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題名 Dichotomous-Data Reliability Models with Auxiliary Measurements
作者 俞一唐
Yu, I-Tang
貢獻者 傅承德<br>余清祥
Fuh, Cheng-Der<br>Yue, Ching-Syang
俞一唐
Yu, I-Tang
關鍵詞 拔靴法
衰變量
二元資料
電火工品
EM演算法
bootstrap method
degradation measurement
dichotomous data
electro-explosive device
EM-algorithm
latent variables
Markov Chain Monte Carlo
reliability
日期 2003
上傳時間 17-Sep-2009 18:43:54 (UTC+8)
摘要 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.
參考文獻 1.Dempster, A. P., Laird, N. M. and Rubin, D. B. (1977). Maximum likelihood from incomplete
data via the EM algorithm (with discussion). Journal of the Royal Statistical Society
B, 39, 1-38.
2. Efron, B. and Tibshirani, R. J. (1993). An Introduction to the Bootstrap.
Chapman \\& Hall, Inc., London.
3. Gelfand, A. E. and Smith A. F. M. (1990). Sampling based approaches to calculating
marginal densities.
Journal of the American Statistical Association 85, 398-409.
4.Geman, S. and Geman, D. (1984). Stochastic relaxation, Gibbs
distribution and the Bayesian restoration of images. IEEE
Trans. Pattn. Anal. Math. Intel., 6, 721-741.
5. Gilks, W. R., Richardson, S. and Spiegelhalter, D. J. (1996).
Markov Chain Monte Carlo in Practice. Chapman \\& Hall/CRC, London.
6.Lawless, J. F. (1982). Statistical Models and Methods for Lifetime Data.
John Wiley \\& Sons, New York.
7.. Hall, P. (1992). The Bootstrap and Edgeworth Expansion.
New York: Springer-Verlag.
8. Hastings, W. K. (1970). Monte carlo sampling methods using
Markov chains and their applications. Biometrika, 57,
97-109.
9. Hudak, S. J. Jr., Saxena, A., Bussi, R. J. and Malcolm, R.
C. (1978). Development of standard methods of testing and analyzing
fatigue crack growth rate data. Technical Report AFML-TR-78-40
Westinghouse R \\& D Center, Westinghouse Electric Corporation,
Pittsburgh, PA 15235.
10. Lu, C. J. and Meeker, W. Q. (1993). Using degradation measures to estimate a time-to-failure distribution.
Technometrics, 35, 161-174.
11. McLachlan, G. J. and Krishnan, T. (1997). The EM Algorithm and Extensions.
John Wiley \\& Sons, New York.
12. Meeker, W. Q. and Escobar, L. A. (1998). Statistical Methods for Reliability Data.
John Wiley \\& Sons, New York.
13. Meng, X. L. and Rubin, D. B. (1993). Maximum likelihood estimation via the ECM algorithm
: a general framework.Biometrika B, 80, 267-278.
14. Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N.,
Teller, A. H. and Teller, E (1953). Equations of state calculations
by fast computing machine. J. Chem. Phys, 21,
1087-1091.
15. Murphy, A, J. and Menichelli, V. J. (1979). Introduction to thermal transient testing.
Technical report, Pasadena Scientific Industries.
16. Sammel, M. D., Ryan, L. M. and Legler, J. M. (1997). Latent variable models for mixed
discrete and continuous outcomes. Journal of the Royal Statistical Society
B, 59, 667-678.
17. Taguchi, G. (1991).Taguchi Methods, Signal-to-Noise Ratio for Quality Evaluation}, Vol 3.
Dearborn, MI: American Supplier Institute Press.
18.Tierney, L. (1994). Markov chains for exploring posterior
distributions (with discussion). Ann. Statist, 22,
1701-1762.
19. Tseng, S. T., Hamada, M. and Chiao, C. H. (1995). Using degradation data from a factorial
experiment to improve fluorescent lamp reliability. Journal of Quality Technology
46, 130-133.
20. Wei, G. C. G. and Tanner, M. A. (1990). A Monte Carlo implementation of the EM algorithm
and the poor man`s data augmentation algorithms.
Journal of the American Statistical Association 85, 699-704.
21.Wu, C. F. J. and Hamada, M. (2000). Experiments Planning, Analysis, and Parameter Design
Optimization. John Wiley \\& Sons, New York.
