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dc.contributor.advisor차지환-
dc.contributor.author이가경-
dc.creator이가경-
dc.date.accessioned2021-01-25T16:30:23Z-
dc.date.available2021-01-25T16:30:23Z-
dc.date.issued2021-
dc.identifier.otherOAK-000000172816-
dc.identifier.urihttp://dcollection.ewha.ac.kr/common/orgView/000000172816en_US
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/256123-
dc.description.abstractMany studies have shown that in the fields of reliability engineering, survival analysis and life insurance, organisms or components are mostly dependent on each other. Failure of a component in the system increases the load of other remaining components and resulting in a change in their lifespan. The bivariate distribution and conditional hazard rate function are used to reflect these phenomena in this paper. First, we derive the joint and marginal probability function constructed from the modeling of conditional hazard rate. Furthermore, we also try to measure the dependency according to the variation of parameters of each distribution. Finally, based on the joint distribution of lifetimes, we study the minimum and maximum lifetimes under stochastic dependence.;일반적으로 시스템 내 개체 혹은 유기체들은 상호 의존적인 관계를 가지고 있다. 신뢰성 공학, 생존 분석 및 생명 보험 분야에서 이러한 의존적인 관계에 대한 다양한 통계 모델이 연구되었다. 시스템 내 개체의 고장은 나머지 개체의 부하를 증가시키고 수명분포의 변화를 초래한다. 이 논문에서는 이변량 분포와 조건부 위험률 함수를 이용해 변화하는 생존 분석 모델을 제시한다. 먼저 조건부 위험률 모델링을 이용해 결합 및 단일 확률밀도함수를 도출한다. 나아가 각 분포의 모수 변동에 따른 개체의 종속성을 측정하고 연생상태의 확률분포를 제시하였다.-
dc.description.tableofcontentsI. Introduction 1 II. General Class of Bivariate Distribution 2 A. Basic Concepts 2 B. Model Based on Conditional Failure Rate 3 C. Dependent Failure Model 6 III. Probability Distributions of Lifetime 8 A. System Status 8 1. Joint Life Status 8 2. Last Survivor Status 9 B. Conditional Hazard Rate Function 9 1. Weibull Distribution 9 2. Gompertz Distribution 10 3. Polynomial Failure Rate Distribution 10 IV. Application of Conditional Failure Rate Model 11 A. Weibull Distribution 11 1. Joint Probability Function 11 2. Marginal Probability Density Function and Covariance 12 3. Distribution of 1 and 2 14 B. Gompertz Distribution 15 1. Joint Probability Function 15 2. Marginal Probability Density Function and Covariance 15 3. Distribution of 1 and 2 19 C. Polynomial Failure-Rate Distribution 20 1. Joint Probability Function 20 2. Marginal Probability Density Function and Covariance 20 3. Distribution of 1 and 2 23 V. Conclusion 24 Reference 25 Abstract(in Korean) 26-
dc.formatapplication/pdf-
dc.format.extent996329 bytes-
dc.languageeng-
dc.publisher이화여자대학교 대학원-
dc.subject.ddc500-
dc.titleA Study on the Minimum and Maximum Lifetimes under Stochastic Dependence-
dc.typeMaster's Thesis-
dc.creator.othernameLee, Ga Gyung-
dc.format.pagev, 26 p.-
dc.identifier.thesisdegreeMaster-
dc.identifier.major대학원 통계학과-
dc.date.awarded2021. 2-
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