A classical mathematical treatment of the techniques, distributions, and inferences based on the multivariate normal distribution. Introduces noncentral distribution theory, decision theoretic estimation of the parameters of a multivariate normal distribution, and the uses of spherical and elliptical distributions in multivariate analysis. Discusses recent advances in multivariate analysis, including decision theory and robustness. Also includes tables of percentage points of many of the standard likelihood statistics used in multivariate statistical procedures.
The Multivariate Normal and Related Distributions.
Jacobians, Exterior Products, Kronecker Products, and Related Topics.
Samples from a Multivariate Normal Distribution, and the Wishart and Multivariate Beta Distributions.
Some Results Concerning Decision-Theoretic Estimation of the Parameters of a Multivariate Normal Distribution.
Invariant Tests and Some Applications.
Zonal Polynomials and Some Functions of Matrix Argument.
Some Standard Tests on Covariance Matrices and Mean Vectors.
Principal Components and Related Topics.
The Multivariate Linear Model.
Testing Independence Between Sets of Variables and Canonical Correlation Analysis.