Nonparametric estimation of bivariate additive models

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초록

In this paper we discuss the estimation of a bivariate additive model where the multivariate regression function is expressed as a sum of unknown univariate and bivariate component functions. We discuss the identifiability of the component functions and show that each component function of the model can be estimated at the optimal rate in bivariate kernel smoothing. (C) 2016 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.

키워드

Additive modelsSmooth backfittingKernel smoothingPOLYNOMIAL SPLINESTENSOR-PRODUCTSREGRESSION
제목
Nonparametric estimation of bivariate additive models
저자
Lee, Young Kyung
DOI
10.1016/j.jkss.2016.11.004
발행일
2017-09
유형
Article
저널명
Journal of the Korean Statistical Society
46
3
페이지
339 ~ 348