• 제목/요약/키워드: binomial distribution

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Bayesian Estimation of Three-parameter Bathtub Shaped Lifetime Distribution Based on Progressive Type-II Censoring with Binomial Removal

  • Chung, Younshik
    • Journal of the Korean Data Analysis Society
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    • 제20권6호
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    • pp.2747-2757
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    • 2018
  • We consider the MLE (maximum likelihood estimate) and Bayesian estimates of three-parameter bathtub-shaped lifetime distribution based on the progressive type II censoring with binomial removal. Jung, Chung (2018) proposed the three-parameter bathtub-shaped distribution which is the extension of the two-parameter bathtub-shaped distribution given by Zhang (2004). Jung, Chung (2018) investigated its properties and estimations. The maximum likelihood estimates are computed using Newton-Raphson algorithm. Also, Bayesian estimates are obtained under the balanced loss function using MCMC (Markov chain Monte Carlo) method. In particular, BSEL (balanced squared error loss) function is considered as a special form of balanced loss function given by Zellner (1994). For comparing theirs MLEs with the corresponding Bayes estimates, some simulations are performed. It shows that Bayes estimates is better than MLEs in terms of risks. Finally, concluding remarks are mentioned.

RUIN PROBABILITIES IN THE RISK MODEL WITH TWO COMPOUND BINOMIAL PROCESSES

  • Zhang, Mao-Jun;Nan, Jiang-Xia;Wang, Sen
    • Journal of applied mathematics & informatics
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    • 제26권1_2호
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    • pp.191-201
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    • 2008
  • In this paper, we consider an insurance risk model governed by a compound Binomial arrival claim process and by a compound Binomial arrival premium process. Some formulas for the probabilities of ruin and the distribution of ruin time are given, we also prove the integral equation of the ultimate ruin probability and obtain the Lundberg inequality by the discrete martingale approach.

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Estimating reliability in discrete distributions

  • Moon, Yeung-Gil;Lee, Chang-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제22권4호
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    • pp.811-817
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    • 2011
  • We shall introduce a general probability mass function which includes several discrete probability mass functions. Especially, when the random variable X is Poisson, binomial, and negative binomial random variables as some special cases of the introduced distribution, the maximum likelihood estimator (MLE) and the uniformly minimum variance unbiased estimator (UMVUE) of the probability P(X ${\leq}$ t) are considered. And the efficiencies of the MLE and the UMVUE of the reliability ar compared each other.

Binomial Distribution Based Reputation for WSNs: A Comprehensive Survey

  • Wei, Zhe;Yu, Shuyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권10호
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    • pp.3793-3814
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    • 2021
  • Most secure solutions like cryptography are software based and they are designed to mainly deal with the outside attacks for traditional networks, but such soft security is hard to be implemented in wireless sensor networks to counter the inside attacks from internal malicious nodes. To address this issue, reputation has been introduced to tackle the inside malicious nodes. Reputation is essentially a stimulating mechanism for nodes' cooperation and is employed to detect node misbehaviors and improve the trust-worthiness between individual nodes. Among the reputation models, binomial distribution based reputation has many advantages such as light weight and ease of implementation in resource-constraint sensor nodes, and accordingly researchers have proposed many insightful related methods. However, some of them either directly use the modelling results, apply the models through simple modifications, or only use the required components while ignoring the others as an integral part of the whole model, this topic still lacks a comprehensive and systematical review. Thus the motivation of this study is to provide a thorough survey concerning each detailed functional components of binomial distribution based reputation for wireless sensor networks. In addition, based on the survey results, we also argue some open research problems and suggest the directions that are worth future efforts. We believe that this study is helpful to better understanding the reputation modeling mechanism and its components for wireless sensor networks, and can further attract more related future studies.

Change-Point Problems in a Sequence of Binomial Variables

  • Jeong, Kwang-Mo
    • Communications for Statistical Applications and Methods
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    • 제3권2호
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    • pp.175-185
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    • 1996
  • For the Change-point problem in a sequence of binomial variables we consider the maximum likelihood estimator (MLE) of unknown change-point. Its asymptotic distribution is quite limited in the case of binomial variables with different numver of trials at each time point. Hinkley and Hinkley (1970) gives an asymptotic distribution of the MLE for a sequence of Bernoulli random variables. To find the asymptotic distribution a numerical method such as bootstrap can be used. Another concern of our interest in the inference on the change-point and we derive confidence sets based on the liklihood ratio test(LRT). We find approximate confidence sets from the bootstrap distribution and compare the two results through an example.

