• Journal of the Korean Data and Information Science Society
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• 제23권4호
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• pp.815-823
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• 2012

In this paper reliability growth model in which the operating time between successive failure is a continuous random variable is proposed. This model is for Burr type XII distribution with two parameters which is discussed in two versions: the order statistics and non-homogeneous Poisson process. The two software reliability measures are obtained. The performance for two versions of the suggested model is tested on real data set by U-plot and Y-plot using Kolmogorov distance.

• Journal of the Korean Statistical Society
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• 제31권3호
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• pp.343-357
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• 2002

This paper proposes a method for producing smooth and positive estimates of the intensity function of an inhomogeneous Poisson process based on the shrinkage of wavelet coefficients of the observed counts. The information projection is used in conjunction with the level-dependent thresholds to yield smooth and positive estimates. This work is motivated by and demonstrated within the context of a problem involving gamma-ray burst data in astronomy. Simulation results are also presented in order to show the performance of the information projection estimators.

• Communications for Statistical Applications and Methods
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• 제18권4호
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• pp.433-443
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• 2011

잉여금의 수준에 따라 이단계의 보험요율이 적용되는 복합 포아송 위험 모형을 고려한다. 먼저 이 위험 모형에 대응되는 이단계 서비스율의 M/G/1 대기행렬 모형을 설정하고, M/G/1 대기행렬 모형에서 작업량이 0에 도달하기 전에 과부하가 발생하는 확률을 유도한다. 이과부하 확률을 이용하여 위험모형에서 잉여금이 목표값에 도달하기 전에 파산하는 확률을 구하고, 보험 청구액이 지수분포를 따르는 경우의 파산 확률을 계산한다.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.261-269
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• 2015

Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum like-lihood estimator and remains good choice specially in confidence interval statistical inference.

• Journal of applied mathematics & informatics
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• 제39권5_6호
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• pp.601-616
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• 2021

Retrial queueing models have been studied extensively in the literature. These have many practical applications, especially in service sectors. However, retrial queueing models have their own limitations. Typically, analyzing such models involve level-dependent quasi-birth-and-death processes, and hence some form of a truncation or an approximate method or simulation approach is needed to study in steady-state. Secondly, in general, the customers are not served on a first-come-first-served basis. The latter is the case when a new arrival may find a free server while prior arrivals are waiting in the retrial orbit due to the servers being busy during their arrivals. In this paper, we take a different approach to the study of multi-server retrial queues in which the signals are generated in such a way to provide a reasonably fair treatment to all the customers seeking service. Further, this approach makes the study to be level-independent quasi-birth-and-death process. This approach is different from any considered in the literature. Using matrix-analytic methods we analyze MAP/M/c-type retrial queueing models along with Poisson signals in steady-state. Illustrative numerical examples including a comparison with previously published retrial queues are presented and they show marked improvements in providing a quality of service to the customers.

• 한국정보통신학회논문지
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• 제24권2호
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• pp.231-237
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• 2020

본 논문에서는 포아송 방정식을 기반으로 하는 영상 합성에 있어서 합성된 영상의 자연성을 향상시키기 위한 효율적인 동영상 혼합 블랜딩 기법을 제안한다. 영상 블랜딩 과정에서는 영상 합성의 목적에 따라 포아송 블랜딩과 알파 브랜딩 등 다양한 방법이 사용되고 있다. 본 논문에서 제안하는 혼합 블랜딩 방식은 포아송 블랜딩과 알파 블랜딩의 장점들을 조합함으로써 합성 영상에서 이음매가 없고 또한 객체의 색상 왜곡이 감소되는 특징을 갖는다. 먼저 소스 영상의 객체를 포아송 블랜딩 방법으로 합성한 후, 블랜딩 된 객체와 원래의 객체의 색차를 비교한다. 그리고 색차값이 임계값 이상인 경우, 소스 영상의 객체에 대해 알파 블랜딩을 수행하고 이를 포아송 블랜딩 된 객체와 가중치를 부여하여 합산한다. 모의실험과 분석을 통해 제안된 방법이 포아송 블랜딩과 알파 블랜딩에 비해 합성 영역의 자연성이 우수할 뿐 아니라 요구되는 계산량도 비교적 적다는 것을 볼 수 있다.

• 산업경영시스템학회지
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• 제28권2호
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• pp.146-151
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• 한국경영과학회지
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• 제23권3호
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• pp.153-168
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• 1998

In this study we consider a CONWIP system in which the processing times at each station follow an exponential distribution and the demands for the finished Products arrive according to a compound Poisson process. The demands that are not satisfied instantaneously are assumed to be backordered. For this system we develop an approximation method to obtain the performance measures such as steady state probabilities of the number of parts at each station, the proportion of backordered demands, the average number of backordered demands and the mean waiting time of a backordered demand. For the analysis of the proposed CONWIP system, we model the CONWIP system as a closed queueing network with a synchronization station and analyze the closed queueing network using a product form approximation method. A matrix geometric method is used to solve the subnetwork in the application of the product-form approximation method. To test the accuracy of the approximation method, the results obtained from the approximation method were compared with those obtained by simulation. Comparisons with simulation have shown that the approximate method provides fairly good results.

• 산업경영시스템학회지
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• 제28권4호
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• pp.79-84
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• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• 응용통계연구
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• 제29권2호
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• pp.345-354
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• 2016

산사태 자료에서 환경변수들이 산사태 발생 위험에 어떻게 영향을 주는지 분석하기 위해 현재까지 비동질적 포아송 과정 모형이 주로 사용되어 왔다. 그렇지만, 이 모형은 산사태 자료에서 쉽게 관측되는 산사태 위치의 군집 현상에 대해 설명하지 못한다. 이러한 한계점을 극복하기 위해 우리는 코시 군집 과정을 사용할 것을 제안한다. 그리고, 제안된 방법이 실제 산사태 자료에서 얼마나 모형의 적합도를 개선시키는지 K-함수의 관점에서 살펴보고자 한다. 또한, 코시 군집 과정의 모수 추론을 위해 제안된 다양한 추정 방법의 성능을 비교하기 위해 시뮬레이션 연구를 진행하였다.