• 산업경영시스템학회지
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• 제19권37호
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• pp.179-186
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• 1996

This paper provides equations for computing the AOQ of an unreliable random FMS. The FMS is described using an open central server model of GI/G/S Queues. The equation for AOQ is simplified due to computational complexities. A Numerical example is used to show the effect of AOQ according to inspection location, reliability of equipment in an FMS. The effect of difference in routing probability is compared after finding the AOQL of each machine center.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.29-37
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• 2001

In this paper, we consider the second order probability matching criterion for the ratio of the variance components under the one-way random effect model. It turns out that among all of the reference priors given in Ye(1994), the only one reference prior satisfies the second order matching criterion. Similar results are also obtained for the intraclass correlation as well.

• Journal of the Korean Data and Information Science Society
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• 제21권2호
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• pp.363-369
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• 2010

In this paper we propose a mixed-effects least squares support vector regression (LS-SVR) for longitudinal data. We add a random-effect term in the optimization function of LS-SVR to take random effects into LS-SVR for analyzing longitudinal data. We also present the model selection method that employs generalized cross validation function for choosing the hyper-parameters which affect the performance of the mixed-effects LS-SVR. A simulated example is provided to indicate the usefulness of mixed-effect method for analyzing longitudinal data.

• 품질경영학회지
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• 제24권1호
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• pp.87-95
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• 1996

We construct bootstrap confidence bounds for reliability, R=P(X>Y), where X and Y are independent normal random variables. 1-way random effect models with equal variances are assumed for the populations of X and Y. We compare the accuracy of the proposed bootstrap confidence bounds and classical confidence bound for small samples via Monte Carlo simulation.

• 대한조선학회논문집
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• 제40권3호
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• pp.45-53
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• 2003

Ships and ocean structures are subjected to random loads caused by irregular waves. The irregularity of amplitude from random loading affects on fatigue crack growth and fatigue life. However the effects of irregularity of loading on fatigue including random loading have not been explained exactly. Therefore in this paper crack growth tests on DENT specimens under constant-amplitude loading including a single tensile overload are conducted to investigate the effect of overload on crack growth rate. The size of plastic zone and crack growth rate before and after a single tensile overloading are measured using ESPI system. Crack growth retardation model that is characterized by crack growth length and the size of plastic zone was proposed and compared with test result. From the research, the validity of proposed model is examined on crack growth retardation, and consequently fatigue life.

• Communications for Statistical Applications and Methods
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• 제23권2호
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• pp.179-187
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• 2016

The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

• 아태비즈니스연구
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• 제10권4호
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• pp.87-118
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• 2019

The purpose of this study is to examine the effects of person-job fit, which consists of educational fit and skill fit, on employees' intrinsic job satisfaction. To the end, the 10-year balanced panel data of the Korean Labor and Income Panel Study(KLIPS) by the Korea Labor Institute (KLI) for 2008-2017 are utilized. This study analyzes 12,730 observations by 1,273 employees by using fixed effect model, random effect model, and pooled OLS estimation method. The empirical results are as follows: First, it is founded that educational fit and skill fit seem affect job satisfaction positively. Second, the negative effects of over-education are clear and the negative effects of under-education are unclear, while the effects of over-skilled and under-skilled are insignificant statistically. Third, the results imply that the size of effect of over-education on intrinsic job satisfaction is larger than that of the effect of over-skilled. Forth, it is shown that the use of fixed effect model is more effective and trustworthy than that of random effect model and pooled OLS estimation method, implying that the effect size of coefficients which are estimated by pooled OLS method and random effect model are likely over-estimated. The empirical results above imply that firms and employees should focus on solving over-education issue before all in order to enhance employees' job satisfaction and it is needed to monitor regularly whether systemic job assignment process is done based on the employees' educational attainment and skill level and to provide more chances for job re-allocation and job rotation.

• Journal of the Korean Data and Information Science Society
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• 제22권1호
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• pp.73-80
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• 2011

본 연구의 목적은 상품판매 비중과 금리가 해약률에 미치는 영향을 분석하는데 있다. 본 연구의 동인은 최근 국제회계기준 및 현금흐름방식의 도입으로 해약률과 관련된 이슈가 중요해지고 있는데서 찾을 수 있다. 패널자료를 적용하여 고정효과모형 및 확률효과모형을 추정하고 하우스만 검정으로 모형을 선택하는 분석방법을 사용한다. 분석 결과 첫째, 확률효과모형이 선택되었으며, 상품 포트폴리오 중 저축성 보험, 질병보험, 사망보험의 구성비가 높고, 금리가 높을수록 해약률이 상승하는 것으로 나타나고 있다. 둘째, 건강보험이나 변액보험의 상품비중이 높을수록 해약률은 감소하는 결과를 보이고 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3656-3671
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• 2016

Most of the research in the area of wireless communications exclusively relies on simulations. Further, it is essential that the mobility management strategies and routing protocols should be validated under realistic conditions. Most appropriate mobility models play a pivotal role to determine, whether there is any subtle error or flaw in a proposed model. Simulators are the standard tool to evaluate the performance of mobility models however sometimes they suffer from numerous documented problems. To accomplish the widely acknowledged lack of formalization in this domain, a Coloured Petri nets (CPNs) based random direction mobility model for specification, analysis and validation is presented in this paper for wireless communications. The proposed model does not suffer from any border effect or speed decay issues. It is important to mention that capturing the mobility patterns through CPN is challenging task in this type of the research. Further, an appropriate formalism of CPNs supported to analyze the future system dynamic status. Finally the formal model is evaluated with the state space analysis to show how predefined behavioral properties can be applied. In addition, proposed model is evaluated based on generated simulations to track origins of errors during debugging.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.353-371
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• 2022

This paper analyzes death counts after World War II of several countries to identify and to compare their stochastic structures. The stochastic structures that this paper entertains are three structural time series models, a local level with a random walk model, a fixed local linear trend model and a local linear trend model. The structural time series models assume that a time series can be formulated directly with the unobserved components such as trend, slope, seasonal, cycle and daily effect. Random effect of each unobserved component is characterized by its own stochastic structure and a distribution of its irregular component. The structural time series models use the Kalman filter to estimate unknown parameters of a stochastic model, to predict future data, and to do filtering data. This paper identifies the best-fitted stochastic model for three types of death counts (Female, Male and Total) of each country. Two diagnostic procedures are used to check the validity of fitted models. Three criteria, AIC, BIC and SSPE are used to select the best-fitted valid stochastic model for each type of death counts of each country.