{"id":"W3124894030","doi":"10.3982/qe994","title":"A persistence‐based Wold‐type decomposition for stationary time series","year":2020,"lang":"en","type":"article","venue":"Quantitative Economics","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Series (stratigraphy); Scaling; Persistence (discontinuity); Decomposition; Uncorrelated; Representation (politics); Mathematics; Time series; Variance decomposition of forecast errors; Operator (biology); Variance (accounting); Econometrics; Type (biology); Applied mathematics; Stationary process; Statistical physics; Computer science; Statistics; Economics; Physics; Engineering; Ecology; Biology; Accounting","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":[0.00110002,0.0005126455,0.0004469416,0.001104748,0.0002693083,0.001124833,0.0003975838,0.0004243833,0.00163238],"category_scores_gemma":[0.002732143,0.0002243881,0.0008781998,0.0008395475,0.0007997794,0.001403206,0.001121869,0.001140547,0.0003334644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003751389,"about_ca_system_score_gemma":0.0005123793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006684079,"about_ca_topic_score_gemma":0.0005642984,"domain_scores_codex":[0.9996116,0.000104182,0.00003697388,0.00009878525,0.0001000903,0.0000484417],"domain_scores_gemma":[0.9992647,0.0002300792,0.0001285463,0.000119885,0.0001752951,0.00008149398],"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":[0.00006551181,0.00005352806,0.003390556,0.0001872683,0.0001035884,0.000253417,0.0003365098,0.06302521,0.01910994,0.7961174,0.002196986,0.1151602],"study_design_scores_gemma":[0.00001087551,0.00005764174,0.002522816,0.0000425206,0.00003268828,0.0001462794,0.00008308933,0.5832967,0.001999896,0.4057134,0.006048854,0.00004529274],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01752496,0.0001900429,0.9805791,0.0001370408,0.00004683863,0.00001624192,0.0001032799,0.00004015968,0.00136228],"genre_scores_gemma":[0.4975165,0.001317959,0.492637,0.0002248606,0.0002560164,0.0001483982,0.0006359483,0.000160086,0.007103178],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00163238,"threshold_uncertainty_score":0.005817533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1125214000487121,"score_gpt":0.2727579902159227,"score_spread":0.1602365901672106,"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."}}