• 제목/요약/키워드: Saddlepoint approximation

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Numerical Comparisons for the Null Distribution of the Bagai Statistic

  • Ha, Hyung-Tae
    • Communications for Statistical Applications and Methods
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    • 제19권2호
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    • pp.267-276
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    • 2012
  • Bagai et al. (1989) proposed a distribution-free test for stochastic ordering in the competing risk model, and recently Murakami (2009) utilized a standard saddlepoint approximation to provide tail probabilities for the Bagai statistic under finite sample sizes. In the present paper, we consider the Gaussian-polynomial approximation proposed in Ha and Provost (2007) and compare it to the saddlepoint approximation in terms of approximating the percentiles of the Bagai statistic. We make numerical comparisons of these approximations for moderate sample sizes as was done in Murakami (2009). From the numerical results, it was observed that the Gaussianpolynomial approximation provides comparable or greater accuracy in the tail probabilities than the saddlepoint approximation. Unlike saddlepoint approximation, the Gaussian-polynomial approximation provides a simple explicit representation of the approximated density function. We also discuss the details of computations.

Saddlepoint 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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    • 제9권2호
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    • pp.255-262
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    • 1998
  • 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 probability density function. In Section 3, 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 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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단일항 안장점근사법에 의한 확산모형의 추정 (A Brief Review of a Term Saddlepoint Approximation Method for Estimating Diffusion Processes)

  • 이은경;이윤동;최영수
    • Communications for Statistical Applications and Methods
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    • 제17권3호
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    • pp.367-376
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    • 2010
  • 최근 확산모형의 추정을 위한 매우 다양한 방법론들이 제시되고 연구 되어 왔다. 본 연구에서는 제안된 확산모형의 추정 방법 중에서, 안장점근사법을 이용한 확산모형의 모수 추정방법에 대하여 살펴보게 되고, 가장 단순한 형태의 안장점근사법인 단일항 안장점근사법의 사용을 제안하게 된다. 단일항 안장점근사법은 오일러근사법과 마찬가지로 계산속도가 빠르고, 다양한 모형에 적용이 가능하면서도 최대우도추정량과 마찬가지로 성능이 우수한 특성을 갖고 있음을 살펴보게 된다. OU 확산모형을 대상으로 한 시뮬레이션 연구를 통하여 단일항 안장점근사를 이용한 추정량과 다른 추정량들과의 성질을 비교한다.

Krawtchouk Polynomial Approximation for Binomial Convolutions

  • Ha, Hyung-Tae
    • Kyungpook Mathematical Journal
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    • 제57권3호
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    • pp.493-502
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    • 2017
  • We propose an accurate approximation method via discrete Krawtchouk orthogonal polynomials to the distribution of a sum of independent but non-identically distributed binomial random variables. This approximation is a weighted binomial distribution with no need for continuity correction unlike commonly used density approximation methods such as saddlepoint, Gram-Charlier A type(GC), and Gaussian approximation methods. The accuracy obtained from the proposed approximation is compared with saddlepoint approximations applied by Eisinga et al. [4], which are the most accurate method among higher order asymptotic approximation methods. The numerical results show that the proposed approximation in general provide more accurate estimates over the entire range for the target probability mass function including the right-tail probabilities. In addition, the method is mathematically tractable and computationally easy to program.

Cubic Equations in General Saddlepoint Approximations

  • Lee, Young-Hoon
    • Communications for Statistical Applications and Methods
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    • 제9권2호
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    • pp.555-563
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    • 2002
  • This paper discusses cubic equations in general saddlepoint approximations. Exact roots are found for various cases by trigonometric identities, the root which is appropriate for the general saddlepoint approximations is selected and discussed, and the defective cases in which the general saddlepoint approximations cannot be used are found.

Saddlepoint Approximation to Quadratic Form and Application to Intraclass Correlation Coefficient

  • Na, Jong-Hwa
    • Journal of the Korean Data and Information Science Society
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    • 제19권2호
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    • pp.497-504
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    • 2008
  • In this paper we studied the saddlepoint approximations to the distribution of quadratic forms in normal variables. We derived the approximations as a special case of Na & Kim (2005). Also applications to a statistic which concerns intraclass correlation coefficient are presented. Simulations show the accuracy and availability of the suggested approximations.

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Efficient simulation using saddlepoint approximation for aggregate losses with large frequencies

  • Cho, Jae-Rin;Ha, Hyung-Tae
    • Communications for Statistical Applications and Methods
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    • 제23권1호
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    • pp.85-91
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    • 2016
  • Aggregate claim amounts with a large claim frequency represent a major concern to automobile insurance companies. In this paper, we show that a new hybrid method to combine the analytical saddlepoint approximation and Monte Carlo simulation can be an efficient computational method. We provide numerical comparisons between the hybrid method and the usual Monte Carlo simulation.

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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다변량 왜정규분포 기반 선형결합통계량에 대한 안장점근사 (Saddlepoint Approximation to the Linear Combination Based on Multivariate Skew-normal Distribution)

  • 나종화
    • 응용통계연구
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    • 제27권5호
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    • pp.809-818
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    • 2014
  • 다변량 왜정규분포는 다변량 정규분포를 포함하는 분포로 최근 많은 응용분야에서 활용되고 있다. 본 논문에서는 다변량 왜정규분포를 기반으로 하는 선형결합통계량의 분포함수에 대한 안장점근사를 다루었다. 이는 단변량 왜정규분포 기반 표본평균에 대한 Na와 Yu (2013)의 결과를 선형결합 및 다변량의 경우로 확장한 것이다. 모의실험과 실제자료분석을 통해 제안된 근사법의 유용성과 정확도를 확인하였다.