Polya Urn Models - Mahmoud, Hosam
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Polya Urn Models presents a complete introduction to the terminology of urns and urn models, which refer to a system of one or more containers with objects of various types. The book begins with a summary of basic issues in discrete probability that forms the foundations of probability from an urn viewpoint. With exercises, examples, and historical notes, it covers classical probability problems connected to and presented within the framework of urns, the Polya urn model, and variations in real time. The book also explores recent developments in the field as well as a broad range of…mehr

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Produktbeschreibung
Polya Urn Models presents a complete introduction to the terminology of urns and urn models, which refer to a system of one or more containers with objects of various types. The book begins with a summary of basic issues in discrete probability that forms the foundations of probability from an urn viewpoint. With exercises, examples, and historical notes, it covers classical probability problems connected to and presented within the framework of urns, the Polya urn model, and variations in real time. The book also explores recent developments in the field as well as a broad range of applications in bioscience and computer science, in particular, data structures, algorithms, and Internet growth.
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Autorenporträt
Hosam Mahmoud
Rezensionen
"Pólya Urn Models describes the established theory and details numerous new developments since the seminal 1977 text Urn Models and Their Application: An Approach to Modern Discrete Probability Theory by Johnson and Kotz. ... the second half of Mahmoud's book largely covers new advances since Johnson and Kotz's book ... This latter material makes the current text unique. ... The end-of-chapter exercises (of greatly varying difficulty) have excellent in-depth solutions at the end of the text. ... The book is exceptionally well written, concise, and compelling. The author obviously commands this material, and his enthusiasm is unmistakable."
-Matthew Bognar, Journal of the American Statistical Association, September 2014, Vol. 109