• 한국운동역학회지
• /
• 제27권3호
• /
• pp.205-210
• /
• 2017

Objective: The aim of the study was to investigate the age-related ability of dynamic balance recovery through perturbation response during standing. Method: Six older and 6 younger adults participated in this study. External perturbation during standing as pulling force applied at the pelvic level in the anterior direction was provided to the subject. The margin of stability was quantified as a measure of postural stability or dynamic balance recovery, and using principal component analysis (PCA), the regularity of the margin of stability (MoS) was calculated. Results: Our results showed that in the older adult group, 60.99% and 28.63% of the total variance were captured using the first and second principal components (PCs), respectively, and in the younger adult group, 81.95% and 10.71% of the total variance were captured using the first and second PCs, respectively. Conclusion: Ninety percent of the total variance captured using the first two PCs indicates that the older adults had decreased regularity of the MoS than the younger adults. Thus, the results of the present study suggest that aging is associated with non-regularity of dynamic postural stability.

• 생명과학회지
• /
• 제14권3호
• /
• pp.400-405
• /
• 2004

한국내 분포하는 음나무(Kalopanox pictus Nakai)의 집단간 분화를 연구하기 위해 형태적 특성을 조사하였다. 23개 형태 형질에 근거하여 지역간 분화는 현저하였다. 아홉 집단에서 138표본으로 유효한 분류학적 단위(OTU)를 표현형 유사도와 형태적 변이를 조사하였으며 주성분 분석을 실시하였다. 첫 세 주성분 요소가 전체 변이의 77.0%에 관련이 있었다. 이 중 첫 번째 주성분 요소가 전체 변이의 52%에 기여하였는데 이에 해당되는 형질은 장상복엽의 장상렬의 수, 그리고 장상렬의 폭이다. 형태적 변이에 근거한 군집분석에서 우리나라 남부와 중부지방의 두 그룹으로 나누어졌다.

• 한국환경보건학회지
• /
• 제31권2호
• /
• pp.134-146
• /
• 2005

Environmental monitoring system has been adopted and supplemented as inspection measures for the quantitative and qualitative changes of environmental impact assessment (EIA). This study compares the results of environmental impact assessment with the results of post-environmental investigation using a correction and principal component analysis (PCA) in the housing development project. Correlation analysis showed that most of air quality variables including TSP, $PM_{10},\;NO_2$, CO were linearly correlated with each other in the environmental impact assessment and the post-environmental investigation. In the water quality, pH and BOD were well correlated with the DO and SS, respectively. As a result of correlation analysis in the noise and vibration, noise in day and night and vibration in day and night were related to each other between EIA and the post-environmental investigation. From the results of analysis of soil, Cu with Cd, Cu with Pb, and Cd with Pb were related to each other in EIA. Principal component analysis (PCA) showed a powerful pattern recognition that had attempted to explain the variance of a large dataset of inter-correlated variable with a smaller set of independent variables (principal components). Principal component (PC1) and principal component (PC2) were obtained with eigenvalues> 1 summing almost $90\%$ of the total variance in the all of the items(air, water, noise, vibration and soil) in EIA and post-environmental investigation.

• 대한치과의사협회지
• /
• 제57권8호
• /
• pp.448-455
• /
• 2019

This study aims to apply the Generalizability Theory (G-theory) for estimation of reliability of evaluation scores between raters on Patient Dentist Interaction. Selecting a number of raters as multiple error sources, this study was analyzed the error sources caused by relative magnitude of error variances of interaction between the factors and proceeded with D-study based on the results of G-study for optimal determination of measurement condition. The estimated outcomes of variance component for accuracy among the Patient Dentist Interaction evaluation with G-theory showed that impact of error was the biggest influence factor in students. The second influence was the item effect, and the rater effect was relatively small. The Generalizability coefficients for case1 and case2 which were estimated through the D- study were calculated relatively low.

