{"id":"W2016394018","doi":"10.1016/j.spl.2004.11.013","title":"Ergodicity and existence of moments for local mixtures of linear autoregressions","year":2005,"lang":"en","type":"article","venue":"Statistics & Probability Letters","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mathematics; Ergodicity; Mixing (physics); Applied mathematics; Nonlinear system; Probabilistic logic; Class (philosophy); Autoregressive model; Series (stratigraphy); Mathematical analysis; Focus (optics); Econometrics; 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":[0.0005335922,0.0001320293,0.000276814,0.00004961788,0.00007140911,0.00001400491,0.0003536017,0.00005544191,0.000003275861],"category_scores_gemma":[0.0001937609,0.0001114167,0.00004987832,0.0001094729,0.0004022151,0.0001221752,0.0001328326,0.00009999969,3.465614e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003302115,"about_ca_system_score_gemma":0.00005795136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004235623,"about_ca_topic_score_gemma":0.00001951071,"domain_scores_codex":[0.9987072,0.0001146012,0.0003929849,0.0003467889,0.0002231212,0.0002152458],"domain_scores_gemma":[0.99878,0.0003790262,0.0001783036,0.0004270136,0.0001443696,0.00009135729],"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":[0.00003758574,0.0002088882,0.0006804439,0.0004608025,0.00003458078,0.00000158534,0.00130794,0.0001132293,0.01139068,0.8235336,0.002384491,0.1598462],"study_design_scores_gemma":[0.0006897055,0.000221653,0.003092069,0.00009830456,0.00003574533,0.000005000379,0.000002346043,0.1266591,0.01138565,0.8564748,0.001078286,0.0002573968],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0150541,0.00008169942,0.9820675,0.002127827,0.00008644718,0.0003534875,0.0001829791,0.00002252106,0.00002343458],"genre_scores_gemma":[0.07071848,0.000008576018,0.9287809,0.0004207792,0.00002749662,0.00001846513,0.00000685221,0.000006027653,0.00001242498],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1595888,"threshold_uncertainty_score":0.4543442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02252282497166945,"score_gpt":0.2920834183770067,"score_spread":0.2695605934053373,"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."}}