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An Introduction to Continuous-Time Stochastic Processes - Theory, Models, and Applications to Finance, Biology, and Medicine (Paperback, 4th ed. 2021)
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An Introduction to Continuous-Time Stochastic Processes - Theory, Models, and Applications to Finance, Biology, and Medicine (Paperback, 4th ed. 2021)
Series: Modeling and Simulation in Science, Engineering and Technology
Expected to ship within 10 - 15 working days
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This textbook, now in its fourth edition, offers a rigorous and
self-contained introduction to the theory of continuous-time
stochastic processes, stochastic integrals, and stochastic
differential equations. Expertly balancing theory and applications,
it features concrete examples of modeling real-world problems from
biology, medicine, finance, and insurance using stochastic methods.
No previous knowledge of stochastic processes is required. Unlike
other books on stochastic methods that specialize in a specific
field of applications, this volume examines the ways in which
similar stochastic methods can be applied across different fields.
Beginning with the fundamentals of probability, the authors go on
to introduce the theory of stochastic processes, the Ito Integral,
and stochastic differential equations. The following chapters then
explore stability, stationarity, and ergodicity. The second half of
the book is dedicated to applications to a variety of fields,
including finance, biology, and medicine. Some highlights of this
fourth edition include a more rigorous introduction to Gaussian
white noise, additional material on the stability of stochastic
semigroups used in models of population dynamics and epidemic
systems, and the expansion of methods of analysis of
one-dimensional stochastic differential equations. An Introduction
to Continuous-Time Stochastic Processes, Fourth Edition is intended
for graduate students taking an introductory course on stochastic
processes, applied probability, stochastic calculus, mathematical
finance, or mathematical biology. Prerequisites include knowledge
of calculus and some analysis; exposure to probability would be
helpful but not required since the necessary fundamentals of
measure and integration are provided. Researchers and practitioners
in mathematical finance, biomathematics, biotechnology, and
engineering will also find this volume to be of interest,
particularly the applications explored in the second half of the
book.
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