• Journal of the Korean Statistical Society
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• 제20권1호
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• pp.67-76
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• 1991

The empirical Bayes version involves ″independent″ repetitions(a sequence) of the component decision problem. With the varying sample size possible, these are not identical components. However, we impose the usual assumption that the parameters sequence $\theta$=($\theta$$_1$, $\theta$$_2$, …) consists of independent G-distributed parameters where G is unknown. We assume that G $\in$ g, a known family of distributions. The sample size $N_i$ and the decisin rule $d_i$ for component i of the sequence are determined in an evolutionary way. The sample size $N_1$ and the decision rule $d_1$$\in$ $D_{N1}$ used in the first component are fixed and chosen in advance. The sample size $N_2$and the decision rule $d_2$ are functions of *see full text($\underline{X}^1$equation omitted), the observations in the first component. In general, $N_i$ is an integer-valued function of *see full text(equation omitted) and, given $N_i$, $d_i$ is a $D_{Ni}$/-valued function of *see full text(equation omitted). The action chosen in the i-th component is *(equation omitted) which hides the display of dependence on *(equation omitted). We construct an empirical Bayes decision rule for estimating normal mean and show that it is asymptotically optimal.

• 천문학회지
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• 제36권spc1호
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• pp.109-115
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• 2003

We report the results of the ionospheric measurement obtained from the instruments on board the Korea Multi-Purpose Satellite - 1 (KOMPSAT-l). We observed a deep electron density trough in the nighttime equatorial ionosphere during the great magnetic storm on 15 July 2000. We attribute the phenomena to the up-lifted F-layer caused by the enhanced eastward electric field, while the spacecraft passed underneath the layer. We also present the results of our statistical study on the equatorial plasma bubble formation. We confirm the previous results regarding its seasonal and longitudinal dependence. In addition, we obtain new statistical results of the bubble temperature variations. The whole data set of measurement for more than a year is compared with the International Reference Ionosphere (IRI). It is seen that the features of the electron density and temperature along the magnetic equator are more prominent in the KOMPSAT-l observations than in the IRI model.

• Geomechanics and Engineering
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• 제11권3호
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• pp.361-372
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• 2016

The soil-concrete interface shear strength, although has been extensively studied, is still difficult to predict as a result of the dependence on many factors such as normal stresses, surface roughness, particle sizes, moisture contents, dilation angles of soils, etc. In this study, a well-known rigorous statistical learning approach, namely the least squares support vector machine (LS-SVM) realized in a ubiquitous spreadsheet platform is firstly used in estimating the soil-structure interface shear strength. Instead of studying the complicated mechanism, LS-SVM enables to explore the possible link between the fundamental factors and the interface shear strengths, via a sophisticated statistic approach. As a preliminary investigation, the authors study the expansive soils that are found extensively in most countries. To reduce the complexity, three major influential factors, e.g., initial moisture contents, initial dry densities and normal stresses of soils are taken into account in developing the LS-SVM models for the soil-concrete interface shear strengths. The predicted results by LS-SVM show reasonably good agreement with experimental data from direct shear tests.

• 한국통신학회논문지
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• 제31권7B호
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• pp.652-659
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• 2006

애드 혹 네트워크에서 라우팅 알고리즘은 매우 중요한 연구 분야중의 하나이다. 기존의 라우팅 알고리즘은 현재의 네트워크 토폴로지 상황만을 고려하여 라우팅 경로를 설정하기 때문에 안정적인 라우팅 경로를 설정하는데 많은 어려움이 있다. 이와 같은 문제점을 해결하기 위해 수신 신호 세기를 이용하여 라우팅을 수행하는 알고리즘들이 제안되었지만, 이들은 평균 수신 신호 세기만을 고려하였기 때문에 라우팅 프로토콜의 성능 향상에는 한계가 있다. 따라서 본 논문에서는 평균 수신 신호 세기와 수신 신호 세기의 변화를 고려한 링크 안정성 기반의 라우팅 알고리즘을 제안하였다. 제안된 알고리즘의 성능을 분석하기 위해 다양한 환경에서의 모의실험을 수행하였으며, 그 결과 기존의 알고리즘보다 우수한 성능을 보임을 확인하였다.

• Spatial Information Research
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• 제10권2호
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• pp.233-246
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• 2002

본 연구에서는 GIS의 공간통계분석을 활용하여 지가 연구에 일반적으로 활용되고있는 특성가격모형에서 입지적 특성이 갖는 영향력을 계량적으로 설명하기 위한 분석방법을 제시하였다. 여기에는 GIS 공간분석방법 가운데 중첩과 내삽 기능을 이용한 공간자료의 처리 과정이 포함되었다. 사례연구를 위해 동대문구 회기동의 1421개 개별지가에서 54개 표준지들을 추출하여 표준지의 중심좌표를 구하고, 이 벡터 자료점들과 공간적 관련성에 기초하여 조사되지 않은 지점의 지가 예측값을 확률적으로 평가할 수 있는 크리깅 분석방법을 적용하였다. 특히 이러한 분석 과정에서 변동도를 통해 분석한 공간적 자기상관관계는 공간 의존성의 형성과정을 추정할 때 장점이 있음을 밝혔다.

