• Journal of the Korean Statistical Society
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• 제22권2호
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• pp.191-200
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• 1993

An asymptotic estimation problem of the unknown mean is studied under a general loss function. The proof of this result is based on the asymptotic expansion of the risk function. Also conditions for second order admissibility and minimaxity of a class of estimators depending only on the sample mean are established.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1289-1297
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• 2012

We consider a general compound Poisson risk model in which the premium rate is surplus dependent. We analyze the joint distribution of the surplus immediately before ruin, the deffcit at ruin and the time of ruin by solving the integro-differential equation for the Gerber-Shiu discounted penalty function.

• 자원ㆍ환경경제연구
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• 제9권4호
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• pp.641-661
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• 2000

The study examines the relation between yield insurance and nitrogen fertilizer in Korea. Since the yield insurance has never been introduced in Korea, the simulation method developed by Babcock & Hennessy is used to see the effect. From the simulation, we obtained the following results: (1) When a farmer is assumed to have a risk-neutral utility function, the yield insurance reduces nitrogen fertilizer by 19.74% (2) When a farmer is assumed to have a risk-averse utility function, the yield insurance reduces nitrogen fertilizer by 24.53%.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 춘계학술대회 논문집
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• pp.1155-1162
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• 2004

This research proposes a new risk analysis method in order to guarantee successful performance of construction projects. The proposed risk analysis methods consists of four phases. First step, AHP model can help contractors decide whether or not they bid for a project by analysing risks involved in the project. Second step, the influence diagraming, decision tree and Monte Carlo simulation are used as tools to analyze and evaluate project risks quantitatively. Third step, Monte Carlo simulation is used to assess risk for groups of activities with probabilistic branching and calendars. Finally, Fuzzy theory suggests a risk management method for construction projects, which is using subjective knowledge of an expert and linguistic value, to analyze and quantify risk. The result of study is expected to improve the accuracy of risk analysis because three factors, such as probability, impact and exposure, for estimating membership function are introduced to quantify each risk factor. Consequently, it will help contractors identify risk elements in their projects and quantify the impact of risk on project time and cost.

• 한국컴퓨터정보학회논문지
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• 제23권7호
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• pp.39-47
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• 2018

This paper confirms the risk of using smartphone through the analysis of collected usage pattern and proposes the smartphone intervention system in risk situations. In order to check the risk of smartphone usage, we made information collecting application and collected smartphone usage pattern from 11 experiment participants for two months. By analyzing smartphone usage pattern, we confirmed that about 12% of smartphone usage is being used in driving, walking, and on the street. In addition, we analyzed the response rate of smartphone notification in risk situations and confirmed that user responds the smartphone notifications in real-time even in risk situations. Therefore, it is required to present a system that intervenes the use of smartphone in order to protect smartphone users in risk situations. In this paper, we classify risk situations of using smartphone. Also, the proposed smartphone intervention system is designed to periodically detect risk situations. In risk situations, smartphone function can be restricted according to user setting of smartphone. And smartphone can be used normally when safe situation is restored.

• Journal of Information Technology Applications and Management
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• 제25권1호
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• pp.67-85
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• 2018

We propose a noise reduced risk aversion index for measuring risk aversion through a laboratory experiment to overcome disadvantages of the multiple pricing list format developed by Holt and Laury (2002). We use randomized multiple list choices with coarser classification and reward weighting, supplement the rank of risk aversion with extra individual characteristics of risk attitude, and construct an index of risk aversion by standardizing the risk aversion ranking with quantile normalization. Our method reduces multiple switching problems that noisy decision makers mistakenly commit in experimental approaches, so that it is free of the framing effect which severely occurred in the HL. Furthermore, the index doesn't utilize any specific utility function or probability weighting, which allows researcher to hold the independence axiom. Since our noise reduced index of risk aversion has many good traits, it is widely used and applied to reveal fundamental characteristics of risk-related behaviors in economics and finance regardless of experimental environment.

• Communications for Statistical Applications and Methods
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• 제21권3호
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• pp.261-274
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• 2014

In this paper we develop Bayes and empirical Bayes estimators of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation under the balanced loss function. We compare the performance of the optimal Bayes estimator with ones of the classical sample mean and the usual Bayes estimator under the squared error loss with respect to the posterior expected losses, risks and Bayes risks when the underlying distribution is normal as well as when they are binomial and Poisson.

• 한국철도학회논문집
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• 제16권2호
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• pp.104-109
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• 2013

The paper will outline how hazard identification and risk evaluation can effectively be performed to obtain Tolerable Hazard Rates (THR). As a target group manufacturers are addressed, who face the situation, that for a generic application THRs are needed for compliance with EN 50129 [1]. Focusing on functional hazards this paper shows a possible hazard log and the relevant analysis methods. The terms safety barrier and barrier function will be introduced and used instead of the term "safety function". As functional hazards and barrier functions depend on each other, emphasis will be put on a comprehensive and detailed definition of barrier functions and the usage of function lists. By using detailed and complete hazard and barrier function definitions THRs can be obtained while at the same time the approach becomes clear how the hazard rates (HR) will be established.

• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.685-696
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• 2014

In this paper, we develop Bayesian inference of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation in the presence of auxiliary information under the balanced loss function. We compare the performance of the optimal Bayes estimator under the balanced loss function with ones of the classical ratio estimator and the usual Bayes estimator in terms of the posterior expected losses, risks and Bayes risks.

• Communications for Statistical Applications and Methods
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• 제23권6호
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• pp.555-562
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• 2016

Interval censored data often occur in an observational study where the subject is followed periodically. Instead of observing an exact failure time, two inspection times that include it are available. There are several methods to analyze interval censored failure time data (Sun, 2006). However, in the presence of competing risks, few methods have been suggested to estimate covariate effect on interval censored competing risk data. A sub-distribution hazard model is a commonly used regression model because it has one-to-one correspondence with a cumulative incidence function. Alternatively, Klein and Andersen (2005) proposed a pseudo-value approach that directly uses the cumulative incidence function. In this paper, we consider an extension of the pseudo-value approach into the interval censored data to estimate regression coefficients. The pseudo-values generated from the estimated cumulative incidence function then become response variables in a generalized estimating equation. Simulation studies show that the suggested method performs well in several situations and an HIV-AIDS cohort study is analyzed as a real data example.