| dc.contributor.author | Liang, Cuiping | |
| dc.description.abstract | A robust D-optimal design that works well for multiple nominal parameter values is presented in this paper. In general, D-optimal design works very well for estimating the model parameters, but it is very sensitive to multiple nominal model parameter values when the response is modeled by nonlinear models. The 5PL-1P model is considered in this study to describe a dose-response function. The sensitivity of the D-optimal design to the model parameter values under the 5PL-1P model is studied. The robust D-optimal design that can reduce the impact of the multiple nominal model parameter values is proposed using the Bayesian technique. Lastly, we compare performances of the proposed design to other well-known designs for estimating the model parameters under the 5PL-1P model. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Robust D-Optimal Design for Multiple Nominal Parameter Values under the 5PL-1P Model | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2018-05-23T14:28:01Z | |
| dc.date.available | 2018-05-23T14:28:01Z | |
| dc.date.issued | 2018 | |
| dc.identifier.uri | https://hdl.handle.net/10365/28149 | |
| dc.subject.lcsh | Optimal designs (Statistics) | en_US |
| dc.subject.lcsh | Experimental design. | en_US |
| dc.subject.lcsh | Bayesian statistical decision theory. | en_US |
| dc.subject.lcsh | Robust optimization. | en_US |
| dc.subject.lcsh | Parameter estimation. | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Science and Mathematics | en_US |
| ndsu.department | Statistics | en_US |
| ndsu.program | Statistics | en_US |
| ndsu.advisor | Hyun, Seung Won | |
