Nonparametric estimation and testing of interaction in additive models

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Show simple item record Sperlich, Stefan Tjostheim, Dag Yang, Lijian
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística 2010-01-14T10:27:16Z 2010-01-14T10:27:16Z 1999-11
dc.description.abstract We consider an additive model with second order interaction terms. Both marginal integration estimators and backfiting-integration efficient estimators are proposed for all components of the model and their derivatives, together with their explicitly derived asymptotic distributions. Moreover, two test statistics for testing the presence of interactions are proposed. Asymptotics for the test functions and local power results are obtained. Since direct implementation of the test procedure based on the asymptotics would produce inaccurate results unless the number of observations is very large, a bootstrap procedure is provided, which is applicable for small or moderate sample sizes. Further, based on these methods a general test for additivity is proposed. Estimation and testing methods are shown to work well in simulation studies. Finally, our methods are illustrated on a five-dimensional production function for a set of Wisconsin farm data. In particular, the separability hypothesis for the production function is discussed.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 99-85-34
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other Derivative estimation
dc.subject.other local linear
dc.subject.other regression
dc.subject.other local power
dc.subject.other sobolev seminorm
dc.subject.other wild bootstrap
dc.title Nonparametric estimation and testing of interaction in additive models
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
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