{"id":"W140397586","doi":"","title":"Efficient computations of multivariate normal distributions with applications to finance","year":2006,"lang":"en","type":"article","venue":"international conference on Modelling and simulation","topic":"Mathematical Approximation and Integration","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Monte Carlo method; Multivariate statistics; Multivariate normal distribution; Bivariate analysis; Computation; Dimension (graph theory); Quasi-Monte Carlo method; Mathematics; Statistical physics; Applied mathematics; Computer science; Hybrid Monte Carlo; Statistics; Algorithm; Markov chain Monte Carlo; Physics; Combinatorics","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":[0.002539015,0.0008844083,0.001377466,0.001558446,0.0006997345,0.001417431,0.001102687,0.0008919133,0.004287784],"category_scores_gemma":[0.01517022,0.0005310326,0.000993529,0.001915628,0.001032417,0.002399701,0.001627072,0.001710319,0.001010189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001036897,"about_ca_system_score_gemma":0.001523194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004432488,"about_ca_topic_score_gemma":0.003518537,"domain_scores_codex":[0.9987499,0.0005496566,0.0000761395,0.0001333785,0.0003837375,0.0001071707],"domain_scores_gemma":[0.9945963,0.00383785,0.0003104071,0.0004326848,0.0006552182,0.0001676516],"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":[0.0001012119,0.00004459831,0.001306784,0.00009352965,0.00004651798,0.0001649132,0.00008524211,0.7392197,0.001307465,0.1909157,0.001842124,0.06487216],"study_design_scores_gemma":[0.00001016414,0.000007065866,0.0001074089,0.0000107665,0.000003422951,0.00003610001,0.000008937212,0.9294894,0.0003359248,0.06886606,0.001117436,0.000007316872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005915431,0.0003966948,0.9914035,0.0002182976,0.00004579542,0.00001913872,0.0000465592,0.0003605777,0.001593992],"genre_scores_gemma":[0.2622252,0.001523175,0.7315091,0.0001685967,0.0001748508,0.0001971537,0.0003181685,0.0004107671,0.003472902],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004432488,"threshold_uncertainty_score":0.01434404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07752930368175344,"score_gpt":0.3444703074842387,"score_spread":0.2669410038024853,"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."}}