描述 國立政治大學
統計研究所
86354503
92
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0086354503
資料類型 thesis
dc.contributor.advisor 傅承德<br>余清祥zh_TW
dc.contributor.advisor Fuh, Cheng-Der<br>Yue, Ching-Syangen_US
dc.contributor.author (Authors) 俞一唐zh_TW
dc.contributor.author (Authors) Yu, I-Tangen_US
dc.creator (作者) 俞一唐zh_TW
dc.creator (作者) Yu, I-Tangen_US
dc.date (日期) 2003en_US
dc.date.accessioned 17-Sep-2009 18:43:54 (UTC+8)-
dc.date.available 17-Sep-2009 18:43:54 (UTC+8)-
dc.date.issued (上傳時間) 17-Sep-2009 18:43:54 (UTC+8)-
dc.identifier (Other Identifiers) G0086354503en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/33887-
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計研究所zh_TW
dc.description (描述) 86354503zh_TW
dc.description (描述) 92zh_TW
dc.description.abstract (摘要) 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。zh_TW
dc.description.abstract (摘要) 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.		en_US
dc.description.tableofcontents 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		zh_TW
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dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0086354503en_US
dc.subject (關鍵詞) 拔靴法zh_TW
dc.subject (關鍵詞) 衰變量zh_TW
dc.subject (關鍵詞) 二元資料zh_TW
dc.subject (關鍵詞) 電火工品zh_TW
dc.subject (關鍵詞) EM演算法zh_TW
dc.subject (關鍵詞) bootstrap methoden_US
dc.subject (關鍵詞) degradation measurementen_US
dc.subject (關鍵詞) dichotomous dataen_US
dc.subject (關鍵詞) electro-explosive deviceen_US
dc.subject (關鍵詞) EM-algorithmen_US
dc.subject (關鍵詞) latent variablesen_US
dc.subject (關鍵詞) Markov Chain Monte Carloen_US
dc.subject (關鍵詞) reliabilityen_US
dc.title (題名) Dichotomous-Data Reliability Models with Auxiliary Measurementszh_TW
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) 1.Dempster, A. P., Laird, N. M. and Rubin, D. B. (1977). Maximum likelihood from incompletezh_TW
dc.relation.reference (參考文獻) data via the EM algorithm (with discussion). Journal of the Royal Statistical Societyzh_TW
dc.relation.reference (參考文獻) B, 39, 1-38.zh_TW
dc.relation.reference (參考文獻) 2. Efron, B. and Tibshirani, R. J. (1993). An Introduction to the Bootstrap.zh_TW
dc.relation.reference (參考文獻) Chapman \\& Hall, Inc., London.zh_TW
dc.relation.reference (參考文獻) 3. Gelfand, A. E. and Smith A. F. M. (1990). Sampling based approaches to calculatingzh_TW
dc.relation.reference (參考文獻) marginal densities.zh_TW
dc.relation.reference (參考文獻) Journal of the American Statistical Association 85, 398-409.zh_TW
dc.relation.reference (參考文獻) 4.Geman, S. and Geman, D. (1984). Stochastic relaxation, Gibbszh_TW
dc.relation.reference (參考文獻) distribution and the Bayesian restoration of images. IEEEzh_TW
dc.relation.reference (參考文獻) Trans. Pattn. Anal. Math. Intel., 6, 721-741.zh_TW
dc.relation.reference (參考文獻) 5. Gilks, W. R., Richardson, S. and Spiegelhalter, D. J. (1996).zh_TW
dc.relation.reference (參考文獻) Markov Chain Monte Carlo in Practice. Chapman \\& Hall/CRC, London.zh_TW
dc.relation.reference (參考文獻) 6.Lawless, J. F. (1982). Statistical Models and Methods for Lifetime Data.zh_TW
dc.relation.reference (參考文獻) John Wiley \\& Sons, New York.zh_TW
dc.relation.reference (參考文獻) 7.. Hall, P. (1992). The Bootstrap and Edgeworth Expansion.zh_TW
dc.relation.reference (參考文獻) New York: Springer-Verlag.zh_TW
dc.relation.reference (參考文獻) 8. Hastings, W. K. (1970). Monte carlo sampling methods usingzh_TW
