{"id":"W2950697494","doi":"10.48550/arxiv.1405.5786","title":"Empirical phi-divergence test statistics for testing simple and composite null hypotheses","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Statistics; Mathematics; Likelihood-ratio test; Test statistic; Score test; Divergence (linguistics); Statistical hypothesis testing; Empirical likelihood; Likelihood principle; Null distribution; Null hypothesis; Null (SQL); Statistic; Pearson's chi-squared test; Alternative hypothesis; Likelihood function; Confidence interval; Estimation theory; Computer science; Quasi-maximum likelihood; Data mining","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":[0.01690078,0.001141172,0.001610454,0.003937821,0.0007673969,0.002082825,0.002506079,0.001955605,0.005029929],"category_scores_gemma":[0.1341938,0.0004271572,0.001111733,0.00361636,0.00347832,0.005035583,0.002907332,0.003961933,0.001125762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009170002,"about_ca_system_score_gemma":0.001699485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005170804,"about_ca_topic_score_gemma":0.0003251453,"domain_scores_codex":[0.9867346,0.007387291,0.0006828216,0.00139534,0.003557462,0.0002425005],"domain_scores_gemma":[0.9002565,0.08360326,0.004528427,0.005796101,0.005106021,0.0007097385],"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":[0.0003051051,0.0001951679,0.02040106,0.000848003,0.0004114654,0.000533372,0.0004956971,0.07703272,0.004204033,0.6507455,0.004917695,0.2399102],"study_design_scores_gemma":[0.0001339221,0.0005594724,0.009174621,0.000289551,0.00009704055,0.001541248,0.0003907349,0.3947127,0.004758135,0.573505,0.01466826,0.0001693153],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00904702,0.0005424087,0.9878339,0.0001646183,0.00006657223,0.00009960419,0.0001830176,0.0001684336,0.001894506],"genre_scores_gemma":[0.2709576,0.001201652,0.722732,0.0003922729,0.0003627045,0.001321426,0.001275886,0.0002140042,0.001542437],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01690078,"threshold_uncertainty_score":0.08938092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4051031826802647,"score_gpt":0.3489198046871,"score_spread":0.0561833779931647,"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."}}