Simulation and inference for stochastic differential equations: with R examples

This book is very different from any other publication in the field and it isunique because of its focus on the practical implementation of the simulationand estimation methods presented. The book should be useful to practitioners and students with minimal mathematical background, but because of the many R programs, probably also to many mathematically well educated practitioners. Many of the methods presented in the book have, so far, not been used much in practice because the lack of an implementation in a unified framework. This book fills the gap. With the R code included in this book, a lot of useful methods become easy to use for practitioners and students. An R package called 'sde' provides functions with easy interfaces ready to be used on empirical data fromreal life applications. Although it contains a wide range of results, the book has an introductory character and necessarily does not cover the whole spectrum of simulation and inference for general stochastic differential equations.Ready-to-use functions allow for instant analysis on real life data. Many figures give immediate feeling on how methods perform. Theoretical results are presented side-by-side with R code to ease the passage from theory to practice INDICE: Stochastic processes and stochastic differential equations. Numerical methods for SDE. Parametric estimation. Miscellaneous topics.

• ISBN: 978-0-387-75838-1
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 257
• Fecha Publicación: 01/04/2008
• Nº Volúmenes: 1
• Idioma: Inglés