"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)

• ​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.

"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)

• ​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.

"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)

• ​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.