소표본 자기상관 자료의 분산 추정을 위한 최적 부분군 크기에 대한 연구

A Study on Optimal Subgroup Size in Estimating Variance of Small Autocorrelated Samples

  • 이종선 (인하대학교 자연과학대학 통계학과) ;
  • 이재준 (인하대학교 자연과학대학 통계학과) ;
  • 배순희 (인하대학교 자연과학대학 통계학과)
  • 발행 : 2007.06.30

초록

In statistical process control, it is assumed that the process data are independent. However, most of chemical processes such as semi-conduct processes do not satisfy the assumption because of presence of autocorrelation between process data. It causes abnormal out of control signal in the process control and misleading estimation in process capability. In this study, we adopted Shore's method to solve the problem and propose an optimal subgroup size to estimate the variance correctly for AR(1) processes. Especially, we focus on finding an actual subgroup size for small samples based on simulation study.

키워드

참고문헌

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