• 한국정보처리학회논문지
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• 제5권11호
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• pp.2954-2972
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• 1998

광대역 종합정보 통신망에서 주문형 비디오 서비스 등의 멀티미디어 서비스가 본격적으로 도입됨에 따라 압축된 비디오의 전송이 전체 통신망 트래픽의 상당 부분을 차지할 것으로 기대된다. 가변 비트율로 부호화된 비디오가 통계적 이득과 일정한 비디오 품질을 제공할 수 있는 장점 때문에 많이 사용이 될 것이다. 비디오 트래픽을 전송하기 위해서는 음성 및 데이터 보다 많은 대역폭을 요구하기 때문에 ATM 통신망에서의 적절한 자원 할당 기법의 설계를 위하여 비디오 소스의 특성화와 트래픽 모델링은 아주 중요하다. 그리고 셀 손실, 지연 및 지터 등과 같은 성능 척도를 분석하기 위하여도 적절한 통계적 소스 모델이 필요하다. 본 논문에서는 MPEG 비디오 소스에 대한 특성화와 트래픽 모델링에 대하여 분석 기술하였다. 모델들을 크게 두 가지 즉, 통계적 모델과 결정적 모델로 분류하였다. 통계적 모델에서는 AR(autoregnessive), Markov, Markov와 AR의 복합, TES, 그리고 자기유사 모델로 분류하였다. 결정적 모델에서는 $({\sigma},\;{\rho}$, 매개변수화된 모델, D-BND, Empirical Envelopes 모델로 분류하였다. 각 모델들에 대한 특성, 장점 및 단점을 분석하고, 각 모델의 복잡도에 대하여 비교 분석하였다.

• 터널과지하공간
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• 제12권1호
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• pp.19-30
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• 2002

절리 방향은 절리 크기 및 밀집도와 더불어 암반 사면 및 터널과 같은 암반구조물의 안정성에 영향을 미치는 중요한 기하학적 속성이다. 이와 같은 절리 기하학적 속성들에 대한 통계 모델링은 암반공학적 문제에 대한 확률론적 접근법을 제공할 수 있다. 암반 공학적 문제의 확률론적 모델링의 결과는 어떠한 통계 모델을 선택하느냐에 따라 많은 영향을 받는다. 따라서 , 절리 방향성 자료에 대한 대표적인 통계 모델을 정의하고 각 모델에 대한 분석적 검증과 자료의 통계적 특성에 기초한 모델링 과정의 정립은 매우 중요하다. 이에 본 연구에서는 회전대칭성 모델인 Fisher 분포와 회전 비대칭성 모델인 이변량 정규분포 모델에 대한 통계량 추정 및 검증에 대한 이론적 방법론에 대해 검토하고 , 암반 절리계 모사 및 위험도 분석에 유용하게 사용할 수 있는 인공자료 발생기 알고리즘을 제안하였다.

• 아동학회지
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• 제11권1호
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• pp.87-99
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• 1990

The present study was designed to investigate the effect of altruistic TV viewing and verbal training on the altruistic behavior of preschoolers. The subjects of this study were a total of 56 boys and 57 girls from a kindergarten in Kwachon, Kyung-gi do. The subjects were assigned to one of three conditions: in the first condition subjects were shown video tapes designed to portray prosocial themes (TV modeling group) ; in the second condition subjects saw the video tapes in addition to verbal training (TV modeling plus verbal training group); in the third condition subjects received neither TV modeling nor verbal training (control group). Statistical analysis was by ANOVA and $Scherr\acute{e}$ test. Significant differences were found in altruistic behavior between the TV modeling and the TV modeling with verbal training groups.

• 지식경영연구
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• 제20권1호
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• pp.1-26
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• 2019

This tutorial introduces procedures and methods for performing structural equation modeling using R. For this, we present the whole process of analyzing the structural equations model from the confirmatory factor analysis to the path diagram generation using the lavaan package, which is relatively well evaluated among the R packages supporting the structural equation modeling, together with the R program codes. Considering that research applying structural equation modeling techniques is the mainstream in a variety of social sciences, including business administration, and that there is growing interest in open source R, this tutorial focuses on researchers who are looking for alternatives to traditional commercial statistical packages and is expected that it will be a useful guidebook for them.

• 전자통신동향분석
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• 제28권1호
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• pp.42-51
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• 2013

The R language is an open source programming language and a software environment for statistical computing and data visualization. The R language is widely used among a lot of statisticians and data scientists to develop statistical software and data analysis. The R language provides a variety of statistical and graphical techniques, including basic descriptive statistics, linear or nonlinear modeling, conventional or advanced statistical tests, time series analysis, clustering, simulation, and others. In this paper, we first introduce the R language and investigate its features as a data analytics tool. As results, we may explore the application possibility of the R language in the field of data analytics.

