• 전자공학회논문지B
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• 제30B권12호
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• pp.1-11
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• 1993

This paper concentrates on models useful for analyzing the error performance of ML(Maximum Likelihood) estimators of a single unknown signal parameter: that is the error intensity model. We first develop the point process representation for the estimation error and the conditional distribution of the estimator as well as the distribution of error candidate point process. Then the error intensity function is defined as the probability dessity of the estimate and the general form of the error intensity function is derived. We then develop several intensity models depending on the way we choose the candidate error locations. For each case, we compute the explicit form of the intensity function and discuss the trade-off among models as well as the extendability to the case of multiple parameter estimation.

• 응용통계연구
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• 제36권4호
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• pp.309-322
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• 2023

혹스 과정은 자기 자극 특성을 가진 점 과정으로서, 지진 발생시 본진으로 인한 여진이 발생되는 현상을 설명하는 데 주로 쓰이는 확률 모형이다. 최근에는 전염병 확산, SNS에서의 소식 확산 등 자기 자극을 특성을 가진 다양한 현상을 설명하는 데 활용되고 있다. 혹스 과정은 다양한 형태의 자극 함수를 도입하여 발생하는 사건의 특성에 따라 유연하게 변형이 가능한데, 최대 우도 추정량을 구하는 것이 쉽지 않기 때문에 최근까지도 개선된 추정 방법이 제시되고 있다. 이 논문에서는 혹스 과정을 설명하기 위해 조건부 강도 함수와 자극 함수에 대해 설명하고, 지진, 전염병, 범죄 및 금융에서 활용되었던 예와 추정 방법을 알아보도록 한다. R-패키지 ETAS를 이용하여 2017년 11월부터 2022년 12월까지 한국 경상도에서 발생한 지진을 분석하도록 한다.

• Journal of the Korean Data and Information Science Society
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• 제10권1호
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• pp.119-133
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• 1999

마코브체인 몬테칼로 방법을 소프트웨어 신뢰모형에 이용하였다. 베이지안 추론에서 조건부 분포를 가지고 사후분포를 결정하는데 있어서의 계산 문제를 고찰하였다. 특히 레코드값을 통계량을 갖고서 혼합과정과 중첩과정에 대하여 깁스샘플링 알고리즘과 메트로폴리스 알고리즘을 활용하여 베이지안 계산과 모형 선택을 제시하고 모의실험자료를 이용하여 수치적 인 계산을 시행하고 그 결과를 비교하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권9호
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• pp.4336-4354
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• 2018

Fuzzy C-means (FCM) algorithm is a most usually technique for medical image segmentation. But conventional FCM fails to perform well enough on magnetic resonance imaging (MRI) data with the noise and intensity inhomogeneity (IIH). In the paper, we propose a Gamma correction conditional FCM algorithm with spatial information (GcsFCM) to solve this problem. Firstly, the pre-processing, Gamma correction, is introduced to enhance the details of images. Secondly, the spatial information is introduced to reduce the effect of noise. Then we introduce the effective neighborhood mechanism into the local space information to improve the robustness for the noise and inhomogeneity. And the mechanism describes the degree of participation in generating local membership values and building clusters. Finally, the adjustment mechanism and the spatial information are combined into the weighted membership function. Experimental results on four image volumes with noise and IIH indicate that the proposed GcsFCM algorithm is more effective and robust to noise and IIH than the FCM, sFCM and csFCM algorithms.

• 응용통계연구
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• 제11권2호
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• pp.377-387
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• 1998

컴퓨터의 발전에 따른 마코브체인 몬테카를로방법을 소프트웨어 신뢰확률모형에 이용하였다. 베이지안 추론에서 조건부분포를 가지고 사후분포를 결정하는데 있어서의 계산문제와 이론적인 정당성을 고려, 마코프연쇄와 메트로폴리스방법의 관계를 고찰하였으며, 특히 Mus-Okumoto와 Erlang(2)의 중첩모형에 대하여 깁스샘플링 알고리즘과 메트로폴리스 알고리즘을 활용하며 베이지안 계산과 예측 우도기준에 의 한 모형선택을 제안하고 Cox-Lewis에 의해 계시된 Thing method를 이용한 모의실험자료를 이용하여 수치적인 계산을 시행하고 그 결과가 제시되었다.

