The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Firework Plot as a Graphical Exploratory Data Analysis Tool to Evaluate the Impact of Outliers in a Mixture Experiment

혼합물 실험에서 특이값의 영향을 평가하기 위한 그래픽 탐색적 자료분석 도구로서의 불꽃그림

  • Jang, Dae-Heung (Department of Statistics, Pukyong National University) ;
  • Ahn, SoJin (Department of Statistics, Pukyong National University) ;
  • Kim, Youngil (School of Business and Economics, ChungAng University)
  • Received : 2014.06.03
  • Accepted : 2014.07.15
  • Published : 2014.08.31
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Abstract

It is common to check the validity of an assumed model with the heavy use of diagnostics tools when conducting data analysis with regression techniques; however, outliers and influential data points often distort the regression output in undesired manner. Jang and Anderson-Cook (2013) proposed a graphical method called a firework plot for exploratory analysis that could visualize the trace of the impact of possible outlying and/or influential data points on individual regression coefficients and the overall residual sum of squares(SSE) measure. They developed 3-D plot as well as pair-wise plot for the appropriate measures of interest. In this paper, the approach was extended further to tell the strength of their approach; in addition, a more meaningful interpretation was possible by adding a measure not mentioned in their paper. This approach was applied to the mixture experiment because we felt that a detailed analysis of statistical measure sensitivity is required in a small experiment.

회귀모형을 이용하여 자료를 분석하는 경우 이상점이나 영향점과 같은 특이값들의 유무를 검정하는 회귀진단기법은 모형의 적합성을 체크하기 위한 필수적인 도구로 잡은 지 오래이다. 이러한 점들이 존재 하는 경우 회귀분석의 결과가 왜곡되어 해석이 된다. Jang과 Anderson-Cook (2013)은 불꽃그림이란 이름을 붙인 그림도구를 발표하였는데 관측값에 부여된 가중치를 1에서 0으로 변화함에 따라 이상점이나 영향점이 회귀계수 및 잔차제곱합(SSE)에 어떠한 영향을 미치는지 3차원 그림에 추적곡선을 그려 보았을 뿐 아니라 쌍으로 대비시켜 봄으로써 분석의 시각적인 효과를 증대시켰다. 본 연구에서는 더 나아가 이러한 시도가 기존 방법과 어떤 차이점이 있는지 2013년에는 반영치 않은 통계량을 포함해서 더 많은 해석이 가능한지 혼합물 실험 계획을 통해 다양한 통계량의 민감도 분석을 실행하였다. 왜냐하면 작은 혼합물실험인 자료인 경우 더욱 세밀한 통계량에 대한 민감도 분석이 필요하기 때문이다.

Keywords

References

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