• Communications for Statistical Applications and Methods
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• 제30권5호
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• pp.437-451
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• 2023

Generalized linear models and generalized linear mixed models (GLMMs) are fundamental tools for predictive analyses. In insurance, GLMMs are particularly important, because they provide not only a tool for prediction but also a theoretical justification for setting premiums. Although thousands of resources are available for introducing GLMMs as a classical and fundamental tool in statistical analysis, few resources seem to be available for the insurance industry. This study targets insurance professionals already familiar with basic actuarial mathematics and explains GLMMs and their linkage with classical actuarial pricing tools, such as the Buhlmann premium method. Focus of the study is mainly on the modeling aspect of GLMMs and their application to pricing, while avoiding technical issues related to statistical estimation, which can be automatically handled by most statistical software.

• Computers and Concrete
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• 제15권6호
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• pp.989-999
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• 2015

An advanced continuum-based multi-physical single particle model was recently introduce for the hydration of tricalcium silicate ($C_3S$). In this model, the dissolution and the precipitation events are modeled as two different yet simultaneous chemical reactions. Product precipitation involves a nucleation and growth mechanism wherein nucleation is assumed to happen only at the surface of the unreacted core and product growth is characterized via a two-step densification mechanism having rapid growth of a low density initial product followed by slow densification. Although this modeling strategy has been shown to nicely mimic all stages of $C_3S$ hydration - dissolution, dormancy (induction), the onset of rapid hydration, the transition to slow hydration and prolonged reaction - the major criticism is that many adjustable parameters are required. If formulated correctly, however, the model parameters are shown here to be statistically independent and significant.

• Computers and Concrete
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• 제21권2호
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• pp.111-116
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• 2018

Establishment of test methods to assess the fresh properties of self-compacting concrete (SCC) are required to ensure the homogeneity in fresh and hardened states. This paper discusses the suitability of a simple test method for assessing the slump flow and stability of SCC by testing on self-compacting mortar (SCM) fraction. The proposed test method aims at investigating slump flow diameter test and sieve stability test of SCC by testing SCM fraction with a plunger penetration apparatus. A central composite modeling design was performed to evaluate the effects of water/cement ratio (W/C), superplasticizer dosage (SP) and powder marble content (MP) on slump flow diameter, stability and plunger penetration test of fresh SCC. The responses of the derived statistical models are slump flow (Sf), sieve stability (S) and plunger penetration (P). Relationships obtained in this study show acceptable correlations between plunger penetration test value and slump flow diameter test results and stability. It should note that the developed relationships are very useful to predict slump flow diameter and stability of studied SCC mixtures by carrying out a simple plunger penetration test on its mortar, which can save labour and time in laboratory experiments.

• Journal of the Korean Statistical Society
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• 제35권4호
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• pp.409-417
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• 2006

This article is concerned with threshold modeling of the bifurcating autoregressive model (BAR) originally suggested by Cowan and Staudte (1986) for tree structured data of cell lineage study where each individual $(X_t)$ gives rise to two off-spring $(X_{2t},\;X_{2t+1})$ in the next generation. The triplet $(X_t,\;X_{2t},\;X_{2t+1})$ refers to mother-daughter relationship. In this paper we propose a threshold model incorporating the difference of 'fertility' of the mother for the first and second off-springs, and thereby extending BAR to threshold-BAR (TBAR, for short). We derive a sufficient condition of stationarity for the suggested TBAR model. Also various inferential methods such as least squares (LS), maximum likelihood (ML) and quasi-likelihood (QL) methods are discussed and relevant limiting distributions are obtained.

• Journal of the Korean Statistical Society
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• 제28권3호
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• pp.371-387
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• 1999

For possibly nonstationary autoregressive moving average, modeling based on the original observations rather than the differenced observations is considered. Under this scheme, sample autocorrelation functions, parameter estimates, model diagnostic statistics, and prediction are all computed from the original data instead of the differenced data. The methods and results established under stationarity of data are shown to naturally extend to the nonstationarity of one autoregressive unit root. The sample ACF and PACF can be used for ARMA order determination. The BIC order is strongly consistent. The parameter estimates are asymptotically normal. The portmanteau statistic has chi-square distribution. The predictor is asymptotically equivalent to that based on the differenced data.