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Please use this identifier to cite or link to this item: http://hdl.handle.net/10016/10079

Google™ Scholar. Others By: Hardle, Wolfgang - Huet, Sylvie - Mammen, Enno - Sperlich, Stefan
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Title: Bootstrap inference in semiparametric generalized additive models
Author(s): Hardle, Wolfgang
Huet, Sylvie
Mammen, Enno
Sperlich, Stefan
Publisher: Universidad Carlos III de Madrid. Departamento de Estadística
Issued date: Oct-2000
URI: http://hdl.handle.net/10016/10079
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.
Serie / Nº.: UC3M Working papers. Statistics and Econometrics
00-70
Keywords: Bootstrap
Specification tests
Generalized Additive models
Appears in Collections:DES - Working Papers. Statistics and Econometrics. WS

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