Title page for etd-0629105-082255


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URN etd-0629105-082255
Author Wei-shan Hsieh
Author's Email Address b8824054@student.nsysu.edu.tw
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Department Applied Mathematics
Year 2004
Semester 2
Degree Master
Type of Document
Language English
Title Optimum Designs for Model Discrimination and Estimation in Binary Response Models
Date of Defense 2005-06-03
Page Count 36
Keyword
  • Least square estimate
  • model robustness
  • model discrimination
  • mean square error
  • symmetric location and scale family
  • Abstract This paper is concerned with the problem of finding an experimental design for discrimination between two rival models and for model robustness that minimizing the maximum bias simultaneously in binary response experiments. The criterion for model discrimination is based on the $T$-optimality criterion proposed in Atkinson and Fedorov (1975), which maximizes the sum of squares of deviations between the two rival models while the criterion for model robustness is based on minimizing the maximum probability bias of the two rival models. In this paper we obtain the optimum designs satisfy the above two criteria for some commonly used rival models in binary response experiments such as the probit and logit models etc.
    Advisory Committee
  • Fu-Chuen Chang - chair
  • Mei-Hui Guo - co-chair
  • Ray-Bing Chen - co-chair
  • Kam-Fai Wong - co-chair
  • Mong-Na Lo Huang - advisor
  • Files
  • etd-0629105-082255.pdf
  • indicate accessible in a year
    Date of Submission 2005-06-29

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