{"id":"W2166484257","doi":"10.22004/ag.econ.273539","title":"Nested Pseudo-likelihood Estimation and Bootstrap-based Inference for Structural Discrete Markov Decision Models","year":2006,"lang":"en","type":"preprint","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Western University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Estimator; Mathematics; Inference; Point estimation; Parametric statistics; Markov chain; Mathematical optimization; Markov chain Monte Carlo; Computer science; Applied mathematics; Econometrics; Monte Carlo method; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005774907,0.0003487896,0.0004984756,0.0006458582,0.000395706,0.0002645268,0.0005202031,0.0002806324,0.0002000146],"category_scores_gemma":[0.00006713316,0.0004152716,0.0002080538,0.0002753479,0.0001960307,0.001227101,0.0008030966,0.0003846168,0.000008978556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005588013,"about_ca_system_score_gemma":0.0001350619,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008202184,"about_ca_topic_score_gemma":0.003273924,"domain_scores_codex":[0.9981551,0.00003921477,0.0002994827,0.0006530383,0.0004284673,0.00042469],"domain_scores_gemma":[0.9983249,0.0003889057,0.000367313,0.0004440672,0.0004276191,0.00004716207],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001403052,0.0001281858,0.1283364,0.004012701,0.0001553785,0.00007990363,0.0004702625,0.0224898,0.0006844351,0.001322731,0.002432363,0.8384848],"study_design_scores_gemma":[0.001422794,0.00002349034,0.2053163,0.0003503515,0.0002808344,0.000001388943,0.0002204879,0.785062,0.00001915269,0.006580851,0.0002650111,0.0004573334],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9105843,0.00007617657,0.08696929,0.0003393536,0.0001723924,0.0008286057,0.0001247756,0.00006146652,0.0008436289],"genre_scores_gemma":[0.9851564,0.0000316902,0.01389905,0.00004006426,0.00008094405,0.0000033216,0.0005723875,0.00002894223,0.0001872165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8380274,"threshold_uncertainty_score":0.9998299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0400148362788875,"score_gpt":0.2750506196843744,"score_spread":0.2350357834054869,"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."}}