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Recurrence Formula for the Central Moments of Number of Successes with n Poisson Trials

  • Moon, Myung-Sang
    • Journal of the Korean Data and Information Science Society
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    • 제14권2호
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    • pp.385-391
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    • 2003
  • A sequence of n Bernoulli trials which violates the constant success probability assumption is termed as "Poisson trials". In this paper, the recurrence formula for the r-th central moment of number of successes with n Poisson trials is derived. Romanovsky's method, based on the differentiation of characteristic function, is used in the derivation of recurrence formula for the central moments of conventional binomial distribution. Romanovsky's method is applied to that of Poisson trials in this paper. Some central moment calculation results are given to compare the central moments of Poisson trials with those of conventional binomial distribution.

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실제포함확률을 이용한 초기하분포 모수의 근사신뢰구간 추정에 관한 모의실험 연구 (A simulation study for the approximate confidence intervals of hypergeometric parameter by using actual coverage probability)

  • 김대학
    • Journal of the Korean Data and Information Science Society
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    • 제22권6호
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    • pp.1175-1182
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    • 2011
  • 본 연구는 초기하분포의 모수, 즉 성공의 확률에 대한 신뢰구간추정에 대하여 설펴보았다. 초기하분포의 성공의 확률에 대한 신뢰구간은 일반적으로 잘 알려져 있지 않으나 그 응용성과 활용성의 측면에서 신뢰구간의 추정은 상당히 중요하다. 본 논문에서는 초기하분포의 성공의 확률에 대한 정확신뢰구간과 이항분포와 정규분포에 의한 근사신뢰구간을 소개하고 여러 가지 모집단의 크기와 표본 수에 대하여, 그리고 몇 가지 관찰값에 대한 정확신뢰구간과 근사신뢰구간을 계산하고 소 표본의 경우에 모의실험을 통하여 실제포함확률의 측면에서 살펴보았다.

베타-이항모형을 이용한 과산포 공정용 p 관리도의 개발 (Development of a p Control Chart for Overdispersed Process with Beta-Binomial Model)

  • 배봉수;서순근
    • 품질경영학회지
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    • 제45권2호
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    • pp.209-225
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    • 2017
  • Purpose: Since traditional p chart is unable to deal with the variation of attribute data, this paper proposes a new attribute control chart for nonconforming proportions incorporating overdispersion with a beta-binomial model. Methods: Statistical theories for control chart developed under the beta-binomial model and a new approach using this control chart are presented Results: False alarm probabilities of p chart with the beta-binomial model are evaluated and demerits of p chart under overdispersion are discussed from three examples. Hence a concrete procedure for the proposed control chart is provided and illustrated with examples Conclusion: The proposed chart is more useful than traditional p chart, individual chart to treat observed proportions nonconforming as variable data and Laney p' chart.

Negative Binomial Varying Coefficient Partially Linear Models

  • Kim, Young-Ju
    • Communications for Statistical Applications and Methods
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    • 제19권6호
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    • pp.809-817
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    • 2012
  • We propose a semiparametric inference for a generalized varying coefficient partially linear model(VCPLM) for negative binomial data. The VCPLM is useful to model real data in that varying coefficients are a special type of interaction between explanatory variables and partially linear models fit both parametric and nonparametric terms. The negative binomial distribution often arise in modelling count data which usually are overdispersed. The varying coefficient function estimators and regression parameters in generalized VCPLM are obtained by formulating a penalized likelihood through smoothing splines for negative binomial data when the shape parameter is known. The performance of the proposed method is then evaluated by simulations.

Extreme Value of Moving Average Processes with Negative Binomial Noise Distribution

  • Park, You-Sung
    • Journal of the Korean Statistical Society
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    • 제21권2호
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    • pp.167-177
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    • 1992
  • In this paper, we investigate the limiting distribution of $M_n = max (X_1, X-2, \cdots, X_n)$ in the infinite moving average process ${X_t = \sum c_i Z_{t-i}}$ generated from i.i.d. negative binomial variables $Z_i$'s. While no limit result is possible, nonetheless asymptotic bounds are derived. We also present the tail behavior of $X_t$, i.e., weighted sum of i.i.d. random variables. This continues a study made by Rootzen (1986) for discrete innovation sequences.

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