• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.3
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• pp.463-472
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• 1994

A method of stochastic response analysis of base-isolated fluid-filled pool structures subject to random ground excitations is studied. Fluid-structure interaction effects between the flexible walls and contained fluid are taken into account in the form of added mass matrix derived by FEM modeling of the contained fluid motion. The stationary ground excitation is represented by Modified Clough-Penzien spectral model and the nonstationary one is obtained by imposing an envelope function on the stationary one. The stationary and nonstationary response statistics of the two different isolation systems are obtained by solving the governing Lyapunov covariance matrix differential equations.

• Journal of The Korean Association For Science Education
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• v.17 no.1
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• pp.1-10
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• 1997

The purpose of this study was to analyze the structural model of causal effects of students' variables on science process skills. Student characteristics investigated in the study included attitude related to the science, logical thinking ability, scientific experiences, cognitive style. Covariance structural modeling procedures were used to test causal inferences about hypothesized relationships. The sample consisted of 319 6th grade students and 321 8th grade students in Seoul City, Korea. Five instruments were used in the study, TSPS(test of science process skills), GALT(group assessment of logical thinking), CEFT(children embedded figures test), questionnaire of attitude related to the science, questionnaire of scientific experience. For statistical analysis, the study adopted the structural equation modeling with LlSREL, a computer statistical program developed by J reskog and S rbom. Major findings of the study are as follows:1) Logical thinking ability has a most strong direct effect on science process skills. 2) The structural coefficient of scientific experience influence on attitude related to the science has the greatest direct one than the others in the covariance structural model. According to the results of this study, it is very importance that various scientific experiences, particularly hands-on activity, should be offer to students to improve science process skills. Also, understanding the relationships of student variable to science process skills will be helpful to decision making on the part of curriculum developers, science teachers and researchers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.117-129
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• 1996

This Study intends to analysis what 3 factors, which are indices of Capital, Labor and Distribution, really affect to Value-Added Productivity through Statistical Analysis. For this, We selected 12 indices of Value-Added from the edition of 'Annual report of Korean companies' published in 'Korea Investors Service., Inc', especially in parts of Chemicals and Chemical products of total 85 companies. Using this data, Multivariate Statistical Analysis such as Principal Component Analysis, Factor Analysis, Covariance Structure Analysis is taken for modeling the effect of 3 factor(Labor Productivity, Capital Productivity and the Index of Distribution) on Value-Added Productivity.

• Journal of the Korean earth science society
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• v.23 no.1
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• pp.15-29
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• 2002

Bayesian inversion for gravity and resistivity data was performed to investigate the cavity structure appearing as a lava tunnel in Cheju Island, Korea. Dipole-dipole DC resistivity data were proposed for a prior information of gravity data and we applied the geostatistical techniques such as kriging and simulation algorithms to provide a prior model information and covariance matrix in data domain. The inverted resistivity section gave the indicator variogram modeling for each threshold and it provided spatial uncertainty to give a prior PDF by sequential indicator simulations. We also presented a more objective way to make data covariance matrix that reflects the state of the achieved field data by geostatistical technique, cross-validation. Then Gaussian approximation was adopted for the inference of characteristics of the marginal distributions of model parameters and Broyden update for simple calculation of sensitivity matrix and SVD was applied. Generally cavity investigation by geophysical exploration is difficult and success is hard to be achieved. However, this exotic multiple interpretations showed remarkable improvement and stability for interpretation when compared to data-fit alone results, and suggested the possibility of diverse application for Bayesian inversion in geophysical inverse problem.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.203-211
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• 2010

This study examines a cointegrated vector autoregressive (VAR) model where parameters are subject to switch across the regimes in the term structure of interest rates. To employ the regime switching framework, the Markov-switching vector error correction model (MS-VECM) is allowed to the regime shifts in the vector of intercept terms, the variance-covariance terms, the error correction terms, and the autoregressive coefficient parts. The corresponding approaches are illustrated using the term structure of interest rates in the US Treasury bonds over the period of 1958 to 2009. Throughout the modeling procedure, we find that the MS-VECM can form a statistically adequate representation of the term structure of interest rate in the US Treasury bonds. Moreover, the regime switching effects are analyzed in connection with the historical government monetary policy and with the recent global financial crisis. Finally, the results from the comparisons both in information criteria and in forecasting exercises with and without the regime switching lead us to conclude that the models in the presence of regime dependence are superior to the linear VECM model.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2516-2520
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• 2005

In this paper, finite impulse response (FIR) smoothers are proposed for discrete-time systems. The proposed FIR smoother is designed under the constraints of linearity, unbiasedness, FIR structure, and independence of the initial state information. It is also obtained by directly minimizing the performance criterion with unbiased constraints. The approach to the MVF smoother proposed in this paper is logical and systematic, while existing results have heuristic assumption, such as infinite covariance of the initial state. Additionally, the proposed MVF smoother is based on the general system model that may have the singular system matrix and has both system and measurement noises. Thorough simulation studies, it is shown that the proposed MVF smoother is more robust against modeling uncertainties numerical errors than fixed-lag Kalman smoother which is infinite impulse response (IIR) type estimator.

• Korean Journal of Child Studies
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• v.22 no.2
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• pp.113-132
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• 2001

In order to develop a model for better understanding of causal relationships in resiliency factors in families of children with disabilities, 200 families participated in this adaptation of the Resiliency Model of McCubbin and McCubbin(1993). The 6 latent variables included in the hypothesized model were family stress, family hardiness, family schema, community support, family problem-solving communication, and family adaptation. The models were developed on the basis of confirmatory factor analysis and compared using covariance structure modeling (LISREL). Adequate fitness of the model was observed. Family stress showed negative effect on family schema and on family hardiness. Family schema showed positive effect on community support and on family hardiness. Family hardiness showed positive effect on family problem-solving communication, and family problem-solving communication showed positive effect on family adaptation.

• The Journal of Information Systems
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• v.14 no.1
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• pp.227-249
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• 2005

In this research, four antecedents of trust ad the effect of trust and perceived risk on attitude and purchase intension in internet shopping malls is investigated. In survey, data were collected from 286 male and female internet shopping mall users, and then covariance structure modeling through Amos was used to test the 10 hypotheses. The survey results as follow: First, this research shows that institution base structural assurance and situational normality and knowledge-based familiarity are important antecedents on trust in internet shopping malls. Second, trust affected attitude and purchase intension. Third, it has a negative relationship between trust and perceived risk. But perceived risk does not influence attitude and purchase intension. This study contribute to understanding on the role of trust and perceived risk in internet shopping malls.

• Korean Journal of Child Studies
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• v.27 no.3
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• pp.271-284
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• 2006

In order to define their relative influence, this study analyzed causal relationships between academic achievement of elementary school students and such related variables as self-esteem and the psychological and economic environment of the home, including clarification of other significant variables affecting academic achievement. Participants were a sample of 485 5th grade students from 8 elementary schools in Busan. Correlation, analysis of covariance structure modeling, and model-fitness tests were applied to the data. Results indicated that the psychological environment of the home has the most significant influence on the academic achievement of children, and the economic environment of the home and self-esteem have relatively low or indirect influence.