• Journal of the Korean Statistical Society
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• 제29권3호
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• pp.337-350
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• 2000

This paper suggests a new diagnostic measure and a stopping rule for detecting influential observations in multiple discriminant analysis (MDA). It is developed from a Bayesian point of view using a default Bayes factor obtained from the fractional Bayes factor methodology. The Bayes factor is taken as a discriminatory information in MDA. It is shown that the effect of an observation over the discriminatory information is fully explained by the diagnostic measure. Based on the measure, we suggest a stopping rule for detecting influential observations in a given training sample. As a tool for interpreting the measure a graphical method is sued. Performance of the method is used. Performance of the method is examined through two illustrative examples.

• 한국임상약학회지
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• 제23권2호
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• pp.137-141
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• 2013

Purpose: This study compared the performance of new NONMEM estimation methods using a population analysis dataset collected from a clinical study that consisted of 40 individuals and 567 observations after a single oral dose of glimepiride. Method: The NONMEM 7.2 estimation methods tested were first-order conditional estimation with interaction (FOCEI), importance sampling (IMP), importance sampling assisted by mode a posteriori (IMPMAP), iterative two stage (ITS), stochastic approximation expectation-maximization (SAEM), and Markov chain Monte Carlo Bayesian (BAYES) using a two-compartment open model. Results: The parameters estimated by IMP, IMPMAP, ITS, SAEM, and BAYES were similar to those estimated using FOCEI, and the objective function value (OFV) for diagnosing the model criteria was significantly decreased in FOCEI, IMPMAP, SAEM, and BAYES in comparison with IMP. Parameter precision in terms of the estimated standard error was estimated precisely with FOCEI, IMP, IMPMAP, and BAYES. The run time for the model analysis was shortest with BAYES. Conclusion: In conclusion, the new estimation methods in NONMEM 7.2 performed similarly in terms of parameter estimation, but the results in terms of parameter precision and model run times using BAYES were most suitable for analyzing this dataset.

• Communications for Statistical Applications and Methods
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• 제29권5호
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• pp.547-559
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• 2022

For a chi-squared test, which is a statistical method used to test the independence of a contingency table of two factors, the expected frequency of each cell must be greater than 5. The percentage of cells with an expected frequency below 5 must be less than 20% of all cells. However, there are many cases in which the regional expected frequency is below 5 in general small area studies. Even in large-scale surveys, it is difficult to forecast the expected frequency to be greater than 5 when there is small area estimation with subgroup analysis. Another statistical method to test independence is to use the Bayes factor, but since there is a high ratio of data dependency due to the nature of the Bayesian approach, the low expected frequency tends to decrease the precision of the test results. To overcome these limitations, we will borrow information from areas with similar characteristics and pool the data statistically to propose a pooled Bayes test of independence in target areas. Jo et al. (2021) suggested hierarchical Bayesian pooling models for small area estimation of categorical data, and we will introduce the pooled Bayes factors calculated by expanding their restricted pooling model. We applied the pooled Bayes factors using bone mineral density and body mass index data from the Third National Health and Nutrition Examination Survey conducted in the United States and compared them with chi-squared tests often used in tests of independence.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.233-244
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• 2006

In this paper, we develop the Bayesian multiple comparisons procedure for the binomial distribution. We suggest the Bayesian procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. An example is illustrated for the proposed method. For this example, the suggested method is straightforward for specifying distributionally and to implement computationally, with output readily adapted for required comparison. Also, some simulation was performed.

• Journal of the Korean Data and Information Science Society
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• 제28권1호
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• pp.207-215
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• 2017

In this paper we study pooling effects in Bayesian testing procedures of independence for contingency tables from small areas. In small area estimation setup, we typically use a hierarchical Bayesian model for borrowing strength across small areas. This techniques of borrowing strength in small area estimation is used to construct a Bayes test of independence for contingency tables from small areas. In specific, we consider the methods of direct or indirect pooling in multinomial models through Dirichlet priors. We use the Bayes factor (or equivalently the ratio of the marginal likelihoods) to construct the Bayes test, and the marginal density is obtained by integrating the joint density function over all parameters. The Bayes test is computed by performing a Monte Carlo integration based on the method proposed by Nandram and Kim (2002).

