This book describes recently developed methods for accurate and efficient computation of the required probability values for problems with two or more variables. It includes examples that illustrate the probability computations for a variety of applications.

Multivariate normal and t probabilities are needed for statistical inference in many applications. Modern statistical computation packages provide functions for the computation of these probabilities for problems with one or two variables. This book describes recently developed methods for accurate and efficient computation of the required probability values for problems with two or more variables. The book discusses methods for specialized problems as well as methods for general problems. The book includes examples that illustrate the probability computations for a variety of applications.

Includes supplementary material: sn.pub/extras

Inhalt
Introduction.- Special Cases.- Methods That Approximate the Problem.- Methods That Approximate the Integral.- Further Topics: Linear Inequality Constraints.- Singular Distributions.- Singular Distributions.- Numerical Tests.- Software Implementations.- Applications.- Description of the R Functions.- Description of the MATLAB Functions.