{"id":"W2983552403","doi":"10.5539/ijsp.v8n6p69","title":"Liu Estimator in Semiparametric Partially Linear Varying Coefficient Models","year":2019,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multicollinearity; Estimator; Mathematics; Applied mathematics; Linear model; Minimax estimator; Constant (computer programming); Minimum-variance unbiased estimator; Linear regression; Statistics; Mathematical optimization; Computer science","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":[0.006054835,0.0005312073,0.001119684,0.000988708,0.0002737715,0.001017313,0.001659407,0.0009434494,0.001869537],"category_scores_gemma":[0.0278491,0.0004898242,0.0007318496,0.001119344,0.0007263591,0.002403516,0.001462727,0.001091128,0.0005127137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00052489,"about_ca_system_score_gemma":0.0008928984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001019596,"about_ca_topic_score_gemma":0.0008165541,"domain_scores_codex":[0.9972256,0.001849173,0.00009876886,0.0003312856,0.000368521,0.0001265942],"domain_scores_gemma":[0.9912661,0.006480318,0.0008986881,0.0006919231,0.0005591657,0.0001038427],"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":[0.0002034254,0.00005693184,0.01228541,0.0005198151,0.0004445837,0.0003795975,0.0002735376,0.3248456,0.003738689,0.4803094,0.004055819,0.1728872],"study_design_scores_gemma":[0.00003769474,0.00009279615,0.00174095,0.00007252926,0.00007263676,0.0001449507,0.00003532829,0.8770195,0.001964715,0.114431,0.004346097,0.0000418143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006533056,0.0003224349,0.9924078,0.0001091606,0.00001347203,0.00001733123,0.0000731796,0.00009291005,0.0004306222],"genre_scores_gemma":[0.5441408,0.002289183,0.4461597,0.0004450281,0.000239771,0.0004343283,0.001041139,0.0001879326,0.005062173],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006054835,"threshold_uncertainty_score":0.0320214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08850325187729727,"score_gpt":0.4048892228644734,"score_spread":0.3163859709871761,"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."}}