{"id":"W2744160819","doi":"10.1016/j.cam.2017.07.017","title":"Computing moments of discrete order statistics from non-identical distributions","year":2017,"lang":"en","type":"article","venue":"Journal of Computational and Applied Mathematics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Narodowe Centrum Nauki","keywords":"Mathematics; Geometric distribution; L-moment; Independent and identically distributed random variables; Order statistic; Beta-binomial distribution; Inverse distribution; Binomial (polynomial); Random variable; Negative binomial distribution; Distribution (mathematics); Moment (physics); Applied mathematics; Statistics; Binomial distribution; Probability distribution; Heavy-tailed distribution; Mathematical analysis; Poisson distribution","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":[0.002258692,0.0005999111,0.001340395,0.001528097,0.0004559355,0.002050373,0.00153415,0.001002585,0.00130667],"category_scores_gemma":[0.0223354,0.0008328362,0.0009619926,0.001419552,0.001183,0.003071145,0.001888406,0.001467176,0.0003674561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008668937,"about_ca_system_score_gemma":0.001133069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001472189,"about_ca_topic_score_gemma":0.002060315,"domain_scores_codex":[0.9989043,0.0003105534,0.0001055092,0.0001651762,0.0003876819,0.0001266423],"domain_scores_gemma":[0.9842971,0.01279104,0.0008482512,0.001108265,0.0005771035,0.000378257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009155294,0.0001802822,0.008394114,0.0002975859,0.0002437841,0.0007084739,0.0003254017,0.6977623,0.01131246,0.1104977,0.001927097,0.1674353],"study_design_scores_gemma":[0.00001305427,0.00002595775,0.0005705571,0.000007046582,0.00001179345,0.00008098559,0.00002376748,0.9495586,0.001428585,0.04804282,0.0002233073,0.00001353541],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07794231,0.0002128861,0.9207755,0.0001335816,0.00003814599,0.00002042199,0.00008909816,0.0003730919,0.0004149427],"genre_scores_gemma":[0.7603909,0.0003894402,0.2370536,0.00008447316,0.0001580068,0.00005973968,0.0006222147,0.0001541182,0.001087491],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002258692,"threshold_uncertainty_score":0.01194525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04099113513215838,"score_gpt":0.3622980584013075,"score_spread":0.3213069232691491,"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."}}