{"id":"W3122206612","doi":"10.26180/21521490","title":"Asymptotic Properties of Approximate Bayesian Computation","year":2016,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Markov Chains and Monte Carlo Methods","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Approximate Bayesian computation; Posterior probability; Bayesian probability; Computation; Limiting; Mathematics; Applied mathematics; Posterior predictive distribution; Distribution (mathematics); Asymptotic distribution; Statistics; Computer science; Bayesian inference; Bayesian linear regression; Artificial intelligence; Algorithm; Mathematical analysis; Engineering","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":[0.01890397,0.0008637971,0.001892146,0.003122882,0.001267844,0.004338918,0.002732202,0.002235419,0.005065066],"category_scores_gemma":[0.2004213,0.0009304141,0.001190555,0.002457542,0.005703692,0.006792834,0.004506542,0.004350512,0.0009885535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002828142,"about_ca_system_score_gemma":0.002204456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002863676,"about_ca_topic_score_gemma":0.001335762,"domain_scores_codex":[0.9894238,0.005354482,0.0004869096,0.001110628,0.003126626,0.0004976655],"domain_scores_gemma":[0.852584,0.1238501,0.005034924,0.009684185,0.007730344,0.001116406],"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":[0.00008766789,0.00002451779,0.002044146,0.0001766264,0.00005082865,0.0000907325,0.0002951861,0.0814923,0.0007976161,0.8923891,0.001353052,0.02119829],"study_design_scores_gemma":[0.0000167876,0.00004179877,0.0007925034,0.0001072563,0.00002008823,0.0001457371,0.00005527118,0.4702349,0.0006332063,0.525674,0.002251461,0.00002693877],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02307546,0.001327332,0.9641769,0.001244985,0.00005817223,0.00007422623,0.0001852416,0.000336557,0.009521121],"genre_scores_gemma":[0.7294377,0.003343981,0.2549952,0.00115988,0.0005982526,0.0008514451,0.0009091509,0.0008321017,0.007872218],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01890397,"threshold_uncertainty_score":0.09997493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03452658436828475,"score_gpt":0.2649957237957925,"score_spread":0.2304691394275077,"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."}}