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Multivariate Gamma-Poisson Model and Parameter Estimation for Polytomous Data : Application to Defective Pixels of LCD  

Ha, Jung-Hoon (School of Information and Computer Engineering, Hongik University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.34, no.1, 2011 , pp. 42-51 More about this Journal
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
Yield Model; Parameter Estimation; Liquid Crystal Display; Polytomous Data; Defective Pixels;
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Times Cited By KSCI : 3  (Citation Analysis)
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