• 한국도로학회논문집
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• 제16권1호
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• pp.49-56
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• 2014

PURPOSES : This study was done to model the headway distribution of rural two lane roads. METHODS : Time headway data for the various level of traffic volumes was measured in twelve sites. Based on the time headway data, existing seven mathematical models were evaluated and selected by comparing graphically the measured and theoretical distributions and conducting the Chi-square test. RESULTS : The results show that both the Schul model and Composite Model were the most appropriate models of the models. Based on the measured time-headway distributions, this study proposed a new headway distribution model by the shift of the Schul model. CONCLUSIONS : The shifted Schul model has the ability to describe time headway distirbutons for random, intermediate, and constant-headway states.

• Communications for Statistical Applications and Methods
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• 제15권2호
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• pp.161-171
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• 2008

This study discusses Johnson's $S_U$-normal distribution capturing a wide range of non-normality in various regression models. We provide the likelihood inference using Johnson's $S_U$-normal distribution, and propose a likelihood ratio (LR) test for normality. We also apply the $S_U$-normal distribution to the binary and censored regression models. Monte Carlo simulations are used to show that the LR test using the $S_U$-normal distribution can be served as a model specification test for normal error distribution, and that the $S_U$-normal maximum likelihood (ML) estimators tend to yield more reliable marginal effect estimates in the binary and censored model when the error distributions are non-normal.

• 산업경영시스템학회지
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• 제21권46호
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• pp.127-136
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• 1998

In many cases where the binomial distribution fails to apply to real world data it is because of more variability in the data than can be explained by that distribution. Several authers have proposed models that are useful in explaining extra-binomial variation. In this paper we point out a characterization of sequences of exchangeable Bernoulli variables which can be used to develop models which show more variability than the binomial. We give sufficient conditions which will yield such models and show how existing models can be continued to generate further models. A numerical example and simulation given.

• 대한안전경영과학회지
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• 제13권1호
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• pp.195-202
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• 2011

The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.

• International Journal of Reliability and Applications
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• 제6권2호
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• pp.101-115
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• 2005

This article provides a new class of multivariate linear failure rate distributions where every component is a mixture of linear failure rate distribution. The new class includes several multivariate and bivariate models including Marslall and Olkin type. The approach in this paper is based on the introducing a linear failure rate distributed latent random variable. The distribution of minimum in a competing risk model is discussed.

• International Journal of Reliability and Applications
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• 제7권1호
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• pp.55-69
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• 2006

This paper presents a new class of multivariate distributions with Pareto where dependence among the components is characterized by a latent random variable. The new class includes several multivariate and bivariate models of Marshall and Olkin type. It is found the bivariate distribution with Pareto is positively quadrant dependent and its mixture. Some important structural properties of the bivariate distributions with Pareto are discussed. The distribution of minimum in a competing risk Pareto model is derived.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제11권2호
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• pp.15-29
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• 2007

In this paper, we explore some interesting models of the quasi-negative-binomial distribution based on difference differential equations applicable to theory of microorganisms and the situations like that. Some characterizations based on conditional distributions and damage process have been obtained. Further, the distribution of number of accidents as the quasi-negative-binomial distribution in the light of Irwin's theory of ";proneness-liability"; model has been derived. Finally, the proposed model (QNBD) has been applied to study the Shunting accidents, home injuries, and strikes in industries.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.487-493
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• 2015

Time series data sometimes show violation of normal assumptions. For cases where the assumption of normality is untenable, more exible models can be adopted to accommodate heavy tails. The exponential power distribution (EPD) is considered as possible candidate for errors of time series model that may show violation of normal assumption. Besides, the use of exible models for errors like EPD might be able to conduct the robust analysis. In this paper, we especially consider EPD as the exible distribution for errors of autoregressive models. Also, we represent this distribution as scale mixture of uniform and this form enables efficient Bayesian estimation via Markov chain Monte Carlo (MCMC) methods.

• Entomological Research
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• 제48권6호
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• pp.505-513
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• 2018

The red imported fire ant is considered one of the most notorious invasive species because of its adverse impact on both humans and ecosystems. Public concern regarding red imported fire ants has been increasing, as they have been found seven times in South Korea. Even if red imported fire ants are not yet colonized in South Korea, a proper quarantine plan is necessary to prevent their widespread distribution. As a basis for quarantine planning, we modeled the potential distribution of the red imported fire ant under current climate conditions using six different species distribution models (SDMs) and then selected the random forest (RF) model for modeling the potential distribution under climate change. We acquired occurrence data from the Global Biodiversity Information Facility (GBIF) and bioclimatic data from WorldClim. We modeled at the global scale to project the potential distribution under the current climate and then applied models at the local scale to project the potential distribution of the red imported fire ant under climate change. Modeled results successfully represent the current distribution of red imported fire ants. The potential distribution area for red imported fire ants increased to include major harbors and airports in South Korea under the climate change scenario (RCP 8.5). Thus, we are able to provide a potential distribution of red imported fire ant that is necessary to establish a proper quarantine plan for their management to minimize adverse impacts of climate change.

• 한국환경복원기술학회지
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• 제18권3호
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• pp.51-64
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• 2015

Climate change will make significant impact on species distribution in forest. Pinus koraiensis which is commonly called as Korean Pine is normally distributed in frigid zones. Climate change which causes severe heat could affect distribution of Korean pine. Therefore, this study predicted the distribution of Korean Pine and the suitable habitat area with consideration on uncertainty by applying climate change scenarios on an ensemble model. First of all, a site index was considered when selecting present and absent points and a stratified method was used to select the points. Secondly, environmental and climate variables were chosen by literature review and then confirmed with experts. Those variables were used as input data of BIOMOD2. Thirdly, the present distribution model was made. The result was validated with ROC. Lastly, RCP scenarios were applied on the models to create the future distribution model. As a results, each individual model shows quite big differences in the results but generally most models and ensemble models estimated that the suitable habitat area would be decreased in midterm future(40s) as well as long term future(90s).