응용통계연구 (The Korean Journal of Applied Statistics)

  • 제27권5호
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  • Pages.819-831
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  • 2014
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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치우친 다변량 t-분포 혼합모형에 대한 최우추정

An Alternating Approach of Maximum Likelihood Estimation for Mixture of Multivariate Skew t-Distribution

  • 김승구 (상지대학교 데이터정보학과)
  • Kim, Seung-Gu (Department of Data and Information, Sangji University)
  • 투고 : 2014.09.01
  • 심사 : 2014.09.22
  • 발행 : 2014.10.31
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⟨ 이전 논문 다음 논문 ⟩

초록

치우친 다변량 t-분포 혼합을 적합하기 위해 Exact-EM 알고리즘이 사용된다. 그러나 이 방법은 E-step에서 매우 긴 처리시간을 요하는 다변량 절단 t-분포의 적률을 계산해야 한다. 본 논문에서는 이러한 문제점을 완화하기 위해 SPU-EM이라 명명한 알고리즘을 제안하는데, 이것은 Meng과 van Dyk (1997)의 AECM 알고리즘의 원리를 이용하여 다차원 적률의 계산상의 어려움을 해결한다. 결과적으로 제안된 방법은 Exact-EM 알고리즘 보다 빠른 처리시간으로 보장한다. 이를 입증하기 위해 실험을 통해 제안된 방법의 유효성을 보인다.

The Exact-EM algorithm can conventionally fit a mixture of multivariate skew distribution. However, it suffers from highly expensive computational costs to calculate the moments of multivariate truncated t-distribution in E-step. This paper proposes a new SPU-EM method that adopts the AECM algorithm principle proposed by Meng and van Dyk (1997)'s to circumvent the multi-dimensionality of the moments. This method offers a shorter execution time than a conventional Exact-EM algorithm. Some experments are provided to show its effectiveness.

키워드

참고문헌

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피인용 문헌

  1. An approximate fitting for mixture of multivariate skew normal distribution via EM algorithm vol.29, pp.3, 2016, https://doi.org/10.5351/KJAS.2016.29.3.513