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| 研究生： |
俞一唐 Yu, I-Tang |
|---|---|
| 論文名稱： |
Dichotomous-Data Reliability Models with Auxiliary Measurements |
| 指導教授： |
傅承德
Fuh, Cheng-Der 余清祥 Yue, Ching-Syang |
| 學位類別： |
博士
Doctor |
| 系所名稱： |
商學院 - 統計學系 Department of Statistics |
| 論文出版年： | 2004 |
| 畢業學年度： | 92 |
| 語文別： | 英文 |
| 論文頁數： | 62 |
| 中文關鍵詞： | 拔靴法 、衰變量 、二元資料 、電火工品 、EM演算法 |
| 外文關鍵詞： | bootstrap method, degradation measurement, dichotomous data, electro-explosive device, EM-algorithm |
| 相關次數： | 點閱：98 下載：27 |
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我們提供一個新的可靠度模型，DwACM，並提供一個模式選擇準則CCP，我們利用DwACM和CCP來選擇衰變量。
We propose a new reliability model, DwACM (Dichotomous-data with Auxiliary Continuous Measurements model) to describe a data set which consists of classical dichotomous response (Go or No Go) associated with a set of continuous auxiliary measurement. In this model, the lifetime of each individual is considered as a latent variable. Given the value of the latent variable, the dichotomous response is either 0 or 1
depending on if it fails or not at the measuring time. The continuous measurement can be regarded as observations of an underlying possible degradation candidate of which descending process is a function of the lifetime. Under the assumption that the failure of products is defined as the time at which the
continuous measurement reaches a threshold, these two measurements can be linked in the proposed model. Statistical inference under this model are both in frequentist and Bayesian frameworks. To evaluate the continuous measurements, we provide a criterion, CCP (correct classification probability),
to select the best degradation measurement. We also report our
simulation studies of the performances of parameters estimators and CCP.
1. INTRODUCTION 1
1.1 Concepts and Data types of Reliability Analysis 1
1.2 Electro-Explosive Device and Thermal Transient Testing 3
1.3 A Motivating Example 4
1.4 Overviews 6
2.STATISTICAL BACKGROUNDS 8
2.1 Reliability Data Analysis 8
2.2 Accelerated Experiment 10
2.3 EM-Algorithm 11
2.4 Bootstrap Methods 14
2.5 Markov Chain Monte Carlo Simulation 16
3.RwACM MODEL 19
3.1 Modeling a Degradation Measurement 19
3.2 The Linkage of Two Types of Data 22
4. MEASUREMENT SELECTION CRITERION 26
4.1 General Concepts of the CCP 26
4.2 The CCP to the Linear Degradation Model 28
5. ESTIMATION PROCEDURES 33
5.1 Frequentist Inferences 33
5.2 Bayesian Inferences 37
6. EXPERIMENTAL SETTINGS AND SIMULATION STUDIES 42
6.1 Experiment Settings 42
6.2 Simulation Studies 43
7. CONCLUSION AND FUTURE RESEARCHES 57
7.1 Conclusion 57
7.2 Future Researches 58
REFERENCES 60
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