응용통계연구 (The Korean Journal of Applied Statistics)

  • 제26권4호
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  • Pages.687-696
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  • 2013
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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벌점 스플라인 회귀모형에서의 이상치 탐지방법

An Outlier Detection Method in Penalized Spline Regression Models

  • 서한손 (건국대학교 응용통계학과) ;
  • 송지은 (건국대학교 응용통계학과) ;
  • 윤민 (부경대학교 통계학과)
  • Seo, Han Son (Department of Applied Statistics, Konkuk University) ;
  • Song, Ji Eun (Department of Applied Statistics, Konkuk University) ;
  • Yoon, Min (Department of Statistics, Pukyong National University)
  • 투고 : 2013.07.15
  • 심사 : 2013.08.21
  • 발행 : 2013.08.31
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초록

이상치가 존재하는 경우 모형 적합의 결과가 왜곡될 수 있기 때문에 이상치 탐색은 데이터분석에 있어서 매우 중요하다. 이상치 탐지 방법은 많은 학자들에 의해 연구되어 왔다. 본 논문에서는 Hadi와 Simonoff (1993)가 제안한 직접적 이상치 탐지 방법을 벌점 스플라인 회귀모형에 적용하여 이상치를 탐지하는 과정을 제안하며 모의실험과 실제 데이터에 적용을 통하여 스플라인 회귀모형, 강건 벌점 스플라인 회귀모형과 효율성을 비교한다.

The detection and the examination of outliers are important parts of data analysis because some outliers in the data may have a detrimental effect on statistical analysis. Outlier detection methods have been discussed by many authors. In this article, we propose to apply Hadi and Simonoff's (1993) method to penalized spline a regression model to detect multiple outliers. Simulated data sets and real data sets are used to illustrate and compare the proposed procedure to a penalized spline regression and a robust penalized spline regression.

키워드

참고문헌

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