• Title/Summary/Keyword: 포아송 분포

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Efficient Cellular Core Network Design based on Traffic Characteristics (트래픽 특성 에 따른 셀룰러 코어 망의 효율적인 설계)

  • 김호수;장주욱;이경근;이정수
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.04d
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    • pp.199-201
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    • 2003
  • 현재 셀룰러(Cellular) 코어(Core) 망에서의 회선산출은 얼랑(Erlang) B 이론으로부터 출발하고 있다 시도호(attempted call)의 특성이 포아송(Poisson)분포임을 가정한 얼랑 공식으로부터 유도된 얼랑 B 테이블을 통해 각구간의 트래픽 및 목표 호손율(Block Rate)에 맞는 적절한 회선 수를 산출한다. 본 논문에서는 유선 전화망에서 주로 쓰이던 얼랑 B 이론이 이동통신 셀룰러 코어 방에서도 적용될 수 있는지의 여부를 판단하기 위해서 1500만 이상의 가입자를 보유하고 있는 셀룰러 코어 망을 실험대상으로 하였다. 트래픽 분포 및 얼랑 B 호손율을 검증하기 위해 실측 실험을 하였으며, 과금 데이터(Billing Data)를 이용하여 실측 실험과 같은 결과를 얻기 위해 Block Generating Program을 개발하였다. 총 108개 루트(Route)에 대한 측정 실험 결과 50%의 트래픽만이 포아송 분포 특성을 만족함을 알아내었고, 포아송 분포를 벗어난 트래픽에서의 얼랑 B 테이블의 보정 방법을 실제 실험 데이터의 통계특성에 따라 도출하는 방식을 제안한다.

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A Study on the Applicability of 2-Poisson Model for Selecting Korean Subject Words (2-포아송 모형을 이용한 한글 주제어 선정에 관한 연구)

  • 정영미;최대식
    • Journal of the Korean Society for information Management
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    • v.17 no.1
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    • pp.129-148
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    • 2000
  • Experiments were performed on three subsets of a Korean test collection in order to determine whether 2-Poisson model's Z value is a good measure for selecting subject words from a document to be indexed. It was found that subject word selection based on the Z value was effective for only one subset with short texts, i.e., the Science and Technology subset. Correlation analyses between 2-Poisson model's Z and TF.IDF weight for the three subsets showed that the correlation was relatively high for two test subsets with short texts, i.e., the Science and Technology subset and the Newspaper subset.

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Bayesian Analysis of a Zero-inflated Poisson Regression Model: An Application to Korean Oral Hygienic Data (영과잉 포아송 회귀모형에 대한 베이지안 추론: 구강위생 자료에의 적용)

  • Lim, Ah-Kyoung;Oh, Man-Suk
    • The Korean Journal of Applied Statistics
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    • v.19 no.3
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    • pp.505-519
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    • 2006
  • We consider zero-inflated count data, which is discrete count data but has too many zeroes compared to the Poisson distribution. Zero-inflated data can be found in various areas. Despite its increasing importance in practice, appropriate statistical inference on zero-inflated data is limited. Classical inference based on a large number theory does not fit unless the sample size is very large. And regular Poisson model shows lack of St due to many zeroes. To handle the difficulties, a mixture of distributions are considered for the zero-inflated data. Specifically, a mixture of a point mass at zero and a Poisson distribution is employed for the data. In addition, when there exist meaningful covariates selected to the response variable, loglinear link is used between the mean of the response and the covariates in the Poisson distribution part. We propose a Bayesian inference for the zero-inflated Poisson regression model by using a Markov Chain Monte Carlo method. We applied the proposed method to a Korean oral hygienic data and compared the inference results with other models. We found that the proposed method is superior in that it gives small parameter estimation error and more accurate predictions.

Analysis of Drought Spatial Distribution Using Poisson Process (포아송과정을 이용한 가뭄의 공간분포 분석)

  • Yoo, Chul-Sang;Ahn, Jae-Hyun;Ryoo, So-Ra
    • Journal of Korea Water Resources Association
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    • v.37 no.10
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    • pp.813-822
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    • 2004
  • This study quantifies and compares the drought return and duration characteristics by applying the Poisson process as well as based on by analyzing the observed data directly. The drought spatial distributions derived for the Gyunggi province are also compared. The monthly rainfall data are used to construct the SPI as a drought index. Especially, this study focuses on the evaluation of the Poisson process model when applying it to various data lengths such as in the spatial analysis 'of drought. Summarizing the results are as follows. (1) The Poisson process is found to be effective for the quantification of drought, especially when the data length is short. When applying the Poisson process, two neighboring sites are found insensitive to the data length to show similar drought characteristics, so the overall drought pattern becomes smoother than that derived directly from the observed data. (2) When the data length is very different site by site, the spatial analysis of drought based on a model application seems better than that based on the direct data analysis. This study also found more obvious spatial pattern of drought occurrence and duration when applying the Poisson process.

