@techreport{Camlong-Viot2003Nonparametric,
abstract = {This paper is concerned with the estimation and inference of nonparametric and semiparametric
additive models in the presence of discrete variables and dependent observations. Among the
different estimation procedures, the method introduced by Linton and Nielsen, based in marginal
integration, has became quite popular because both its computational simplicity and the fact
that it allows an asymptotic distribution theory. Here, an asymptotic treatment of the marginal
integration estimator under different mixtures of continuous-discrete variables is offered, and furthermore,
in the semiparametric partially additive setting, an estimator for the parametric part
that is consistent and asymptotically efficient is proposed. The estimator is based in minimizing
the L2 distance between the additive nonparametric component and its correspondent linear direction.
Finally, we present an application to show the feasibility of all methods introduced in
the paper.},
author = {Christine Camlong-Viot and Juan M. Rodr\'{\i}guez-P\'{o}o and Philippe Vieu},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {330; Additive Models; Dimension reduction techniques; semiparametric models; strong mixing conditions; marginal integration; Nichtparametrisches Verfahren; Sch\"{a}tztheorie; Sch\"{a}tztheorie; Lohnniveau; Sch\"{a}tzung; Theorie; Spanien; Lohnkurve},
language = {eng},
note = {urn:nbn:de:kobv:11-10050528},
number = {2003,38},
title = {Nonparametric and Semiparametric Estimation of Additive Models with both Discrete and Continuous Variables under Dependence},
type = {Discussion papers of interdisciplinary research project 373},
url = {http://hdl.handle.net/10419/22253},
year = {2003}
}
