• Communications for Statistical Applications and Methods
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• 제30권1호
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• pp.65-73
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• 2023

Contemporary biomedical data often involve an ill-posed problem owing to small sample size and large number of multi-collinear variables. Partial least squares (PLS) method could be a plausible alternative to an ill-conditioned ordinary least squares. However, in the case of a PLS model that includes a random-effect, how to deal with a random-effect or mixed effects remains a widely open question worth further investigation. In the present study, we propose a modified multivariate PLS method implementing mixed-effect model (PLSM). The advantage of PLSM is its versatility in handling serial longitudinal data or its ability for taking a randomeffect into account. We conduct simulations to investigate statistical properties of PLSM, and showcase its real clinical application to predict treatment outcome of esthetic surgical procedures of human faces. The proposed PLSM seemed to be particularly beneficial 1) when random-effect is conspicuous; 2) the number of predictors is relatively large compared to the sample size; 3) the multicollinearity is weak or moderate; and/or 4) the random error is considerable.

• 자원ㆍ환경경제연구
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• 제16권4호
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• pp.803-832
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• 2007

새로운 접단에너지 사업에 대한 경제성 평가와 기존 집단에너지 시설의 최적운용을 위해서는 적어도 시간대 단위로 계측된 세부용도별 에너지 부하패턴에 관한 정보가 필수적이다. 본 연구에서는 기상자료와 냉난방 실측자료를 활용하여 열부하를 추정 예측하기 위하여 다계층모형을 선태하였다. 다계층모형은 수집한 자료의 패널자료 특성을 유연하게 모형화할 수 있는 이점이 있다. 다계층모형을 일대일의 대응관계에 있는 선형혼합효과모형으로 변환한 후 패널 FGLS(연산가능한 일반화최소자승추정법)를 적용하여 세부용도별로 열부하모형을 추정하였다. 추정된 부하모형은 온도, 습도, 시간대, 요일, 설날연휴/추석연휴 등 법정공휴일 특성, 난방면적/냉방면적이 열에너지사용량에 미치는 영향을 고려하고 있다. 지면을 고려하여 본 논문에서는 가정용 난방부하모형의 추정치와 난방부하곡선의 예측치에 제한하여 실증결과를 설명하고 있다.

• 응용통계연구
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• 제27권6호
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• pp.923-932
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• 2014

허들모형은 영이 과잉 가산자료를 분석하기 위해서 사용되어 왔다. 이 모형은 이산부분을 위한 로짓모형과 절삭된 가산부분을 위한 절삭된 포아송모형의 혼합모형이다. 이 논문에서 우리는 경시적 영과잉 가산자료를 분석하기 위해서 수정된 콜레스키 분해을 이용하여 일반적인 이분산성을 가지는 변량효과 공분산행렬을 제안한다. 수정된 콜레스키 분해는 변량효과 공분산행렬을 일반화자기상관 모수와 혁신분산모수로 분리되면, 이러한 모수들은 베이지안 일반화 선형모형을 통해 추정된다. 그리고 실제 자료분석을 통하여 설명한다.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권1호
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• pp.33-39
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• 2018

Purpose: Accelerated degradation tests can be effective in assessing product reliability when degradation leading to failure can be observed. This article proposes an accelerated degradation test model for highly reliable solid state drives (SSDs). Methods: We suggest a nonlinear mixed-effects (NLME) model to degradation data for SSDs. A Monte Carlo simulation is used to estimate lifetime distribution in accelerated degradation testing data. This simulation is performed by generating random samples from the assumed NLME model. Conclusion: We apply the proposed method to degradation data collected from SSDs. The derived power model is shown to be much better at fitting the degradation data than other existing models. Finally, the Monte Carlo simulation based on the NLME model provides reasonable results in lifetime estimation.

• Asian-Australasian Journal of Animal Sciences
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• 제13권12호
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• pp.1691-1698
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• 2000

