Simulation and Inference for Stochastic Differential Equations: With R Examples (Hardback)

Condition

LIKE NEW: This book is in excellent, like-new condition. It was printed on acid-free paper.

Product Details

This volume belongs to theSpringer Series in Statistics .
Continued from the back cover: "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 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.

"The book is organized in 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 milestones publication known so far. The third one is focused 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 which should allow for instant use of the proposed material. A documentation page is available at the end of the book for each R function presented in the book."

Chapters

1. Stochastic Processes and Stochastic Differential Equations
2. Numerical Methods for SDE
3. Parametric Estimation
4. Miscellaneous Topics

Appendices

1. A brief excursus into R
2. The sde Package

The book concludes with References and Index.