Simulation and Inference for Stochastic Differential Equations

Name: Simulation and Inference for Stochastic Differential Equations
Brand: Springer-Verlag New York Inc.
SKU: 9780387758381
Price: 3571 CZK
Availability: InStock

With R Examples

Autor: Stefano M. Iacus

Jazyk:

Vazba: Pevná

Vydavatel: Springer-Verlag New York Inc.

Dostupnost: Skladem u dodavatele

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This book is very different from any other publication in the field and it is unique because of its...

Informace o knize

Autor

Stefano M. Iacus

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2008

Stránek

285

EAN

9780387758381

ISBN

0387758380

Enbook ID

05247897

Vydavatel

Springer-Verlag New York Inc.

Hmotnost

612

Rozměry

162 x 238 x 19

Kompletní popis

This book is very different from any other publication in the field and it is unique because of its focus on the practical implementation of the simulation and 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 functionswith 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 non-expert in 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. To each R functions presented in the book a documentation page is available at the end of the book.

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Simulation and Inference for Stochastic Differential Equations

With R Examples

Informace o knize

Kompletní popis

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