• 한국컴퓨터정보학회논문지
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• 제26권6호
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• pp.29-35
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• 2021

본 논문에서는 위치 측위의 정확도를 높일 수 있는 방안으로 KNN(K-Nearest Neighbor)과 Local Map Classification 및 Bayes Filter를 융합한 기법을 제안한다. 먼저 이 기법은 Local Map Classification이 실제 지도를 여러 개의 Cluster로 나누고, 다음으로 KNN으로 Cluster들을 분류한다. 그리고 Bayes Filter가 획득한 각 Cluster의 확률을 통하여 Posterior Probability을 계산한다. 이 Posterior Probability으로 로봇이 위치한 Cluster를 검색한다. 성능 평가를 위하여 KNN과 Local Map Classification 및 Bayes Filter을 적용하여서 얻은 위치 측위의 결과를 분석하였다. 분석 결과로 RSSI 신호가 변하더라도 위치 정보는 한 Cluster에 고정되면서 위치 측위의 정확도가 높아진다는 사실을 확인하였다.

• 응용통계연구
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• 제28권3호
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• pp.407-415
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• 2015

단순 베이즈 분류($Na{\ddot{i}}ve$ Bayes classification)는 출력변수가 주어졌을 때 입력변수들이 조건부 독립이라는 가정에 기반한다. 단순 베이즈 가정은 비현실적이지만 고차원의 확률 추정 문제를 일련의 일차원 확률 추정 문제로 단순화 시킨다는 장점이 있으며, 특히 스팸 메일 필터링, 추천 시스템(recommendation system) 등 방대한 데이터를 다루는 분야야에서 흔히 사용된다. 본 논문에서는 입력변수와 출력변수간의 카이제곱 통계량에 기반한 변수선택법을 제안한다. 이 방법은 단순 베이즈 분류의 장점인 데이터 처리 및 계산의 단순성을 유지하면서도 설명력이 있는 변수를 선택할 수 있으며 SNP(single nucleotide polymorphism)에 의한 질병의 분류 등의 초고차원 혹은 빅데이터에서 유용할 것으로 기대된다.

• 방송공학회논문지
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• 제4권1호
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• pp.22-31
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• 1999

이동물체 추적 시스템은 감시, 방송, 영상회의 등의 시스템에 관한 품질 및 처리 효율을 개선시킨다. 본 논문에서는 능동 카메라 환경에서 이동물체의 검출 및 추적을 위한 개선된 bayes 결정이론을 제안한다. 제안한 시스템은 손실함수를 최소화 하는 최적의 패턴 클래스를 선택할 수 있도록 결정함수를 제공해주는 bayes 결정이론에 기반을 둔다. bayes 결정은 연속적인 영상을 통계적으로 분석하고, 능동카메라 환경에서 물체와 배경에 맞게 각 픽셀에 존재하는 pdf를 재구성 함으로써 이동 물체의 영역을 찾아낸다. 제안된 방법에 의해 만들어진 시스템은 능동카메라 환경에서 이동물체의 영역을 명확하게 찾아내고 그 영역을 표시함을 실험결과를 통해 알 수 있다. 본 논문에서는 제안된 방법과 기존의 방법들을 성능면에서 비교함으로서, 제안된 시스템이 정확하고, 노이즈에 대한 대처능력이 우수함을 알 수 있다.

• 품질경영학회지
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• 제25권3호
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• pp.108-118
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• 1997

A commercial nuclear power station contains at least two emergency diesel generates(EDG) to control the risk of severe core demage during the station blackout accidents. Therefore the reliability of the EDG's to start and load-run on demend must be maintained at a sufficiently high level. Until now, a simple assessment of start and load-run success rates was used to calculate the EDG's reliability. However, this method has been found to contain many defects. Recently, the work of Martz et al.(1996) proposed the use of the Bayes estimator to find the EDG's reliability. In this paper, we will propose confidence interval for the Bayes estimator, compare the above two methods and, using practical examples, illustrate why the Bayes estimator method is more reasonable in our situation.

• International Journal of Reliability and Applications
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• 제6권1호
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• pp.41-51
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• 2005

The Bayes estimators of the parameters included in the complementary Weibull reliability model are obtained. In the process of deriving Bayes estimators, the scale and shape parameters of the complementary Weibull distribution are considered to be independent random variables having prior exponential distributions. The maximum likelihood estimators of the desired parameters are derived. Further, the least square estimators are obtained in closed forms. Simulation study is made using Monte Carlo method to make a comparison among the obtained estimators. The comparison is made by computing the root mean squared errors associated to each point estimation. Based on the numerical study, the Bayes procedure seems better than the maximum likelihood and least square procedures in the sense of having smaller root mean squared errors.