Numerical Solution of Stochastic Differential Equations (Stochastic Modelling and Applied Probability)

^ Numerical Solution of Stochastic Differential Equations (Stochastic Modelling and Applied Probability) ✓ PDF Read by ^ Peter E. Kloeden, Eckhard Platen eBook or Kindle ePUB Online free. Numerical Solution of Stochastic Differential Equations (Stochastic Modelling and Applied Probability) The numerical analysis of stochastic differential equations (SDEs) differs significantly from that of ordinary differential equations. From the reviews:The authors draw upon their own research and experiences in obviously many disciplines considerable time has obviously been spent writing this in the simplest language possible. --ZAMP. This book provides an easily accessible introduction to SDEs, their applications and the numerical methods to solve such equations]

Numerical Solution of Stochastic Differential Equations (Stochastic Modelling and Applied Probability)

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Rating : 4.58 (952 Votes)
Asin : 3540540628
Format Type : paperback
Number of Pages : 636 Pages
Publish Date : 0000-00-00
Language : English

DESCRIPTION:

The numerical analysis of stochastic differential equations (SDEs) differs significantly from that of ordinary differential equations. From the reviews:"The authors draw upon their own research and experiences in obviously many disciplines considerable time has obviously been spent writing this in the simplest language possible." --ZAMP. This book provides an easily accessible introduction to SDEs, their applications and the numerical methods to solve such equations

" the authors draw upon their own research and experiences in obviously many disciplines considerable time has obviously been spent writing this in the simplest language possible. This was not an easy task Their exposition stresses clarity, not formality - a very welcome approach." ZAMP

Five Stars A classic.. A reference book in the domain Much literature is published on numerical methods for stochastic differential systems but most of it focuses on their use in pricing financial products. There is genuinely a lack of reference books that provide a stronger mathematical basis for the domain. Luckily, this is one of the few books that fill that gap. An excellent book, although the scope of numerical methods presented is limited.. "Extensive material, but lots of boring stuff" according to Luke. This book covers a lot of stuff about simulation of SDEs. It includes descriptions of various higher-order techniques, something you won't find elsewhere but can be useful for programmers looking to tune their implementations. However, despite the vast amount of material in this book, it's pretty dry. The practicality of different methods isn't really discussed very well why would I choose implicit over explicit? how high order is really worth it? what about efficiency of sampling the cross-term integrals? Somehow I also felt the theory did not go very far; nothing i

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