• Journal of the Korean Data and Information Science Society
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• 제17권3호
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• pp.953-961
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• 2006

Let's say that we are given a k number of random variables following Poisson distribution that are individually dependent and which forms multivariate Poisson distribution. We particularly dealt with a method of creating random numbers that satisfies the covariance matrix, where the elements of covariance matrix are parameters forming a multivariate Poisson distribution. To create such random numbers, we propose a new algorithm based on the method reducing the number of parameter set and deal with its relationship to the Park et al.(1996) algorithm used in creating multivariate Bernoulli random numbers.

• Journal of the Korean Data and Information Science Society
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• 제17권1호
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• pp.161-171
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• 2006

In this paper, we consider the random number generation method for multivariate Poisson distribution with specific covariance matrix. Random number generating method for the multivariate Poisson distribution is considered into two part, by first solving the linear equation to determine the univariate Poisson parameter, then convoluting independent univariate Poisson variates with appropriate expectations. We propose a numerical algorithm to solve the linear equation given the specific covariance matrix.

• Communications for Statistical Applications and Methods
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• 제2권1호
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• pp.137-144
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• 1995

Hierarchical Bayes estimations of exchangeable mean vector of a multivariate Poisson distribution are obtained. Since sophiscated analytic integration procedures are needed, the Laplace method is employed in order tocompute these estimations approximately. An example is presented.

• Communications for Statistical Applications and Methods
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• 제5권2호
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• pp.503-515
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• 1998

When a neutral particle beam(NPB) aimed at the object and receive a small number of neutron signals at the detector, it follows approximately Poisson distribution. Under the four assumptions in the presence of errors and uncertainties for the Poisson parameters, an exact probability distribution of neutral particles have been derived. The probability distribution for the neutron signals received by a detector averaged over the three sources of errors is expressed as a four-dimensional integral of certain data. Two of the four integrals can be evaluated analytically and thereby the integral is reduced to a two-dimensional integral. The monotone likelihood ratio(MLR) property of the distribution is proved by using the Cauchy mean value theorem for the univariate distribution and multivariate distribution. Its MLR property can be used to find a criteria for the hypothesis testing problem related to the distribution.

• 경영과학
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• 제32권2호
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• pp.69-78
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• 2015

This paper considers a Bayesian Poisson model for multivariate count data using multiplicative rates. More specifically we compose the parameter for overall arrival rates by the product of two parameters, a common effect and an individual effect. The common effect is composed of autoregressive evolution of the parameter, which allows for analysis on seasonal effects on all multivariate time series. In addition, analysis on individual effects allows the researcher to differentiate the time series by whatevercharacterization of their choice. This type of model allows the researcher to specifically analyze two different forms of effects separately and produce a more robust result. We illustrate a simple MCMC generation combined with a Gibbs sampler step in estimating the posterior joint distribution of all parameters in the model. On the whole, the model presented in this study is an intuitive model which may handle complicated problems, and we highlight the properties and possible applications of the model with an example, analyzing real time series data involving customer arrivals to a large retail store.

• 한국전자통신학회논문지
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• 제9권2호
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• pp.187-194
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• 2014

본 논문에서는 다른 모바일 단말에서의 통합적 간섭을 고려하여 셀룰러 네트워크에서 매크로 다이버시티 결합을 사용하였을 경우의 Outage 확률을 분석한다. Outage 확률을 분석한 타 논문과 달리 본 논문에서는 상대적으로 간섭이 적은 기지국을 선택하였을 때의 다이버시티 이득을 분석한다. 분석을 위해 모바일 단말이 포아송 포인트 프로세스에 따라 확률적으로 분포한다고 가정하였다. 다수의 기지국에 가해지는 통합적 간섭의 다변수 분포를 다변수 로그노멀 분포로 근사시켜 분석을 수행하였다.

• Communications for Statistical Applications and Methods
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• 제20권6호
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• pp.439-454
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• 2013

This study presents a Bayesian multiple change-point detection approach to segment and classify the observations that no longer come from an initial population after a certain time. Inferences are based on the multiple change-points in a sequence of random variables where the probability distribution changes. Bayesian multiple change-point estimation is classifies each observation into a segment. We use a truncated Poisson distribution for the number of change-points and conjugate prior for the exponential family distributions. The Bayesian method can lead the unsupervised classification of discrete, continuous variables and multivariate vectors based on latent class models; therefore, the solution for change-points corresponds to the stochastic partitions of observed data. We demonstrate segmentation with real data.

• 응용통계연구
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• 제22권4호
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• pp.687-695
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• 2009

The Bayesian multiple change-point estimation has been applied to the daily means of ozone and PM10 data in Seoul for the period 1999. We focus on the detection of multiple change-points in the ozone and PM10 bivariate vectors by evaluating the posterior probabilities and Bayesian information criterion(BIC) using the stochastic approximation Monte Carlo(SAMC) algorithm. The result gives 5 change-points of mean vectors of ozone and PM10, which are related with the seasonal characteristics.

• 한국해안·해양공학회논문집
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• 제24권5호
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• pp.305-318
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• 2012

직립 케이슨 방파제에 대한 기존의 성능설계법은 임의의 시간 동안의 평균활동량을 산정하지만 허용활동량을 최초로 초과하는 사건의 발생확률(최초통과확률)은 계산하지 못한다. 설계자는 구조물이 최초로 피해를 입을 확률에 대한 정보를 구조물의 설계 단계뿐 아니라 관리 및 운영에서도 필요로 한다. 따라서 본 연구에서는 케이슨 활동의 최초통과확률을 산정하기 위해 확률과정에 기반한 시간의존 신뢰성 설계법을 개발하였다. 방파제의 활동을 일으키는 폭풍파는 발생 시간과 강도의 임의성의 특징이 있기 때문에 Poisson spike process를 사용하여 케이슨 활동을 정식화할 수 있다. 여기서 방파제의 활동을 일으키는 폭풍파의 발생률은 활동량분포함수와 폭풍파의 평균발생률로 표현된다. 성능설계법으로 모의된 이들은 설계변수들의 다변량 회귀함수로 나타내진다. 결과적으로 활동량분포함수와 폭풍파의 평균발생률은 유의파고, 케이슨 폭, 수심의 함수로 표현되어 케이슨 활동에 대한 최초통과확률을 손쉽게 산정할 수 있다.