The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Optimal Thresholds from Non-Normal Mixture

비정규 혼합분포에서의 최적분류점

  • Hong, Chong-Sun (Department of Statistics, Sungkyunkwan University) ;
  • Joo, Jae-Seon (Statistics and Panel Center, Korean Women's Development Institute)
  • 홍종선 (성균관대학교 통계학과) ;
  • 주재선 (한국여성정책연구원 통계패널센터)
  • Received : 20100600
  • Accepted : 20100800
  • Published : 2010.10.31
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Abstract

From a mixture distribution of the score random variable for credit evaluation, there are many methods of estimating optimal thresholds. Most the research news is based on the assumption of normal distributions. In this paper, we extend non-normal distributions such as Weibull, Logistic and Gamma distributions to estimate an optimal threshold by using a hypotheses test method and other methods maximizing the total accuracy and the true rate. The type I and II errors are obtained and compared with their sums. Finally we discuss their e ciency and derive conclusions for non-normal distributions.

신용평가연구에서 확률변수 스코어와 정상과 부도상태의 모수공간으로 정의된 혼합분포에서 확률밀도함수의 관계식으로 최적분류점을 추정하고 이에 대응하는 오류합의 크기를 비교하는 연구가 정규분포의 가정하에 이루어져있는데 본 연구에서는 비정규분포인 와이블, 로지스틱 그리고 감마분포로 확장하여 가설검정을 이용하는 방법과 전체정확도와 진실율을 최대화하는 방법에 의한 최적분류점을 각각 구하고 최적분류점에 대응하는 제I종과 제II종 오류합의 크기를 비교하여 효율성을 비교 토론한다.

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References

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