When portfolio selection is implemented by using the past sample values, parameter uncertainty may lead to suboptimal portfolios. Previous studies of portfolio selection demonstrate that classical approach based on the simple mean estimator is less reliable cause of inherent estimation error. In this paper, we investigate a shrinkage estimator based on Stein’s idea in measuring the expected returns. We apply the research of Jorion (1985) to Taiwan Stock market, present the effects of estimation error on the portfolio selection and demonstrate that the shrinkage estimator is robust and dominates the classical estimator on the MSE criterion. In addition, we also examine the effect of different shrinkage target on the performance of the Bayes-Stein estimator and find that this estimator still has lower risk than the classical sample mean.

We address the problem of multi-view multi-target tracking using multiple stationary cameras in the application of hockey tracking and test the approach with data from two cameras. The system is based on the previous work by Okuma et al. [50]. We replace AdaBoost detection with blob detection in both image coordinate systems after background subtraction. The sets of blob-detection results are then mapped to the rink coordinate system using a homography transformation. These observations are further merged into the final detection result which will be incorporated into the particle filter. In addition, we extend the particle filter to use multiple observation models, each corresponding to a view. An observation likelihood and a reference color model are also maintained for each player in each view and are updated only when the player is not occluded in that view. As a result of the expanded coverage range and multiple perspectives in the multi-view tracking, even when the target is occluded in one view, it still can be tracked as long as it is visible from another view. The multi-view tracking data are further processed by trajectory smoothing using the Maximum a posteriori smoother. Finally, automatic camera selection is performed using the Hidden Markov Model to create personalized video programs.

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Photocopy of typescript / v, 177 leaves, 6 leaves of plates : ill. (part col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.) Dept. of Agronomy, University of Adelaide, 1981

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