{"id":"W2537339385","doi":"10.1016/j.spl.2018.08.006","title":"Linear process bootstrap unit root test","year":2018,"lang":"en","type":"article","venue":"Statistics & Probability Letters","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematics; Unit root; Root (linguistics); Statistics; Noise (video); Unit root test; Process (computing); Test (biology); Statistical hypothesis testing; Unit (ring theory); Applied mathematics; Algorithm; Artificial intelligence; Computer science","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":[0.0186379,0.00105793,0.003401096,0.002315637,0.001684113,0.002233363,0.004269022,0.003302876,0.03934457],"category_scores_gemma":[0.1456641,0.0006114659,0.001536505,0.002622257,0.002932884,0.004451791,0.003238043,0.004203489,0.009291629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009418866,"about_ca_system_score_gemma":0.00209919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001174124,"about_ca_topic_score_gemma":0.0008505965,"domain_scores_codex":[0.9796061,0.01381481,0.000535633,0.002791858,0.002446871,0.0008047685],"domain_scores_gemma":[0.8837568,0.0886092,0.003435058,0.01629298,0.006588211,0.001317758],"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":[0.003025038,0.001074834,0.01262774,0.0008235552,0.001225075,0.001064665,0.001052082,0.05529538,0.00355483,0.4889216,0.02954823,0.401787],"study_design_scores_gemma":[0.0006224962,0.0009988014,0.009366309,0.000300759,0.0002947437,0.0006577552,0.0007633256,0.5175539,0.005172503,0.445196,0.01891094,0.000162476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03273114,0.0003277881,0.9553346,0.0006660798,0.000443244,0.0002352294,0.000654113,0.001494622,0.008113182],"genre_scores_gemma":[0.7374084,0.0002690413,0.2417968,0.001097528,0.0007133692,0.001358814,0.002303515,0.001399998,0.01365263],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03934457,"threshold_uncertainty_score":0.1316207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.127591866020806,"score_gpt":0.4052198823765114,"score_spread":0.2776280163557054,"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."}}