• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.585-594
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• 2010

This study, investigates the effects of dispersion parameters between two response variables in zero-truncated bivariate generalized Poisson distributions. A Monte Carlo study shows that the zero-truncated bivariate Poisson and negative binomial models fit poorly wherein the zero-truncated bivariate count data has heterogeneous dispersion parameters on dependent variables. In addition, we derive the score test for testing the equality of the dispersion parameters and compare its efficiency with the likelihood ratio test.

• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.819-827
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• 2009

Kim et al. (2006) analyzed the donation data surveyed by Voluneteer 21 in year 2002 at South Korea using a Poisson regression based on the mixture of two Poissons and detected significant variables for affecting the number of donations. However, noting the large deviation between the predicted and the actual frequencies of zero, we developed in this note a Poisson regression model based on a distribution in which zero inflated Poisson was added to the mixture of two Poissons. Thus the population distribution is now a mixture of three Poissons in which one component is concentrated on zero mass. We used the EM algorithm for estimating the regression parameters and detected the same variables with Kim et al's for significantly affecting the response. However, we could estimate the proportion of the fixed zero group to be 0.201, which was the characteristic of this model. We also noted that among two significant variables, the income and the volunteer experience(yes, no), the second variable could be utilized as a strategric variable for promoting the donation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1764-1770
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• 2011

In this paper, the subthreshold swings for doping distribution in the channel have been analyzed in double gate MOSFET(DGMOSFET). The DGMOSFET is extensively been studying since it can lessen the short channel effects(SCEs) as next -generation nano device. The degradation of subthreshold swing(SS) known as SCEs has greatly influenced on application of digital devices, and has been analyzed for structural parameter and variation of channel doping profile in DGMOSFET. The analytical model of Poisson equation has been derived from nonuniform doping distribution for DGMOSFET. To verify potential and subthreshold swing model based on this analytical Poisson's equation, the results have been compared with those of the numerical Poisson's equation, and subthreshold swing for DGMOSFET has been analyzed using these models.

• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.109-124
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• 2002

This study is an effort to develop a stochastic model of precipitation series that preserves the pattern of occurrence of precipitation events throughout the year as well as several characteristics of the duration, amount, and intensity of precipitation events. In this study an event cluster model is used to describe the occurrence of precipitation events. A logarithmic negative mixture distribution is used to describe event duration and separation. The number of events within each cluster is also described by the Poisson cluster process. The duration of each event within a cluster and the separation of events within a single cluster are described by a logarithmic negative mixture distribution. The stochastic model for hourly precipitation occurrence process is fitted to historical precipitation data by estimating the model parameters. To allow for seasonal variations in the precipitation process, the model parameters are estimated separately for each month. an analysis of thirty-four years of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many features of historical precipitation. The seasonal variations in number of precipitation events in each month for the historical and simulated data are also approximately identical. The marginal distributions for event characteristics for the historical and simulated data were similar. The conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.143-152
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• 2018

Purpose: In this paper, we propose calculation methods of Maintenance Float (M/F). Results of each method are compared and verified by using commercial tool (OPUS Suite). As modern weapon systems become more expensive, we need to find the most economical and efficient method to achieve the target operational availability (Ao). Methods: Three kinds of methods (Considering the number of CSP, Applying the Poisson distribution, and Applying M&S Tool) are used to find the number of M/F. Three methods (Considering the number of CSP, Applying the Poisson distribution, and Applying M&S Tool) were used to estimate the required number of M/F. The analysis results were verified by SIMLOX. The cost of equipment calculated by each analysis method was compared and the cause of the difference was analyzed. Conclusion: Ao and cost must be considered to find the optimal number of M/F. In general, it costs more to increase availability. But the cost is not necessarily proportional to Ao. Therefore, it is better to compare the calculation method and determine the final MF quantity.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.55-67
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• 2010

Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The applied model of release time exploited infinite non-homogeneous Poisson process. This infinite non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used generalized gamma type distribution which has the efficient various property because of various shape and scale parameter. Thus, software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.408-413
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• 2005

