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dc.contributor.authorMeintanis, Simos G.
dc.contributor.authorEinbeck, Jochen
dc.date.accessioned2016-09-06T06:33:51Z
dc.date.available2016-09-06T06:33:51Z
dc.date.issued2015
dc.identifier.citationMeintanis, S.G. & Einbeck, J, 2015. Validation tests for semi-parametric models. Journal of statistical computation and simulation, 85(1):131-146. [http://dx.doi.org/10.1080/00949655.2013.806922]en_US
dc.identifier.issn0094-9655
dc.identifier.issn1563-5163 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/18546
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/00949655.2013.806922
dc.identifier.urihttps://doi.org/10.1080/00949655.2013.806922
dc.description.abstractTests are proposed for validation of the hypothesis that a partial linear regression model adequately describes the structure of a given data set. The test statistics are formulated following the approach of Fourier-type conditional expectations first suggested by Bierens [Consistent model specification tests. J Econometr. 1982;20:105–134]. The proposed procedures are computationally convenient, and under fairly mild conditions lead to consistent tests. Corresponding bootstrap versions are compared with alternative procedures for a wide selection of different estimators of the underlying partial linear modelen_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectSemi-linear modelen_US
dc.subjectgoodness-of-fit testen_US
dc.subjectempirical characteristic functionen_US
dc.subjectbootstrap testen_US
dc.titleValidation tests for semi-parametric modelsen_US
dc.typeArticleen_US
dc.contributor.researchID21262977 - Meintanis, Simos George


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