• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1017-1028
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• 2014

Well-known Bayes and empirical Bayes estimators have a disadvantage in respecting to overshink the parameter estimator error; therefore, a constrained Bayes estimator is suggested by matching the first two moments. Also traditional loss function such as mean square error loss function only considers the precision of estimation and to consider both precision and goodness of fit, balanced loss function is suggested. With these reasons, constrained Bayes estimators under balanced loss function is recommended for non-life insurance pricing.; however, most studies focus on the performance of estimation since Bayes risk of newly suggested estimators such as constrained Bayes and constrained empirical Bayes estimators under specific loss function is difficult to derive. This study compares the Bayes risk of several Bayes estimators under two different loss functions for estimating the risk in the auto insurance business and indicates the effectiveness of the newly suggested Bayes estimators with regards to Bayes risk perspective through auto insurance real data analysis.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.71-87
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• 2014

The Bayes premium or the net premium in the credibility theory does not reflect the underlying tail risk. In this study we examine how the tail risk measures can be utilized in determining the risk premium. First, we show that the risk measures can not only provide the proper risk loading, but also allow the insurer to avoid the wrong decision made with the Bayesian premium alone. Second, it is illustrated that the rank of the tail thickness among different conditional loss distributions does not preserve for the corresponding predictive distributions, even if they share the identical prior variable. The implication of this result is that the risk loading for a contract should be based on the risk measure of the predictive loss distribution not the conditional one.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.353-366
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• 1997

In this paper, we derive an approximate optimal Bayes group sequential design for a given loss function. We use the Monte-Carlo method to compare the ASN(average sample size) function and Bayes risk of approximate optimal Bayes group sequential design, Pocock design and O'Brien and Fleming design. Also introduced is the concept of Bayes efficiency and percentage loss of information due to grouping for the group sequential design and use it to measure the loss of information for different group sizes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.637-659
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• 2021

Since the creation of the first Bitcoin blockchain in 2009, the number of cryptocurrency users has steadily increased. However, the number of hacking attacks targeting assets stored in these users' cryptocurrency wallets is also increasing. Therefore, we evaluate the security of the wallets currently on the market to ensure that they are safe. We first conduct threat modeling to identify threats to cryptocurrency wallets and identify the security requirements. Second, based on the derived security requirements, we utilize attack trees and Bayesian network analysis to quantitatively measure the risks inherent in each wallet and compare them. According to the results, the average total risk in software wallets is 1.22 times greater than that in hardware wallets. In the comparison of different hardware wallets, we found that the total risk inherent to the Trezor One wallet, which has a general-purpose MCU, is 1.11 times greater than that of the Ledger Nano S wallet, which has a secure element. However, use of a secure element in a cryptocurrency wallet has been shown to be less effective at reducing risks.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.403-409
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• 1997

일단-집락 추출을 할 때에 예비표본으로 부터 얻은 정보를 활용하여 추가표본을 추출한다. 특히, 예비표본의 크기(예비표본의 집락의수) $n_1$ 과 추가표본의 크기$n_2$를 모두 변수로 간주하여 베이즈 위험을 최소로 하는 $n_1$과 $n_2$의 크기를 결정한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.35-35
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• 2021

최근 우리나라는 기후변화로 인한 이상기후 현상으로 호우 및 홍수 등에 의한 수재해를 예방하기 위한 설계빈도 적용방안 개발이 필요하다. 과거 지방하천의 일률적인 설계빈도의 적용 및 간접·주관적인 하천의 중요도와 지역특성에 대한 등급의 결정은 하천사업의 효율적 관리와 수행에 있어서 저해요소로 작용되어 왔다. 또한, 미래 기후변화 시나리오에 따라 하천의 중요도 및 계획 규모가 적절히 적용되어야 한다. 본 연구는 충청남도의 492개 지방하천에 대하여 유역특성(유역면적, 형상계수), 하천특성(하도경사, 수계 및 하천차수, 배수영향 구간), 이상강우 특성(이상강우 발생빈도, 시가화 침수면적)에 대한 현재 설계빈도에 대한 적절성을 평가하였다. 설계빈도에 대한 정량적 추정은 베이즈 이론을 활용하여 가중치를 산정한 후 최적분포형을 선정하였다. 최적분포형의 중앙값을 일반적인 지방하천의 설계빈도인 80년 빈도로 설정하고 상·하위 0.5%가 각각 100년, 50년 빈도로 가정하여 492개 지방하천을 평가하였다. 이상강우의 발생빈도와 시가화 침수면적에 따라 하천의 설계빈도가 높게 산정되는 것으로 분석되었다. 미래 기후변화 시나리오를 적용할 경우 현재 설계빈도(설계수명)에 대한 시나리오별 미래 재현기간을 산정하여 미래 설계빈도에 대한 위험도를 평가하였다. 13개 기후변화 시나리오의 대표농도경로 4.5와 8.5를 분석한 결과, 평균 3.2%, 12.8%의 위험도가 증가하는 것으로 분석되었다. 본 연구결과는 객관적인 지방하천의 적정 설계빈도 결정방안을 제시하였으며, 미래 계획홍수량 증가로 인하여 효율적인 토지이용이 제한될 것으로 예상됨에 따라 하천사업의 예산절감 및 우선순위 결정 등에 활용 가능할 것으로 판단된다.

