From elementary probability to stochastic differential equations with Maple

Sasha Cyganowski, Peter Kloeden, Jerzy Ombach

312 pages, parution le 30/11/2001

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Résumé

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. As prerequisites the authors assume a familiarity with basic calculus and linear algebra, as well as with elementary ordinary differential equations and, in the final chapter, simple numerical methods for such ODEs. Although statistics is not systematically treated, they introduce statistical concepts such as sampling, estimators, hypothesis testing, confidence intervals, significance levels and p-values and use them in a large number of examples, problems and simulations.

Table of Contents

Probality basics
Measures and Integral
Randon Variables and Distributions
Parameters of Probability distributions
A Tour of Important Distributions
Numerical Simulations and Statistical Inference
Stochastic Processes
Stochastic Calculus
Stochastic Differential Equations
Numerical Methods for SDEs
Bibliographie Notes
References
Index

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Sasha Cyganowski, Peter Kloeden, Jerzy Ombach
Parution	30/11/2001
Nb. de pages	312
Format	15,5 x 23,5
Couverture	Broché
Poids	494g
Intérieur	Noir et Blanc
EAN13	9783540426660