{"id":"W2015733689","doi":"10.1016/j.csda.2008.11.015","title":"Strong convergence rate of estimators of change point and its application","year":2008,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Estimator; CUSUM; Mathematics; Rate of convergence; Sequence (biology); Convergence (economics); Moment (physics); Applied mathematics; Point (geometry); Change detection; Statistics; Algorithm; Combinatorics; Computer science; Artificial intelligence; Geometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.04552085,0.002064704,0.003247476,0.005588973,0.001504926,0.003567542,0.004931722,0.004648727,0.004245962],"category_scores_gemma":[0.199125,0.001750436,0.003895115,0.003366222,0.005911057,0.010386,0.007418732,0.00728276,0.001125284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001802363,"about_ca_system_score_gemma":0.002462795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001390326,"about_ca_topic_score_gemma":0.0005528856,"domain_scores_codex":[0.9867115,0.007958644,0.0006217561,0.002045247,0.002138571,0.0005242361],"domain_scores_gemma":[0.7689773,0.1965942,0.005315768,0.01002342,0.01693605,0.002153171],"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":[0.0003041821,0.00008260332,0.004817594,0.0006454911,0.0003257676,0.0004000816,0.0006900216,0.1020295,0.003287315,0.8322294,0.004415117,0.05077284],"study_design_scores_gemma":[0.00004327602,0.0001454324,0.001304604,0.0001183752,0.0001265073,0.0005638315,0.00008246068,0.6554995,0.00277869,0.3350449,0.004204043,0.00008845136],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007021139,0.001561156,0.9877821,0.0008276652,0.0001299308,0.00005471295,0.00008284012,0.0001728261,0.002367577],"genre_scores_gemma":[0.5058808,0.008153035,0.4613385,0.001366159,0.001774557,0.001323964,0.0008257543,0.001106616,0.01823053],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04552085,"threshold_uncertainty_score":0.2407401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3635850956380579,"score_gpt":0.4306854840897243,"score_spread":0.06710038845166644,"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."}}