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Simulation and Inference for Stochastic Differential Equations
With R Examples
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This book 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 the book 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 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 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.
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Subject categories
- Academic > Mathematics > Probabilities. Mathematical statistics > Stochastic processes
- Academic > Mathematics > Probabilities. Mathematical statistics > Stochastic analysis
- Academic > Mathematics > Probabilities. Mathematical statistics > Stochastic differential equations
- Academic > Mathematics > General
- Mathematics > Differential Equations
ISBNs
0387758399
9780387758381
9780387758398