Browsing by Author "Wang, R. S."

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Generalized inferences on the common mean vector of several multivariate normal populations
(2007-07-01)
Lin, S. H.
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Lee, Jack C.
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Wang, R. S.
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統計學研究所
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資訊管理與財務金融系註：原資管所+財金所
The hypothesis testing and confidence region are considered for the common mean vector of several multivariate normal populations when the covariance matrices are unknown and possibly unequal. A generalized confidence region is derived using the concepts of generalized method based on the generalized p-value. The generalized confidence region is illustrated with two numerical examples. The merits of the proposed method are numerically compared with those of existing methods with respect to their expected area or expected d-dimensional volumes and coverage probabilities under different scenarios. (c) 2006 Elsevier B.V. All rights reserved.
Inferences on a linear combination of K multivariate normal mean vectors
(2009)
Lin, S. H.
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Wang, R. S.
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統計學研究所
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Institute of Statistics
In this paper, the hypothesis testing and confidence region construction for a linear combination of mean vectors for K independent multivariate normal populations are considered. A new generalized pivotal quantity and a new generalized test variable are derived based on the concepts of generalized p-values and generalized confidence regions. When only two populations are considered, our results are equivalent to those proposed by Gamage et al. [Generalized p-values and confidence regions for the multivariate Behrens-Fisher problem and MANOVA, J. Multivariate Aanal. 88 (2004), pp. 117-189] in the bivariate case, which is also known as the bivariate Behrens-Fisher problem. However, in some higher dimension cases, these two results are quite different. The generalized confidence region is illustrated with two numerical examples and the merits of the proposed method are numerically compared with those of the existing methods with respect to their expected areas, coverage probabilities under different scenarios.