Comparisons of stochastic matrices, with applications in information theory, statistics, economics, and population sciences
By: Joel E. Cohen, J.H.B. Kemperman, Gheorghe Zbăganu.
Contributors: Kemperman, Johannes Henricus Bernardus.; Zbăganu, Gh. 1951-
Publisher: Birkhäuser; Birkhäuser
Published: 1998
Place of publication: Boston
Language: eng
Number of pages: 158
Subjects: Stochastic matrices.; Kernel functions.
Description: The focus of this work is on generalizing the notion of variation in a set of numbers to variation in a set of probability distributions. The authors collect some known ways of comparing stochastic matrices in the context of information theory, statistics, economics, and population sciences. They then generalize these comparisons, introduce new comparisons, and establish the relations of implication or equivalence among sixteen of these comparisons.

Some of the possible implications among these comparisons remain open questions. The results in this book establish a new field of investigation for both mathematicians and scientific users interested in the variations among multiple probability distributions.

A great strength of this text is the resulting connections among ideas from diverse fields - mathematics, statistics, economics, and population biology. In providing this array of new tools and concepts, the work will appeal to the practitioner. At the same time, it will serve as an excellent resource for self-study or for a graduate seminar course, as well as a stimulus to further research.
Notes: Includes bibliographical references (p. [149]-154) and indexes.