• Communications for Statistical Applications and Methods
• /
• 제15권5호
• /
• pp.793-798
• /
• 2008

Extreme value inference deals with fitting the generalized extreme value distribution model and the generalized Pareto distribution model, which are recently combined to give a single model, namely a two-dimensional non-homogeneous Poisson exceedance point process model. In this paper, we extend the two-dimensional non-homogeneous Poisson process model to include non-stationary effect or dependence on covariates and then derive the likelihood for the extended model.

• 충청수학회지
• /
• 제13권2호
• /
• pp.19-27
• /
• 2001

In this paper we study another kind of the large deviation property, i.e. moderate deviation type for random amount of random measures on $R^d$ about a Poisson point process and a Poisson center cluster random measure.

• Journal of the Korean Data and Information Science Society
• /
• 제15권2호
• /
• pp.387-394
• /
• 2004

Zero-Inflated Poisson distribution is Poisson distribution with excess zeros. Recently defects of product hardley happen in the manufacturing process. In this case it is desirable to apply to the Zero-Inflated Poisson distribution rather than Poisson. Our target of this paper is to study the tests for changes of rate of defects after the unknown change-point. We are going to compare the powers of the two proposed tests with likelihood tests by the simulations.

• 한국수자원학회논문집
• /
• 제41권7호
• /
• pp.747-759
• /
• 2008

본 연구에서는 관측강우의 통계특성 및 발생특성을 가장 적절하게 재현해 주는 강우모형을 선정하고자 하였다. 강우모형으로 Poisson과정에 근거한 점과정모형인 RPPM, NS-RPPM, modified NS-RPPM을 고려하여 모의자료에 대한 통계분석을 수행하였다. 그 결과, NS-RPPM과 modified NS-RPPM을 이용하여 모의된 자료가 여러 집성시간의 통계치를 적절하게 재현하였다. 또한 modified NS-RPPM을 이용하여 모의된 자료가 관측자료와 가장 유사한 발생특성을 가지는 것을 알 수 있었다. 특히, 홍수, 산사태 등 자연재해의 발생에 큰 영향을 주는 큰 강도를 가지는 강우를 관측치와 가장 유사하게 재현하였다. 모의된 강우사상의 총 강우량, 강우기간, 강우사상 간의 간격을 관측강우와 비교해본 결과 또한 modified NS-RPPM이 가장 좋은 결과를 보였다. 본 연구의 결과를 종합해 볼 때, 강우의 장기 모의를 위해 modified NS-RPPM을 이용하는 것이 가장 적절할 것으로 판단된다.

• International Journal of Quality Innovation
• /
• 제5권1호
• /
• pp.1-9
• /
• 2004

The nonhomogeneous poisson process (NHPP) is often used to model repairable systems that are subject to a minimal repair strategy, with negligible repair times. In this situation, the system can be characterized by its intensity function. There have been many NHPP models according to intensity functions. However, the intensity function of system in use can be changed because of repair or its aging. We consider the single change point model as the modification of the power law process. The shape parameter of its intensity function is changed before and after the change point. We detect the presence of the change point using Bayesian methodology. Some numerical results are also presented.

• 대한수학회지
• /
• 제59권6호
• /
• pp.1083-1101
• /
• 2022

In this paper, we study backward stochastic differential equations (BSDEs shortly) with jumps that have Lipschitz generator in a general filtration supporting a Brownian motion and an independent Poisson random measure. Under just integrability on the data we show that such equations admit a unique solution which belongs to class 𝔻.

• Communications for Statistical Applications and Methods
• /
• 제16권3호
• /
• pp.511-518
• /
• 2009

We consider the problem of testing for change and estimating the unknown change-point in a sequence of time-ordered observations from the binomial and Poisson distributions. Including the likelihood ratio test, Gombay and Horvath (1990) tests are studied and the proposed change-point estimator is derived from their test statistic. A power study of tests and a comparison study of change-point estimators are done via simulation.

• 정보통신설비학회논문지
• /
• 제10권1호
• /
• pp.33-39
• /
• 2011

This paper considers a performance analysis of set-top box (STB) power saving schemes. STB converts the signal into content which is then displayed on the television (TV) screen, and there are typically two operation modes: on mode and stand-by mode. The total energy consumption (TEC), a typical measure of power consumption of STB, is defined by the sum of power consumption in each mode. Recently there are some works of STB power saving schemes that transit STB operation modes efficiently, and the mode transition time point of those schemes can be different. Thus it is required to develop a performance evaluation method that reflects mode transition time points of each scheme to get TEC correctly. This paper proposes a performance evaluation method for STB power consumption using Poisson process to consider the mode transition time point. By modeling STB mode transitions as events of Poisson process, the average time duration of STB mode is computed and accordingly the effect of power saving is evaluated. The performance evaluation result shows that the proposed method achieves 1 to 19% improvement in power consumption compared with a conventional performance evaluation method.

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

• 대한수학회논문집
• /
• 제17권1호
• /
• pp.71-80
• /
• 2002

We give a formulation of the large deviation property for rescalings of random measures on the d-dimensional Euclidean space R$^{d}$ . The approach is global in the sense that the objects are Radon measures on R$^{d}$ and the dual objects are the continuous functions with compact support. This is applied to the cluster random measures with Poisson centers, a large class of random measures that includes the Poisson processes.