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From elementary probability to stochastic differential equations with MAPLE UNIVERSITEXT

By: Contributor(s): Material type: TextTextSeries: UniversitextPublication details: Germany Springer-Verlag Berl 2001Description: 375p., paperbackISBN:
  • 3540426663
Subject(s):
Contents:
Probability basics; measure and integral; random variables and distributions; parameters of distributions; a tour of important distributions; numerical simulations and statistical inference; stochastic processes; stochastic calculus; stochastic differential equations; Numerical methods of SDEs.
Holdings
Item type Current library Call number Status Date due Barcode
Standard Loan Thurles Library Main Collection 519.2 CYG (Browse shelf(Opens below)) Available R06722KRCC
Standard Loan Thurles Library Main Collection 519.2 CYG (Browse shelf(Opens below)) Available R09205KRCT
Standard Loan Thurles Library Main Collection 519.2 CYG (Browse shelf(Opens below)) Available R09399KRCT
Standard Loan Thurles Library Main Collection 519.2 CYG (Browse shelf(Opens below)) Available R09400KRCT

Enhanced descriptions from Syndetics:

Measure and integration wereonceconsidered,especially by many ofthe more practically inclined, to be an esoteric area ofabstract mathematics best left to pure mathematicians. However,it has become increasingly obvious in recent years that this area is now an indispensable, even unavoidable, language and provides a fundamental methodology for modern probability theory, stochas­ tic analysis and their applications, especially in financial mathematics. Our aim in writing this book is to provide a smooth and fast introduction to the language and basic results ofmodern probability theory and stochastic differential equations with help ofthe computer manipulator software package MAPLE. It is intended for advanced undergraduate students or graduates, not necessarily in mathematics, to provide an overviewand intuitive background for more advanced studies as wellas somepractical skillsin the use of MAPLE software in the context of probability and its applications. This book is not a conventional mathematics book. Like such books it provides precise definitions and mathematical statements, particularly those based on measure and integration theory, but instead ofmathematical proofs it uses numerous MAPLE experiments and examples to help the reader un­ derstand intuitively the ideas under discussion. The pace increases from ex­ tensive and detailed explanations in the first chapters to a more advanced presentation in the latter part of the book. The MAPLE is handled in a sim­ ilar way, at first with simple commands, then some simple procedures are gardually developed and, finally, the stochastic package is introduced.

THE AUTHORS PROVIDE A FAST INTRODUCTION TO PROBABILISTIC AND STATISTICAL CONCEPTS NECESSARY TO UNDERSTAND THE BASIC IDEAS AND METHODS OF STOCHASTIC DIFFERENTIAL EQUATIONS. THE BOOK IS BASED ON MEASURE THEORY WHICH IS INTRODUCED AS SMOOTHLY AS POSSIBLE. IT IS INTENDED FOR ADVANCED UNDERGRADUATE STUDENTS OR GRADUATES, NOT NECESSARILY IN MATHEMATICS, PROVIDING AN OVERVIEW AND INTUITIVE BACKGROUND FOR MORE ADVANCED STUDIES AS WELL AS SOME PRACTICAL SKILLS IN THE USE OF MAPLE IN THE CONTEXT OF PROBABILITY AND ITS APPLICATIONS.

The authors provide a fast introduction to probabilistic and statistical concepts necessary to understand the basic ideas and methods of stochastic differential equations. The book is based on measure theory.

Probability basics; measure and integral; random variables and distributions; parameters of distributions; a tour of important distributions; numerical simulations and statistical inference; stochastic processes; stochastic calculus; stochastic differential equations; Numerical methods of SDEs.

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