Goodness of fit tests in random coefficient regression models.

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dc.contributor.author Delicado, Pedro
dc.contributor.author Romo, Juan
dc.date.accessioned 2012-07-10T10:15:50Z
dc.date.available 2012-07-10T10:15:50Z
dc.date.issued 1999-03
dc.identifier.bibliographicCitation Annals of the Institute of Statistical Mathematics, (Mar. 1999), 51(1), 125-148.
dc.identifier.issn 0020-3157 (print)
dc.identifier.issn 1572-9052 (online)
dc.identifier.uri http://hdl.handle.net/10016/14865
dc.description.abstract Random coefficient regressions have been applied in a wide range of fields, from biology to economics, and constitute a common frame for several important statistical models. A nonparametric approach to inference in random coefficient models was initiated by Beran and Hall. In this paper we introduce and study goodness of fit tests for the coefficient distributions; their asymptotic behavior under the null hypothesis is obtained. We also propose bootstrap resampling strategies to approach these distributions and prove their asymptotic validity using results by Giné and Zinn on bootstrap empirical processes. A simulation study illustrates the properties of these tests.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer.
dc.subject.other Empirical processes
dc.subject.other Goodness of fit
dc.subject.other Linear regression
dc.subject.other Random coefficient
dc.subject.other Vapnik-Cervonenkis classes
dc.title Goodness of fit tests in random coefficient regression models.
dc.type article
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1023/A:1003887303233
dc.subject.eciencia Estadística
dc.identifier.doi 10.1023/A:1003887303233
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
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