• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.187-199
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• 2010

This study evaluated applicability and confidence of probability rainfalls estimated by the non-stationary rainfall frequency analysis which was recently developed. Using rainfall data at 4 sites which have an obvious increasing trend in observations, we estimated 3 type probability rainfalls; probability rainfalls from stationary rainfall frequency analysis using data from 1973-1997, probability rainfalls from stationary rainfall frequency analysis using data from 1973-2006, probability rainfalls from non-stationary rainfall frequency analysis assuming that the current year is 1997 and the target year is 2006. Based on the comparison of residuals from 3 probability rainfalls, the non-stationary rainfall frequency analysis provided more effective and well-directed estimates of probability rainfalls in the target year. Using Bootstrap resampling, this study also evaluated the parameter estimation methods for the non-stationary rainfall frequency analysis based on confidence intervals. The confidence interval length estimated by the maximum likelihood estimation (MLE) is narrower than the probability weighted moments (PWM). The results indicated that MLE provides more proper confidence than PWM for non-stationary probability rainfalls.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.177-187
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• 1997

This article considers the power performance of the tests in unbalanced two way mixed linear models with one fixed factor. The generalized least squares (GLS) F statistic testing no differences among the effects of the levels of the fixed factor is estimated using Henderson's method III, minimum norm quadratic unbiased estimator (MINQUE) with prior guess 1, maximum likelihood (ML) and resticted maximum likelihood (REML). We investigate the power performance of these test statistics. It can be shown, through simulation, that the GLS F statistics using four estimators produce similar type I error rates and power performance.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.197-206
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• 2000

For estimating missing cells in contingency table, we suggest an iterative method which extends IPF (Iterative Proportional Fitting) method. The suggested m~thod is not restricted by the number and the location of missing cells, and does not distort the given quasi-independency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.559-562
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• 2011

In this research, We derived Recursive Least Squares(RLS) algorithm with adaptive maximum-likelihood channel estimate for digital pulse amplitude modulated sequence in the presence of intersymbol interference and additive white Gaussian noise. RLS algorithms have better convergence characteristics than conventional algorithms, LMS (Least Mean Squares) algorithms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.151-161
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• 1993

The log-Gumbel distribution in real space is defined by transforming the conventional log-Gumbel distribution in log space. For this model, the parameter estimation techniques are applied based on the methods of moments, maximum likelihood and probability weighted moments. The asymptotic variances of estimator of the quantiles for each estimation method are derived to find the confidence limits for a given return period. Finally, the log-Gumbel model is applied to actual flood data to estimate the parameters, quantiles and confidence limits.

• 전기의세계
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• v.22 no.2
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• pp.51-56
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• 1973

The comparative study of maximum likelihood estimation with Bayesian approach was made by statistical & computational methods in center of a priori information of static systems and the effect of a priori information on the accuracy of the estimatiion was also analyzed. Through the numerical computations of some examples by digital computer, we concluded that maximum likelihood method is better than Bayesian estimation except for almost certain a priori informations. The study may therefore contribute in identification problems of dynamical systems connected with a priori informations.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.819-831
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• 2014

The Exact-EM algorithm can conventionally fit a mixture of multivariate skew distribution. However, it suffers from highly expensive computational costs to calculate the moments of multivariate truncated t-distribution in E-step. This paper proposes a new SPU-EM method that adopts the AECM algorithm principle proposed by Meng and van Dyk (1997)'s to circumvent the multi-dimensionality of the moments. This method offers a shorter execution time than a conventional Exact-EM algorithm. Some experments are provided to show its effectiveness.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.366-366
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• 2012

확률강우량은 하천설계, 수자원설계 및 계획을 위한 기초자료로 활용되며 최근 이상기후 및 기후변화로 인한 극치강우의 빈도 및 양적 증가로 인한 확률강우량 산정의 불확실성 분석에 대한 관심이 크게 증가하고 있다. 수문빈도 해석에 있어서 대부분 지역이 50년 이하의 수문자료가 이용되고 있으며 수문설계에서 요구되는 50년 이상의 확률강수량 추정시에는 상당한 불확실성을 내포하고 있다. 이러한 점에서 본 연구에서는 자료연수에 따른 Sampling Error와 분포형의 매개변수의 불확실성을 고려한 해석모형을 구축하고자 한다. 빈도해석에서 매개변수를 추정하기 위해서는 일반적으로 모멘트법, 최우도법, 확률가중모멘트법이 이용되고 있으나 사용되는 분포형에 따라서 통계학적으로 불확실성 구간을 정량화하는 과정이 난해할 뿐만 아니라 극치 수문자료가 Thick-Tailed분포의 특성을 가짐에도 불구하고 신뢰구간 산정시 정규분포로 가정하는 등 기존 해석 방법에는 많은 문제점을 내포하고 있다. 본 연구에서는 이러한 매개변수의 불확실성 평가에 있어서 우수한 해석능력을 발휘하는 Bayesian기법을 도입하여 분포형의 매개변수를 추정하고 매개변수 추정과 관련된 불확실성을 평가하고자 한다. 이와 별개로 자료연한에 따른 Sampling Error를 추정하기 위해서 Bootstrapping 기반의 해석모형을 구축하고자 하며 최종적으로 빈도해석시에 나타나는 불확실성을 종합적으로 검토하였다. 빈도해석을 위한 확률분포형으로 GEV(generalized extreme value)분포를 이용하였으며 Gibbs 샘플러를 활용한 Bayesian Markov Chain Monte Carlo 모의를 기본 해석모형으로 활용하였다.

• Convergence Security Journal
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• v.12 no.3
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• pp.19-26
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• 2012

In this study, software products developed in the course of testing, software managers in the process of testing software and tools for effective learning effects perspective has been studied using the NHPP software. The log type hazard function applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$(coefficient of determination).

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.279-279
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• 2020

최근 copula 모형은 여러 확률변수를 갖는 수문현상에 대해 빈도해석을 수행할 경우 결합확률분포형으로 유용하게 사용되고 있다. 하나의 자료를 확률변수로 사용하는 단변량 빈도해석에 비해 여러 수문자료를 동시에 각각 확률변수로 취하여 결합확률분포형을 추정할 수 있는 다변량 빈도해석은 수문자료의 상관성을 고려하면서 확률분포형을 추정할 수 있다는 장점이 있다. Copula 모형 중 Gumbel copula는 extreme-value 확률분포형으로 극치사상에 적합한 확률분포형이다. 본 연구에서는 Gumbel copula를 이용하여 우리나라 기상청 64개 종관기상관측소의 강우자료로부터 극치 강우사상을 추출하고, 이를 이용하여 빈도해석을 수행하였다. 극치 강우사상은 전체 강우사상 중 각 년도별로 최대강우량을 갖는 연최대강우량사상(annual maximum volume event)을 사용하였다. 각 확률변수의 주변분포형으로는 gamma, Gumbel, generalized extreme value, generalized logistic, Weibull 등 5개 확률분포형을 검토하였으며 각각 적합한 주변분포형을 적용하고 copula 모형의 매개변수는 의사최우도법(maximum pseudo-likelihood method)를 사용하여 추정하였다. 또한 추정된 copula 모형은 Cramer-von Mises 함수와 경험적 copula를 이용하여 적합도 검정을 수행하였다. 이를 통해 극치강우사상에 대하여 Gumbel copula 모형의 적용성을 검토하였으며 추정된 결합확률분포형을 이용하여 빈도별 확률강우사상을 2차원 등치선(contour line)형태로 제시하였다.