xiv, 476 S., 24x17 cm Ill. OPp.; ohne Umschlag. Einige s/w Ill. Kapitale leicht besto�en, schwacher Kratzer auf Hinterdeckel; innen sehr sauber und fest; noch sehr gutes Exemplar. / Hardcover, without jacket. Some illustrations. Head and tail of spine lightly bumped, otherwise clean and tight. Sprache: Englisch Gewicht in Gramm: 850.

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Detalles bibliogr�ficos

T�tulo

Stochastic Simulation: Algorithms and Analysis. [= Stochastic Modelling and Applied Probability, 57]

Editor

New York, Springer,

Fecha de publicaci�n

2007

Idioma

Ingl�s

ISBN 10

038730679X

ISBN 13

9780387306797

Encuadernaci�n

Hardcover/Pappeinband

Estado

Sehr gut

Cat�logos de vendedores

Mathematik

Acerca de

Sinopsis

Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods; the second half discusses model-specific algorithms. Exercises and illustrations are included.

De la contraportada

Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods, as well as accompanying mathematical analysis of the convergence properties of the methods discussed. The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focuses on general methods, whereas the second half discusses model-specific algorithms.

Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value.

S�ren Asmussen is a professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is the Thomas Ford professor of Engineering at Stanford University.

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