| dc.contributor.author | Ming, Yue | |
| dc.description.abstract | When dose-response functions have a downturn, one interesting feature to study is the significance of the downturn. The interesting feature can be studied using model discrimination between two rival models (model describing dose-response functions with a downturn versus model describing only increasing part of the response functions). In this article, we study T-optimal designs that can best discriminate between these two rival models. Three different sets of model parameter values are considered to demonstrate various shapes of dose-response functions. Under the different sets of the parameter values, the T-optimal designs are obtained, and their performances are compared to two other known designs for the model discrimination (Ds-optimal design and Uniform design) through Monte Carlo Simulation. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | T-Optimal Designs for Model Discrimination in Probit Models | en_US |
| dc.type | Thesis | en_US |
| dc.date.accessioned | 2018-02-02T16:57:20Z | |
| dc.date.available | 2018-02-02T16:57:20Z | |
| dc.date.issued | 2014 | |
| dc.identifier.uri | https://hdl.handle.net/10365/27407 | |
| 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 | |