• Communications for Statistical Applications and Methods
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• v.1 no.1
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• pp.157-164
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• 1994

본 연구에서는 확률화응답기법을 이용하여 모집단내의 민감집단의 비율을 추정함에 있어 조사의 효율성을 높이기 위한 층화표본의 최적할당방법을 제안한다. 확률화응답기법은 Warner(1965)에 의하여 제안된 방법으로 민감한 사안에 대한 조사시 무응답이나 거짓응답으로 인한 비표본오차를 줄일수 있는 기법으로 간접질문에 의한 조사방법이다. 여기에서 최적할당이란 베이즈위험을 최소로 하는 할당법을 의미하며, 이 과정에서 민감집단의 모비율에 대한 사전분포로는 베타분포를 취하였다.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.183-194
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• 1997

In accelerated life tests, the failure time of an item is observed under a high stress level and based on the time, the failure rates of items we estimated at the normal stress level. In this paper, when the mean of the prior distribution of a parameter is known in Weibull lifetime model with censored failure time data, we study various estimating methods to obtain the empirical Bayes estimator of a parameter from the empirical Bayes approach under the normal stress level by considering the fact that the Bayes estimator is the function of prior parameters and of the acceleration parameter representing the effect of acceleration. And we compare the performance of several empirical Bayes estimators of a parameter in terms of the Bayes risk.

• Journal of Radiation Protection and Research
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• v.30 no.2
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• pp.91-97
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• 2005

Bayesian methodology is appropriated for use in PRA because subjective knowledges as well as objective data are applied to assessment. In this study, radiological risk based on Bayesian methodology is assessed for the loss of source in field radiography. The exposure scenario for the lost source presented in U.S. NRC is reconstructed by considering the domestic situation and Bayes theorem is applied to updating of failure probabilities of safety functions. In case of updating of failure probabilities, it shows that 5 % Bayes credible intervals using Jeffreys prior distribution are lower than ones using vague prior distribution. It is noted that Jeffreys prior distribution is appropriated in risk assessment for systems having very low failure probabilities. And, it shows that the mean of the expected annual dose for the public based on Bayesian methodology is higher than the dose based on classical methodology because the means of the updated probabilities are higher than classical probabilities. The database for radiological risk assessment are sparse in domestic. It summarizes that Bayesian methodology can be applied as an useful alternative lot risk assessment and the study on risk assessment will be contributed to risk-informed regulation in the field of radiation safety.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.160-168
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• 2017

In the past 10 years, the accidents caused by drowsy driving have occupied about 23% of all traffic accidents in Korea expressway network and this rate is the highest one among all accident causes. Unlike other types of accidents caused by speeding and distraction to the road, the accidents by drowsy driving should be managed differently because the drowsiness might not be controlled by human's will. To reduce the number of accidents caused by drowsy driving, researchers previously focused on the spot based analysis. However, what we actually need is a segment (link) and occurring time based analysis, rather than spot based analysis. Hence, this research performs initial effort by adapting link concept in terms of drowsy driving on highway. First of all, we analyze the accidents caused by drowsy in historical accident data along with their road environments. Then, links associate with driving time are analyzed using digital tachograph (DTG) data. To carry this out, negative binomial regression models, which are broadly used in the field, including highway safety manual, are used to define the relationship between the number of traffic accidents on expressway and drivers' behavior derived from DTG. From the results, empirical Bayes (EB) and potential for safety improvement (PSI) analysis are performed for potential risk segments of accident caused by drowsy driving on the future. As the result of traffic accidents caused by drowsy driving, the number of the traffic accidents increases with increase in annual average daily traffic (AADT), the proportion of trucks, the amount of DTG data, the average proportion of speeding over 20km/h, the average proportion of deceleration, and the average proportion of sudden lane-changing.