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研究生: 許丞淋
Hsu, Cheng-Lin
論文名稱: 尋找最適模型分辨設計之最佳化數值方法
Numerical Optimization Approaches for Searching Discrimination Designs
指導教授: 陳瑞彬
Chen, Ray-Bing
學位類別: 碩士
Master
系所名稱: 管理學院 - 統計學系
Department of Statistics
論文出版年: 2016
畢業學年度: 104
語文別: 英文
論文頁數: 35
中文關鍵詞: 模型分辨設計T-最適設計KL-最適設計粒子群最佳化演算法
外文關鍵詞: Model discrimination design, T-optimality, KL-optimality, Particle Swarm Optimization
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  • 在考慮不同模型數量和分佈假設的情況下有多種分辨設計的準則被提出。然而如何找出在相對應準則下的最適模型分辨設計是一個難題。主要是因為此最適設計的數值搜尋方法中包含了極為複雜的最佳化問題結構。此篇論文的目標就是建立在不同準則下所對應的有效數值方法,最後並以對應的等價定理來驗證我們提出的數值方法所找到的答案是否為最適設計。

    The problems of constructing optimal discrimination designs are considered. Given a discrimination design criterion, we transfer the corresponding design search problem as an optimization problem. Due to the complex optimization problems, we proposed efficient numerical search algorithms by combining several different optimization approaches. Finally the equivalence theorems are used to check the best designs identified by the proposed approaches are optimal or not.

    摘要 i Abstract ii 致謝 iii Table of Contents iv List of Tables vi List of Figures vii Chapter 1. Introduction 1 Chapter 2. Discrimination designs 3 2.1. T-optimal designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2. KL-optimal discrimination designs . . . . . . . . . . . . . . . . . . . . . . 4 2.3. KL-efficiency designs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.4. Standardized maximin T-optimal designs . . . . . . . . . . . . . . . . . . 7 Chapter 3. Numerical approaches for discrimination designs 9 3.1. Quasi-Newton method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2. Particle Swarm Optimization . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.3. Hybrid approaches for T- and KL-optimal discrimination designs . . . . . . 12 3.4. Numerical approach for Max-min T- and KL-efficiency discrimination designs 13 3.5. Numerical approach for standardized maximin T-optimal designs . . . . . 14 Chapter 4. Numerical examples 17 4.1. T-optimal discrimination design . . . . . . . . . . . . . . . . . . . . . . . 17 4.2. KL-optimal discrimination design . . . . . . . . . . . . . . . . . . . . . . 19 4.3. Max-min KL-efficiency discrimination design for several models . . . . . . 21 4.4. Max-min T-efficiency discrimination design for several models . . . . . . 23 4.5. Standardized maximin T-optimal discrimination designs . . . . . . . . . . 25 4.5.1. Discrimination among constant and quadratic models . . . . . . . . 25 4.5.2. Discrimination among linear and third-order models . . . . . . . . . 27 Chapter 5. Conclusion 30 References 31 Appendix A. Flow-chart for different numerical approach 33 A.1. PSO-Newton approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 A.2. Modify PSO-Newton approach . . . . . . . . . . . . . . . . . . . . . . . . 34 A.3. Multi-nested PSO-Newton approach . . . . . . . . . . . . . . . . . . . . . 35

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