In this article, we extend smoothing splines to model the regression mean structure when data are sampled through a complex survey. Smoothing splines are evaluated both with and without sample weights, and are compared with local linear estimator. Simulation studies find that nonparametric estimators perform better when sample weights are incorporated, rather than being treated as if iid. They also find that smoothing splines perform better than local linear estimator through completely data-driven bandwidth selection methods.
机构:
Univ Buenos Aires, Fac Ciencias Exactas & Nat, Dept Matemat, RA-1428 Buenos Aires, DF, Argentina
Consejo Nacl Invest Cient & Tecn, IMAS, RA-1428 Buenos Aires, DF, ArgentinaUniv Buenos Aires, Fac Ciencias Exactas & Nat, Dept Matemat, RA-1428 Buenos Aires, DF, Argentina
Boente, Graciela
Vahnovan, Alejandra
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Univ Nacl La Plata, Fac Ciencias Exactas, Dept Matemat, RA-1900 La Plata, Buenos Aires, Argentina
Consejo Nacl Invest Cient & Tecn, La Plata, Buenos Aires, ArgentinaUniv Buenos Aires, Fac Ciencias Exactas & Nat, Dept Matemat, RA-1428 Buenos Aires, DF, Argentina
机构:
Science Branch, Fisheries and Oceans Canada, Northwest Atlantic Fisheries Center, NL, AIC 5XI, 80 East White Hills Road, P.O. Box 5667, St. John’sScience Branch, Fisheries and Oceans Canada, Northwest Atlantic Fisheries Center, NL, AIC 5XI, 80 East White Hills Road, P.O. Box 5667, St. John’s
Cadigan N.G.
Chen J.
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University of British Columbia, VancouverScience Branch, Fisheries and Oceans Canada, Northwest Atlantic Fisheries Center, NL, AIC 5XI, 80 East White Hills Road, P.O. Box 5667, St. John’s
机构:
China Normal Univ, Sch Finance & Stat, Shanghai 200241, Peoples R China
Univ Wisconsin, Dept Stat, Madison, WI 53706 USAChina Normal Univ, Sch Finance & Stat, Shanghai 200241, Peoples R China
Shao, Jun
Wang, Sheng
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Math Policy Res, Princeton, NJ 08540 USAChina Normal Univ, Sch Finance & Stat, Shanghai 200241, Peoples R China