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Classical and Spatial Stochastic Processes
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Classical and Spatial Stochastic Processes : With Applications to Biology

Third Edition 2024

Book Details

Format Hardback or Cased Book
ISBN-10 303177759X
ISBN-13 9783031777592
Edition Third Edition 2024
Publisher Birkhauser Verlag AG
Imprint Birkhauser Verlag AG
Country of Manufacture GB
Country of Publication GB
Publication Date Dec 27th, 2024
Print length 286 Pages
Ksh 8,300.00
Werezi Extended Catalogue 0 in stock

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These topics elegantly apply various classical stochastic models and are motivated throughout with many worked out examples.This third edition of Classical and Spatial Stochastic Processes is suitable as a textbook for a first course in stochastic processes at the upper-undergraduate or graduate level.

This textbook provides an accessible approach to concepts and applications of stochastic processes ideal for a wide range of readers. This revised third edition features an intuitive reorganization with concrete topics introduced early on which are then used to demonstrate more abstract concepts in later chapters. The author has kept chapters short and independent from each other, with several of the longer chapters from previous editions now divided into smaller, more manageable parts. These changes build upon previous editions to allow readers even greater flexibility.

The applications that are covered feature active areas of research within biological modeling, such as cancerous mutations, influenza evolution, drug resistance, and immune response. Important problems in fields such as engineering and mathematical physics are presented as well. These topics elegantly apply various classical stochastic models and are motivated throughout with many worked out examples.

This third edition of Classical and Spatial Stochastic Processes is suitable as a textbook for a first course in stochastic processes at the upper-undergraduate or graduate level. Because of its accessible approach, it may also be used as a self-study resource for researchers and practitioners in mathematics, engineering, physics, and mathematical biology.


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