• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 추계학술발표회논문집(1)
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• pp.97-102
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• 1997

A new method based on the alternating conditional expectation (ACE) algorithm is developed to calculate axial shape index (ASI) for the 3-level excore detector. The ACE algorithm, a type of non-parametric regression algorithms, yields an optimal relationship between a dependent variable and multiple independent variables. In this study, the simple correlation between ASI and excore detector signals is developed using the Younggwang nuclear power plant unit 3 (YGN-3) data without any preprocessing on the relationships between independent variables and dependent variable. The numerical results show that simple correlations exist between the three excore signals and ASI of the core. The accuracy of the new method is much better than those of the current CPC and COLSS algorithms.

• Journal of the Korean Data and Information Science Society
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• 제28권2호
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• pp.421-433
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• 2017

The CTE (conditional tail expectation) is a useful risk management measure for a diversified investment portfolio that can be generally estimated by using a transformed univariate distribution. Hong et al. (2016) proposed a multivariate CTE based on multivariate quantile vectors, and explored its characteristics for multivariate normal distributions. Since most real financial data is not distributed symmetrically, it is problematic to apply the CTE to normal distributions. In order to obtain a multivariate CTE for various kinds of joint distributions, distribution fitting methods using copula functions are proposed in this work. Among the many copula functions, the Clayton, Frank, and Gumbel functions are considered, and the multivariate CTEs are obtained by using their generator functions and parameters. These CTEs are compared with CTEs obtained using other distribution functions. The characteristics of the multivariate CTEs are discussed, as are the properties of the distribution functions and their corresponding accuracy. Finally, conclusions are derived and presented with illustrative examples.

• 충청수학회지
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• 제27권3호
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• pp.475-477
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• 2014

Lee and Lim (2009) state three characterizations of Loamax, exponential and power function distributions, the proofs of which, are based on the solutions of certain second order non-linear differential equations. For these characterizations, they make the following statement : "Therefore there exists a unique solution of the differential equation that satisfies the given initial conditions". Although the general solution of their first differential equation is easily obtainable, they do not obtain the general solutions of the other two differential equations to ensure their claim via initial conditions. In this very short report, we present the general solutions of these equations and show that the particular solutions satisfying the initial conditions are uniquely determined to be Lomax, exponential and power function distributions respectively.

• Journal of Communications and Networks
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• 제7권1호
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• pp.29-35
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• 2005

This paper deals with the problem of multiuser detection over a direct-sequence code-division multiple access (DS-CDMA) channel with incomplete channel state informations (I-CSI). We devise and assess two novel recursive detectors based on the expectation conditional maximization (ECM) algorithm and the generalized likelihood ratio (GLR) principle, respectively. Both receivers entail an affordable computational complexity. Moreover, the performance assessment, conducted via Monte Carlo techniques, shows that they achieve satisfactory performance levels and outperform linear detectors.

• Communications for Statistical Applications and Methods
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• 제26권5호
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• pp.473-495
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• 2019

In this paper, a new extension of Lindley distribution has been introduced. Certain characterizations based on truncated moments, hazard and reverse hazard function, conditional expectation of the proposed distribution are presented. Besides, these characterizations, other statistical/mathematical properties of the proposed model are also discussed. The estimation of the parameters is performed through different classical methods of estimation. Bayes estimation is computed under gamma informative prior under the squared error loss function. The performances of all estimation methods are studied via Monte Carlo simulations in mean square error sense. The potential of the proposed model is analyzed through two data sets. A modified goodness-of-fit test using the Nikulin-Rao-Robson statistic test is investigated via two examples and is observed that the new extension might be used as an alternative lifetime model.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.605-629
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• 2023

This paper proposes some diagnostics procedures for the skew-t linear regression model with censored response. The skew-t distribution is an attractive family of asymmetrical heavy-tailed densities that includes the normal, skew-normal and student's-t distributions as special cases. Inspired by the power and wide applicability of the EM-type algorithm, local and global influence analysis, based on the conditional expectation of the complete-data log-likelihood function are developed, following Zhu and Lee's approach. For the local influence analysis, four specific perturbation schemes are discussed. Two real data sets, from education and economics, which are right and left censoring, respectively, are analyzed in order to illustrate the usefulness of the proposed methodology.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권3호
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• pp.186-199
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• 2013

We pose pattern classification as a density estimation problem where we consider mixtures of generative models under partially labeled data setups. Unlike traditional approaches that estimate density everywhere in data space, we focus on the density along the decision boundary that can yield more discriminative models with superior classification performance. We extend our earlier work on the recursive estimation method for discriminative mixture models to semi-supervised learning setups where some of the data points lack class labels. Our model exploits the mixture structure in the functional gradient framework: it searches for the base mixture component model in a greedy fashion, maximizing the conditional class likelihoods for the labeled data and at the same time minimizing the uncertainty of class label prediction for unlabeled data points. The objective can be effectively imposed as individual mixture component learning on weighted data, hence our mixture learning typically becomes highly efficient for popular base generative models like Gaussians or hidden Markov models. Moreover, apart from the expectation-maximization algorithm, the proposed recursive estimation has several advantages including the lack of need for a pre-determined mixture order and robustness to the choice of initial parameters. We demonstrate the benefits of the proposed approach on a comprehensive set of evaluations consisting of diverse time-series classification problems in semi-supervised scenarios.

• Communications for Statistical Applications and Methods
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• 제17권2호
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• pp.263-273
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• 2010

시계열의 결측값은 미지의 모수 또는 확률변수로 취급할 수 있으며 이에 따른 최대가능도방법과 확률변수방법에 의해 결측치를 추정할수 있으며 또한 주어진 자료 하에서 미지의 값에 대한 조건부기대치로 예측할수 있다. 이 연구의 주된 목적은 불완전한 자료에 대해 기존에는 ARMA모형만을 고려하였는데 이를 확장하여 공간시계열모형인 STAR모형에 적용하여 두 가지 추정방법을 이용해 결측값의 추정 정밀도를 비교하는데 있다. 사례분석을 위해 한국질병관리본부에서 전산보고 하고 있는 전염병 자료 중에서 2001~2009년 동안의 월별 Mumps 자료를 이용하여 두 가지 추정방법의 추정 정밀도와 예측정확도를 비교하였다.

• 응용통계연구
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• 제23권6호
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• pp.1201-1208
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• 2010

확률과 통계 교육에서 학생들의 관심을 집중시켜 강의 효과를 높일 수 있는 예제들을 발굴하는 데 있어 많은 학자들의 꾸준한 노력이 뒤따라야 한다. 여러 분야의 예제를 제시할 수 있지만, 특히 다양한 예제들을 찾을 수 있는 분야가 스포츠이며, 그 중에서도 월드컵 축구는 여러 가지 흥미로운 문제들의 보고(寶庫)이다. 월드컵 축구대회는 전 국민적 관심사이기 때문에, 이 분야의 예제를 통한 학습 역시 확률과 통계에 대한 학생들의 관심도를 진작시킬 수 있는 효과적인 방법이라 본다. 본 논문에서는 월드컵 축구의 조별 리그와 16강 토너먼트 등의 경기 방식과 승점제 및 조편성과 관련된 경우의 수와 확률 문제들을 제시하였으며, 통계모형을 이용한 시뮬레이션을 통해 2010 남아공 월드컵을 앞둔 시점이라 가정하고 본선 진출 각 팀의 16강 진출 확률과 우승 확률을 계산하는 논리적 방법을 제안하였다.