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1دورية أكاديمية
المؤلفون: Boente, Graciela, He, Xuming, Zhou, Jianhui
المصدر: The Annals of Statistics, 2006 Dec 01. 34(6), 2856-2878.
الوصول الحر: https://www.jstor.org/stable/25463535Test
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2
المؤلفون: Graciela Boente, Xuming He, Jianhui Zhou
المصدر: Ann. Statist. 34, no. 6 (2006), 2856-2878
Ann. Stat. 2006;34(6):2856-2878
Biblioteca Digital (UBA-FCEN)
Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
instacron:UBA-FCENمصطلحات موضوعية: FOS: Computer and information sciences, Statistics and Probability, Generalized linear model, Monte Carlo method, Asymptotic distribution, Methodology (stat.ME), symbols.namesake, 62F35 (Primary) 62G08 (Secondary), 62G08, Applied mathematics, Partially linear models, Statistics - Methodology, Mathematics, Parametric statistics, partially linear models, Nonparametric statistics, Linear model, Estimator, smoothing, robust estimation, Rate of convergence, F-distribution, Robust estimation, Kernel weights, symbols, Statistics, Probability and Uncertainty, 62F35, Smoothing, rate of convergence
وصف الملف: application/pdf
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2688ec5c415af940132014ad91320e7Test
https://doi.org/10.1214/009053606000000858Test -
3دورية أكاديمية
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4
المؤلفون: Boente, Graciela Lina
مصطلحات موضوعية: Kernel weights, Partially linear models, Rate of convergence, Robust estimation, Smoothing
العلاقة: https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00905364_v34_n6_p2856_BoenteTest; http://hdl.handle.net/20.500.12110/paper_00905364_v34_n6_p2856_BoenteTest
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5دورية أكاديمية
مصطلحات موضوعية: ISOTONIC REGRESSION, PARTIALLY LINEAR MODELS, ROBUST ESTIMATION, ROBUST REGRESSION, SEMI–PARAMETRIC ESTIMATORS, https://purl.org/becyt/ford/1.1Test, https://purl.org/becyt/ford/1Test
وصف الملف: application/pdf
العلاقة: http://hdl.handle.net/11336/143181Test; Rodriguez, Daniela Andrea; Valdora, Marina Silvia; Vena, Pablo Claudio; Robust estimation in partially linear regression models with monotonicity constraints; Taylor & Francis; Communications In Statistics-simulation And Computation; 11-2019; 1-14; CONICET Digital; CONICET