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Books > Science & Mathematics > Mathematics > Applied mathematics > Stochastics
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Stochastic Modeling (Paperback, 1st ed. 2017)
Loot Price: R3,225
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Stochastic Modeling (Paperback, 1st ed. 2017)
Series: Universitext
Expected to ship within 18 - 22 working days
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Three coherent parts form the material covered in this text,
portions of which have not been widely covered in traditional
textbooks. In this coverage the reader is quickly introduced to
several different topics enriched with 175 exercises which focus on
real-world problems. Exercises range from the classics of
probability theory to more exotic research-oriented problems based
on numerical simulations. Intended for graduate students in
mathematics and applied sciences, the text provides the tools and
training needed to write and use programs for research purposes.
The first part of the text begins with a brief review of measure
theory and revisits the main concepts of probability theory, from
random variables to the standard limit theorems. The second part
covers traditional material on stochastic processes, including
martingales, discrete-time Markov chains, Poisson processes, and
continuous-time Markov chains. The theory developed is illustrated
by a variety of examples surrounding applications such as the
gambler's ruin chain, branching processes, symmetric random walks,
and queueing systems. The third, more research-oriented part of the
text, discusses special stochastic processes of interest in
physics, biology, and sociology. Additional emphasis is placed on
minimal models that have been used historically to develop new
mathematical techniques in the field of stochastic processes: the
logistic growth process, the Wright -Fisher model, Kingman's
coalescent, percolation models, the contact process, and the voter
model. Further treatment of the material explains how these special
processes are connected to each other from a modeling perspective
as well as their simulation capabilities in C and Matlab (TM).
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