• Communications for Statistical Applications and Methods
• /
• 제24권1호
• /
• pp.81-96
• /
• 2017

Cumulative logit random effects models are typically used to analyze longitudinal ordinal data. The random effects covariance matrix is used in the models to demonstrate both subject-specific and time variations. The covariance matrix may also be homogeneous; however, the structure of the covariance matrix is assumed to be homoscedastic and restricted because the matrix is high-dimensional and should be positive definite. To satisfy these restrictions two Cholesky decomposition methods were proposed in linear (mixed) models for the random effects precision matrix and the random effects covariance matrix, respectively: modified Cholesky and moving average Cholesky decompositions. In this paper, we use these two methods to model the random effects precision matrix and the random effects covariance matrix in cumulative logit random effects models for longitudinal ordinal data. The methods are illustrated by a lung cancer data set.

• Macromolecular Research
• /
• 제9권3호
• /
• pp.164-170
• /
• 2001

Recently in order to describe the complex rheological behavior of polymer melts with long side branches like low density polyethylene, new constitutive equations called the pom-pom equations have been derived by McLeish and Larson on the basis of the reptation dynamics with simplified branch structure taken into account. In this study mathematical stability analysis under short and high frequency wave disturbances has been performed for the simplified differential version of these constitutive equations. It is proved that they are globally Hadamard stable except for the case of maximum constant backbone stretch (λ = q) with arm withdrawal s$\_$c/ neglected, as long as the orientation tensor remains positive definite or the smooth strain history in the now is previously given. However this model is dissipative unstable, since the steady shear How curves exhibit non-monotonic dependence on shear rate. This type of instability corresponds to the nonlinear instability in simple shear flow under finite amplitude disturbances. Additionally in the flow regime of creep shear flow where the applied constant shear stress exceeds the maximum achievable value in the steady now curves, the constitutive equations will possibly violate the positive definiteness of the orientation tensor and thus become Hadamard unstable.

• 대한화학회지
• /
• 제23권1호
• /
• pp.15-19
• /
• 1979

Integral Hellmann-Feynman Theorem과 천이밀도의 positive definite한 성질로 부터, 천이 밀도 공간을 "결합공간"과 "반결합공간"으로 구분할 수 있음을 보였고, 이러한 개념의 유용성을 H2계에 대하여 증명하였다. 핵의 배치의 변화에 기인한 전자 섭동에너지의 본질을 이 개념을 이용함으로써 성공적으로 이해할 수 있으리라는 결론을 얻었다. 천이밀도의 성질에 관하여 논의하였다.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2007년도 한국컴퓨터종합학술대회논문집 Vol.34 No.1 (B)
• /
• pp.15-20
• /
• 2007

기존의 연구는 DNA 커널을 통한 기계 학습이 DNA 분자들을 통한 in vitro 실험을 통해 가능함을 보였다. 이 때, DNA 커널을 통한 분류 분제는 온도 조절을 통해 양한정(positive definite) 조건을 만족시킬 때 분류 문제를 잘 풀며, 양한정 조건을 만족시키기 위한 조건으로 높은 온도에서 시작하여 온도를 내리며 hybridization시키는 방법을 제안하였다. 이 논문에서는 보다 정량적인 분석을 통해서 이 hybridization 방법이 양한정 조건을 만족시키기에 적합한 방법임을 보이고, 간단한 hybridization 모델을 통해 양한정 조건을 만족시킬 수 있는 hybridization 온도 계획의 충분 조건을 유도한다. 또한 시작 온도와 끝 온도의 경계 조건으로 제시되는 이 충분 조건을 통해 현실적인 온도 조절 계획을 위한 시퀀스의 코딩 방법을 알게 된다.

• Communications for Statistical Applications and Methods
• /
• 제23권6호
• /
• pp.575-585
• /
• 2016

Longitudinal studies repeatedly measure outcomes over time. Therefore, repeated measurements are serially correlated from same subject (within-subject variation) and there is also variation between subjects (between-subject variation). The serial correlation and the between-subject variation must be taken into account to make proper inference on covariate effects (Diggle et al., 2002). However, estimation of the covariance matrix is challenging because of many parameters and positive definiteness of the matrix. To overcome these limitations, we propose autoregressive moving average Cholesky decomposition (ARMACD) for the linear mixed models. The ARMACD allows a class of flexible, nonstationary, and heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the random effects covariance matrix. We analyze a real dataset to illustrate our proposed methods.

• Communications for Statistical Applications and Methods
• /
• 제25권1호
• /
• pp.61-70
• /
• 2018

Modeling of the random effects covariance matrix in generalized linear mixed models (GLMMs) is an issue in analysis of longitudinal categorical data because the covariance matrix can be high-dimensional and its estimate must satisfy positive-definiteness. To satisfy these constraints, we consider the autoregressive and moving average Cholesky decomposition (ARMACD) to model the covariance matrix. The ARMACD creates a more flexible decomposition of the covariance matrix that provides generalized autoregressive parameters, generalized moving average parameters, and innovation variances. In this paper, we analyze longitudinal count data with overdispersion using GLMMs. We propose negative binomial loglinear mixed models to analyze longitudinal count data and we also present modeling of the random effects covariance matrix using the ARMACD. Epilepsy data are analyzed using our proposed model.

