• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.262-262
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• 2008

• Environmental and Resource Economics Review
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• v.17 no.1
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• pp.3-22
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• 2008

We study nonlinearities of $CO_2$ emissions and economic growth m Korea using the Smooth Transition Autoregressive (or STAR) model. We find evidence for nonlinearities and cyclical regime changes of both time series. In the extended nonlinear empirical work, we characterize dynamic properties of the two time series and then find mutually significant Granger causality between $CO_2$ emissions and economic growth. All these empirical evidences together reinforce long standing concern that economy-wide restrictions on $CO_2$ emissions would hurt economic growth for Korean styled medium industrialized countries.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.173-184
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• 2004

A statistical software for nonlinear regression analysis, NLIN2000, is introduced. This software, operated tinder the Window systems, has many user-friendly functions and Provides various statistics. As an upgraded version of the Previous Program operated under the DOS system, NLIN2000 provides easier steps for model specification and fitting process than any other statistical packages. Also it has a database system for model functions which has addition and deletion options. While it can be a useful research tool for statisticians, NLIN2000 can be used practically also by researchers in many other scientific fields, who needs nonlinear regression analysis for their study.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.4 no.2
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• pp.108-120
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• 1992

An ADI model for linearized shallow water equation is modified using the method of factorization. In order to show its validity. the computational results are compared both with the analytical solution and with those from existing models, for a rectangualr domain with constant and varying amplitudes at the open boundary. It is shown the accuracy of numerical solutions depends on the size of time step. depth and bottom friction. The modified ADI model is shown to be superior to the existing models such as Leendertse (1971). Butler (1980) and Sheng (1983).

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.213-222
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• 2002

The 3-hour-interval prediction of ground-level temperature up to +45 hours in Seoul area is performed using dynamic linear models(DLM). Numerical outputs and observations we used as input values of DLM. According to compare DLM forecasts to RDAPS forecasts using RMSE, DLM improve the accuracy of prediction and systematic error of numerical model outputs are eliminated by DLM.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1516-1519
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• 2011

예측에 필요한 중요한 자료에는 비선형 자료와 시계열과 같은 선형 자료 등이 있다. 이들 자료는 그 함축적인 관계가 매우 복잡하여 전통적인 통계분석 도구로 식별하는데 어려움이 많다. 신경망 분석은 비모수적 문제나 비선형 곡선 적합능력의 우수성 때문에 현실세계에서의 고유한 복잡성을 다루는 많은 경제 응용 분야에서 널리 이용되고 있다. 신경망은 또한 경제 시계열자료의 예측분야에서도 여러 연구에서 훌륭한 도구로서 적용되고 있다. 전통적으로 우리나라에서 시계열자료의 예측은 선형 자료적 분석을 중심으로 하는 분석도구인 자기회귀누적이동평균(ARIMA)모형을 이용한 시계열분석이 일반적이다. 이 연구에서는 신경망과 ARIMA 모형을 이용하여 한국의 주가변동 자료 및 자동차등록 현황 자료등과 같은 시계열자료를 이용한 예측결과를 비교한다. 연구의 결과는 신경망을 이용한 예측 방법들이 ARIMA 예측 결과보다 통계적으로 작은 오차를 주는 보다 효율적인 방법임을 보여주고 있다.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.123-137
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• 2018

A nonlinear mixed effects model is mainly used to analyze repeated measurement data in various fields. A nonlinear mixed effects model consists of two stages: the first-stage individual-level model considers intra-individual variation and the second-stage population model considers inter-individual variation. The individual-level model, which is the first stage of the nonlinear mixed effects model, estimates the parameters of the nonlinear regression model. It is the same as the general nonlinear regression model, and usually estimates parameters using the least squares estimation method. However, the least squares estimation method may have a problem that the estimated value of the parameters and standard errors become extremely large if the assumed nonlinear function is not explicitly revealed by the data. In this paper, a new estimation method is proposed to solve this problem by introducing the ridge regression method recently proposed in the nonlinear regression model into the first-stage individual-level model of the nonlinear mixed effects model. The performance of the proposed estimator is compared with the performance with the standard estimator through a simulation study. The proposed methodology is also illustrated using quantitative high throughput screening data obtained from the US National Toxicology Program.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.123-132
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• 2000

In the study the instantaneous unit hydrographs (IUHs) based on the linear Nash (1957) and the nonlinear Diskin (1964) models are derived and compared for the Soyang river basin. Total 14 rainfall runoff events are used for the study and the model parameters are estimated by minimizing the sum of square error considering runoff hydrograph ordinates as relative weights. The representative IUHs for both models are decided to show an average shape of derived IUHs. In the application of the representative IUHs of Nash and Diskin, Diskin model shows better performances in reproducing the observed outflows, especially the peak flow. In the comparison of two Diskin models little difference could be found between the IUHs with the same or different number of two characteristic reservoirs.rvoirs.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.217-225
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• 2019

The Latent Growth Modeling(LGM) is known as the typical analysis method of longitudinal data and it could be classified into unconditional model and conditional model. It is common to assume that the growth trajectory of unconditional model of LGM is linear. In the case of quasi-linear, the methodology for improving the model fitness using Sequential Pattern of Association Rule Mining is suggested. To do this, we divide longitudinal data into quintiles and extract periodic changes of the longitudinal data in each quintiles and make sequential pattern based on this periodic changes. To evaluate the effectiveness, the LGM module in SPSS AMOS was used and the dataset of the Youth Panel from 2001 to 2006 of Korea Employment Information Service. Our methodology was able to increase the fitness of the model compared to the simple linear growth trajectory.

• 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.