Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Biedermann, Stefanie | de |
dc.contributor.author | Dette, Holger | de |
dc.contributor.author | Pepelyshev, Andrey | de |
dc.date.accessioned | 2004-12-06T18:39:07Z | - |
dc.date.available | 2004-12-06T18:39:07Z | - |
dc.date.issued | 2004 | de |
dc.identifier.uri | http://hdl.handle.net/2003/4890 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-16156 | - |
dc.format.extent | 191298 bytes | - |
dc.format.extent | 353076 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.format.mimetype | application/postscript | - |
dc.language.iso | en | de |
dc.publisher | Universitätsbibliothek Dortmund | de |
dc.subject | For the problem of percentile estimation of a quantal response curve, we determine multi-objective designs which are robust with respect to misspecifications of the model assumptions. We propose a maximin approach based on efficiencies and provide designs that are simultaneously efficient with respect to the particular choice of various parameter regions and link functions. Furthermore, we deal with the problems of designing model and percentile robust experiments and give various examples of such designs, which are calculated numerically. | en |
dc.subject | binary response model | en |
dc.subject | robust optimal design | en |
dc.subject | c-efficiency | en |
dc.subject | percentile estimation | en |
dc.subject | multi-objective designs | en |
dc.subject.ddc | 310 | de |
dc.title | Some Robust Design Strategies for Percentile Estimation in Binary Response Models | en |
dc.type | Text | de |
dc.type.publicationtype | report | en |
dcterms.accessRights | open access | - |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
Files in This Item:
File | Description | Size | Format | |
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19_04.pdf | DNB | 186.81 kB | Adobe PDF | View/Open |
tr19-04.ps | 344.8 kB | Postscript | View/Open |
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