Browsing by Author "Chen, CR"

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An empirical Bayes process monitoring technique for polytomous data
(2005-02-01)
Shiau, JJH
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Chen, CR
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Feltz, CJ
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統計學研究所
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Institute of Statistics
When a product item is tested, usually one has more information than just pass or fail. Often there are categories of failure modes. The purpose of this paper is to develop a method to monitor the fractions of the tested items falling into different categories of pass/fail modes. Using the multinomial model with Dirichlet prior, we describe the theory underlying an empirical Bayes approach to monitoring polytomous data generated in manufacturing processes. A pseudo maximum likelihood estimator (PMLE) and the method-of-moments estimator (MME) of the hyperparameters of the prior distribution are considered and compared by a simulation study. It is found that the PMLE performs slightly better than the MME. A monitoring scheme based on the marginal distributions of the observed pass/fail fractions is proposed. The average run length behavior of the proposed monitoring scheme is investigated. Finally, an example to illustrate the use of the technique is given. Copyright (C) 2004 John Wiley Sons, Ltd.
Fixed-sample optimal non-orthogonal estimating functions in the presence of nuisance parameters
(2004-12-01)
Chen, CR
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Wang, LC
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統計學研究所
;
Institute of Statistics
In the paper, an important necessary and sufficient condition for a commonly used non-orthogonal estimating function to be fixed-sample optimal is proposed. The class of all fixed-sample optimal non-orthogonal estimating functions is characterized under the proposed condition. A simple counterexample without any fixed-sample optimal non-orthogonal estimating function is constructed to show that the proposed condition does not necessarily hold. The usefulness and applicability of the proposed method are illustrated by two classical examples with many nuisance parameters.
Generalized Tchakaloff's Theorem for semi-spectral measures
(2003)
Wang, LC
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Chen, CR
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統計學研究所
;
Institute of Statistics
We proved the existence of exact quadrature formulae with semipositive definite coefficient matrices for polynomials of prescribed degree in n variables and with respect to a semi-spectral measure. Our proof could be viewed as a direct translation (generalization) of Putinar's result on the existence of quadrature formulae for a positive measure without compact support.
Likelihood inference under the general response transformation model with heteroscedastic errors
(2003-06-01)
Chen, CR
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Wang, LC
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統計學研究所
;
Institute of Statistics
In this paper, we propose the likelihood inference under the general response transformation model with heteroscedastic errors when the range of the response transformation is possibly different from the whole real line. Three commonly used families of response transformations are reviewed to illustrate the importance and applicability of the proposed model.
Non-saturated binary image learning and recognition using the ratio-memory cellular neural network (RMCNN)
(2002)
Wu, CY
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Hsieh, CY
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Chen, SH
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Hsieh, BCY
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Chen, CR
dIn this paper, cellular neural network with ratio memory is proposed for non-saturated binary image processing. The Hebbien learning rule will be used to learn the weight of template A. The RMCNN system can recognize one non-saturated binary image and remove most of the noise added to the image pattern during the recognition period. The behavior of recognizing non-saturated binary images will be proved by mathematics equations. The effect will be simulated by Matlab software. With the method for non-saturated binary image processing, this theory can be easily implemented in hardware.