• 수산경영론집
• /
• 제14권2호
• /
• pp.1-14
• /
• 1983

This paper considers a classification of the 88 islands located at Kyong-nam area in Korea, using by examples of 12 components of the islands. By means of principal component analysis 2 principle components were extracted, which explained a total of 73.7% of the variance. Using an eigen variable criterion (λ>1), no further principle components were discussed. Principal component 1 and 2 explained 63.4% and 10.3% of the total variance respectively, The representation of the unrelated factor scores along the first and second principal axes produced a new information with respect to the classification of the islands. Based upon the representation, 88 islands were classified into 6 groups i. e. A, B, C, D, E, and F according to similarity of the components among them in this paper. The "Group F" belongs to a miscellaneous assortment that does not fit into the logical category. category.

• Communications for Statistical Applications and Methods
• /
• 제27권5호
• /
• pp.523-533
• /
• 2020

This paper suggests three available methods for finding nonnegative estimates of variance components of the random effects in mixed models. The three proposed methods based on the concepts of projections are called projection method I, II, and III. Each method derives sums of squares uniquely based on its own method of projections. All the sums of squares in quadratic forms are calculated as the squared lengths of projections of an observation vector; therefore, there is discussion on the decomposition of the observation vector into the sum of orthogonal projections for establishing a projection model. The projection model in matrix form is constructed by ascertaining the orthogonal projections defined on vector subspaces. Nonnegative estimates are then obtained by the projection model where all the coefficient matrices of the effects in the model are orthogonal to each other. Each method provides its own system of linear equations in a different way for the estimation of variance components; however, the estimates are given as the same regardless of the methods, whichever is used. Hartley's synthesis is used as a method for finding the coefficients of variance components.

• Journal of the Korean Statistical Society
• /
• 제29권1호
• /
• pp.81-94
• /
• 2000

For the balanced variance component model, sometimes intraclass correlation coefficient is of interest. If there is little information about the parameter, then the reference prior(Berger and Bernardo, 1992) is widely used. Pettit nd Young(1990) considered a measrue of the effect of a single observation on a logarithmic Bayes factor. However, under such a reference prior, the Bayes factor depends on the ratio of unspecified constants. In order to discard this problem, influence diagnostic measures using the intrinsic Bayes factor(Berger and Pericchi, 1996) is presented. Finally, one simulated dataset is provided which illustrates the methodology with appropriate simulation based computational formulas. In order to overcome the difficult Bayesian computation, MCMC methods, such as Gibbs sampler(Gelfand and Smith, 1990) and Metropolis algorithm, are empolyed.

• Asian-Australasian Journal of Animal Sciences
• /
• 제13권8호
• /
• pp.1035-1039
• /
• 2000

This study developed a Poisson generalized linear mixed model and a procedure to estimate genetic parameters for count traits. The method derived from a frequentist perspective was based on hierarchical likelihood, and the maximum adjusted profile hierarchical likelihood was employed to estimate dispersion parameters of genetic random effects. Current approach is a generalization of Henderson's method to non-normal data, and was applied to simulated data. Underestimation was observed in the genetic variance component estimates for the data simulated with large heritability by using the Poisson generalized linear mixed model and the corresponding maximum adjusted profile hierarchical likelihood. However, the current method fitted the data generated with small heritability better than those generated with large heritability.

• Communications for Statistical Applications and Methods
• /
• 제26권4호
• /
• pp.337-346
• /
• 2019

This paper discusses a method for obtaining nonnegative estimates for variance components in a random effects model. A variance component should be positive by definition. Nevertheless, estimates of variance components are sometimes given as negative values, which is not desirable. The proposed method is based on two basic ideas. One is the identification of the orthogonal vector subspaces according to factors and the other is to ascertain the projection in each orthogonal vector subspace. Hence, an observation vector can be denoted by the sum of projections. The method suggested here always produces nonnegative estimates using projections. Hartley's synthesis is used for the calculation of expected values of quadratic forms. It also discusses how to set up a residual model for each projection.

• Journal of the Korean Statistical Society
• /
• 제25권4호
• /
• pp.457-469
• /
• 1996

In this paper, we propose a method for an exact test of H : $p_i$ = $r_i$ for all i against K : $p_i$ $\neq$ $r_i$ for some i in an unbalanced random effect linear model, where $p_i$ denotes the ratio of the i-th variance component to the error variance. Then we present a method to test H : $p_i$ $\leq$ r against K : $p_i$> r for some specific i by applying orthogonal projection on the model. We also show that any test statistic that follows an F-distribution on the boundary of the hypotheses is equal to the one given here.