§ 瀏覽學位論文書目資料
  
系統識別號 U0002-3006201014213000
DOI 10.6846/TKU.2010.01119
論文名稱(中文) 指數型設限資料的貝氏計量值抽樣計畫
論文名稱(英文) Bayesian Variable Sampling Plans for the Exponential Distribution Based on Censored Samples
第三語言論文名稱
校院名稱 淡江大學
系所名稱(中文) 數學學系博士班
系所名稱(英文) Department of Mathematics
外國學位學校名稱
外國學位學院名稱
外國學位研究所名稱
學年度 98
學期 2
出版年 99
研究生(中文) 黃彥龍
研究生(英文) Yen-Lung Huang
學號 892150029
學位類別 博士
語言別 英文
第二語言別
口試日期 2010-06-25
論文頁數 69頁
口試委員 指導教授 - 林千代
委員 - 黃連成
委員 - 陳麗霞
委員 - 吳秀芬
委員 - 吳碩傑
關鍵字(中) 貝氏風險
離散分割法
最大概似估計法
普通的混合設限
(修正) 逐步混合設限
模擬退火演算法
關鍵字(英) Bayes risk
Discretization method
Maximum likelihood estimation
Ordinary hybrid censoring
(Adaptive) Progressive hybrid censoring
Simulated annealing algorithm
第三語言關鍵字
學科別分類
中文摘要
本論文首先提出一個新的修正逐步混合型I設限計畫。然後,我們根據 Childs et al. (2003) 和 Childs et al. (2008) 的結果推導出指數型I設限和修正的逐步混合型I及型II設限資料下之最大概似估計值的分配。利用不同設限資料下所得之最大概似估計值的分配,我們分別針對簡單和一般性的損失函數建立抽樣計畫之貝氏風險函數,再應用 Lam (1994) 的離散分割法或模擬退火演算法找出最佳的抽樣計畫。最後,我們呈現一些數據及比較來驗證本論文所提出的方法之有效性及穩定性。
英文摘要
In this dissertation, we propose a new adaptive Type-I progressive hybrid censoring scheme. We follow the work of Childs et al. (2003) and Childs et al. (2008) to derive the exact distributions of the maximum likelihood estimator of the mean lifetime of an exponential distribution under Type-I censoring and both types of adaptive progressive hybrid censoring schemes. Based on the distributions of maximum likelihood estimator, we obtain the explicit expressions for the Bayes risks of sampling plans when a simple or general loss function is used. The discretization method of Lam (1994) and the simulated annealing algorithm are then used to determine the optimal sampling plans under different censoring schemes. Some numerical examples and comparisons are presented to illustrate the effectiveness of the proposed method.
第三語言摘要
論文目次
Contents
1 Introduction	1
1.1 Background and Motivation	1
1.2 Censoring Schemes	4
1.3 Overview	10
2 The Distributions of MLE of θ	11
2.1 Pdf of hat{θ} under Type-I censoring 	12
2.2 Pdf of hat{θ} under HCS	14
2.3 Pdf of hat{θ} under PHCS	15
2.4 Pdf of hat{θ} under APHCS	16
3 Variable Sampling Plans With a Simple Loss Function	21
3.1 Bayes Risks	22
3.2 Algorithm for Optimal Solutions	25
3.3 Numerical Results	26
3.3.1 Results for Type-I Censoring	27
3.3.2 Results for HCS	28
3.3.3 Results for PHCS	30
4 Variable Sampling Plans With a General Loss Function	45
4.1 Loss function and Bayes Risks	46
4.2 PMF of m*	47
4.3 The expressions of EλEX|λ[m*|λ] and EλEX|λ[τ|λ]	52
4.3.1 Results for Type-II APHCS	52
4.3.2 Results for Type-I APHCS	53
4.3.3 Results for PHCS	54
4.4 Numerical Results	57
5 Concluding Remarks and Areas for Further Research	62
Appendix: Simulated Annealing Algorithm	64
References	66
List of Tables
3.1 The minimum Bayes risks and optimal sampling plans for a0 = 2.0, a1 =2.0, 
a2 = 2.0, Cs = 0.5, Cr = 30, and some selected values of a and b	32
3.2 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8,
a1 = 2.0, a2 = 2.0, Cs = 0.5, Cr = 30, and some selected values of a0	33
3.3 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8,
a0 = 2.0, a2 = 2.0, Cs = 0.5, Cr = 30, and some selected values of a1	33
3.4 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8,
a0 = 2.0, a1 = 2.0, Cs = 0.5, Cr = 30, and some selected values of a2	34
3.5 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8,
a0 = 2.0, a1 = 2.0, a2 = 2.0, Cs = 0.5, and some selected values of Cr	34
3.6 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8,
a0 = 2.0, a1 = 2.0, a2 = 2.0, Cr = 30, and some selected values of Cs	35
3.7 The minimum Bayes risks and optimal sampling plans for a0 = 2.0, a1 =2.0,
a2 = 2.0, Cs = 0.5, Cr = 30, and some selected values of a and b	36
3.8 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8,
a1 = 2.0, a2 = 2.0, Cs = 0.5, Cr = 30, and some selected values of a0	37
3.9 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8,
a0 = 2.0, a2 = 2.0, Cs = 0.5, Cr = 30, and some selected values of a1	38
3.10 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8, 
a0 = 2.0, a1 = 2.0, Cs = 0.5, Cr = 30, and some selected values of a2	39
3.11 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8,
a0 = 2.0, a1 = 2.0, a2 = 2.0, Cr = 30, and some selected values of Cs	 40
3.12 The minimum Bayes risks and optimal sampling plans for a = 2.5, b = 0.8,
a0 = 2.0, a1 = 2.0, a2 = 2.0, Cs = 0.5, and some selected values of Cr	41
3.13 The minimum Bayes risks and optimal sampling plans for some selected 
values of a, b, a0, a1, a2, Cs, and Cr under Type-I censoring	42
3.14 The minimum Bayes risks and optimal sampling plans for some selected
values of a, b, a0, a1, a2, Cs, and Cr under Type-II censoring	43
3.15 The minimum Bayes risks and optimal sampling plans for some selected
values of a, b, a0, a1, a2, Cs, and Cr under Type-I censoring	44
4.1 The minimum Bayes risk and optimal sampling plans for some selected
values of a, b, a2, C3 and C4 under Type-II censoring	60
4.2 The minimum Bayes risk and optimal sampling plans for some selected
values of a, b, a2, C3 and C4 under Type-I censoring	61
List of Figures
1.1 Schematic representation of HCS	5
1.2 Schematic representation of Type-I PHCS	6
1.3 Schematic representation of Type-II PHCS	7
1.4 Schematic representation of Type-II APHCS	8
1.5 Schematic representation of Type-I APHCS	9
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