• Title/Summary/Keyword: Saddlepoint Approximation

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Saddlepoint approximation for distribution function of sample mean of skew-normal distribution (왜정규 표본평균의 분포함수에 대한 안장점근사)

  • Na, Jong-Hwa;Yu, Hye-Kyung
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1211-1219
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    • 2013
  • Recently, the usage of skew-normal distribution, instead of classical normal distribution, is rising up in many statistical theories and applications. In this paper, we deal with saddlepoint approximation for the distribution function of sample mean of skew-normal distribution. Comparing to normal approximation, saddlepoint approximation provides very accurate results in small sample sizes as well as for large or moderate sample sizes. Saddlepoint approximations related to the skew-normal distribution, suggested in this paper, can be used as a approximate approach to the classical method of Gupta and Chen (2001) and Chen et al. (2004) which need very complicate calculations. Through simulation study, we verified the accuracy of the suggested approximation and applied the approximation to Robert's (1966) twin data.

ON THE CURIE-WEISS MODEL WITH A NEW HAMILTONIAN

  • Lee, Sang Ho
    • Korean Journal of Mathematics
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    • v.7 no.2
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    • pp.301-313
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    • 1999
  • In this paper we obtain similar limit theorems of the Generalized Curie - Weiss model for a new class Hamiltonian. We expressed the saddlepoint approximation by large deviation rate and then obtain the limit theorems.

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Saddlepoint approximation to the distribution function of quadratic forms based on multivariate skew-normal distribution (다변량 왜정규분포 기반 이차형식의 분포함수에 대한 안장점근사)

  • Na, Jonghwa
    • The Korean Journal of Applied Statistics
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    • v.29 no.4
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    • pp.571-579
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    • 2016
  • Most of studies related to the distributions of quadratic forms are conducted under the assumption of multivariate normal distribution. In this paper, we suggested an approximation to the distribution of quadratic forms based on multivariate skew-normal distribution as alternatives for multivariate normal distribution. Saddlepoint approximations are considered and the accuracy of the approximations are verified through simulation studies.

Small Sample Asymptotic Inferences for Autoregressive Coefficients via Saddlepoint Approximation (안장점근사를 이용한 자기회귀계수에 대한 소표본 점근추론)

  • Na, Jong-Hwa;Kim, Jeong-Sook
    • The Korean Journal of Applied Statistics
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    • v.20 no.1
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    • pp.103-115
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    • 2007
  • In this paper we studied the small sample asymptotic inference for the autoregressive coefficient in AR(1) model. Based on saddlepoint approximations to the distribution of quadratic forms, we suggest a new approximation to the distribution of the estimators of the noncircular autoregressive coefficients. Simulation results show that the suggested methods are very accurate even in the small sample sizes and extreme tail area.

Saddlepoint Approximations to the Distribution Function of Non-homogeneous Quadratic Forms (비동차 이차형식의 분포함수에 대한 안장점근사)

  • Na Jong-Hwa;Kim Jeong-Soak
    • The Korean Journal of Applied Statistics
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    • v.18 no.1
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    • pp.183-196
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    • 2005
  • In this paper we studied the saddlepoint approximations to the distribution of non-homogeneous quadratic forms in normal variables. The results are the extension of Kuonen's which provide the same approximations to homogeneous quadratic forms. The CGF of interested statistics and related properties are derived for applications of saddlepoint techniques. Simulation results are also provided to show the accuracy of saddlepoint approximations.

Asymptotic Inference on the Odds Ratio via Saddlepoint Method (안부점근사를 이용한 승산비에 대한 점근적 추론)

  • Na, Jong-Hwa
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.1
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    • pp.29-36
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    • 1999
  • We propose a new method of asymptotic inference on the odds ratio (or cross-product ratio) in $2{\times}2$ contingency table. Saddlepoint approximations to the conditional tail probability we used in this procedure. We assess the accuracy of the suggested method by comparing with the exact one. To obtain the exact values, we need very complicated calculations containing the cumulative probabilities of non-central hypergeometric distribution. The suggested method in this paper is very accurate even for small or moderate sample sizes as well as simple and easy to use. Example with a real data is also considered.

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Saddlepoint Approximation to the Distribution of General Statistic (일반적 통계량의 분포함수에 대한 안부점 근사)

  • 나종화
    • The Korean Journal of Applied Statistics
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    • v.11 no.2
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    • pp.287-302
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    • 1998
  • Saddlepoint approximation to the distribution function of sample mean(Daniels, 1987) is extended to the case of general statistic in this paper. The suggested approximation methods are applied to derive the approximations to the distributions of some statistics, including sample valiance and studentized mean. Some comparisons with other methods show that the suggested approximations are very accurate for moderate or small sample sizes. Even in extreme tail the accuracies are also maintained.

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Saddlepoint approximations for the risk measures of portfolios based on skew-normal risk factors (왜정규 위험요인 기반 포트폴리오 위험측도에 대한 안장점근사)

  • Yu, Hye-Kyung;Na, Jong-Hwa
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.6
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    • pp.1171-1180
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    • 2014
  • We considered saddlepoint approximations to VaR (value at risk) and ES (expected shortfall) which frequently encountered in finance and insurance as the measures of risk management. In this paper we supposed univariate and multivariate skew-normal distributions, instead of traditional normal class distributions, as underlying distribution of linear portfolios. Simulation results are provided and showed the suggested saddlepoint approximations are very accurate than normal approximations.

Fourier Series Approximation for the Generalized Baumgartner Statistic

  • Ha, Hyung-Tae
    • Communications for Statistical Applications and Methods
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    • v.19 no.3
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    • pp.451-457
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    • 2012
  • Baumgartner et al. (1998) proposed a novel statistical test for the null hypothesis that two independently drawn samples of data originate from the same population, and Murakami (2006) generalized the test statistic for more than two samples. Whereas the expressions of the exact density and distribution functions of the generalized Baumgartner statistic are not yet found, the characteristic function of its limiting distribution has been obtained. Due to the development of computational power, the Fourier series approximation can be readily utilized to accurately and efficiently approximate its density function based on its Laplace transform. Numerical examples show that the Fourier series method provides an accurate approximation for statistical quantities of the generalized Baumgartner statistic.