dc.relation.reference (參考文獻) Markov chains and their applications. Biometrika, 57,zh_TW
dc.relation.reference (參考文獻) 97-109.zh_TW
dc.relation.reference (參考文獻) 9. Hudak, S. J. Jr., Saxena, A., Bussi, R. J. and Malcolm, R.zh_TW
dc.relation.reference (參考文獻) C. (1978). Development of standard methods of testing and analyzingzh_TW
dc.relation.reference (參考文獻) fatigue crack growth rate data. Technical Report AFML-TR-78-40zh_TW
dc.relation.reference (參考文獻) Westinghouse R \\& D Center, Westinghouse Electric Corporation,zh_TW
dc.relation.reference (參考文獻) Pittsburgh, PA 15235.zh_TW
dc.relation.reference (參考文獻) 10. Lu, C. J. and Meeker, W. Q. (1993). Using degradation measures to estimate a time-to-failure distribution.zh_TW
dc.relation.reference (參考文獻) Technometrics, 35, 161-174.zh_TW
dc.relation.reference (參考文獻) 11. McLachlan, G. J. and Krishnan, T. (1997). The EM Algorithm and Extensions.zh_TW
dc.relation.reference (參考文獻) John Wiley \\& Sons, New York.zh_TW
dc.relation.reference (參考文獻) 12. Meeker, W. Q. and Escobar, L. A. (1998). Statistical Methods for Reliability Data.zh_TW
dc.relation.reference (參考文獻) John Wiley \\& Sons, New York.zh_TW
dc.relation.reference (參考文獻) 13. Meng, X. L. and Rubin, D. B. (1993). Maximum likelihood estimation via the ECM algorithmzh_TW
dc.relation.reference (參考文獻) : a general framework.Biometrika B, 80, 267-278.zh_TW
dc.relation.reference (參考文獻) 14. Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N.,zh_TW
dc.relation.reference (參考文獻) Teller, A. H. and Teller, E (1953). Equations of state calculationszh_TW
dc.relation.reference (參考文獻) by fast computing machine. J. Chem. Phys, 21,zh_TW
dc.relation.reference (參考文獻) 1087-1091.zh_TW
dc.relation.reference (參考文獻) 15. Murphy, A, J. and Menichelli, V. J. (1979). Introduction to thermal transient testing.zh_TW
dc.relation.reference (參考文獻) Technical report, Pasadena Scientific Industries.zh_TW
dc.relation.reference (參考文獻) 16. Sammel, M. D., Ryan, L. M. and Legler, J. M. (1997). Latent variable models for mixedzh_TW
dc.relation.reference (參考文獻) discrete and continuous outcomes. Journal of the Royal Statistical Societyzh_TW
dc.relation.reference (參考文獻) B, 59, 667-678.zh_TW
dc.relation.reference (參考文獻) 17. Taguchi, G. (1991).Taguchi Methods, Signal-to-Noise Ratio for Quality Evaluation}, Vol 3.zh_TW
dc.relation.reference (參考文獻) Dearborn, MI: American Supplier Institute Press.zh_TW
dc.relation.reference (參考文獻) 18.Tierney, L. (1994). Markov chains for exploring posteriorzh_TW
dc.relation.reference (參考文獻) distributions (with discussion). Ann. Statist, 22,zh_TW
dc.relation.reference (參考文獻) 1701-1762.zh_TW
dc.relation.reference (參考文獻) 19. Tseng, S. T., Hamada, M. and Chiao, C. H. (1995). Using degradation data from a factorialzh_TW
dc.relation.reference (參考文獻) experiment to improve fluorescent lamp reliability. Journal of Quality Technologyzh_TW
dc.relation.reference (參考文獻) 46, 130-133.zh_TW
dc.relation.reference (參考文獻) 20. Wei, G. C. G. and Tanner, M. A. (1990). A Monte Carlo implementation of the EM algorithmzh_TW
dc.relation.reference (參考文獻) and the poor man`s data augmentation algorithms.zh_TW
dc.relation.reference (參考文獻) Journal of the American Statistical Association 85, 699-704.zh_TW
dc.relation.reference (參考文獻) 21.Wu, C. F. J. and Hamada, M. (2000). Experiments Planning, Analysis, and Parameter Designzh_TW
dc.relation.reference (參考文獻) Optimization. John Wiley \\& Sons, New York.zh_TW