• Title/Summary/Keyword: Poisson model

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Statistical Analysis of K-League Data using Poisson Model

  • Kim, Yang-Jin
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.775-783
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    • 2012
  • Several statistical models for bivariate poisson data are suggested and used to analyze 2011 K-league data. Our interest is composed of two purposes: The first purpose is to exploit potential attacking and defensive abilities of each team. Particular, a bivariate poisson model with diagonal inflation is incorporated for the estimation of draws. A joint model is applied to estimate an association between poisson distribution and probability of draw. The second one is to investigate causes on scoring time of goals and a regression technique of recurrent event data is applied. Some related future works are suggested.

Classification Analysis in Information Retrieval by Using Gauss Patterns

  • Lee, Jung-Jin;Kim, Soo-Kwan
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.1-11
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    • 2002
  • This paper discusses problems of the Poisson Mixture model which Is widely used to decide the effective words in judging relevant document. Gamma Distribution model and Gauss Patterns model as an alternative of the Poisson Mixture model are studied. Classification experiments by using TREC sub-collection, WSJ[1,2] with MGQUERY and AidSearch3.0 system are discussed.

Modelling Count Responses with Overdispersion

  • Jeong, Kwang Mo
    • Communications for Statistical Applications and Methods
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    • v.19 no.6
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    • pp.761-770
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    • 2012
  • We frequently encounter outcomes of count that have extra variation. This paper considers several alternative models for overdispersed count responses such as a quasi-Poisson model, zero-inflated Poisson model and a negative binomial model with a special focus on a generalized linear mixed model. We also explain various goodness-of-fit criteria by discussing their appropriateness of applicability and cautions on misuses according to the patterns of response categories. The overdispersion models for counts data have been explained through two examples with different response patterns.

A Compound Poisson Risk Model with a Two-Step Premium Rule

  • Song, Mi Jung;Lee, Jiyeon
    • Communications for Statistical Applications and Methods
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    • v.20 no.5
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    • pp.377-385
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    • 2013
  • We consider a compound Poisson risk model in which the premium rate changes when the surplus exceeds a threshold. The explicit form of the ruin probability for the risk model is obtained by deriving and using the overflow probability of the workload process in the corresponding M/G/1 queueing model.

Comparison of probability distributions to analyze the number of occurrence of torrential rainfall events (집중호우사상의 발생횟수 분석을 위한 확률분포의 비교)

  • Kim, Sang Ug;Kim, Hyeung Bae
    • Journal of Korea Water Resources Association
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    • v.49 no.6
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    • pp.481-493
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    • 2016
  • The statistical analysis to the torrential rainfall data that is defined as a rainfall amount more than 80 mm/day is performed with Daegu and Busan rainfall data which is collected during 384 months. The number of occurrence of the torrential rainfall events can be simulated usually using Poisson distribution. However, the Poisson distribution can be frequently failed to simulate the statistical characteristics of the observed value when the observed data is zero-inflated. Therefore, in this study, Generalized Poisson distribution (GPD), Zero-Inflated Poisson distribution (ZIP), Zero-Inflated Generalized Poisson distribution (ZIGP), and Bayesian ZIGP model were used to resolve the zero-inflated problem in the torrential rainfall data. Especially, in Bayesian ZIGP model, a informative prior distribution was used to increase the accuracy of that model. Finally, it was suggested that POI and GPD model should be discouraged to fit the frequency of the torrential rainfall data. Also, Bayesian ZIGP model using informative prior provided the most accurate results. Additionally, it was recommended that ZIP model could be alternative choice on the practical aspect since the Bayesian approach of this study was considerably complex.

