{"id":"W2993361656","doi":"10.1007/s42519-019-0076-1","title":"Adaptive Estimation Strategies in Gamma Regression Model","year":2019,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Practice","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Estimator; Covariate; Shrinkage estimator; Monte Carlo method; Inference; Estimation; Statistics; Shrinkage; Regression; Nuisance parameter; Regression analysis; Applied mathematics; Econometrics; Efficient estimator; Computer science; Artificial intelligence; Minimum-variance unbiased estimator","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005638825,0.00115816,0.001259505,0.001135269,0.0004751678,0.001464194,0.002614736,0.00157731,0.002169552],"category_scores_gemma":[0.03248684,0.001155819,0.0008962965,0.001229026,0.001313903,0.002872412,0.002497297,0.002341611,0.0006299819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008912231,"about_ca_system_score_gemma":0.00124596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004206366,"about_ca_topic_score_gemma":0.002835119,"domain_scores_codex":[0.9977553,0.001559456,0.00008675238,0.0002731476,0.0002234063,0.000102014],"domain_scores_gemma":[0.9853426,0.01285169,0.0004836436,0.0005615557,0.0006268323,0.0001337817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000176772,0.00006733507,0.001815791,0.0002466441,0.0001746472,0.0002185742,0.0003679535,0.5903236,0.002359457,0.2814133,0.002438144,0.1203978],"study_design_scores_gemma":[0.0000153943,0.00002110649,0.0001877405,0.00002491374,0.00002634285,0.00004266767,0.00001769856,0.9225031,0.0003951332,0.07606351,0.0006862259,0.00001618138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006025574,0.0003224345,0.992703,0.0001688177,0.00001774405,0.00001315957,0.00001748499,0.00008583117,0.0006459742],"genre_scores_gemma":[0.4551782,0.001945682,0.5330405,0.0003545771,0.0001888707,0.0003347613,0.0003025526,0.0003863818,0.008268455],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005638825,"threshold_uncertainty_score":0.02982128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1175635904809021,"score_gpt":0.4810354650668036,"score_spread":0.3634718745859016,"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."}}