Seneta | Non-negative Matrices and Markov Chains | Buch | 978-0-387-29765-1 | sack.de

Buch, Englisch, 281 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 458 g

Reihe: Springer Series in Statistics

Seneta

Non-negative Matrices and Markov Chains


Softcover Nachdruck of the original 2. Auflage 1981
ISBN: 978-0-387-29765-1
Verlag: Springer

Buch, Englisch, 281 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 458 g

Reihe: Springer Series in Statistics

ISBN: 978-0-387-29765-1
Verlag: Springer


Since its inception by Perron and Frobenius, the theory of non-negative matrices has developed enormously and is now being used and extended in applied fields of study as diverse as probability theory, numerical analysis, demography, mathematical economics, and dynamic programming, while its development is still proceeding rapidly as a branch of pure mathematics in its own right. While there are books which cover this or that aspect of the theory, it is nevertheless not uncommon for workers in one or another branch of its development to be unaware of what is known in other branches, even though there is often formal overlap. One of the purposes of this book is to relate several aspects of the theory, insofar as this is possible. The author hopes that the book will be useful to mathematicians; but in particular to the workers in applied fields, so the mathematics has been kept as simple as could be managed. The mathematical requisites for reading it are: some knowledge of real-variable theory, and matrix theory; and a little knowledge of complex-variable; the emphasis is on real-variable methods. (There is only one part of the book, the second part of 55.5, which is of rather specialist interest, and requires deeper knowledge.) Appendices provide brief expositions of those areas of mathematics needed which may be less g- erally known to the average reader.

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Weitere Infos & Material


Finite Non-Negative Matrices.- Fundamental Concepts and Results in the Theory of Non-negative Matrices.- Some Secondary Theory with Emphasis on Irreducible Matrices, and Applications.- Inhomogeneous Products of Non-negative Matrices.- Markov Chains and Finite Stochastic Matrices.- Countable Non-Negative Matrices.- Countable Stochastic Matrices.- Countable Non-negative Matrices.- Truncations of Infinite Stochastic Matrices.



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