{"id":"W3123166771","doi":"10.22004/ag.econ.273632","title":"Empirical Likelihood Block Bootstrapping","year":2008,"lang":"en","type":"preprint","venue":"Econstor (Econstor)","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Bank of Canada","funders":"Queen's University","keywords":"Bootstrapping (finance); Moment (physics); Monte Carlo method; Mathematics; Resampling; Multinomial distribution; Inference; Empirical likelihood; Applied mathematics; Edgeworth series; Asymptotic analysis; Statistics; Series (stratigraphy); Econometrics; Estimator; Computer science; Artificial intelligence","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":[0.01011483,0.0006207932,0.001476482,0.001562229,0.0007694194,0.001495056,0.001933702,0.001396893,0.01241091],"category_scores_gemma":[0.0858098,0.0005382423,0.0009190294,0.002310521,0.001320884,0.00225062,0.002178587,0.002366804,0.00393352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008315698,"about_ca_system_score_gemma":0.00164795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002777441,"about_ca_topic_score_gemma":0.002102778,"domain_scores_codex":[0.9904978,0.007039707,0.0002363413,0.0006490655,0.001294656,0.0002823934],"domain_scores_gemma":[0.9748321,0.01699465,0.001063496,0.00491546,0.001908382,0.0002859526],"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":[0.0004218752,0.0002059034,0.005501064,0.0003207404,0.0002392292,0.0003827005,0.0004611035,0.1104089,0.002785578,0.5562865,0.01203168,0.3109547],"study_design_scores_gemma":[0.0001428212,0.0001109957,0.002958178,0.00009441261,0.00004583386,0.0002116961,0.00006223407,0.6330934,0.002138973,0.3428144,0.01827943,0.00004765995],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008584413,0.0002505995,0.9856653,0.0002612793,0.00005335978,0.000183657,0.0002263317,0.0004774233,0.004297667],"genre_scores_gemma":[0.2561769,0.0004978467,0.7345616,0.0002642094,0.0001535376,0.001085823,0.001163417,0.0004947655,0.005601821],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01241091,"threshold_uncertainty_score":0.05349296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09914387566844492,"score_gpt":0.3627146959792519,"score_spread":0.263570820310807,"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."}}