• 보건행정학회지
• /
• 제9권1호
• /
• pp.201-233
• /
• 1999

This study was carried out to find out the factors affecting on organizational commitment of hospital employees. For the purpose, the questionnaire-based research was done with 1280 hospital employees who were working in 2 university hospitals and 4 general hospitals located in Taegu City and Kyungpook Province from November 20, 1997 to December 22, 1997. The results of the study were summarized as follows. There were significant correlations among environmental variables, psychological variables, structural variables, vertical conflict, horizontal conflict, job satisfaction, and organizational commitment. By path analysis, variables such as pay, work involvement, work definiteness, met expectations, positive affectivity, distributive justice, job security, expectations before entering a hospital had significant positive effect on job satisfaction in order of size, while, vertical conflict, job opportunity, and horizontal conflict had significant positive effect on job satisfaction in order of size, while, vertical conflict, job opportunity, and horizontal conflict had signifecant negative effect in order of size. Variables such as job satisfaction, job security, work involvement, pay, vertical conflict, met expectations, distributive justice, positive affectivity, work unit control, job autonomy, and job routinization had significant positive direct effect on organizational commitment in order of size, while, job opportunity, job hazards and resource inadequacy had significant negative direct effects in order of size. It was found that the following variables, listed in order of size, had significant total effects on organizational commitment : job satisfaction, job security, job opportunity, work involvement, pay, met expectations, distributive justice, positive affectivity, job hazards, and work unit control. In considering abovc findings, it is recommended that programs for job satisfaction promotion, job security, decrease of intent to leave, work involvement promotion, adequate pay, met expectations, distributive justice, positive affectivity promotion, job hazards decrease, and work unit control grant should be implemented to increase organizational commitment.

• Journal of Mechanical Science and Technology
• /
• 제16권11호
• /
• pp.1522-1539
• /
• 2002

In the present study, an explicit algebraic stress model is shown to be the exact tensor representation of algebraic stress model by directly solving a set of algebraic equations without resort to tensor representation theory. This repeals the constraints on the Reynolds stress, which are based on the principle of material frame indifference and positive semi-definiteness. An a priori test of the explicit algebraic stress model is carried out by using the DNS database for a fully developed channel flow at Rer = 135. It is confirmed that two-point correlation function between the velocity fluctuation and the Laplacians of the pressure-gradient i s anisotropic and asymmetric in the wall-normal direction. Thus, a novel composite algebraic Reynolds stress model is proposed and applied to the channel flow calculation, which incorporates non-local effect in the algebraic framework to predict near-wall behavior correctly.

• 대한전자공학회논문지
• /
• 제17권1호
• /
• pp.1-9
• /
• 1980

신호처리와 analysis를 위한 여러 기초적인 기술이 소개되었다. 이들은 먼저 불확정성순리의 개입에 의하여 특히 교환불가능한 operator 들이 작용한 결과의 등호는 tolerance가 있을 수 있음과 random process 처리방법과 manmum entropy estimate적인 ,사고방식을 통하여 재래식 확정론적 사고방식으로부터의 이탈을 길잡았다. 마지막으로 검출, 추정 및 함수추정의 여러 기법과 covariance functron의 posltive semi-definite-ness 그리고 Karhunen-Loeve 전개, 한 화상의 SVD 등이 설명됐다.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2009년도 정기 학술대회
• /
• pp.89-92
• /
• 2009

본 논문에서는 비선형구조물의 위상최적화를 위하여 개발된 요소 연결 매개법 (Element Connectivity Parameterization Method)을 이용하여 기하비선형 구조물의 고유진동수(Eigenfrequency)를 최적화하는 연구를 소개한다. 기존의 밀도를 기반으로 한 위상최적화기법은 비선형 구조물의 위상최적화를 수행할 때 약한 탄성계수를 가지는 요소가 대변형을 일으켜 전체 강성행렬(Tangent Stiffness Matrix)이 양정정성(Positive definiteness)를 잃어버리는 문제점이 있어서 위상최적화를 수행하기 어렵다. 이 문제점을 해결하기 위하여 최근에 요소 연결 매개법(Element Connectivity Parameterization Method)이 개발되었다. 이 요소 연결 매개법은 요소의 강성을 설계하는 것이 아니라 요소의 연결성을 설계하는 기법으로 이를 이용하여 비선형 구조물의 위상최적화를 효과적으로 수행할 수 있다. 이 연구에서는 요소 연결 매개법을 동적인 문제에 적용하기 위한 연구를 수행하며 이를 이용하여 비선형 구조물의 고유진동수를 최적화 하는 위상최적화 문제에 적용하였다. 비선형 수치 예제를 통하여 기하 비선형 구조물의 고유진동수를 최대화를 통하여 기하 비선형 구조물의 강성최대화 문제와 같은 결과를 얻을 수 있었다.