• Communications for Statistical Applications and Methods
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• 제15권6호
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• pp.1003-1011
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• 2008

Mixed-effect Poisson regression models are widely used for analysis of correlated count data such as those found in longitudinal studies. In this paper, we consider kernel extensions with semiparametric fixed effects and parametric random effects. The estimation is through the penalized likelihood method based on kernel trick and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of hyperparameters, cross-validation techniques are employed. Examples illustrating usage and features of the proposed method are provided.

• Communications for Statistical Applications and Methods
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• 제24권5호
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• pp.481-492
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• 2017

This paper investigates a convergence rate of a test statistics given by two scale sampling method based on $A\ddot{i}t$-Sahalia and Jacod (Annals of Statistics, 37, 184-222, 2009). This statistics tests for longitudinal data having the existence of long memory dependence driven by fractional Brownian motion with Hurst parameter $H{\in}(1/2,\;1)$. We obtain an upper bound in the Kolmogorov distance for normal approximation of this test statistic. As a main tool for our works, the recent results in Nourdin and Peccati (Probability Theory and Related Fields, 145, 75-118, 2009; Annals of Probability, 37, 2231-2261, 2009) will be used. These results are obtained by employing techniques based on the combination between Malliavin calculus and Stein's method for normal approximation.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.15-35
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• 2020

In research on behavioral studies, significant attention has been paid to the stage-sequential process for multiple latent class variables. We now explore the stage-sequential process of multiple latent class variables using the multivariate latent class profile analysis (MLCPA). A latent profile variable, representing the stage-sequential process in MLCPA, is formed by a set of repeatedly measured categorical response variables. This paper proposes the extended MLCPA in order to explain an association between the latent profile variable and the latent group variable as a form of a two-dimensional contingency table. We applied the extended MLCPA to the National Longitudinal Survey on Youth 1997 (NLSY97) data to investigate the association between of developmental progression of depression and substance use behaviors among adolescents who experienced Authoritarian parental styles in their youth.

• Communications for Statistical Applications and Methods
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• 제22권3호
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• pp.295-304
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• 2015

This paper considers the problem of estimation of the Hurst parameter H ${\in}$ (1/2, 1) from longitudinal data with the error term of a fractional Brownian motion with Hurst parameter H that gives the amount of the long memory of its increment. We provide a new estimator of Hurst parameter H using a two scale sampling method based on $A{\ddot{i}}t$-Sahalia and Jacod (2009). Asymptotic behaviors (consistent and central limit theorem) of the proposed estimator will be investigated. For the proof of a central limit theorem, we use recent results on necessary and sufficient conditions for multi-dimensional vectors of multiple stochastic integrals to converges in distribution to multivariate normal distribution studied by Nourdin et al. (2010), Nualart and Ortiz-Latorre (2008), and Peccati and Tudor (2005).

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 춘계학술대회 논문집
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• pp.1102-1107
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• 2004

High-speed railway bridges subject to effect of statical loads by temperature change as well as dynamic loads by interaction between vehicle load which run specially fast and behavior of bridges, If suitable longitudinal expansion by temperature change of bridge does not happened, it can cause unhealthy condition for the parts of bridges as well as can generate addition stress to bridges, For these reason, Analysis and Estimation of data about behavior of bridges occupies important factor in that estimate the remaining life of bridges and select the maintenance, repair and retrofit. In this paper, Analysis for the long-term behavior of bridges using Longitudinal displacement and Temperature data that is actuality measured data to the bridges of Seoul-Busan high speed railroad test section has been made.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.301-311
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• 2020

Schwarz's Bayesian information criterion (BIC) is one of the most popular criteria for model selection, that was derived under the assumption of independent and identical distribution. For correlated data in longitudinal studies, Jones (Statistics in Medicine, 30, 3050-3056, 2011) modified the BIC to select the best linear mixed effects model based on the effective sample size where the number of parameters in covariance structure was not considered. In this paper, we propose an extended Jones' modified BIC by considering covariance parameters. We conducted simulation studies under a variety of parameter configurations for linear mixed effects models. Our simulation study indicates that our proposed BIC performs better in model selection than Schwarz's BIC and Jones' modified BIC do in most scenarios. We also illustrate an example of smoking data using a longitudinal cohort of cancer patients.

