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Shift-Power Transformation

이동-멱변환에 관한 연구

  • Cho Ki-Jong (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Jeong Seok-Oh (Department of Statistics, Hankuk University of Foreign Studies) ;
  • Shin Key-Il (Department of Statistics, Hankuk University of Foreign Studies)
  • 조기종 (고려대학교 환경생태학부) ;
  • 정석오 (한국외국어대학교 정보통계학과) ;
  • 신기일 (한국외국어대학교 정보통계학과)
  • Published : 2006.07.01

Abstract

Generally speaking, power transformations such as Box-Cox transformation(1964) is applied for variance stabilization and symmetry. But, when the distribution of the original data has a large mean with a small variance or the coefficient of variation is very small, they don't work at all. This paper propose a simple method to introduce a shift parameter before applying power transformations and showed the numerical evidence by Monte Carlo simulation and a real data analysis.

일반적으로 Box-Cox변환과 같은 류의 멱변환은 분산 안정화 혹은 분포의 대칭성 향상 등을 목적으로 사용된다. 그러나 원 자료의 평균의 크기가 크면서 분산이 상대 적으로 작은 경우, 즉 변동계수가 작은 경우에는 제대로 작동하지 않는 것이 알려져 있다. 본 논문에서는 이러한 문제점을 해결하기 위한 이동-멱변환을 제안하고 모의실험과 실제 자료 분석을 통하여 그 효과를 확인하였다.

Keywords

References

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