{"id":"W2605685194","doi":"10.1002/env.2445","title":"Goodness‐of‐fit tests for copula‐based spatial models","year":2017,"lang":"en","type":"article","venue":"Environmetrics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Copula (linguistics); Goodness of fit; Bivariate analysis; Random field; Spatial dependence; Statistics; Parametric statistics; Spatial analysis; Mathematics; Statistic; Econometrics; Multivariate statistics; Test statistic; Computer science; Statistical hypothesis testing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.04555954,0.001459079,0.002299415,0.007091612,0.001046895,0.002690568,0.003606256,0.002981378,0.004357797],"category_scores_gemma":[0.2862355,0.0006440173,0.003378216,0.00535106,0.004764488,0.006017689,0.004050904,0.00323661,0.0008785278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001164632,"about_ca_system_score_gemma":0.001236982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00101373,"about_ca_topic_score_gemma":0.0006753577,"domain_scores_codex":[0.9562953,0.03444279,0.001723855,0.002631464,0.004207934,0.000698607],"domain_scores_gemma":[0.5687007,0.3942714,0.01106387,0.01844932,0.005389517,0.002125187],"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":[0.001589312,0.0004980483,0.1654315,0.0009943338,0.004104254,0.00121908,0.001152856,0.4514823,0.002493804,0.1874143,0.005709951,0.1779104],"study_design_scores_gemma":[0.0001390557,0.0009504074,0.03456711,0.0001409682,0.000185544,0.0006699123,0.0006014013,0.7986464,0.001398744,0.1601297,0.002438155,0.0001325297],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.138609,0.0007247517,0.8553499,0.0006439945,0.0001063035,0.0002088535,0.0007502421,0.0007275723,0.00287946],"genre_scores_gemma":[0.9004267,0.0003320482,0.09586304,0.0001919502,0.0001551163,0.0005296127,0.001851351,0.0002573915,0.0003926229],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04555954,"threshold_uncertainty_score":0.2409447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1815350213898136,"score_gpt":0.2746156126284441,"score_spread":0.0930805912386305,"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."}}