dc.contributor.author | MORA, Juan | |
dc.contributor.author | PEREZ-ALONSO, Alicia | |
dc.date.accessioned | 2007-12-11T09:39:46Z | |
dc.date.available | 2007-12-11T09:39:46Z | |
dc.date.issued | 2007 | |
dc.identifier.issn | 1830-7728 | |
dc.identifier.uri | https://hdl.handle.net/1814/7638 | |
dc.description.abstract | We discuss how to test whether the distribution of regression errors belongs to a
parametric family of continuous distribution functions, making no parametric
assumption about the conditional mean or the conditional variance in the regression
model. We propose using test statistics that are based on a martingale transform of the
estimated empirical process. We prove that the resulting test statistics are asymptotically
distribution-free, and a set of Monte Carlo experiments shows that they work reasonably
well in practice. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | en |
dc.publisher | European University Institute | |
dc.relation.ispartofseries | EUI MWP | en |
dc.relation.ispartofseries | 2007/34 | en |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | Empirical Process | en |
dc.subject | Nonparametric residual | en |
dc.subject | Martingale Transform | en |
dc.subject | Monte Carlo simulation | en |
dc.title | Specification tests for the distribution of errors in nonparametric regression: a martingale approach | en |
dc.type | Working Paper | en |
dc.neeo.contributor | MORA|Juan|aut| | |
dc.neeo.contributor | PEREZ-ALONSO|Alicia|aut| | |
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