A new test for the parametric form of the variance function in nonparametric regression
| dc.contributor.author | Dette, Holger | |
| dc.contributor.author | Van Keilegom, Ingrid | |
| dc.date.accessioned | 2005-10-11T14:37:10Z | |
| dc.date.available | 2005-10-11T14:37:10Z | |
| dc.date.issued | 2005-10-11T14:37:10Z | |
| dc.description.abstract | In the common nonparametric regression model the problem of testing for the parametric form of the conditional variance is considered. A stochastic process based on the difference between the empirical processes obtained from the standardized nonparametric residuals under the null hypothesis (of a specific parametric form of the variance function) and the alternative is introduced and its weak convergence established. This result is used for the construction of a Cramér von Mises type statistic for testing the parametric form of the conditional variance. The finite sample properties of a bootstrap version of this test are investigated by means of a simulation study. In particular the new procedure is compared with some of the currently available methods for this problem and its performance is illustrated by means of a data example. | en |
| dc.format.extent | 207669 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/2003/21636 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-14489 | |
| dc.language.iso | en | |
| dc.subject | Bootstrap | en |
| dc.subject | Kernel estimation | en |
| dc.subject | Nonparametric regression | en |
| dc.subject | Residual distribution | en |
| dc.subject | Testing heteroscedasticity | en |
| dc.subject | Testing homoscedasticity | en |
| dc.subject.ddc | 004 | |
| dc.title | A new test for the parametric form of the variance function in nonparametric regression | en |
| dc.type | Text | |
| dc.type.publicationtype | report | en |
| dcterms.accessRights | open access | |
| eldorado.dnb.deposit | true |