Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Multivariate Gamma-Poisson Model and Parameter Estimation for Polytomous Data : Application to Defective Pixels of LCD

다가자료에 적합한 다변수 감마-포아송 모델과 파라미터 추정방법 : LCD 화소불량 응용

  • Ha, Jung-Hoon (School of Information and Computer Engineering, Hongik University)
  • 하정훈 (홍익대학교 정보컴퓨터공학부 산업공학)
  • Received : 2011.01.14
  • Accepted : 2011.03.14
  • Published : 2011.03.31
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Abstract

Poisson model and Gamma-Poisson model are popularly used to analyze statistical behavior from defective data. The methods are based on binary criteria, that is, good or failure. However, manufacturing industries prefer polytomous criteria for classifying manufactured products due to flexibility of marketing. In this paper, I introduce two multivariate Gamma-Poisson(MGP) models and estimation methods of the parameters in the models, which are able to handle polytomous data. The models and estimators are verified on defective pixels of LCD manufacturing. Experimental results show that both the independent MGP model and the multinomial MGP model have excellent performance in terms of mean absolute deviation and the choice of method depends on the purpose of use.

Keywords

References

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