• 제목/요약/키워드: tail probability

검색결과 99건 처리시간 0.017초

The UMVUE and MLE of the Tail Probability in Discrete Model

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제17권4호
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    • pp.1405-1412
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    • 2006
  • We shall derive the UMVUE of the tail probability in Poisson, Binomial, and negative Binomial distributions, and compare means squared errors of the UMVUE and the MLE of the tail probability in each case.

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A NOTE ON THE SEVERITY OF RUIN IN THE RENEWAL MODEL WITH CLAIMS OF DOMINATED VARIATION

  • Tang, Qihe
    • 대한수학회보
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    • 제40권4호
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    • pp.663-669
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    • 2003
  • This paper investigates the tail asymptotic behavior of the severity of ruin (the deficit at ruin) in the renewal model. Under the assumption that the tail probability of the claimsize is dominatedly varying, a uniform asymptotic formula for the tail probability of the deficit at ruin is obtained.

두꺼운 꼬리를 갖는 연속 확률분포들의 꼬리 확률에 관하여 (On Tail Probabilities of Continuous Probability Distributions with Heavy Tails)

  • 윤석훈
    • 응용통계연구
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    • 제26권5호
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    • pp.759-766
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    • 2013
  • 본 논문에서는 두꺼운 꼬리를 갖는 확률분포들의 여러 부류에 대해서 살펴본다. 주어진 하나의 확률분포가 이들 중 어떤 부류에 속하는 지를 알려면 해당 분포의 꼬리 확률에 대한 (점근) 표현식을 알아야만 한다. 그러나 대다수의 절대 연속 확률분포들은 분포함수가 아닌 확률밀도함수로 명시되기 때문에 통상적으로 이들의 꼬리 확률에 대한 표현식을 얻는 작업은 그리 쉬운 일이 아니다. 본 논문에서는 이러한 경우 확률밀도함수만을 이용하여 꼬리 확률에 대한 점근 표현식을 쉽게 얻을 수 있는 하나의 방법을 제안한다. 또한 제안한 방법을 설명하기 위하여 몇가지 예를 첨부한다.

On Reliability and UMVUE of Right-Tail Probability in a Half-Normal Variable

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제18권1호
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    • pp.259-267
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    • 2007
  • We consider parametric estimation in a half-normal variable and a UMVUE of its right-tail probability. Also we consider estimation of reliability in two independent half-normal variables, and derive k-th moment of ratio of two same variables.

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Tail Probability Approximations for the Ratio of two Independent Sequences of Random Variables

  • Cho, Dae-Hyeon
    • Journal of the Korean Data and Information Science Society
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    • 제10권2호
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    • pp.415-428
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    • 1999
  • In this paper, we study the saddlepoint approximations for the ratio of two independent sequences of random variables. In Section 2, we review the saddlepoint approximation to the probability density function. In section 3, we derive an saddlepoint approximation formular for the tail probability by following Daniels'(1987) method. In Section 4, we represent a numerical example which shows that the errors are small even for small sample size.

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Tail Probability Approximations for the Ratio of the Independent Random Variables

  • Cho, Dae-Hyeon
    • Journal of the Korean Data and Information Science Society
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    • 제7권2호
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    • pp.189-201
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    • 1996
  • In this paper, we study the saddlepoint approximations for the ratio of independent random variables. In Section 2, we derive the saddlepoint approximation to the density. And in Section 3, we derive two approximation formulae for the tail probability, one by following Daniels'(1987) method and the other by following Lugannani and Rice's (1980). In Section 4, we represent some numerical examples which show that the errors are small even for small sample size.

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Inference on Reliability in an Exponentiated Uniform Distribution

  • Lee, Chang-Soo;Won, Ho-Yon
    • Journal of the Korean Data and Information Science Society
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    • 제17권2호
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    • pp.507-513
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    • 2006
  • We shall consider an inference of the reliability and an estimation of the right-tail probability in an exponentiated uniform distribution. And we shall compare numerically efficiencies for proposed estimators of the scale parameter and right-tail probability in the small sample sizes.

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Notes on the Ratio and the Right-Tail Probability in a Log-Laplace Distribution

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • 제18권4호
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    • pp.1171-1177
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    • 2007
  • We consider estimation of the right-tail probability in a log-Laplace random variable, As we derive the density of ratio of two independent log-Laplace random variables, the k-th moment of the ratio is represented by a special mathematical function. and hence variance of the ratio can be represented by a psi-function.

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