Generated Covariates in Nonparametric Estimation: A Short Review


Mammen, Enno ; Rothe, Christoph ; Schienle, Melanie



DOI: https://doi.org/10.1007/978-3-642-32419-2_11
Document Type: Book chapter
Year of publication: 2013
Book title: Recent Developments in Modeling and Applications in Statistics
Page range: 97-106
Publisher: Oliveira, Paulo Eduardo
Place of publication: Berlin [u.a.]
Publishing house: Springer
ISBN: 978-3-642-32418-5 , 978-3-642-32419-2
Publication language: English
Institution: Außerfakultäre Einrichtungen > SFB 884
Subject: 310 Statistics
Abstract: In many applications, covariates are not observed but have to be estimated from data. We outline some regression-type models where such a situation occurs and discuss estimation of the regression function in this context. We review theoretical results on how asymptotic properties of nonparametric estimators differ in the presence of generated covariates from the standard case where all covariates are observed. These results also extend to settings where the focus of interest is on average functionals of the regression function.

Dieser Eintrag ist Teil der Universitätsbibliographie.




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