000965403,0.002512034,0.7133525,0.00007687541,0.03969111,0.002392229,0.0009337331],"study_design_scores_gemma":[0.001914205,0.001238491,0.04876968,0.00006178264,0.001277298,0.0002083359,0.0001226559,0.8391492,0.00009156036,0.07671785,0.02962412,0.0008247652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3754869,0.001875363,0.6194965,0.0005739605,0.00008302661,0.0001090932,0.0001143053,0.00001393751,0.002246958],"genre_scores_gemma":[0.9564186,0.0008550356,0.04037167,0.00009450891,0.0001590575,0.000003972987,0.000009051407,0.00002007023,0.002068036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5809317,"threshold_uncertainty_score":0.5299603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04031938970019313,"score_gpt":0.224571353257446,"score_spread":0.1842519635572528,"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."}}