• Journal of applied mathematics & informatics
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• 제8권1호
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• pp.243-252
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• 2001

The points of failure of a decomposition process are defined to be the union of the points of failure from two component point processes for software reliability systems. Because sampling from the likelihood function of the decomposition model is difficulty, Gibbs Sampler can be applied in a straightforward manner. A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For model determination, we explored the prequential conditional predictive ordinate criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. A numerical example with a simulated data set is given.

• 대한수학회보
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• 제47권6호
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• pp.1105-1119
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• 2010

We consider jump processes which has only downward jumps with size a fixed fraction of the current process. The jumps of the pro cesses are interpreted as crashes and we assume that the jump intensity is a nondecreasing function of the current process say $\lambda$(X) (X = X(t) process). For the case of $\lambda$(X) = $X^{\alpha}$, $\alpha$ > 0, we show that the process X shold explode in finite time, say $t_e$, conditional on no crash For the case of $\lambda$(X) = (lnX)$^{\alpha}$, we show that $\alpha$ = 1 is the borderline of two different classes of processes. We generalize the model by adding a Brownian noise and examine the blow up properties of the sample paths.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.151-151
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• 2019

Because drought is a complex and stochastic phenomenon in nature, statistical approaches for drought assessment receive great attention for water resource planning and management. Generally drought characteristics such as severity, duration and intensity are modelled separately. This study aims to develop a relationship between drought characteristics using a bivariate copula model. To achieve the objective, we calculated the Standardized Precipitation Index (SPI) using rainfall data at 6 rain gauge stations for the period of 1961-1999 in Jehlum River Basin, Pakistan, and investigated the drought characteristics. Since there is a significant correlation between drought severity and duration, they are usually modeled using different marginal distributions and joint distribution function. Using exponential distribution for drought severity and log-logistic distribution for drought duration, the Galambos copula was recognized as best copula to model joint distribution of drought severity and duration based on the KS-statistic. Various return periods of drought were calculated to identify time interval of repeated drought events. The result of this study can provide useful information for effective water resource management and shows superiority against univariate drought analysis.

• 대한기계학회논문집
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• 제16권9호
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• pp.1788-1795
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• 1992

본 연구에서는 상술한 특성을 갖는 유동자에 대하여 신뢰성이 보장된 스펙트 럼 추정법의 모색과 화립을 위해 의사 난류신호(turbulent-like signal)를 자기회기 모형(autoregressive model:AR model)으로 생성하고 추출간격이 유동장에 영향을 받는 비주기적 확률과정을 수치적으로 모사한다. 이 비주기적 실현 신호로 부터 현재 가 장 많이 사용되고 있는 Roberts와 Gaster의 직접 변화법과 추출 및 유지신호의 피리오 도그램(periodogram)법에 대해 데이터 밀도와 난류강도의 다양한 변화에 따른 속도편 의의 영향 등을 살펴보는데 목적을 둔다.

• Earthquakes and Structures
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• 제2권4호
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• pp.357-376
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• 2011

Ground motion models predict the mean and standard deviation of the logarithm of spectral acceleration, as a function of predictor variables such as earthquake magnitude, distance and site condition. Such models have been developed for a variety of seismic environments throughout the world. Some calculations, such as the Conditional Mean Spectrum calculation, use this information but additionally require knowledge of correlation coefficients between logarithmic spectral acceleration values at multiple periods. Such correlation predictions have, to date, been developed primarily from data recorded in the Western United States from active shallow crustal earthquakes. This paper describes results from a study of spectral acceleration correlations from Japanese earthquake ground motion data that includes both crustal and subduction zone earthquakes. Comparisons are made between estimated correlations for Japanese response spectral ordinates and correlation estimates developed from Western United States ground motion data. The effect of ground motion model, earthquake source mechanism, seismic zone, site conditions, and source to site distance on estimated correlations is evaluated and discussed. Confidence intervals on these correlation estimates are introduced, to aid in identifying statistically significant differences in correlations among the factors considered. Observed general trends in correlation are similar to previous studies, with the exception of correlation of spectral accelerations between orthogonal components, which is seen to be higher here than previously observed. Some differences in correlations between earthquake source zones and earthquake mechanisms are observed, and so tables of correlations coefficients for each specific case are provided.