On the Extension of Test Statistics for Detecting Negative Binomial Departures from the Poisson Assumption (포아송으로부터 부의 이항분포로의 이탈에 대한 검정통계량의 확장)

  • 이선호
    • Journal of the Korean Statistical Society
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    • v.22 no.2
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    • pp.171-190
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    • 1993
  • 포아송분포로부터 부의 이항분포로의 이탈을 검색하는 통계량들이 자료의 형태에 따라 여러가지 제시되었다. 그런데 대립가설인 부의 이항분포의 모수화 방법에 따라 분산과 평균의 구조가 변하고 국소 최적 검정 통계량도 달라진다는 것이 알려졌다. 본 논문에서는 대립가설을 일반적인 포아송 혼합분포로까지 확장시키고, 일반적인 형태의 분산과 평균의 구조에도 검정 가능한 새로운 통계량 L을 소개하고 있다. 또한 L 통계량은 포아송 분포로부터 부의 이항분포로의 이탈을 다루는 기존의 여러 통계량들의 일반화된 형태임을 보였다. 점근적 상대효율과 모의 실험을 통하여 L 통계량과 기존의 통계량들을 비교한 결과 분산과 평균사이의 구조에 상관없이 L 통계량이 우수한 것임을 입증하였다.

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The discretization method of Poisson equation by considering Fermi-Dirac distribution (Fermi-Dirac 분포를 고려한 Poisson 방정식의 이산화 방법)

  • 윤석성;이은구;김철성
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.907-910
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    • 1999
  • 본 논문에서는 고 농도로 불순물이 주입된 영역에서 전자 및 정공 농도를 정교하게 구현하기 위해 Fermi-Dirac 분포함수를 고려한 포아송 방정식의 이산화 방법을 제안하였다. Fermi-Dirac 분포를 근사시키기 위해서 Least-Squares 및 점근선 근사법을 사용하였으며 Galerkin 방법을 근간으로 한 유한 요소법을 이용하여 포아송 방정식을 이산화하였다. 구현한 모델을 검증하기 위해 전력 BJT 시료를 제작하여 자체 개발된 소자 시뮬레이터인 BANDIS를 이용하여 모의 실험을 수행한 결과, 상업용 2차원 소자 시뮬레이터인 MEDICI에 비해 최대 4%이내의 상대 오차를 보였다.

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Zero-Inflated INGARCH Using Conditional Poisson and Negative Binomial: Data Application (조건부 포아송 및 음이항 분포를 이용한 영-과잉 INGARCH 자료 분석)

  • Yoon, J.E.;Hwang, S.Y.
    • The Korean Journal of Applied Statistics
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    • v.28 no.3
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    • pp.583-592
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    • 2015
  • Zero-inflation has recently attracted much attention in integer-valued time series. This article deals with conditional variance (volatility) modeling for the zero-inflated count time series. We incorporate zero-inflation property into integer-valued GARCH (INGARCH) via conditional Poisson and negative binomial marginals. The Cholera frequency time series is analyzed as a data application. Estimation is carried out using EM-algorithm as suggested by Zhu (2012).

Bayesian Multiple Change-Point Estimation for Single Quantum Dot Luminescence Intensity Data (단일 양자점으로부터 발생한 발광세기 변화에 대한 베이지안 다중 변화점 추정)

  • Kima, Jaehee;Kimb, Hahkjoon
    • The Korean Journal of Applied Statistics
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    • v.26 no.4
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    • pp.569-579
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    • 2013
  • In the field of single-molecule spectroscopy, it is essential to analyze luminescence Intensity changes that result from a single molecule. With the CdSe/ZnS core-shell structured quantum dot photon emission data Bayesian multiple change-point estimation is done with the gamma prior for Poisson parameters and truncated Poisson distribution for the number of change-points.

An application to Zero-Inflated Poisson Regression Model

  • Kim, Kyung-Moo
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.45-53
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    • 2003
  • The Zero-Inflated Poisson regression is a model for count data with exess zeros. When the reponse variables have excess zeros, it is not easy to apply the Poisson regression model. In this paper, we study and simulate the zero-inflated Poisson regression model. An real example was applied to this model. Regression parameters are estimated by using MLE's. We also compare the fitness of zero-inflated Poisson model with the Poisson regression and decision tree model.

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Subset Selection in the Poisson Models - A Normal Predictors case - (포아송 모형에서의 설명변수 선택문제 - 정규분포 설명변수하에서 -)

  • 박종선
    • The Korean Journal of Applied Statistics
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    • v.11 no.2
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    • pp.247-255
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    • 1998
  • In this paper, a new subset selection problem in the Poisson model is considered under the normal predictors. It turns out that the subset model has bigger valiance than that of the Poisson model with random predictors and this has been used to derive new subset selection method similar to Mallows'$C_p$.

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