Information Criteria and Statistical Modeling (Springer Series in Statistics) [Repost]

Information Criteria and Statistical Modeling (Springer Series in Statistics) by Genshiro Kitagawa


English | Oct. 12, 2007 | ISBN: 0387718869 | 276 Pages | PDF | 4.03 MB

Statistical modeling is a critical tool in scientific research. This book provides comprehensive explanations of the concepts and philosophy of statistical modeling, together with a wide range of practical and numerical examples. The authors expect this work to be of great value not just to statisticians but also to researchers and practitioners in various fields of research such as information science, computer science, engineering, bioinformatics, economics, marketing and environmental science. It’s a crucial area of study, as statistical models are used to understand phenomena with uncertainty and to determine the structure of complex systems. They’re also used to control such systems, as well as to make reliable predictions in various natural and social science fields.

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Mathematical Modeling of Disperse Two-Phase Flows (repost)

Christophe Morel, "Mathematical Modeling of Disperse Two-Phase Flows"


2015 | ISBN-10: 3319201034 | 350 pages | PDF | 4 MB

This book develops the theoretical foundations of disperse two-phase flows, which are characterized by the existence of bubbles, droplets or solid particles finely dispersed in a carrier fluid, which can be a liquid or a gas. Chapters clarify many difficult subjects, including modeling of the interfacial area concentration. Basic knowledge of the subjects treated in this book is essential to practitioners of Computational Fluid Dynamics for two-phase flows in a variety of industrial and environmental settings.




The author provides a complete derivation of the basic equations, followed by more advanced subjects like turbulence equations for the two phases (continuous and disperse) and multi-size particulate flow modeling. As well as theoretical material, readers will discover chapters concerned with closure relations and numerical issues. Many physical models are presented, covering key subjects including heat and mass transfers between phases, interfacial forces and fluid particles coalescence and breakup, amongst others.




This book is highly suitable for students in the subject area, but may also be a useful reference text for more advanced scientists and engineers.

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A Biologist"s Guide to Mathematical Modeling in Ecology and Evolution (repost)

Sarah P. Otto, Troy Day, "A Biologist"s Guide to Mathematical Modeling in Ecology and Evolution"


2007 | ISBN: 0691123446 | EPUB | 744 pages | 13 MB

Thirty years ago, biologists could get by with a rudimentary grasp of mathematics and modeling. Not so today. In seeking to answer fundamental questions about how biological systems function and change over time, the modern biologist is as likely to rely on sophisticated mathematical and computer-based models as traditional fieldwork. In this book, Sarah Otto and Troy Day provide biology students with the tools necessary to both interpret models and to build their own.




The book starts at an elementary level of mathematical modeling, assuming that the reader has had high school mathematics and first-year calculus. Otto and Day then gradually build in depth and complexity, from classic models in ecology and evolution to more intricate class-structured and probabilistic models. The authors provide primers with instructive exercises to introduce readers to the more advanced subjects of linear algebra and probability theory. Through examples, they describe how models have been used to understand such topics as the spread of HIV, chaos, the age structure of a country, speciation, and extinction.




Ecologists and evolutionary biologists today need enough mathematical training to be able to assess the power and limits of biological models and to develop theories and models themselves. This innovative book will be an indispensable guide to the world of mathematical models for the next generation of biologists.


• A how-to guide for developing new mathematical models in biology


• Provides step-by-step recipes for constructing and analyzing models


• Interesting biological applications


• Explores classical models in ecology and evolution


• Questions at the end of every chapter


• Primers cover important mathematical topics


• Exercises with answers


• Appendixes summarize useful rules


• Labs and advanced material available

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