Books  Data Analysis & Modelling  Data Analysis & Statistics 

Simulation and Inference for Stochastic Differential Equations: With R Examples

  • Ready to use functions allow for instant analysis on real life data
  • Many figures give immediate impression of how the methods perform
  • Theoretical results are presented side-by-side with R code to ease the passage from theory to practice

Series: Springer Series in Statistics

By: Stefano M Iacus(Author)

284 pages, b/w illustrations


Paperback | Oct 2010 | #209138 | ISBN-13: 9781441926074
Availability: Usually dispatched within 1 week Details
NHBS Price: £96.99 $131/€110 approx
Hardback | May 2008 | #209181 | ISBN-13: 9780387758381
Availability: Usually dispatched within 1 week Details
NHBS Price: £96.99 $131/€110 approx

About this book

Simulation and Inference for Stochastic Differential Equations is unique because of its focus on the practical implementation of the simulation and estimation methods presented. The book will be useful to practitioners and students with only a minimal mathematical background because of the many R programs, and to more mathematically-educated practitioners.

Many of the methods presented in Simulation and Inference for Stochastic Differential Equations have 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 Simulation and Inference for Stochastic Differential Equations, 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 from real 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.

Simulation and Inference for Stochastic Differential Equations is organized into four chapters. The first one introduces the subject and presents several classes of processes used in many fields of mathematics, computational biology, finance and the social sciences. The second chapter is devoted to simulation schemes and covers new methods not available in other publications. The third one focuses on parametric estimation techniques. In particular, it includes exact likelihood inference, approximated and pseudo-likelihood methods, estimating functions, generalized method of moments, and other techniques. The last chapter contains miscellaneous topics like nonparametric estimation, model identification and change point estimation. The reader who is not an expert in the R language will find a concise introduction to this environment focused on the subject of the book. A documentation page is available at the end of the book for each R function presented in the book.


- Stochastic processes and stochastic differential equations
- Numerical methods for SDE
- Parametric estimation
- Miscellaneous topics

Write a review

There are currently no reviews for this product. Be the first to review this product!


Stefano M. Iacus is associate professor of Probability and Mathematical Statistics at the University of Milan, Department of Economics, Business and Statistics. He has a PhD in Statistics at Padua University, Italy and in Mathematics at Université du Maine, France.

He is a member of the R Core team for the development of the R statistical environment, Data Base manager for the Current Index to Statistics, and IMS Group Manager for the Institute of Mathematical Statistics. He has been associate editor of the Journal of Statistical Software.

Bestsellers in this subject

Choosing and Using Statistics

NHBS Price: £28.10 $38/€32 approx

Statistics for Ecologists Using R and Excel

NHBS Price: £34.99 $47/€40 approx

Handbook of Meta-analysis in Ecology and Evolution

NHBS Price: £62.95 $85/€71 approx

The New Statistics with R

NHBS Price: £29.99 $40/€34 approx


NHBS Price: £60.99 $82/€69 approx

VAT: GB 407 4846 44
NHBS Ltd is registered in England and Wales: 1875194