On The Estimation Of Stochastic Differential Equations PDF Download
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| Author | : Jaya P. N. Bishwal |
| Publisher | : Springer |
| Total Pages | : 271 |
| Release | : 2007-09-26 |
| Genre | : Mathematics |
| ISBN | : 3540744487 |
Download Parameter Estimation in Stochastic Differential Equations Book in PDF, ePub and Kindle
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.
| Author | : Simo Särkkä |
| Publisher | : Cambridge University Press |
| Total Pages | : 327 |
| Release | : 2019-05-02 |
| Genre | : Business & Economics |
| ISBN | : 1316510085 |
Download Applied Stochastic Differential Equations Book in PDF, ePub and Kindle
With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.
| Author | : Rong SITU |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 444 |
| Release | : 2006-05-06 |
| Genre | : Technology & Engineering |
| ISBN | : 0387251758 |
Download Theory of Stochastic Differential Equations with Jumps and Applications Book in PDF, ePub and Kindle
Stochastic differential equations (SDEs) are a powerful tool in science, mathematics, economics and finance. This book will help the reader to master the basic theory and learn some applications of SDEs. In particular, the reader will be provided with the backward SDE technique for use in research when considering financial problems in the market, and with the reflecting SDE technique to enable study of optimal stochastic population control problems. These two techniques are powerful and efficient, and can also be applied to research in many other problems in nature, science and elsewhere.
| Author | : Riccardo Cesari |
| Publisher | : |
| Total Pages | : 48 |
| Release | : 1989 |
| Genre | : Diffusion processes |
| ISBN | : |
Download On the Estimation of Stochastic Differential Equations Book in PDF, ePub and Kindle
| Author | : M. Baadsgaard |
| Publisher | : |
| Total Pages | : 124 |
| Release | : 1996 |
| Genre | : |
| ISBN | : |
Download Estimation in Stochastic Differential Equations Book in PDF, ePub and Kindle
| Author | : Mathieu Kessler |
| Publisher | : CRC Press |
| Total Pages | : 507 |
| Release | : 2012-05-17 |
| Genre | : Mathematics |
| ISBN | : 1439849765 |
Download Statistical Methods for Stochastic Differential Equations Book in PDF, ePub and Kindle
The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to th
| Author | : Peter E. Kloeden |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 666 |
| Release | : 2013-04-17 |
| Genre | : Mathematics |
| ISBN | : 3662126168 |
Download Numerical Solution of Stochastic Differential Equations Book in PDF, ePub and Kindle
The numerical analysis of stochastic differential equations (SDEs) differs significantly from that of ordinary differential equations. This book provides an easily accessible introduction to SDEs, their applications and the numerical methods to solve such 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
| Author | : E. Allen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 239 |
| Release | : 2007-03-08 |
| Genre | : Mathematics |
| ISBN | : 1402059531 |
Download Modeling with Itô Stochastic Differential Equations Book in PDF, ePub and Kindle
This book explains a procedure for constructing realistic stochastic differential equation models for randomly varying systems in biology, chemistry, physics, engineering, and finance. Introductory chapters present the fundamental concepts of random variables, stochastic processes, stochastic integration, and stochastic differential equations. These concepts are explained in a Hilbert space setting which unifies and simplifies the presentation.
| Author | : Stefano M. Iacus |
| Publisher | : Springer |
| Total Pages | : 286 |
| Release | : 2010-11-16 |
| Genre | : Computers |
| ISBN | : 9780387567471 |
Download Simulation and Inference for Stochastic Differential Equations Book in PDF, ePub and Kindle
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.
| Author | : Avner Friedman |
| Publisher | : Academic Press |
| Total Pages | : 248 |
| Release | : 2014-06-20 |
| Genre | : Mathematics |
| ISBN | : 1483217876 |
Download Stochastic Differential Equations and Applications Book in PDF, ePub and Kindle
Stochastic Differential Equations and Applications, Volume 1 covers the development of the basic theory of stochastic differential equation systems. This volume is divided into nine chapters. Chapters 1 to 5 deal with the basic theory of stochastic differential equations, including discussions of the Markov processes, Brownian motion, and the stochastic integral. Chapter 6 examines the connections between solutions of partial differential equations and stochastic differential equations, while Chapter 7 describes the Girsanov’s formula that is useful in the stochastic control theory. Chapters 8 and 9 evaluate the behavior of sample paths of the solution of a stochastic differential system, as time increases to infinity. This book is intended primarily for undergraduate and graduate mathematics students.
