{"id":"W3080136927","doi":"10.1002/cjs.11565","title":"Estimation of nonparametric additive models with high order spatial autoregressive errors","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Estimator; Nonparametric statistics; Autoregressive model; Asymptotic distribution; Mathematics; Additive model; Applied mathematics; Nonparametric regression; Asymptotic analysis; Consistency (knowledge bases); Moment (physics); Econometrics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005082026,0.0006203892,0.000968643,0.001141813,0.000244654,0.001059603,0.001853104,0.0007850574,0.0008496253],"category_scores_gemma":[0.01737778,0.0004488112,0.001080635,0.001334337,0.0009957815,0.001006606,0.001647089,0.001294588,0.0001726958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005590533,"about_ca_system_score_gemma":0.0009436691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003172773,"about_ca_topic_score_gemma":0.003399716,"domain_scores_codex":[0.9967733,0.002273423,0.00008841015,0.0002453644,0.0005037776,0.0001156929],"domain_scores_gemma":[0.9921996,0.005597048,0.0008689932,0.0007360041,0.000516067,0.00008229019],"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":[0.00007491713,0.00007216717,0.004522366,0.0001202695,0.0002224661,0.0001657598,0.0001316144,0.8038617,0.001978089,0.1127866,0.0007574007,0.07530664],"study_design_scores_gemma":[0.000005231337,0.00001479943,0.0006101287,0.000007473546,0.000009445636,0.00001913845,0.000009621993,0.9775202,0.0003137616,0.02108602,0.0003940554,0.00001025955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01232023,0.00007599578,0.987242,0.00005273299,0.000008624497,0.000009199792,0.00002798081,0.00006626725,0.0001970045],"genre_scores_gemma":[0.6413141,0.0003846182,0.3556137,0.00008328803,0.00009352178,0.0001356791,0.0002969214,0.00008004897,0.001998067],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005082026,"threshold_uncertainty_score":0.02687663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03157888762756116,"score_gpt":0.1986871001114303,"score_spread":0.1671082124838691,"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."}}