Polya Urn Models

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A01=Hosam Mahmoud
advanced urn model probability systems
Author_Hosam Mahmoud
ball
balls
Bernoulli Random Variables
Binary Search Tree
bioscience applications
blue
Blue Balls
Category=PBT
Category=PBWL
Category=PS
Category=UY
Central Limit Theorem
clinical trials
Conditional Expectation
Constant Row Sum
discrete probability
discrete time analysis
Ehrenfest Urn
epidemiology
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
evolution models
exchangeable processes
External Node
Feasible Partition
Gambler's Ruin
Gambler’s Ruin
Hosam Mahmoud
Independent Exp
Independent Geometric Random Variables
Interarrival Times
Martingale Central Limit Theorem
moment generating functions
Negative Binomial Distribution
plya
Poisson Process
poissonization
polya urn models
probability theory
random
random circuits
Random Variable
recursive
Recursive Trees
scheme
Sigma Field
Slutsky's Theorem
Slutsky’s Theorem
Stirling Numbers
stochastic modeling
Transition Matrix
tree
Urn Models
Urn Scheme
variable
white
White Balls

Product details

  • ISBN 9781420059830
  • Weight: 566g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Jun 2008
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Incorporating a collection of recent results, Pólya Urn Models deals with discrete probability through the modern and evolving urn theory and its numerous applications.

The book first substantiates the realization of distributions with urn arguments and introduces several modern tools, including exchangeability and stochastic processes via urns. It reviews classical probability problems and presents dichromatic Pólya urns as a basic discrete structure growing in discrete time. The author then embeds the discrete Pólya urn scheme in Poisson processes to achieve an equivalent view in continuous time, provides heuristical arguments to connect the Pólya process to the discrete urn scheme, and explores extensions and generalizations. He also discusses how functional equations for moment generating functions can be obtained and solved. The final chapters cover applications of urns to computer science and bioscience.

Examining how urns can help conceptualize discrete probability principles, this book provides information pertinent to the modeling of dynamically evolving systems where particles come and go according to governing rules.

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