• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.371-385
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• 1995

The yield of semiconductor chips is dependent not only on the average defect density but also on the distribution of defects over a wafer. The distribution of defects leads to consider a cluster index. This paper briefly reviews the existing yield prediction models ad proposes a new cluster index, which utilizes the information about the defect location on a wafer in terms of the coefficient of variation. An extensive simulation is performed under a variety of defect distributions and a yield prediction model is derived through the regression analysis to relate the yield with the proposed cluster index and the average number of defects per chip. The performance of the proposed simulation-based yield prediction model is compared with that of the well-known negative binomial model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5585-5593
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• 2014

This study tested the hypothesis that the significance of the heterogeneous dispersion parameter in safety performance function (SPF) used to estimate the expected crashes is affected by the endogenous heterogeneous prior distributions, and analyzed the impacts of the mis-specified dispersion parameter on the evaluation results for traffic safety countermeasures. In particular, this study simulated the Poisson means based on the heterogeneous dispersion parameters and estimated the SPFs using both the negative binomial (NB) model and the heterogeneous negative binomial (HNB) model for analyzing the impacts of the model mis-specification on the mean and dispersion functions in SPF. In addition, this study analyzed the characteristics of errors in the crash reduction factors (CRFs) obtained when the two models are used to estimate the posterior means and variances, which are essentially estimated through the estimated hyper-parameters in the heterogeneous prior distributions. The simulation study results showed that a mis-estimation on the heterogeneous dispersion parameters through the NB model does not affect the coefficient of the mean functions, but the variances of the prior distribution are seriously mis-estimated when the NB model is used to develop SPFs without considering the heterogeneity in dispersion. Consequently, when the NB model is used erroneously to estimate the prior distributions with heterogeneous dispersion parameters, the mis-estimated posterior mean can produce large errors in CRFs up to 120%.

• Journal of Distribution Science
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• v.13 no.11
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• pp.59-67
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• 2015

Purpose - The number of consumers adopting a lifestyle of health and sustainability has recently increased with the rise of trends in healthy living. The size of the organic agricultural product market has also increased given that these consumers prefer consuming environmentally friendly products that promote family health. However, awareness of organic agricultural products remains insufficient because of the characteristics of the Korean organic agriculture system, which only focuses on food safety inspection. The object of this research is to suggest a policy approach to increase understanding and to expand the purchasing of organic agricultural products by analyzing the influence of customer recognition of such products on their willingness to repurchase. Research design, data, and methodology - This study used binomial logistic regression analysis with the aim of explaining the effects of consumers' socio-demographic characteristics, their awareness of the equivalence arrangement for organic food and of the abolishment of low-pesticide agricultural product certification, and their viewing of negative broadcasts about organic agricultural products on their repurchase intention of such products. A questionnaire survey was conducted with 655 respondents who were in their 20s, lived either in Seoul or in its metropolitan area, and had purchased organic agricultural products. Result - From the results of the analysis, the majority of the respondents recognized organic agricultural products, but they found their prices to be expensive. The majority of the respondents were also aware of the certification system and the reliability of organic agricultural products. However, the results indicate that efforts need to be made to recover consumer trust as many respondents stated that their trust levels in these products were low. In general, those purchasing organic agricultural products were satisfied, but those answering "very satisfied" were not in the majority. Binomial logistic regression analysis results revealed that repurchase intention decreased as consumers viewed a greater number of negative broadcasts about these products. On the other hand, repurchase intention increased as they became more aware of the abolishment of low-pesticide certification. Repurchase intention also increased as income increased, as the number of family members decreased, and when a consumer was a member of a consumer organization. In addition, the older the consumers were who watched the TV programs, the smaller the number of family members that were aware of the abolishment of low-pesticide agricultural product certification and, the higher the income of the consumers aware of organic equivalence arrangement, the greater their repurchase intention. Conclusion - External stimuli, such as negative TV programs on organic agricultural products and the abolishment of the low-pesticide agricultural product certification, relevant social issues and systems, influence consumer repurchase intention. To that end, positive environmental and ecological broadcasting about organic agricultural products would contribute to an increase in purchasing. Additionally, this could be used for promotion and marketing plans as the results indicate that trust in organic agricultural products would cause a positive repurchasing effect.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.3
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• pp.509-521
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• 1994

This study is an effort to develop computer simulation model that produce precipitation patterns from stochastic model. A stochastic model is formulated for the process of daily precipitation with considering the sequences of wet and dry days and the precipitation amounts on wet days. This study consists of 2 papers and the process of precipitation occurrence is modelled by an alternate renewal process (ARP) in paper (I). In the ARP model for the precipitation occurrence, four discrete distributions, used to fit the wet and dry spells, were as follows; truncated binomial distribution (TBD), truncated Poisson distribution (TPD), truncated negative binomial distribution (TNBD), logarithmic series distribution (LSD). In companion paper (II) the process of occurrence is developed by Markov chain. The amounts of precipitation, given that precipitation has occurred, are described by a Gamma. Pearson Type-III, Extremal Type-III, and 3 parameter Weibull distribution. Daily precipitation series model consists of two models, A-Wand A-G model, by combining the process of precipitation occurrence and a continuous probability distribution on the precipitation of wet days. To evaluate the performance of the simulation model, output from the model was compared with historical data of 7 stations in the Nakdong and Seomjin river basin. The results of paper (1) show that it is possible to design a model for the synthetic generation of IX)int precipitation patterns.

