The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Modeling of The Learning-Curve Effects on Count Responses

개수형 자료에 대한 학습곡선효과의 모형화

  • Choi, Minji (Department of Statistics, Sungshin Women's University) ;
  • Park, Man Sik (Institute of Statistics, Sungshin Women's University)
  • 최민지 (성신여자대학교 통계학과) ;
  • 박만식 (성신여자대학교 통계연구소)
  • Received : 2014.03.03
  • Accepted : 2014.06.09
  • Published : 2014.06.30
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Abstract

As a certain job is repeatedly done by a worker, the outcome comparative to the effort to complete the job gets more remarkable. The outcome may be the time required and fraction defective. This phenomenon is referred to a learning-curve effect. We focus on the parametric modeling of the learning-curve effects on count data using a logistic cumulative distribution function and some probability mass functions such as a Poisson and negative binomial. We conduct various simulation scenarios to clarify the characteristics of the proposed model. We also consider a real application to compare the two discrete-type distribution functions.

일반적으로 특정한 작업에 익숙해진다는 것은 그 작업에 투입되는 노력에 비해 산출되는 성과가 보다 뚜렷해진다는 것을 의미한다. 동일한 양이나 정도의 노력을 들여 특정한 작업을 반복적으로 수행하게 되면 초기 시점보다 원하는 성과를 기대 이상으로 얻게 된다는 것을 의미한다. 이를 학습곡선효과(learning-curve effects)'라고 한다. 본 연구에서는 특정한 작업을 반복시행한 결과가 개수형인 형태로 측정되는 변수에 대해 (역)S자 형태를 가지는 통계적 모형을 적용하고자 한다. 다양한 모의실험 하에서의 모형의 성능을 평가하고 특정질환으로 인한 사망자 자료에 적합하였다.

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References

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