• 한국방재학회 논문집
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• 제9권6호
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• pp.143-151
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• 2009

최근의 극한 수문사상은 홍수, 가뭄과 같은 심각한 재해를 발생시킨다. 많은 연구자들은 불확실한 미래의 확률강우량 및 유출량의 예측을 위해 많은 노력을 하고 있다. 본 연구에서는 불확실성이 낮은 확률강우량의 산정을 위하여 매개변수 추정법을 평가하였다. 인천, 강릉, 광주, 부산, 추풍령 관측소를 연구 대상 관측소로 선정하여 자료를 수집하였고, ARMA모형을 이용하여 합성강우자료를 구축하였다. 본 연구에서는 극치강우사상에 적합한 것으로 알려진 Gumbel 분포와 GEV 분포모형에 대한 매개변수를 최우도법과 베이지안 추론방법을 사용하여 추정하였으며, Bootstrap 방법을 이용하여 확률강우량의 신뢰구간 길이를 추정하였다. 매개변수 추정 방법별 산정된 확률강우량의 신뢰구간 길이를 비교함으로서 불확실성이 낮은 확률강우량을 산정할 수 있는 매개변수 추정방법을 선정하였다.

• Communications for Statistical Applications and Methods
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• 제5권2호
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• pp.277-285
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• 1998

The smoothing parameter $\lambda$ in smoothing spline regression is usually selected by minimizing cross-validation (CV) or generalized cross-validation (GCV). But, simple CV or GCV is poor candidate for estimating prediction error. We defined MGCV (Multifold Generalized Cross-validation) as a criterion for selecting smoothing parameter in smoothing spline regression. This is a version of cross-validation using $leave-\kappa-out$ method. Some numerical results comparing MGCV and GCV are done.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제4권1호
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• pp.11-22
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• 2000

Nonhysteretic infiltration in nonswelling soil is modelled by the Burgers equation under appropriate physical conditions. For this nonlinear partial differential equation the modal approximation scheme is used for estimating parameters such as soil water diffusivity and hydraulic conductivity. The parameter estimation convergence is proved, and numerical experiments are performed.

• Communications for Statistical Applications and Methods
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• 제1권1호
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• pp.87-93
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• 1994

Consider the problem of estimating the parameter of the model in which an observable random variable is represented by a unknown scalar parameter plus another random variable and the parameter, sample, and decision spaces consist of all integers. We first characterize the class of all admissible estimators and then characterize the class of all finitely admissible estimators. Finally, we show that two classes are identical.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.413-423
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• 2005

Consider the problem of estimating the underlying regression function from a set of noisy data which is contaminated by a long tailed error distribution. There exist several robust smoothing techniques and these are turned out to be very useful to reduce the influence of outlying observations. However, no matter what kind of robust smoother we use, we should choose the smoothing parameter and relatively less attention has been made for the robust bandwidth selection method. In this paper, we adopt the idea of robust location parameter estimation technique and propose the robust cross validation score functions.

• 산업경영시스템학회지
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• 제32권3호
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• pp.99-109
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• 2009

Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

• 한국소음진동공학회논문집
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• 제16권11호
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• pp.1158-1164
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• 2006

For the description of the elastic properties of linear objects a convenient parameter is the ratio of the stress to the strain, a parameter called the Young's modulus of the material. Young's modulus can be used to predict the elongation or compression of an object as long as the stress is less than the yield strength of the material. Conventional method for estimating Young's modulus measured the ratio of stress to corresponding strain below the proportional limit of a material using a tensile testing machine. But the method needs precision specimens and expensive equipment. In this paper, we proposed method for estimating Young's modulus using accelerometer. The basic idea comes from that the wave velocity is different as the Young's modulus. To obtain Young's modulus, a group velocity is obtained. It is difficult to measure group velocity. This is because plate medium has a dispersive characteristics which has different wave speed as frequency. In this paper, we used Wigner-Ville distribution to measure group velocity. To verify the proposed method, steel and acryl plate experiments have been performed. Experimental results show that the proposed method is powerful for estimating Young's modulus.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.1027-1032
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• 2007

For the description of the elastic properties of linear objects a convenient parameter is the ratio of the stress to the strain, a parameter called the Young's modulus of the material. Young's modulus can be used to predict the elongation or compression of an object as long as the stress is less than the yield strength of the material. Conventional method for estimating Young's modulus measured the ratio of stress to corresponding strain below the proportional limit of a material using a tensile testing machine. But the method needs precision specimens and expensive equipment. In this paper, we proposed method for estimating Young's modulus using accelerometer. The basic idea comes from that the wave velocity is different as the Young's modulus. To obtain Young's modulus, a group velocity is obtained. It is difficult to measure group velocity. This is because plate medium has a dispersive characteristics which has different wave speed as frequency. In this paper, we used Wigner-Ville distribution to measure group velocity. To verify the proposed method, steel and acryl plate experiments have been performed. Experimental results show that the proposed method is powerful for estimating Young's modulus.

• 한국산학기술학회논문지
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• 제13권2호
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• pp.772-778
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• 2012

본 논문은 비선형 시스템의 상태 추정에 널리 사용 되는 Unscented Kalman Filter(UKF)를 활용하여 동역학 시스템의 상태를 추정함과 동시에 파라미터를 추정하였다. 파라미터의 추정은 시스템 제어, 모델링, 성능분석 및 예측 등 다양한 분야에서 매우 중요하다. 공학에서 다루는 대부분의 시스템은 비선형성과 잡음이 존재하므로 파라미터 추정이 매우 어렵다. 이러한 경우에 대하여 본 논문에서는 비선형 필터로서 잡음에 강한 UKF를 이용하여 상태와 파라미터를 추정하였다. 본 논문에서 제안한 파라미터 추정은 기존의 상태방정식에 파라미터 항을 추가하여 확장된 비선형 방정식을 사용하였으며, 진자와 슬라이드로 구성된 2-자유도 동역학 시스템에 적용하였으며, 시스템 운동방정식의 측정 잡음으로 가우시안 잡음을 추가하여 컴퓨터 시뮬레이션을 실시하였다. 시뮬레이션 결과 제안한 방법이 LSM보다 좋은 성능을 보였다. 추정 오차는 3%이내이며, 0.1sec 이내의 수렴하는 것을 확인하였다. 결과적으로 UKF는 상태나 측정 데이터에 잡음이 존재하더라도 시스템의 상태 및 파라미터 추정이 가능하다.

• Management Science and Financial Engineering
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• 제14권2호
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• pp.89-104
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• 2008

Growth curves including Bass, Logistic and Gompertz functions are widely used in forecasting the market demand. Nonlinear least square method is often adopted for estimating the model parameters but it is difficult to set up the starting value for each parameter. If a wrong starting point is selected, the result may lead to erroneous forecasts. This paper proposes a method of selecting starting values for model parameters in estimating some growth curves by nonlinear least square method through grid search and transformation into linear regression model. Resealing the market data using the national economic index makes it possible to figure out the range of parameters and to utilize the grid search method. Application to some real data is also included, where the performance of our method is demonstrated.