Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Simulation and Inference for Stochastic Differential Equations: With R Examples

Simulation and Inference for Stochastic Differential Equations: With R Examples

Iacus, Stefano M.

Paperback

Series: Springer Statistics

General ComputersGeneral MathematicsProbability & Statistics

ISBN10: 1441926070
ISBN13: 9781441926074
Publisher: Springer Nature
Published: Dec 1 2010
Pages: 285
Weight: 0.94
Height: 0.64 Width: 6.14 Depth: 9.21
Language: English

This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover stochastic differential equations, the concentration here on inference makes this book stand out. No other direct competitors are known to date. With an emphasis on the practical implementation of the simulation and estimation methods presented, the text will be useful to practitioners and students with minimal mathematical background. What's more, because of the many R programs, the information here is appropriate for many mathematically well educated practitioners, too. Many of the methods presented in the book have, so far, not been used much in practice because of the lack of an implementation in a unified framework. Iacus' book bridges this gap. With the R code included, a lot of useful methods become easy to use.

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