Displaying similar documents to “On the pseudoinverse of a sum of symmetric matrices with applications to estimation”

Regularization for high-dimensional covariance matrix

Xiangzhao Cui, Chun Li, Jine Zhao, Li Zeng, Defei Zhang, Jianxin Pan (2016)

Special Matrices

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In many applications, high-dimensional problem may occur often for various reasons, for example, when the number of variables under consideration is much bigger than the sample size, i.e., p >> n. For highdimensional data, the underlying structures of certain covariance matrix estimates are usually blurred due to substantial random noises, which is an obstacle to draw statistical inferences. In this paper, we propose a method to identify the underlying covariance structure by regularizing...

Inverting covariance matrices

Czesław Stępniak (2006)

Discussiones Mathematicae Probability and Statistics

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Some useful tools in modelling linear experiments with general multi-way classification of the random effects and some convenient forms of the covariance matrix and its inverse are presented. Moreover, the Sherman-Morrison-Woodbury formula is applied for inverting the covariance matrix in such experiments.