Bootstrap inference in semiparametric generalized additive models

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Show simple item record Hardle, Wolfgang Huet, Sylvie Mammen, Enno Sperlich, Stefan
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística 2011-01-25T16:17:28Z 2011-01-25T16:17:28Z 2000-10
dc.description.abstract Semiparametric generalized additive models are a powerful tool in quantitative econometrics. The main focus is the application of bootstrap methods. It is shown that bootstrap can be used for bias correction, hypothesis testing (e.g. component-wise analysis) and the construction of uniform confidence bands. Various bootstrap tests for model specification and parametrization are given, in particular for testing additivity and link function specification. The practical performance of our methods is illustrated in simulations and in an application to East-West German migration.
dc.format.mimetype application/octet-stream
dc.format.mimetype application/octet-stream
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 00-70
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other Bootstrap
dc.subject.other Specification tests
dc.subject.other Generalized Additive models
dc.title Bootstrap inference in semiparametric generalized additive models
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
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