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Cohen, Joel E.; Kempermann, J.H.B.; Zbaganu, G. - Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population - 9780817640828 - V9780817640828
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Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population

€ 124.48
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Description for Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population Hardback. Focuses on generalizing the notion of variation in a set of numbers to the notion of variation in a set of probability distributions. The work collects known ways of comparing stochastic matrices, and then generalizes these, and establishes the relations of implication or equivalence among some. Num Pages: 166 pages, biography. BIC Classification: PBT; PBWL. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 11. Weight in Grams: 415.
The focus of this monograph 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 ... Read more

Product Details

Format
Hardback
Publication date
1998
Publisher
Birkhauser Boston Inc United States
Number of pages
166
Condition
New
Number of Pages
158
Place of Publication
Secaucus, United States
ISBN
9780817640828
SKU
V9780817640828
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

Reviews for Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population
"This book gives a mathematical treatment of a variety of methods for quantifying divergence or similarity between sets of proability distributions on a common space. Classical metrics, such as total variation and Kullback
Liebler divergence, are generalized. Such problems arise in statistics, economics and information theory. The book gives Brief but useful treatments of these and other applications with abundant references... ... Read more

Goodreads reviews for Comparisons of Stochastic Matrices with Applications in Information Theory, Statistics, Economics and Population


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