• 한국농공학회지
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• 제40권2호
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• pp.59-68
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• 1998

This study was conducted to derive optimal design floods by generalized gamma distribution model of the annual maximum series at eight watersheds along Geum, Yeongsan and Seomjin river systems. Design floods obtained by different methods for evaluation of parameters and for plotting positions in the generalized gamma distribution model were compared by the relative mean errors and graphical fit along with 95% confidence limits plotted on gamma probability paper. The results were analyzed and summarized as follows. 1. Basic statistics and parameters were calculated by the generalized gamma distribution model using different methods for parameters. 2. Design floods according to the return periods were obtained by different methods for evaluation of parameters and for plotting positions in the generalized gamma distribution model. 3. It was found that design floods derived by sundry averages method for parameters and Cunnane method for plotting position in the generalized gamma distribution are much closer to those of the observed data in comparison with those obtained by the other methods for parameters and for plotting positions from the viewpoint of relative mean errors. 4. Reliability of design floods derived by sundry averages method in the generalized gamma distribution was acknowledged within 95% confidence interval.

• Communications for Statistical Applications and Methods
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• 제15권5호
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• pp.793-798
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• 2008

Extreme value inference deals with fitting the generalized extreme value distribution model and the generalized Pareto distribution model, which are recently combined to give a single model, namely a two-dimensional non-homogeneous Poisson exceedance point process model. In this paper, we extend the two-dimensional non-homogeneous Poisson process model to include non-stationary effect or dependence on covariates and then derive the likelihood for the extended model.

• Journal of the Korean Data and Information Science Society
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• 제10권2호
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• pp.289-298
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• 1999

We consider a minimax approach to make a design robust to many types or uncertainty arising in reality when dealing with non-normal linear models. We try to build a design to protect against the worst case, i.e. to improve the "efficiency" of the worst situation that can happen. In this paper, we especially deal with the generalized linear model. It is a known fact that the generalized linear model is a universal approach, an extension of the normal linear regression model to cover other distributions. Therefore, the optimal design for the generalized linear model has very similar properties as the normal linear model except that it has some special characteristics. Uncertainties regarding the unknown parameters, link function, and the model structure are discussed. We show that the suggested approach is proven to be highly efficient and useful in practice. In the meantime, a computer algorithm is discussed and a conclusion follows.

• 한국농공학회논문집
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• 제54권1호
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• pp.19-26
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• 2012

Soils exhibit creep behavior in which deformation and movement proceed under a state of constant stress or load. In this study, A series of triaxial tests were performed under constant principal stress in order to interpret the undrained creep characteristics of silty sands. Although samples are non-plastic silty sands, the results of tests show that the creep deformation increasing over time. Based on the results of test, Singh-Mitchell model parameters and Generalized model coefficients were calculated. Generalized model showed slightly larger deformation in the primary creep range but secondary creep deformation was almost identical. Although Singh-Mitchell model showed relatively large errors compared to Generalized model because it uses the average of test results, but Singh-Mitchell model can be easily represented by three creep parameters.

• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.516-522
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• 2004

In this paper we investigate the properties of a generalized impulse response Gramian. The recursive relationship satisfied by the family of Gramians is established. It is shown that the generalized impulse response Gramian contains information on the characteristic polynomial of a linear time-invariant continuous system. The results are applied to model reduction problem.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.923-931
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• 2005

The two parameter generalized exponential distribution was recently introduced by Gupta and Kundu (1999). It is observed that the generalized exponential distribution can be used quite effectively to analyze skewed data set. This paper develops the accelerated life test model using generalized exponential distribution and considers maximum likelihood estimation of parameters under the tampered random variable model. To show the performance of proposed maximum likelihood estimates, some simulation will be performed. Using a real data set, an example will be given.

• 응용통계연구
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• 제30권5호
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• pp.775-791
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• 2017

이진 데이터는 일상 생활에서 자주 접할 수 있는 데이터이다. 이진 데이터를 회귀 분석하는 방법으로 로지스틱(Logistic), 프로빗(Probit), Cauchit, Complementary log-log 모형이 주로 쓰이는데, 이 방법 이외에도 Liu(2004)가 제시한 t 분포를 이용한 로빗(Robit) 모형, Kim 등 (2008)에서 제시한 일반화 t-link 모형을 이용한 방법 등이 있다. 유연한 분포를 이용하면 유연한 회귀 모형이 가능해지는 점에 착안하여, 이 논문에서는 Theodossiou(1998)에서 제시된 기운 일반화 t 분포 (Skewed Generalized t Distribution)의 이용하여 우도 함수를 최대로 하는 이진 데이터 회귀 모형을 소개한다. 기운 일반화 t 분포를 R glm 함수, R sgt 패키지를 연결하여 이 논문에서 제시한 방법을 R로 분석할 수 있는 방법을 소개하고, 피마 인디언(Pima Indian) 데이터를 분석한다.

• Communications for Statistical Applications and Methods
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• 제22권3호
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• pp.305-312
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• 2015

We extend a generalized partially linear single-index model and newly define a generalized partially double-index model (GPDIM). The philosophy of sufficient dimension reduction is adopted in GPDIM to estimate unknown coefficient vectors in the model. Subsequently, various combinations of popular sufficient dimension reduction methods are constructed with the best combination among many candidates determined through a bootstrapping procedure that measures distances between subspaces. Distinguishing values are newly defined to match the estimates to the corresponding population coefficient vectors. One of the strengths of the proposed model is that it can investigate the appropriateness of GPDIM over a single-index model. Various numerical studies confirm the proposed approach, and real data application are presented for illustration purposes.

• Asian-Australasian Journal of Animal Sciences
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• 제11권6호
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• pp.642-647
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• 1998

A Poisson error model as a generalized linear mixed model (GLMM) has been suggested for genetic analysis of counted observations. One of the assumptions in this model is the normality for random effects. Since this assumption is not always appropriate, a more flexible model is needed. For count traits, a Poisson hierarchical generalized linear model (HGLM) that does not require the normality for random effects was proposed. In this paper, a Poisson-Gamma HGLM was examined along with corresponding analytical methods. While a difficulty arises with Poisson GLMM in making inferences to the expected values of observations, it can be avoided with the Poisson-Gamma HGLM. A numerical example with simulated embryo yield data is presented.

• 한국지능시스템학회논문지
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• 제24권2호
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• pp.193-200
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• 2014

압전 액추에이터(Piezoelectric actuator)는 빠른 응답 특성, 넓은 대역폭, 우수한 반복 정밀도, 그리고 높은 분해능의 특성으로 인하여 다양한 산업분야에서 폭넓게 사용되고 있다. 하지만, 압전 액추에이터에는 히스테리시스 효과(Hysteresis effect)가 발생되는 단점이 있으며, 이는 시스템의 성능을 저하시키는 주요한 원인으로 알려져 있다. Generalized Prandtl-Ishlinskii(GPI) model을 이용한 기존 연구에서는 히스테리시스 효과를 제거하기 위하여 히스테리시스를 수리적으로 모델링하고, 그 결과로부터 역 히스테리시스를 도출하였다. 하지만 모델링된 변수 값에 따라서는 역 히스테리시스 루프를 형성하지 못하는 치명적 문제점이 발생된다. 따라서 본 논문에서는 이러한 문제점을 해결하기 위하여 Inverse Generalized Prandtl-Ishlinskii(IGPI) model을 이용하여 역 히스테리시스를 직접 모델링하는 방법을 제안하였다. 또한 모델링 정밀도는 다양한 입력신호를 이용한 실험 결과를 기반으로 검증하였다.