Statistical Methods for Quality Assurance: Basics, Measurement, Control, Capability, and Improvement (Universitext)

Kloeden Peter/ Platen Eckhard/ Schurz Henri; H. Schurz; Eckhard Platen

ISBN 10: 0387570748 / ISBN 13: 9780387570747

Published by Springer Verlag, 1997

About this Item

Seller Inventory # SHUB87241

Bibliographic Details

• Title: Statistical Methods for Quality Assurance: Basics, Measurement, Control, Capability, and Improvement (Universitext)
• Publisher: Springer Verlag
• Publication Date: 1997
• Language: English
• ISBN 10: 0387570748
• ISBN 13: 9780387570747
• Binding: Soft cover
• Condition: New

About this title

Synopsis

The numerical analysis of stochastic differential equations differs significantly from that of ordinary differential equations, due to the peculiarities of stochastic calculus. The book proposes to the reader whose background knowledge is limited to undergraduate level methods for engineering and physics, and easily accessible introductions to SDE and then applications as well as the numerical methods for dealing with them. To help the reader develop an intuitive understanding and hand-on numerical skills, numerous exercises including PC-exercises are included.

From the Back Cover

This is a computer experimental introduction to the numerical solution of stochastic differential equations. A downloadable software software containing programs for over 100 problems is provided at one of the following homepages:

http://www.math.uni-frankfurt.de/numerik/kloeden/

http://www.business.uts.edu.au/finance/staff/eckard.html

http://www.math.siu.edu/schurz/SOFTWARE/

to enable the reader to develop an intuitive understanding of the issues involved. Applications include stochastic dynamical systems, filtering, parametric estimation and finance modeling.

The book is intended for readers without specialist stochastic background who want to apply such numerical methods to stochastic differential equations that arise in their own field. It can also be used as an introductory textbook for upper-level undergraduate or graduate students in engineering, physics and economics.