Iacus Simulation and Inference for Stochastic Differential Equations

With R Examples
1. Auflage 2009
ISBN: 978-0-387-75839-8
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 286 Seiten, Web PDF

Reihe: Mathematics and Statistics

This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover stochastic differential equations, the concentration here on inference makes this book stand out. No other direct competitors are known to date. With an emphasis on the practical implementation of the simulation and estimation methods presented, the text will be useful to practitioners and students with minimal mathematical background. What’s more, because of the many R programs, the information here is appropriate for many mathematically well educated practitioners, too. Many of the methods presented in the book have, so far, not been used much in practice because of the lack of an implementation in a unified framework. Iacus’ book bridges this gap. With the R code included, a lot of useful methods become easy to use.

Zielgruppe

Research

Autoren/Hrsg.

Iacus, Stefano M.

Inhaltsverzeichnis

Stochastic Processes and Stochastic Differential Equations.- Numerical Methods for SDE.- Parametric Estimation.- Miscellaneous Topics.