This book depicts a wide range of situations in which there exist finite
form representations for the Meijer G and the Fox H functions.
Accordingly, it will be of interest to researchers and graduate students
who, when implementing likelihood ratio tests in multivariate analysis,
would like to know if there exists an explicit manageable finite form
for the distribution of the test statistics. In these cases, both the
exact quantiles and the exact p-values of the likelihood ratio tests can
be computed quickly and efficiently.
The test statistics in question range from common ones, such as those
used to test e.g. the equality of means or the independence of blocks of
variables in real or complex normally distributed random vectors; to far
more elaborate tests on the structure of covariance matrices and
equality of mean vectors. The book also provides computational modules
in Mathematica(R), MAXIMA and R, which allow readers to
easily implement, plot and compute the distributions of any of these
statistics, or any other statistics that fit into the general paradigm
described here.