Conditional Monte Carlo

Name: Conditional Monte Carlo
Brand: Springer
SKU: 9780792398738
Price: 76036 HUF
Availability: InStock

Gradient Estimation and Optimization Applications

Szerző: Michael C. Fu, Jian-Qiang Hu

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer

Elérhetőség: Beszállítói készleten

Küldés 10-13 napon belül

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Conditional Monte Carlo: Gradient Estimation and Optimization Applications deals with various gradie...

Információk a könyvről

Szerző

Michael C. Fu, Jian-Qiang Hu

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

1997

oldal

399

EAN

9780792398738

ISBN

0792398734

Enbook ID

01398512

Kiadó

Springer

Súly

1680

Méretek

155 x 235 x 23

Teljes leírás

Conditional Monte Carlo: Gradient Estimation and Optimization Applications deals with various gradient estimation techniques of perturbation analysis based on the use of conditional expectation. The primary setting is discrete-event stochastic simulation. This book presents applications to queueing and inventory, and to other diverse areas such as financial derivatives, pricing and statistical quality control. To researchers already in the area, this book offers a unified perspective and adequately summarizes the state of the art. To researchers new to the area, this book offers a more systematic and accessible means of understanding the techniques without having to scour through the immense literature and learn a new set of notation with each paper. To practitioners, this book provides a number of diverse application areas that makes the intuition accessible without having to fully commit to understanding all the theoretical niceties. In sum, the objectives of this monograph are two-fold: to bring together many of the interesting developments in perturbation analysis based on conditioning under a more unified framework, and to illustrate the diversity of applications to which these techniques can be applied. Conditional Monte Carlo: Gradient Estimation and Optimization Applications is suitable as a secondary text for graduate level courses on stochastic simulations, and as a reference for researchers and practitioners in industry.

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Conditional Monte Carlo

Gradient Estimation and Optimization Applications

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