• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.865-877
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• 2009

While characterized initially as an urban-scale pollutant, ozone has increasingly been recognized as a regional and even global-scale phenomenon. The complexity of environmental data dynamics often requires models covering non-linearity. This study deals with modeling ozone with meteorology in Seoul area. The relationships are used to construct a nonlinear regression model relating ozone to meteorology. The model can be used to estimate that part of the trend in ozone levels that cannot be accounted for by trends in meteorology.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.139-151
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• 2002

This study is concerned with model selection and diagnostics for nonlinear regression model through Bayes factor. In this paper, we use informative prior and simulate observations from the posterior distribution via Markov chain Monte Carlo. We propose the Laplace approximation method and apply the Laplace-Metropolis estimator to solve the computational difficulty of Bayes factor.

• Journal of KIISE:Software and Applications
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• v.27 no.9
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• pp.952-960
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• 2000

본 논문에서는 퍼지 자동회귀 이동평균 (Fuzzy Auto-Regressive Moving Average, FARMA)제어기를 전력계통의 비선형 2기 5모선 (Two Machine - Five Bus)모형의 주파수 안정화에 적용한 결과를 제시한다 퍼지 자동회귀 이동 평균 제어기는 기존의 전문가에 의존하였던 퍼지제어 규칙을 실시간으로 형성해 나가는 구조이다. 복잡성, 비선형성 등 전력계통의 일반적인 특징들을 기술하고, 그 특징을 표현할 수 있는 비선형 2기5모선 모형을 제시한다. 제시된 모형을 바탕으로 기존 제어 방식과의 성능 비교를 실시하였고, 이를 통하여 FARMA 제어기의 우수성을 확인하였다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1013-1025
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• 2016

The purpose of this study was to analyze longitudinal effect of physical education activity (PEA) score on self-rated health evaluation change (SHEC). This study used hierarchical linear and nonlinear models to investigate of the SHEC during the transition into adolescence (from middle school 1st to high school 2nd grade). Using the Korea children and youth panel survey (KCYPA), data were collected over the course of five years (from 2010 and 2014). HLM 6.8 computer program was used to analyze the data. The result were as follows. First, boys' SHEC increased across the five years, and girls' SHEC decreased across the five years. Second, boys' the self-rated health was increased across the three years and decreased across the two years. Third, girls' the self-rated health was increased across the two years and decreased across the three years. Fourth, the PEA score of 1st grade of high school showed a significant positive association with the boys' SHEC. Fifth, the PEA score of 1st grade of middle school showed a significant negative association with the girls' SHEC.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.265-275
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• 1993

This paper deals with the M-estimators in regression model. The class of M-estimators is defined on nonlinear regression model and the conditions to hold the consistency of the considered estimators are suggested when the parameter space of the model is compact.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.263-264
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• 2012

본 논문은 여러 개의 독립적인 시계열로 구성된 시계열 패널 자료를 이용하여 비선형 모형인 GRCA모형과 신경망을 이용하여 예측값을 구하여 서로 비교 분석하고자 한다. 먼저 GRCA모형에 대하여 연구하고 신경망의 구조와 예측값을 구하기 위한 여러 가지 변환함수를 유도한다. 단기 예측에서는 신경망 방법의 예측값이 더 좋았고, 장기예측에서는 비선형모형을 이용한 예측값이 더 좋은 것으로 나타났다.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 2003.08a
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• pp.240-244
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• 2003

파랑의 변형 가운데 천수, 굴절, 회절, 반사를 예측하는 수학적 모형은 크게 두 가지 유형으로 나눌 수 있는데, 첫 번째로 파형경사인 ha(k：파수. $\alpha$：진폭)를 비선형의 매개변수로 하는 Stokes 파랑식이 있고, 두 번째로 상대파고인 $\alpha$/h를 비선형의 매개변수로 하고 상대수심인 kh를 분산성의 매개변수로 하는 천수방정식(Shallow water equation)이 있다. 파랑의 변형 가운데 천수, 굴절만을 예측하고 회절, 반사를 예측하지 못하는 수학적 모형으로는 에너지 이송방정식이 있다. (중략)

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.2
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• pp.72-85
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• 2000

Rock is a very complex and heterogeneous material, containing structural flaws due to geologic generation process. Because of those structural flaws, deformation and failure of rock when subjected to differential compressive stresses is non-linear. To simulate the non-linear behavior of rock, mechanical crack models, that is, sliding and shear crack models have been used in several studies. In those studies, non-linear stress-strain curves and various behaviors of rock including the changes of effective elastic moduli ($E_1$, $E_2$, ${\nu}_1$, ${\nu}_2$, $G_2$) due to crack growth were simulated (Kemeny, 1993; Jeon, 1996, 1998). Most of the studies have mainly focused on the verification of the mechanical crack model with relatively less attempt to apply it to practical purposes such as numerical analysis for underground and/or slope design. In this study, the validity of mechanical crack model was checked out by simulating the non-linear behavior of rock and consequently it was applied to a practical numerical analysis, finite element analysis commonly used.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.33-39
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• 2013

In the transformation of response variable in partial linear models outliers can cause a bad effect on estimating the transformation parameter, just as in the linear models. To solve this problem the processes of estimating transformation parameter and detecting outliers are needed, but have difficulties to be performed due to the arbitrariness of the nonparametric function included in the partial linear model. In this study, through the estimation of nonparametric function and outlier detection methods such as a sequential test and a maximum trimmed likelihood estimation, processes for transforming response variable robust to outliers in partial linear models are suggested. The proposed methods are verified and compared their effectiveness by simulation study and examples.

• The Korean Journal of Applied Statistics
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• v.4 no.1
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• pp.13-24
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• 1991

This paper presents a Monte Carlo evaluation of estimators for nonlinear consored simultaneous equations models. We examine the performance of the maximum likelihood estimator (MLE), the two-step quasi maximum likelihood estimator (2QMLE) proposed by Lee and Hurd (1989), and another quasi MLe using least squares at the first step (LSAE) under varying degrees of freedom and underlying distributions, Although QMLE's are not necessarily consistent, the Monte Carlo results show that the 2QMLE may be used as an alternative to MLE when MLE is not applicable in practice.