Random Vectors and Matrices
This chapter builds the foundation for the statistical analysis of multivariate data. We first give the notation we use in this book, followed by a quick review of the rules for manipulating vectors and matrices. Then, we learn about random vectors and matrices, which are the fundamental building blocks for multivariate analysis. We then describe the properties of a variety of estimators of an unknown mean vector and unknown covariance matrix of a multivariate Gaussian distribution.
KeywordsCovariance Matrix Loss Function Random Vector Marginal Distribution Generalize Inverse
Unable to display preview. Download preview PDF.