• International Journal of Highway Engineering
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• v.18 no.4
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• pp.93-102
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• 2016

PURPOSES : There are many recently constructed roundabouts in Jeollabuk-do province. This study analyzed how roundabouts reduce the risk of accidents and improve safety in the province. METHODS : This study analyzed safety improvement at roundabouts by using an accident prediction model that uses an Empirical Bayes method based on negative binomial distribution. RESULTS : The results of our analysis model showed that the total number of accidents decreased from 130 to 51. Roundabouts also decreased casualties; the number of casualties decreased from 7 to 0 and the seriously wounded from 87 to 16. The effectiveness of accident reduction as analyzed by the accident prediction model with the Empirical Bayes method was 60%. CONCLUSIONS : The construction of roundabouts can bring about a reduction in the number of accidents and casualties, and make intersections safer.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.845-852
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• 2010

The outcomes of counts commonly occur in the area of disease mapping for mortality rates or disease rates. A Poisson distribution is usually assumed as a model of disease rates in conjunction with a gamma prior. The small area typically refers to a small geographical area or demographic group for which very little information is available from the sample surveys. Under this situation the model-based estimation is very popular, in which the auxiliary variables from various administrative sources are used. The empirical Bayes estimator under Poissongamma model has been considered with its accuracy measures. An accuracy measure using a bootstrap samples adjust the underestimation incurred by the posterior variance as an estimator of true mean squared error. We explain the suggested method through a practical dataset of hitters in baseball games. We also perform a Monte Carlo study to compare the accuracy measures of mean squared error.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.173-184
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• 2018

In medical or public health research, it is common to encounter clustered or longitudinal count data that exhibit excess zeros. For example, health care utilization data often have a multi-modal distribution with excess zeroes as well as a multilevel structure where patients are nested within physicians and hospitals. To analyze this type of data, zero-inflated count models with mixed effects have been developed where a count response variable is assumed to be distributed as a mixture of a Poisson or negative binomial and a distribution with a point mass of zeros that include random effects. However, no study has considered a situation where data are also censored due to the finite nature of the observation period or follow-up. In this paper, we present a weighted version of zero-inflated Poisson model with random effects accounting for variable individual follow-up times. We suggested two different types of weight function. The performance of the proposed model is evaluated and compared to a standard zero-inflated mixed model through simulation studies. This approach is then applied to Medicaid data analysis.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1231-1239
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• 2014

In this paper we analyse the distributions of the number of goals scored by home teams and away teams in K-league soccer outcomes between 1983 and 2012. Real soccer data is explained in K-league using statistical distributions such that Poisson, negative binomial, extreme value and zero inflated Poisson. How close the goals of home and away fits the different distributions are tested by performing chi-square goodness of fit tests. According to these tests, the Poisson distribution gives the best fit to the home goals data. But it is best to model the away goals data on zero inflated Poisson distribution. Also, there is some weak evidence of the dependence for home and away goals.

• Journal of agricultural medicine and community health
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• v.14 no.1
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• pp.44-53
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• 1989

The distribution pattern of Clonorchis sinensis metacercaria in Pseudorasvora parva population and correlation between P. parva and metacercaria of C. sinensis were studied. The surveved areas were Chomanpo and Bulamdong, Kim-Hae Gun which were endemic area of clonorchiasis, and wansa, Sa-Chon Gun, Souh Kyong-Sang Do. The results are as follows: 1) The areas of Chornanpo and Wansa showed high infectivity in 99-100% of infection rate and 282-308 of average infection number per-fish. But the area of Bulamdong showed relatively. low infectivity in 95.8% of infection rate and 44 of average infection number. 2) The distribution patterns of C. sinensis metacercaria in P. parva population which were collected in Chomanpo and Wansa were shown Poisson distribution and the distribution pattern in Bulamdong showed mid-pattern of shifting over from Poisson distribution to Negative binomial distribution. 3) The correlation between P. parva length and average number of C. sinensis metacercaria in the present studied areas represented as direct proportion relationship.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.1-15
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• 2011

The RLC systems is one of the intelligent transportation systems that has gained a nation-wide support for last decades and being installed to discourage motorists from running the red lights at signalized intersections. It is taken for granted that the RLC will provide motorists with increased safety, so that their installments are always justifiable. However, in order to acquire more efficiency and wider supports from the general public in future RLC installments, an improved methodology for analyzing the effects of the RLC systems is required. In order to satisfy this requirement, this research performed the following tasks. First, the number of signal violations after the RLC systems were investigated in order to check its resulting effects. Second, the number of crashes after the RLC systems were collected and compared with the number of signal violations. Third, a statistical analysis was carried out to develop the relationships between the signal violations and the crashes based on negative binomial distribution. The analysis revealed that the number of crashes has a close relationship with the RLC placement, traffic volume, vehicle speed, the number of phases, and the number of lanes for major approaches. Finally, based on the results found in this analysis, this research presents a methodology for analyzing the safety effects of placing the RLC that should be of service when investigating the economic consequences of the RLC systems.