Probabilistic Conditional Independence Structures provides the
mathematical description of probabilistic conditional independence
structures; the author uses non-graphical methods of their
description, and takes an algebraic approach.
The monograph presents the methods of structural imsets and
supermodular functions, and deals with independence implication and
equivalence of structural imsets. Motivation, mathematical
foundations and areas of application are included, and a rough
overview of graphical methods is also given. In particular, the
author has been careful to use suitable terminology, and presents
the work so that it will be understood by both statisticians, and
by researchers in artificial intelligence. The necessary elementary
mathematical notions are recalled in an appendix.
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