• 제목/요약/키워드: skew-normal

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EM 알고리즘에 의한 다변량 치우친 정규분포 혼합모형의 근사적 적합 (An approximate fitting for mixture of multivariate skew normal distribution via EM algorithm)

  • 김승구
    • 응용통계연구
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    • 제29권3호
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    • pp.513-523
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    • 2016
  • 다중 치우침 모수벡터를 가진 다변량 치우친 정규분포 (MSNMix)를 EM 알고리즘으로 적합하려면 E-step에서 다변량 절단 정규분포의 적률과 확률을 계산해야 하는데 이것은 매우 큰 계산 시간을 요구한다. 그래서 비대칭 자료를 적합하는데 흔히 단순 치우침 모수를 가진 모형을 적용한다. 이 모형은 단변량 처리방식으로 적합하는 것이 가능하기 때문에 처리속도가 매우 빠르다. 그러나 단순 치우침 모수를 적용하는 것은 응용에서 비현실적인 경우가 많다. 본 논문에서는 다중 치우침 모수를 가지는 MSNMix의 근사적 추정법을 제안하는데, 이 방법은 단변량 처리방식이 적용되므로 향상된 처리속도를 보장한다. 그리고 제안된 방법의 실효성을 보이기 위해 몇 가지 실험 결과를 제공한다.

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

  • 유혜경;나종화
    • Journal of the Korean Data and Information Science Society
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    • 제25권6호
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    • pp.1171-1180
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    • 2014
  • 본 논문에서는 금융분야에서 사용되고 있는 포트폴리오 위험측도인 VaR (value at risk)와 ES (expected shortfall)의 측정 방법으로 안장점근사의 적용 방법을 제시하였다. 본 연구의 특징은 금융자료에 대하여 정규분포를 가정하지 않고, 치우침을 가정한 왜정규분포를 가정하여 왜정규분포를 따르는 위험요인으로 구성된 선형 포트폴리오 위험측도에 대해 안장점근사를 실시하였다. 또한 모의실험을 통해 위험측도의 안장점근사의 정도가 매우 우수함을 확인하였다.

SUBPERMUTABLE SUBGROUPS OF SKEW LINEAR GROUPS AND UNIT GROUPS OF REAL GROUP ALGEBRAS

  • Le, Qui Danh;Nguyen, Trung Nghia;Nguyen, Kim Ngoc
    • 대한수학회보
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    • 제58권1호
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    • pp.225-234
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    • 2021
  • Let D be a division ring and n > 1 be an integer. In this paper, it is shown that if D ≠ ��3, then every subpermutable subgroup of the general skew linear group GLn(D) is normal. By applying this result, we show that every subpermutable subgroup of the unit group (ℝG)∗ of the real group algebras RG of finite groups G is normal in (ℝG)∗.

Monitoring the asymmetry parameter of a skew-normal distribution

  • Hyun Jun Kim;Jaeheon Lee
    • Communications for Statistical Applications and Methods
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    • 제31권1호
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    • pp.129-142
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    • 2024
  • In various industries, especially manufacturing and chemical industries, it is often observed that the distribution of a specific process, initially having followed a normal distribution, becomes skewed as a result of unexpected causes. That is, a process deviates from a normal distribution and becomes a skewed distribution. The skew-normal (SN) distribution is one of the most employed models to characterize such processes. The shape of this distribution is determined by the asymmetry parameter. When this parameter is set to zero, the distribution is equal to the normal distribution. Moreover, when there is a shift in the asymmetry parameter, the mean and variance of a SN distribution shift accordingly. In this paper, we propose procedures for monitoring the asymmetry parameter, based on the statistic derived from the noncentral t-distribution. After applying the statistic to Shewhart and the exponentially weighted moving average (EWMA) charts, we evaluate the performance of the proposed procedures and compare it with previously studied procedures based on other skewness statistics.

On Some Skew Constants in Banach Spaces

  • Yuankang Fu;Zhijian Yang;Yongjin Li;Qi Liu
    • Kyungpook Mathematical Journal
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    • 제63권2호
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    • pp.199-223
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    • 2023
  • We introduce the constants E[t, X], CNJ[X] and J[t, X] to describe the asymmetry of the norm. They can be seen as the skew version of the Gao's parameter, von Neumann-Jordan constant and Milman's moduli, respectively. We establish basic properties of these constants, relating them other well known constants, and use these properties to calculate the constants for specific spaces. We then use these constants to study Hilbert spaces, uniformly non-square spaces and their normal structures. With the Banach-Mazur distance, we use them to study isomorphic Banach spaces.

