{"id":"W4220710361","doi":"10.1007/s13253-022-00495-1","title":"Robust Functional Principal Component Analysis Based on a New Regression Framework","year":2022,"lang":"en","type":"article","venue":"Journal of Agricultural Biological and Environmental Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Functional principal component analysis; Outlier; Functional data analysis; Principal component analysis; Robust regression; Regression; Estimator; Computer science; Robust statistics; Regression analysis; Principal component regression; Covariate; Data mining; Artificial intelligence; Mathematics; Statistics; Machine learning","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":[0.002674358,0.001556006,0.001344112,0.00129189,0.0004613931,0.001386239,0.001775399,0.0009920072,0.002058752],"category_scores_gemma":[0.005762847,0.0006112727,0.001609684,0.001394027,0.0009445462,0.00182692,0.001445873,0.001777427,0.001033103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005077443,"about_ca_system_score_gemma":0.001386005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003060617,"about_ca_topic_score_gemma":0.002998888,"domain_scores_codex":[0.9985267,0.0006504452,0.00008534043,0.0003051144,0.0003500119,0.00008237149],"domain_scores_gemma":[0.998291,0.0006757553,0.0001788268,0.0002546703,0.0005357771,0.00006398921],"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":[0.0002343289,0.0001494072,0.001063231,0.000279694,0.000357422,0.000152699,0.0001068191,0.4985594,0.0200313,0.225807,0.004818099,0.2484407],"study_design_scores_gemma":[0.000007280775,0.00003042859,0.0003044445,0.00000736518,0.00002878466,0.00003349224,0.000004894393,0.9822931,0.0009081493,0.01469726,0.001658847,0.00002600078],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001268599,0.00008447637,0.9982861,0.00004103757,0.00002314213,0.000006597093,0.00003258607,0.00009080156,0.000166716],"genre_scores_gemma":[0.115629,0.0007293859,0.877547,0.00009516074,0.0002377357,0.0001900995,0.0006034567,0.000529572,0.004438518],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003060617,"threshold_uncertainty_score":0.01414353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1091095235144707,"score_gpt":0.31435489049368,"score_spread":0.2052453669792093,"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."}}