Compact Model of a pH Sensor with Depletion-Mode Silicon-Nanowire Field-Effect Transistor

  • Yu, Yun Seop
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.14 no.4
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    • pp.451-456
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    • 2014
  • A compact model of a depletion-mode silicon-nanowire (Si-NW) pH sensor is proposed. This drain current model is obtained from the Pao-Sah integral and the continuous charge-based model, which is derived by applying the parabolic potential approximation to the Poisson's equation in the cylindrical coordinate system. The threshold-voltage shift in the drain-current model is obtained by solving the nonlinear Poisson-Boltzmann equation for the electrolyte. The simulation results obtained from the proposed drain-current model for the Si-NW field-effect transistor (SiNWFET) agree well with those of the three-dimensional (3D) device simulation, and those from the Si-NW pH sensor model also agree with the experimental data.

A Selection of the Point Rainfall Process Model Considered on Temporal Clustering Characteristics (시간적 군집특성을 고려한 강우모의모형의 선정)

  • Kim, Kee-Wook;Yoo, Chul-Sang
    • Journal of Korea Water Resources Association
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    • v.41 no.7
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    • pp.747-759
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    • 2008
  • This study, a point rainfall process model, which could represent appropriately observed rainfall data, was to select. The point process models-rectangular pulses Poisson process model(RPPM), Neyman-Scott rectangular pulses Poisson process model(NS-RPPM), and modified Neyman-Scott rectangular pulses Poisson process model(modified NS-RPPM)-all based on Poisson process were considered as possible rainfall models, whose statistical analyses were performed with their simulation rainfall data. As results, simulated rainfall data using the NS-RPPM and the modified NS-RPPM represent appropriately statistics of observed data for several aggregation levels. Also, simulated rainfall data using the modified NS-RPPM shows similar characteristics of rainfall occurrence to the observed rainfall data. Especially, the modified NS-RPPM reproduces high-intensity rainfall events that contribute largely to occurrence of natural harzard such as flood and landslides most similarly. Also, the modified NS-RPPM shows the best results with respect to the total rainfall amount, duration, and inter-event time. In conclusions, the modified NS-RPPM was found to be the most appropriate model for the long-term simulation of rainfall.

Multivariate Gamma-Poisson Model and Parameter Estimation for Polytomous Data : Application to Defective Pixels of LCD (다가자료에 적합한 다변수 감마-포아송 모델과 파라미터 추정방법 : LCD 화소불량 응용)

  • Ha, Jung-Hoon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.34 no.1
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    • pp.42-51
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    • 2011
  • Poisson model and Gamma-Poisson model are popularly used to analyze statistical behavior from defective data. The methods are based on binary criteria, that is, good or failure. However, manufacturing industries prefer polytomous criteria for classifying manufactured products due to flexibility of marketing. In this paper, I introduce two multivariate Gamma-Poisson(MGP) models and estimation methods of the parameters in the models, which are able to handle polytomous data. The models and estimators are verified on defective pixels of LCD manufacturing. Experimental results show that both the independent MGP model and the multinomial MGP model have excellent performance in terms of mean absolute deviation and the choice of method depends on the purpose of use.

Simulation of the Shifted Poisson Distribution with an Application to the CEV Model

  • Kang, Chulmin
    • Management Science and Financial Engineering
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    • v.20 no.1
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    • pp.27-32
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    • 2014
  • This paper introduces three different simulation algorithms of the shifted Poisson distribution. The first algorithm is the inverse transform method, the second is the rejection sampling, and the third is gamma-Poisson hierarchy sampling. Three algorithms have different regions of parameters at which they are efficient. We numerically compare those algorithms with different sets of parameters. As an application, we give a simulation method of the constant elasticity of variance model.

DEPENCENCE CONCEPT OF BIVARIATE POISSON SHOCK MODEL

  • Baek, Jong-Il;Park, Chun-Ho;Choi, Jeong-Yeol
    • Journal of applied mathematics & informatics
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    • v.8 no.3
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    • pp.989-999
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    • 2001
  • In this paper we show that certain notions of negative dependence are preserved under a bivariate homogenous poisson shock model in which two devices shocks form two independent poisson processes.