Geometric Modeling in Probability and Statistics
Author:   Ovidiu Calin ,  Constantin Udrişte
Publisher:   Springer International Publishing AG
Edition:   2014 ed.
ISBN:  

9783319077789


Pages:   375
Publication Date:   01 August 2014
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Geometric Modeling in Probability and Statistics


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Full Product Details

Author:   Ovidiu Calin ,  Constantin Udrişte
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2014 ed.
Dimensions:   Width: 15.50cm , Height: 2.20cm , Length: 23.50cm
Weight:   7.939kg
ISBN:  

9783319077789


ISBN 10:   3319077783
Pages:   375
Publication Date:   01 August 2014
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

​Part I: The Geometry of Statistical Models.- Statistical Models.- Explicit Examples.- Entropy on Statistical Models.- Kullback–Leibler Relative Entropy.- Informational Energy.- Maximum Entropy Distributions.- Part II: Statistical Manifolds.- An Introduction to Manifolds.- Dualistic Structure.- Dual Volume Elements.- Dual Laplacians.- Contrast Functions Geometry.- Contrast Functions on Statistical Models.- Statistical Submanifolds.- Appendix A: Information Geometry Calculator.

Reviews

The book under review presents a concise introduction to the mathematical foundation of information geometry and contains an overview of other related areas of interest and applications. ... This book is well-written and will be a useful and important addition to the resources of practitioners and many others engaged in probability theory, mathematical statistics and related subjects. I recommend it highly as a textbook for a course directed at graduate or advanced undergraduate students. (Prasanna Sahoo, zbMATH, Vol. 1325.60001, 2016)


The book under review presents a concise introduction to the mathematical foundation of information geometry and contains an overview of other related areas of interest and applications. ... This book is well-written and will be a useful and important addition to the resources of practitioners and many others engaged in probability theory, mathematical statistics and related subjects. I recommend it highly as a textbook for a course directed at graduate or advanced undergraduate students. (Prasanna Sahoo, zbMATH, Vol. 1325.60001, 2016)


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