• 천문학회보
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• 제43권1호
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• pp.34.1-34.1
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• 2018

Using cosmological N-body simulations we investigate statistical properties of flyby encounters between halos in comparison with mergers. We classify halo pairs into two groups based on the total energy (E12); flybys (E12 > 0) and mergers (E12 < 0). By measuring the flyby and merger fractions, we assess their dependencies on redshift (0 < z < 4), halo mass (10.8 < log Mhalo/Msun < 13.0), and large-scale environment (from field to cluster). We find that the flyby and merger fractions similarly increase with redshift until z = 1, and that the flyby fraction at higher redshift (1 < z < 4) slightly decreases in contrast to the continuously increasing merger fraction. While the merger fraction has little or no dependence on the mass and environment, the flyby fraction correlates negatively with mass and positively with environment. The flyby fraction exceeds the merger fraction in filaments and clusters; even 10 times greater in the densest environment. Our results suggest that the flyby makes a substantial contribution to the observed pair fraction, thus heavily influencing galactic evolution across the cosmic time.

• Structural Engineering and Mechanics
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• 제12권3호
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• pp.249-266
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• 2001

Current seismic design provisions allow structures to deform into inelastic range during design level earthquakes since the chance to meet such event is quite rare. For this purpose, design base shear is defined in current seismic design provisions as the value of elastic seismic shear force divided by strength reduction factor, R (${\geq}1$). Strength reduction factor generally consists of four different factors, which can account for ductility capacity, overstrength, damping, and redundancy inherent in structures respectively. In this study, R factor is assumed to account for only the ductility rather than overstrength, damping, and redundancy. The R factor considering ductility is called "ductility factor" ($R_{\mu}$). This study proposes ductility factor with correction factor, C, which can account for dynamic P-${\Delta}$ effect. Correction factor, C is established as the functional form since it requires computational efforts and time for calculating this factor. From the statistical study using the results of nonlinear dynamic analysis for 40 earthquake ground motions (EQGM) it is shown that the dependence of C factor on structural period is weak, whereas C factor is strongly dependant on the change of ductility ratio and stability coefficient. To propose the functional form of C factor statistical study is carried out using 79,920 nonlinear dynamic analysis results for different combination of parameters and 40 EQGM.

• PNF and Movement
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• 제18권1호
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• pp.133-141
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• 2020

Purpose: The purpose of this study was to conduct balance training through vision control to improve the balance, postural control, and balance confidence and to decrease the visual and sensory dependence of stroke patients. Methods: Twenty-eight chronic stroke patients volunteered to participate in the study. They were randomly assigned to the eyes-closed and the eyes-open training groups. Three times a week for four weeks each group performed an unstable-support session and a balance training session for thirty minutes per set. Their balance, postural control, and balance confidence were assessed using BIO Rescue (BR), the postural assessment scale for stroke (PASS), and the Korean activity-specific balance confidence scale (K-ABC), respectively. All data were analyzed using SPSS version 22.0. Statistical methods before and after working around the average value of each dataset were independent T-test. The significance level for statistical analyses was set at 0.05. Results: Comparison between the groups showed statistically significant effects on all variables before and after the intervention (p < 0.05). Conclusion: This study reflected that balance-training programs involving vision control improve the balance, postural control, and balance confidence of chronic stroke patients. Thus, stroke patients should undergo training programs that increase the use of their other senses with vision control in clinical practice.

• Communications for Statistical Applications and Methods
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• 제26권3호
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• pp.261-272
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• 2019

In this paper, we propose a procedure to build a prediction interval of the sum of dependent binary random variables over a graph to account for the dependence among binary variables. Our main interest is to find a prediction interval of the weighted sum of dependent binary random variables indexed by a graph. This problem is motivated by the prediction problem of various elections including Korean National Assembly and US presidential election. Traditional and popular approaches to construct the prediction interval of the seats won by major parties are normal approximation by the CLT and Monte Carlo method by generating many independent Bernoulli random variables assuming that those binary random variables are independent and the success probabilities are known constants. However, in practice, the survey results (also the exit polls) on the election are random and hardly independent to each other. They are more often spatially correlated random variables. To take this into account, we suggest a spatial auto-regressive (AR) model for the surveyed success probabilities, and propose a residual based bootstrap procedure to construct the prediction interval of the sum of the binary outcomes. Finally, we apply the procedure to building the prediction intervals of the number of legislative seats won by each party from the exit poll data in the $19^{th}$ and $20^{th}$ Korea National Assembly elections.

• Genomics & Informatics
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• 제20권1호
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• pp.8.1-8.14
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• 2022

Despite the success of recent genome-wide association studies investigating longitudinal traits, a large fraction of overall heritability remains unexplained. This suggests that some of the missing heritability may be accounted for by gene-gene and gene-time/environment interactions. In this paper, we develop a Bayesian variable selection method for longitudinal genetic data based on mixed models. The method jointly models the main effects and interactions of all candidate genetic variants and non-genetic factors and has higher statistical power than previous approaches. To account for the within-subject dependence structure, we propose a grid-based approach that models only one fixed-dimensional covariance matrix, which is thus applicable to data where subjects have different numbers of time points. We provide the theoretical basis of our Bayesian method and then illustrate its performance using data from the 1000 Genome Project with various simulation settings. Several simulation studies show that our multivariate method increases the statistical power compared to the corresponding univariate method and can detect gene-time/ environment interactions well. We further evaluate our method with different numbers of individuals, variants, and causal variants, as well as different trait-heritability, and conclude that our method performs reasonably well with various simulation settings.