Aerostatic load on the deck of cable-stayed bridge in erection stage under skew wind

  • Li, Shaopeng;Li, Mingshui;Zeng, Jiadong;Liao, Haili
    • Wind and Structures
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    • 제22권1호
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    • pp.43-63
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    • 2016
  • In conventional buffeting theory, it is assumed that the aerostatic coefficients along a bridge deck follow the strip assumption. The validity of this assumption is suspect for a cable-stayed bridge in the construction stages, due to the effect of significant aerodynamic interference from the pylon. This situation may be aggravated in skew winds. Therefore, the most adverse buffeting usually occurs when the wind is not normal to bridge axis, which indicates the invalidity of the traditional "cosine rule". In order to refine the studies of static wind load on the deck of cable-stayed bridge under skew wind during its most adverse construction stage, a full bridge 'aero-stiff' model technique was used to identify the aerostatic loads on each deck segment, in smooth oncoming flow, with various yaw angles. The results show that the shelter effect of the pylon may not be ignored, and can amplify the aerostatic loading on the bridge deck under skew winds ($10^{\circ}-30^{\circ}$) with certain wind attack angles, and consequently results in the "cosine rule" becoming invalid for the buffeting estimation of cable-stayed bridge during erection for these wind directions.

보험 청구액에 대한 새로운 복합분포 (New composite distributions for insurance claim sizes)

  • 정대현;이지연
    • 응용통계연구
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    • 제30권3호
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    • pp.363-376
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    • 2017
  • 보험 시장은 포화되고 그 성장 동력은 소진되어 보험 산업이 저성장에 머물러 있는 가운데 보험사들은 치열한 경쟁 환경에 놓여있다. 이러한 상황에서 보험 상품에 대한 보험수리적 계산의 기초가 되는 보험 청구액의 흐름을 잘 설명할 수 있는 확률분포를 찾아내는 것은 중요한 쟁점이 될 것이다. 보험 청구액의 분포는 일반적으로 두꺼운 꼬리를 가지면서 왼쪽으로 치우친 로그정규분포나 파레토 분포로 잘 설명된다고 알려져 있으나 최근에는 기운 정규분포나 기운 t 분포가 보험 청구액 분포로 적절한 것으로 고찰되었다. Cooray와 Ananda (2005)는 로그정규분포와 파레토 분포의 장점을 모두 가진 로그정규-파레토 복합분포를 제시하고 단일분포보다 더 높은 적합도를 가짐을 확인하였다. 본 논문에서는 기운 정규분포와 기운 t 분포를 머리 부분으로 결합한 새로운 복합분포를 소개하고 덴마크의 화재보험 청구액 데이터와 미국의 배상 지불금 데이터에 적용하여 기존의 다른 복합분포들을 포함하여 여러 단일분포들과 그 성능을 비교한다.

ON BAYESIAN ESTIMATION AND PROPERTIES OF THE MARGINAL DISTRIBUTION OF A TRUNCATED BIVARIATE t-DISTRIBUTION

  • KIM HEA-JUNG;KIM Ju SUNG
    • Journal of the Korean Statistical Society
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    • 제34권3호
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    • pp.245-261
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    • 2005
  • The marginal distribution of X is considered when (X, Y) has a truncated bivariate t-distribution. This paper mainly focuses on the marginal nontruncated distribution of X where Y is truncated below at its mean and its observations are not available. Several properties and applications of this distribution, including relationship with Azzalini's skew-normal distribution, are obtained. To circumvent inferential problem arises from adopting the frequentist's approach, a Bayesian method utilizing a data augmentation method is suggested. Illustrative examples demonstrate the performance of the method.

New Calibration Methods with Asymmetric Data

  • Kim, Sung-Su
    • 응용통계연구
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    • 제23권4호
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    • pp.759-765
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    • 2010
  • In this paper, two new inverse regression methods are introduced. One is a distance based method, and the other is a likelihood based method. While a model is fitted by minimizing the sum of squared prediction errors of y's and x's in the classical and inverse methods, respectively. In the new distance based method, we simultaneously minimize the sum of both squared prediction errors. In the likelihood based method, we propose an inverse regression with Arnold-Beaver Skew Normal(ABSN) error distribution. Using the cross validation method with an asymmetric real data set, two new and two existing methods are studied based on the relative prediction bias(RBP) criteria.

Modeling Circular Data with Uniformly Dispersed Noise

  • Yu, Hye-Kyung;Jun, Kyoung-Ho;Na, Jong-Hwa
    • 응용통계연구
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    • 제25권4호
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    • pp.651-659
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    • 2012
  • In this paper we developed a statistical model for circular data with noises. In this case, model fitting by single circular model has a lack-of-fit problem. To overcome this problem, we consider some mixture models that include circular uniform distribution and apply an EM algorithm to estimate the parameters. Both von Mises and Wrapped skew normal distributions are considered in this paper. Simulation studies are executed to assess the suggested EM algorithms. Finally, we applied the suggested method to fit 2008 EHFRS(Epidemic Hemorrhagic Fever with Renal Syndrome) data provided by the KCDC(Korea Centers for Disease Control and Prevention).