{"id":"W2790849781","doi":"10.1002/asmb.2324","title":"Time series with Birnbaum‐Saunders marginal distributions","year":2018,"lang":"en","type":"article","venue":"Applied Stochastic Models in Business and Industry","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; American Society for Metabolic and Bariatric Surgery","keywords":"Autoregressive model; Estimator; Series (stratigraphy); Mathematics; Statistics; Sequence (biology); Marginal distribution; Maximum likelihood; Applied mathematics; Marginal likelihood; Gaussian; Econometrics; Random variable","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":[],"consensus_categories":[],"category_scores_codex":[0.0001113948,0.0001923874,0.0002278551,0.00007158487,0.0002485777,0.0000546533,0.0001089771,0.0002083089,0.0003131531],"category_scores_gemma":[0.0000905307,0.0001657374,0.00001219784,0.0005766086,0.000703272,0.0001551098,0.00005322133,0.0002796228,0.00003508795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005386439,"about_ca_system_score_gemma":0.00009075778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001566411,"about_ca_topic_score_gemma":0.0000142195,"domain_scores_codex":[0.99893,0.00001220739,0.0002786803,0.0003062348,0.000193029,0.0002798311],"domain_scores_gemma":[0.9992229,0.000148873,0.00008706703,0.0002352087,0.000189497,0.0001164807],"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":[0.00006124339,0.0001115448,0.000009472784,0.00002538648,0.00001113348,0.000001288431,0.00007151019,0.0007691846,0.00005756817,0.9972703,0.0009628265,0.0006485654],"study_design_scores_gemma":[0.001826197,0.00006748179,0.005311742,0.0001573221,0.00008128573,0.00005990904,0.0004949283,0.07363427,0.00008585401,0.917479,0.0002456678,0.0005563577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04417869,0.000004853005,0.9483367,0.001041612,0.00002102727,0.0003205298,0.0002175854,0.00008704023,0.005791912],"genre_scores_gemma":[0.9872985,0.000001202575,0.01200459,0.00007281891,0.00007159365,0.0001927887,0.0001119246,0.00001993243,0.0002266275],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9431198,"threshold_uncertainty_score":0.6758577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04657574737155369,"score_gpt":0.2927811226496654,"score_spread":0.2462053752781117,"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."}}