• Title/Summary/Keyword: POISSON

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ON SIZE-BIASED POISSON DISTRIBUTION AND ITS USE IN ZERO-TRUNCATED CASES

  • Mir, Khurshid Ahmad
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.12 no.3
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    • pp.153-160
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    • 2008
  • A size-biased Poisson distribution is defined. Its characterization by using a recurrence relation for first order negative moment of the distribution is obtained. Different estimation methods for the parameter of the model are also discussed. R-Software has been used for making a comparison among the three different estimation methods.

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Optimal Control of a Dam with a Compound Poisson Input

  • Lee, Ji-Yeon;Lee, Eui-Yong
    • Journal of the Korean Statistical Society
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    • v.26 no.1
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    • pp.147-154
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    • 1997
  • An infinite dam with a compound Poisson input having exponential jumps is considered. As an output policy, we adopt the $P_{\lambda}$$^{M}$ Policy. After assigning costs to the dam we obtain the long-rum average cost per unit time of operating the dam and find the optimal values of .lambda. and M which minimize the long-run average cost.t.

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A Bayesian Approach to Paired Comparison of Several Products of Poisson Rates

  • Kim Dae-Hwang;Kim Hea-Jung
    • Proceedings of the Korean Statistical Society Conference
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    • 2004.11a
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    • pp.229-236
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    • 2004
  • This article presents a multiple comparison ranking procedure for several products of the Poisson rates. A preference probability matrix that warrants the optimal comparison ranking is introduced. Using a Bayesian Monte Carlo method, we develop simulation-based procedure to estimate the matrix and obtain the optimal ranking via a row-sum scores method. Necessary theory and two illustrative examples are provided.

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Semiparametric Bayesian multiple comparisons for Poisson Populations

  • Cho, Jang Sik;Kim, Dal Ho;Kang, Sang Gil
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.427-434
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    • 2001
  • In this paper, we consider the nonparametric Bayesian approach to the multiple comparisons problem for I Poisson populations using Dirichlet process priors. We describe Gibbs sampling algorithm for calculating posterior probabilities for the hypotheses and calculate posterior probabilities for the hypotheses using Markov chain Monte Carlo. Also we provide a numerical example to illustrate the developed numerical technique.

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Default Bayes Factors for Testing the Equality of Poisson Population Means

  • Son, Young Sook;Kim, Seong W.
    • Communications for Statistical Applications and Methods
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    • v.7 no.2
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    • pp.549-562
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    • 2000
  • Default Bayes factors are computed to test the equality of one Poisson population mean and the equality of two independent Possion population means. As default priors are assumed Jeffreys priors, noninformative improper priors, and default Bayes factors such as three intrinsic Bayes factors of Berger and Pericchi(1996, 1998), the arithmetic, the median, and the geometric intrinsic Bayes factor, and the factional Bayes factor of O'Hagan(1995) are computed. The testing results by each default Bayes factor are compared with those by the classical method in the simulation study.

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Subthreshold Current Model of FinFET Using Three Dimensional Poisson's Equation

  • Jung, Hak-Kee
    • Journal of information and communication convergence engineering
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    • v.7 no.1
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    • pp.57-61
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    • 2009
  • This paper has presented the subthreshold current model of FinFET using the potential variation in the doped channel based on the analytical solution of three dimensional Poisson's equation. The model has been verified by the comparison with the data from 3D numerical device simulator. The variation of subthreshold current with front and back gate bias has been studied. The variation of subthreshold swing and threshold voltage with front and back gate bias has been investigated.

A compound Poisson risk model with variable premium rate

  • Song, Mi Jung;Kim, Jongwoo;Lee, Jiyeon
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1289-1297
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    • 2012
  • We consider a general compound Poisson risk model in which the premium rate is surplus dependent. We analyze the joint distribution of the surplus immediately before ruin, the deffcit at ruin and the time of ruin by solving the integro-differential equation for the Gerber-Shiu discounted penalty function.

Discretization of Pressure-Poisson Equation for Solving Incompressible Navier-Stokes Equations Using Non-Staggered Grid (정규격자를 사용한 비압축성 Navier-Stokes 방정식의 수치해석을 위한 압력 Poisson 방정식의 이산화)

  • Kim Y. G.;Kim H. T.;Kim J. J.
    • 한국전산유체공학회:학술대회논문집
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    • 1998.11a
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    • pp.96-101
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    • 1998
  • Various discretiation methods of Laplacian operator in the Pressure-Poisson equation are investigated for the solution of incompressible Navier-Stokes equations using the non-staggered grid. Laplacian operators previously proposed by other researchers are applied to a Driven-Cavity problem. The computational results are compared with those of Ghia. The results show the characteristics of the discrete Laplacian operators.

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THE EFFECT OF TRACER PARTICLE SIZE ON FEED MIXING QUALITY

  • Heping, Z.;Chuanping, F.
    • Asian-Australasian Journal of Animal Sciences
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    • v.1 no.4
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    • pp.189-193
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    • 1988
  • Distribution of tracer particles in carrier conform to Poisson distribution and the effect of Poisson distribution on mixing uniformity can be reduced by increasing the tracer particle number per unit weight. In this paper, above-mentioned theory has been demonstrated by using three kinds of rotor whose pitches are different.

THE AVERAGING VALUE OF A SAMPLING OF THE RIEMANN ZETA FUNCTION ON THE CRITICAL LINE USING POISSON DISTRIBUTION

  • Jo, Sihun
    • East Asian mathematical journal
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    • v.34 no.3
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    • pp.287-293
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    • 2018
  • We investigate the averaging value of a random sampling ${\zeta}(1/2+iX_t)$ of the Riemann zeta function on the critical line. Our result is that if $X_t$ is an increasing random sampling with Poisson distribution, then $${\mathbb{E}}{\zeta}(1/2+iX_t)=O({\sqrt{\;log\;t}}$$, for all sufficiently large t in ${\mathbb{R}}$.