{"id":"W3202523284","doi":"10.1002/cjs.11661","title":"Robust estimation and variable selection for function‐on‐scalar regression","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Mathematics; Estimator; Least absolute deviations; Scalar (mathematics); Robustness (evolution); Applied mathematics; Regression analysis; Regression; Feature selection; Statistics; Mathematical optimization; Algorithm; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.009634485,0.002025958,0.002027929,0.001399673,0.000599455,0.001099814,0.002063216,0.001617668,0.002027342],"category_scores_gemma":[0.02539602,0.0007464966,0.001683084,0.001473701,0.001768654,0.001638007,0.001807686,0.002483021,0.000809953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007417526,"about_ca_system_score_gemma":0.001700851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002425551,"about_ca_topic_score_gemma":0.00172879,"domain_scores_codex":[0.995402,0.003083518,0.0001464844,0.0006457032,0.0005591225,0.0001631997],"domain_scores_gemma":[0.9916025,0.006029798,0.0006308326,0.0007964644,0.0008289673,0.0001113815],"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":[0.0002434823,0.0001162812,0.001900562,0.0002965548,0.0003556418,0.00021628,0.0001095913,0.7063623,0.007288398,0.1155762,0.002870245,0.1646644],"study_design_scores_gemma":[0.00002099183,0.00005064209,0.0003235968,0.00001196836,0.00001776535,0.00003118009,0.000006006271,0.9795877,0.001358671,0.01774899,0.0008225858,0.00001997454],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001729313,0.0001182321,0.997827,0.00005540131,0.00001084396,0.00001839019,0.00002492638,0.0001143097,0.0001015393],"genre_scores_gemma":[0.2463912,0.001038101,0.7478065,0.0002520225,0.0002544085,0.0005763572,0.0007635318,0.0003417354,0.002576143],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009634485,"threshold_uncertainty_score":0.05095261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1040892775418899,"score_gpt":0.3171644884129491,"score_spread":0.2130752108710593,"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."}}