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신뢰성 해석을 위한 입력변수의 상관성을 고려한 아카이케 정보척도를 기반 코플라 추정 방법

Title
신뢰성 해석을 위한 입력변수의 상관성을 고려한 아카이케 정보척도를 기반 코플라 추정 방법
Other Titles
Copula estimation method by inference function for margins using Akaike information criterion for reliability analysis under correlated input variables
Author
이태희
Keywords
Akaike information criterion; Copula; Joint cumulative distribution function; Maximum likelihood estimation; Reliability Analysis; 아카이케 정보척도; 코플라; 결합누적분포함수; 최우량추정; 신뢰성 해석
Issue Date
2015-11
Publisher
대한기계학회
Citation
대한기계학회 창립 70주년 기념 학술대회, 2015.11, Page. 1641-1642
Abstract
For reliability analysis, statistical modeling of input random variables such as joint cumulative distribution function is required. In some statistical models in engineering applications, input random variables are considered independent even though correlation exists between the variables. Copula is widely employed for modeling multivariate distributions since it captures the dependence between the marginal variables. Among many copula estimation methods, semiparametric method is preferred because assumption for marginal distributions is not required, thus estimation of copula is considered to be more accurate than other methods. However, semiparametric method needs assumption of marginal distributions while performing reliability analysis. In this paper, Akaike information criterion is employed for estimating marginal distributions and maximum likelihood estimation for estimating copula. The proposed method can use discrete information without any assumption for marginal distributions and is capable of performing reliability analysis when correlation exists between input random variables.
URI
http://www.dbpia.co.kr/Article/NODE06575920http://hdl.handle.net/20.500.11754/28913
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > AUTOMOTIVE ENGINEERING(미래자동차공학과) > Articles
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