{"id":"W4312164547","doi":"10.1002/cjs.11755","title":"Asymptotic distribution of one‐component partial least squares regression estimators in high dimensions","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidad Nacional del Litoral; Fondo para la Investigación Científica y Tecnológica; Consejo Nacional de Investigaciones Científicas y Técnicas","keywords":"Mathematics; Asymptotic distribution; Estimator; Partial least squares regression; Statistics; Linear regression; Univariate; Applied mathematics; Regression analysis; Asymptotic analysis; Confidence interval; Least-squares function approximation; Linear model; Infinity; Multivariate statistics; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02615768,0.0008084972,0.001255061,0.001654553,0.0006269732,0.001553886,0.001925046,0.001101992,0.00187979],"category_scores_gemma":[0.1804443,0.0006169092,0.0007662438,0.001439258,0.003473585,0.00339591,0.002288138,0.002586904,0.0005815164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00125218,"about_ca_system_score_gemma":0.001208048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003100397,"about_ca_topic_score_gemma":0.001511168,"domain_scores_codex":[0.9926546,0.004573222,0.0003069938,0.0007578891,0.001473962,0.0002333576],"domain_scores_gemma":[0.8449345,0.1293086,0.003865935,0.01088189,0.01034874,0.000660479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003626521,0.0001846741,0.02152022,0.0005639992,0.0002453455,0.0005552653,0.000788226,0.5095895,0.005620454,0.3333271,0.004386313,0.1228563],"study_design_scores_gemma":[0.00002358418,0.00006963647,0.005287572,0.00007774521,0.00002596813,0.0002212509,0.0001027147,0.8896481,0.001557275,0.1019996,0.0009333363,0.0000530834],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04031942,0.0004869163,0.9565849,0.0003468112,0.0000341819,0.00004491678,0.0001137994,0.0005443801,0.00152461],"genre_scores_gemma":[0.8302856,0.0007361188,0.1654898,0.0002468962,0.0001238628,0.0003324211,0.0007617217,0.0004154875,0.001608104],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02615768,"threshold_uncertainty_score":0.1383367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01700833823382478,"score_gpt":0.2453101476248169,"score_spread":0.2283018093909921,"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."}}