{"id":"W2025168569","doi":"10.1016/j.jmva.2008.08.005","title":"Monitoring parameter change in<mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si50.gif\" display=\"inline\" overflow=\"scroll\"><mml:mstyle mathvariant=\"normal\"><mml:mi>AR</mml:mi></mml:mstyle><mml:mrow><mml:mo>(</mml:mo><mml:mi>p</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math>time series models","year":2008,"lang":"lv","type":"article","venue":"Journal of Multivariate Analysis","topic":"Advanced Statistical Process Monitoring","field":"Decision Sciences","cited_by":83,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"CUSUM; Autoregressive model; Mathematics; Scroll; Series (stratigraphy); Algorithm; Statistics; Autoregressive–moving-average model; Applied mathematics","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":[0.00184647,0.0009034876,0.0007449645,0.001998736,0.000321618,0.001884193,0.0008438962,0.00113859,0.01571006],"category_scores_gemma":[0.018491,0.0003567374,0.0006138989,0.001776795,0.0002729253,0.00204335,0.0009457939,0.001710933,0.007019605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006646041,"about_ca_system_score_gemma":0.0009511464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007222068,"about_ca_topic_score_gemma":0.004913114,"domain_scores_codex":[0.9986216,0.00022359,0.0000848669,0.0004405523,0.00054173,0.00008766347],"domain_scores_gemma":[0.9952342,0.001936066,0.0006472873,0.00119507,0.0008341467,0.000153171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001943386,0.0008682761,0.1049913,0.0005377641,0.0004132909,0.0005459759,0.0008932498,0.1293548,0.04992333,0.01716069,0.08401845,0.6093495],"study_design_scores_gemma":[0.00005192307,0.0003877548,0.04050442,0.00007110673,0.0001077077,0.0003149661,0.000181824,0.8594584,0.06455728,0.0113315,0.02287693,0.000156089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.261733,0.0003909902,0.6489722,0.001354121,0.0004472193,0.0004202441,0.02818064,0.03601346,0.0224881],"genre_scores_gemma":[0.8280355,0.0003700113,0.1300143,0.0002688557,0.0001293619,0.0004417484,0.0212589,0.002323723,0.01715748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01571006,"threshold_uncertainty_score":0.05255538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04217043394014507,"score_gpt":0.2981876160440374,"score_spread":0.2560171821038923,"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."}}