A martingale-transform goodness-of-fit test for the form of the conditional variance
| dc.contributor.author | Dette, Holger | |
| dc.contributor.author | Hetzler, Benjamin | |
| dc.date.accessioned | 2008-11-26T14:35:29Z | |
| dc.date.available | 2008-11-26T14:35:29Z | |
| dc.date.issued | 2008-11-26T14:35:29Z | |
| dc.description.abstract | In the common nonparametric regression model the problem of testing for a specific para- metric form of the variance function is considered. Recently Dette and Hetzler (2008) proposed a test statistic, which is based on an empirical process of pseudo residuals. The process converges weakly to a Gaussian process with a complicated covariance kernel depending on the data generating process. In the present paper we consider a standardized version of this process and propose a martingale transform to obtain asymptotically distribution free tests for the corresponding Kolmogorov-Smirnov and Cramer-von-Mises functionals. The finite sample properties of the proposed tests are investigated by means of a simulation study. | en |
| dc.identifier.uri | http://hdl.handle.net/2003/25870 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-14287 | |
| dc.language.iso | en | de |
| dc.subject | Conditional variance | en |
| dc.subject | Goodness-of-fit test | en |
| dc.subject | Martingale transform | en |
| dc.subject | Nonparametric regression | en |
| dc.subject.ddc | 004 | |
| dc.title | A martingale-transform goodness-of-fit test for the form of the conditional variance | en |
| dc.type | Text | de |
| dc.type.publicationtype | report | en |
| dcterms.accessRights | open access |