Essentials of Stochastic Processes (Springer Texts in Statistics)

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Description

Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn an issue by seeing it in action, so there are a lot of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding.
 
 Drawing from teaching experience and student feedback, there are lots of new examples and problems with solutions that use TI-83 to do away with the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. In the beginning included in previous editions, material too advanced for this first course in stochastic processes has been eliminated at the same time as remedy of other topics useful for applications has been expanded.  As well as, the ordering of topics has been improved; for instance, the difficult subject of martingales is delayed until its usefulness may also be applied in the remedy of mathematical finance.

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