A new methodology for discrete non-Gaussian probability density estimation is investigated in this paper based on a dynamic Bayesian network (DBN) and kernel functions. The estimator consists of a DBN in which the transition distribution is represented with kernel functions. The estimator parameters are determined through a recursive learning algorithm according to the maximum likelihood (ML) scheme. A discrete-type Poisson distribution is generated in a simulation experiment to evaluate the proposed method. In addition, an unknown probability density generated by nonlinear transformation of a Poisson random variable is simulated. Computer simulations numerically demonstrate that the method successfully estimates the unknown probability distribution function (PDF).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.133-141
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• 1990

Human blood is a perishable product : it has a legal lifetime of 21 days from collection, during which it can be used for transfusion to a Patient of the same type, and after which it has to be discarded. Therefore, blood must be supplied safely and effectively because it is one of the medical resources which keep humanlife. In this study, the effects of blood issuing policies on average inventory levels and average age of blood at transfusion are determined by simulation applied the theory of absorbing Markov chains. And as a practical study, the daily demand distribution of blood is estimated by using the data of B General Hospital. The distribution estimated follows poisson distribution and the estimator of parameter estimated from the poisson distribution is 0.762. Simulation is done by using the parameter. The most important problem when control blood is the amount of outdata. So we compared random policy with Modified LIFO and Modified FIFO by using outdata. As a results it is shown that Modified LIFO and Modified FIFO by using outdata. As a results it Is shown that Modified LIFO and Modified FIFO present better issuing policy than Random Policy.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.246-246
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• 2016

본 연구에서는 최근 기후변화로 인한 집중호우의 발생횟수의 경향을 확률적으로 분석함에 있어 1개월 동안 80 mm/day 이상의 강우사상을 집중호우로 정의하여, 대구 및 부산 강우관측소로부터 수집된 384개월 동안의 집중호우를 분석하였다. 집중호우 월별 발생횟수와 같은 형식의 자료의 확률적 분석은 대개 Poisson 분포 (POI)가 사용되나 자료에 포함된 0자료의 과잉은 확률분포를 왜곡시키는 문제를 발생시킨다. 본 연구에서는 이 문제를 개선하기 위하여 개발된 일반화 Poisson 확률분포 (GPD), 0-과잉 Poisson 확률분포 (ZIP), 0-과잉 일반화 Poisson 확률분포 (ZIGP), Bayesian 0-과잉 일반화 Poisson 확률분포 (Bayesian ZIGP)를 집중호우 자료에 적용하고, 5개 모형의 특성을 비교분석하였으며, Bayesian ZIGP 모형의 구축에 있어서는 정보적 사전분포를 사용함으로써 모형의 정확도를 개선하였다. 분석결과 분석하고자 하는 자료에 0이 과다하게 포함되어 있는 경우 POI 및 GPD 분포는 관측결과와는 다른 결과를 제시하여 적절한 모형으로 고려되지 못함을 알 수 있었다. 5가지 모형 중 정보적 사전분포를 탑재한 Bayesian ZIGP 모형이 가장 관측 자료와 유사한 결과를 도출하였으나 모형의 구축에 수반되는 실용적인 측면을 고려하면 ZIP 모형도 충분히 사용될 수 있는 모형으로 추천되었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2621-2626
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• 2013

This paper has presented the potential distribution for asymmetric double gate(DG) MOSFET, and sloved Poisson equation to obtain the analytical solution of potential distribution. The symmetric DGMOSFET where both the front and the back gates are tied together is three terminal device and has the same current controllability for front and back gates. Meanwhile the asymmetric DGMOSFET is four terminal device and can separately determine current controllability for front and back gates. To approximate with experimental values, we have used the Gaussian function as doping distribution in Poisson equation. The potential distribution has been observed for gate bias voltage and gate oxide thickness and channel doping concentration of the asymmetric DGMOSFET. As a results, we know potential distribution is greatly changed for gate bias voltage and gate oxide thickness, especially for gate to increase gate oxide thickness. Also the potential distribution for source is changed greater than one of drain with increasing of channel doping concentration.