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
Summary
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
Analysis
statistiek
statistics
statistische analyse
statistical analysis
toegepaste statistiek
applied statistics
Statistics (General)
Statistiek (algemeen)
Bibliography
Includes bibliographical references (pages 105-122) and index