• 컴퓨터교육학회논문지
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• 제23권1호
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• pp.53-61
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• 2020

정보사회에서 학습자가 자기주도적으로 학습을 수행하기 위해서 컴퓨터를 활용할 수 있는 능력은 중요하다. 실제로 컴퓨터를 활용할 수 있는 능력이 높은 학습자의 학업성취도가 어떠할지 분석할 필요가 있다. 본 연구는 2010년-2018년에 시행한 서울교육종단연구의 1-9차년도 자료를 활용하여 컴퓨터 활용에 대한 인식과 빈도의 종단적 변화 패턴을 비모수 통계방식인 종단적 K-평균 군집(KML)을 통해 도출하고, 종단적 패턴에 따른 학업성취도를 분석하였다. 분석결과 컴퓨터 활용과 사용 빈도가 높은 종단적 패턴이 그렇지 않은 패턴에 비해 학업성취도가 높은 것으로 분석되었고, 고등학교 3학년의 대학전공 선택에서 컴퓨터 활용과 빈도가 높은 종단적 패턴이 공학계열을 선호하는 것으로 분석되었다.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2001년도 가을 학술발표회 논문집
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• pp.477-482
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• 2001

This paper is to study the effect of longitudinal reinforcement ratios and axial deformation on the frame analysis in reinforced concrete(RC) columns and to investigate the effect of confined concrete core, the length-width ratio and longitudinal steel ratios on frame analysis in Concrete-Filled steel Tubular(CFT) columns. An equation if derived to evaluate the modulus of elasticity for core concrete. The 34 reference data have been collected for the purpose and are processed by the mean of a multiple regression analysis technique. The equation and longitudinal reinforcement ratios was applied to RC columns for structural analysis. Then, the difference of beam moment was identified. In general, the results of analysis was indicated reasonable differences in beam moment, in case of longitudinal reinforcement ratios applied to RC columns when compared with the plain concrete columns. In CFT columns the equation was also applied in order to the effect of confined concrete core on structural analysis. Beam moment was increased as volumetric ratio of lateral steel was decreased. The effect of longitudinal steel ratios was investigated in CFT columns and was confirmed beam moment variety. The result was appeared reasonable difference in beam moment as longitudinal steel was increased.

• 대한기계학회논문집A
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• 제20권9호
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• pp.2770-2781
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• 1996

Longitudinal shear modulus of continuous fiber reinforced 2-phase composites is predicted by theoretical and numerical analysis methods. In this paper, circular, hexagonal and rectangular shapes of reinforced fiber are considered using unit cell concept. And fiber array is regular rectangular and hexagonal fiber arrangement. Longitudinal shear modulus is a function of fiber distribution pattern and fiber volume change. It is found that the rectangular array has a higher longitudinal shear modulus than the hexagonal one. Also, the rectangular fiber shape in lower fiber volume fraction and the circular fiber shape in higher fiber volume fraction show the higher longitudinal shear modulus. And it has been found that the theoretical and numerical predictions of the longitudinal shear modulus give a good agreement with the experimental data at lower fiber volume fraction. Both the distance and stress transfer between the fibers are discussed as the major determing factors.

• 응용통계연구
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• 제33권3호
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• pp.281-296
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• 2020

같은 개체로부터 반복 측정한 자료를 경시적 자료(longitudinal data)라고 한다. 이러한 자료를 분석하려면 흔히 사용되는 횡단 자료 분석과는 다른 분석 방법이 필요하다. 즉, 경시적 자료에서 공변량의 효과를 추정할 때에는 반복 측정된 결과 간의 상관성을 고려해야 하며, 따라서 공분산행렬을 모형화 하는 것이 매우 중요하다. 그러나 추정해야 할 모수가 많고, 추정된 공분산행렬이 양정치성을 만족해야 하므로 공분산 행렬의 모형화는 쉽지 않다. 특히 다변량 경시적 자료분석을 위한 공분산행렬의 모형화는 더욱더 심층적인 방법론을 사용해야 한다. 본 논문은 다변량 경시적 자료분석을 위한 공분산행렬을 모형화하기 위해 두 가지 방법론을 고찰한다. 두 방법 모두 수정된 콜레스키 분해(modified Cholesky decomposition)를 이용하여 시간에 따른 응답변수들의 상관관계를 설명하고 있다. 하지만 같은 시간에서 관측된 응답변수들간의 상관관계를 설명하는 방법이 다르다. 첫 번째 방법론에서는 향상된 선형 공분산 모형(enhanced linear covariance models)을 사용하여 공분산행렬이 양정치성을 만족하도록 한다. 두 번째 방법론에서는 분산-공분산 분해(variance-correlation decomposition)와 초구분해(hypersphere decomposition)을 이용하여 공분산 행렬을 모형화 한다. 이 두 방법론의 성능을 비교하고자 모의실험을 진행한다.