An in situ digestion trial (Experiment 1) and a lactation trial (Experiment 2) were conducted to determine the effects of replacing corn and wheat bran with soyhulls (SH) in lactating dairy cow diets on the extent and kinetics of digestion of DM and NDF, and lactation performance. In experiment 1, five mixed feeds consisting of mixed concentrate and roughages (50:50 on a DM basis) were formulated on isonitrogenous and isoenergetic bases to produce five levels (0, 25, 50, 75 and 100%) of SH replacement for corn and wheat bran. SH had high in situ digestion (92 and 89% for potentially digestible DM and NDF) and fairly fast digestion rate (7.2 and 6.3 %/h for DM and NDF). Increasing level of SH replacement resulted in increased NDF digestibility (linear, p=0.001-0.04) and similar DM digestibility (beyond 12 h incubation, p=0.10-0.41). As level of SH replacement increased, percentage of slowly digestible fraction (b) of DM increased (linear, p=0.03), percentage of rapidly digestible fraction (a) of DM tended to decrease (linear, p=0.14), and DM digestion lag time tended to be longer (linear, p=0.13). Percentage of potentially digestible fraction (a+b) and digestion rate (c) of slowly digestible fraction of dietary DM remained unaltered (p=0.36-0.90) with increasing SH in the diet. Increasing level of SH for replacing corn and wheat bran in the diet resulted in increases in percentages of b (quadratic, p<0.001), a (linear, p=0.08), a+b (quadratic, p=0.001) and a tendency to increase in c for NDF (linear, p<0.19). It was also observed that there was a satisfactory fit of a non-linear regression model to NDF digestion data ($R^2=0.986-0.998$), but a relatively poor fit of the model to DM digestion data ($R^2=0.915-0.968$). In experiment 2, 42 lactating Holstein cows were used in a randomized complete block design. SH replaced corn and wheat bran in mixed concentrates at 0, 25, and 50%, respectively. These mixed concentrates were mixed with roughages and fed ad libitum as complete diets. Replacing corn and wheat bran with SH at 0, 25 and 50% levels did not influence (p=0.56-0.95) DM intakes (18.4, 18.6, and 18.5 kg/d), milk yields (27.7, 28.4 and 27.6 kg/d), 4% fat-corrected-milk (FCM) yields (26.2, 27.6, and 27.3 kg/d) and percentages of milk protein (3.12, 3.17 and 3.18%), milk lactose (4.69, 4.76 and 4.68%) and SNF (8.50, 8.64, and 8.54%). On the other hand, milk fat percentges linearly increased (3.63, 3.85 and 3.90% for SH replacement rates of 0, 25 and 50% in the diet, p=0.08), while feed costs per kg FCM production were reduced.

• Journal of the Korean Data and Information Science Society
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• 제28권1호
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• pp.1-10
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• 2017

경시적 자료를 이용한 아동 학업성취도에 영향을 주는 요인을 찾기 위한 기존의 분석들은 각 아동의 반복 측정된 자료들이 독립이라고 가정한 모형을 주로 이용하였다. 본 연구에서는 기존 연구들에서 고려한 아동 학업성취도에 영향을 주는 변수들을 선택하여 반복 측정된 경시적 자료의 종속성을 고려한 고정효과와 임의효과를 포함하는 선형혼합모형으로 분석하여 아동 학업성취도에 영향을 주는 변수들은 무엇인지, 각 아동의 특성들이 반영되는 임의절편과 임의기울기가 있는지를 파악하는 것이 연구의 목적이다. 본 연구에 사용된 자료는 한국복지패널 1, 4, 7차 부가조사 중에서 아동용 설문문항에 대한 자료이고, 국어, 영어와 수학의 학업성취도 점수의 합을 아동 학업성취도로 한다. 선형혼합모형을 이용한 분석 시에 다중공선성의 검토와 결측치의 특성을 파악하고 적절한 오차의 상관행렬을 선택한다.

• Asian-Australasian Journal of Animal Sciences
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• 제13권3호
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• pp.413-422
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• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

• Journal of the Korean Data and Information Science Society
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• 제25권4호
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• pp.941-949
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• 2014

Unit level logistic regression model with mixed effects has been used for estimating small area proportions, which treats the spatial effects as random effects and assumes linearity between the logistic link and the covariates. However, when the functional form of the relationship between the logistic link and the covariates is not linear, it may lead to biased estimators of the small area proportions. In this paper, we relax the linearity assumption and propose two types of kernel-based logistic regression models for estimating small area proportions. We also demonstrate the efficiency of our propose models using simulated data and real data.

• Communications for Statistical Applications and Methods
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• 제12권3호
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• pp.759-771
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• 2005

Twin studies are one of the most widely used methods for quantifying the influence of genetic and environmental factors on some traits such as a life span or a disease. In this paper we propose a genetic mixed linear model for twin survival time data, which allows us to separate the genetic component from the environmental component. Inferences are based upon the hierarchical likelihood (h-likelihood), which provides a statistically efficient and simple unified framework for various random-effect models. We also propose a simple and fast computation method for analyzing a large data set on twin survival study. The new method is illustrated to the survival data in Swedish Twin Registry. A simulation study is carried out to evaluate the performance.

• 응용통계연구
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• 제28권2호
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• pp.201-210
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• 2015

생명과학 또는 의학 연구에서는 반복 측정된 변수들 간의 상관 관계를 보고자 하는 경우가 발생한다. 반복 측정된 것을 고려하지 않으면 상관관계를 과소 추정하는 경향이 나타나므로 이를 고려해야 하며, 선형혼합모형의 분산-공분산 행렬을 이용하여 상관관계를 추정할 수 있다. 본 연구에서는 변수들의 반복 측정이 동시에 된 경우와 그렇지 않은 경우로 나누어 혼합모형을 이용한 상관계수의 추정방법을 소개한다. 고속 음향 복사력 임펄스 영상(acoustic radiation force impulse imaging; ARFI)으로 간과 비장에서 각각 세 번씩 전단파 속도를 반복 측정하고 복부 초음파 검사로 비장 길이를 측정한 자료에서 전단파 속도와 비장 길이 간의 상관 관계를 분석하기 위해 본 논문에서 소개한 방법들을 적용하였고 SAS의 PROC MIXED를 이용하는 방법을 제시하였다.