Confidence bands for inverse regression models with application to gel electrophoresis
| dc.contributor.author | Birke, Melanie | |
| dc.contributor.author | Bissantz, Nicolai | |
| dc.contributor.author | Holzmann, Hajo | |
| dc.date.accessioned | 2008-11-26T14:50:14Z | |
| dc.date.available | 2008-11-26T14:50:14Z | |
| dc.date.issued | 2008-11-26T14:50:14Z | |
| dc.description.abstract | We construct uniform confidence bands for the regression function in inverse, homoscedastic regression models with convolution-type operators. Here, the convolution is between two non-periodic functions on the whole real line rather than between two period functions on a compact interval, since the former situation arguably arises more often in applications. First, following Bickel and Rosenblatt [Ann. Statist. 1, 1071–1095] we construct asymptotic confidence bands which are based on strong approximations and on a limit theorem for the supremum of a stationary Gaussian process. Further, we propose bootstrap confidence bands based on the residual bootstrap. A simulation study shows that the bootstrap confidence bands perform reasonably well for moderate sample sizes. Finally, we apply our method to data from a gel electrophoresis experiment with genetically engineered neuronal receptor subunits incubated with rat brain extract. | en |
| dc.identifier.uri | http://hdl.handle.net/2003/25879 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-14439 | |
| dc.language.iso | en | de |
| dc.subject | Confidence band | en |
| dc.subject | Deconvolution | en |
| dc.subject | Inverse problem | en |
| dc.subject | Nonparametric regression | en |
| dc.subject | Rate of convergence | en |
| dc.subject.ddc | 004 | |
| dc.title | Confidence bands for inverse regression models with application to gel electrophoresis | en |
| dc.type | Text | de |
| dc.type.publicationtype | report | en |
| dcterms.accessRights | open access |