Comparison Methods for Stochastic Models and Risks

330 pages, parution le 03/05/2002

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Résumé

Stochastic orders are important approximation tools that provide valuable insight into the behaviour of complex stochastic models. Research into stochastic orders is blossoming, with many open problems being studied and a wide range of applications explored. In this book the authors explore the most important concepts of the field, from the basic univariate theory through to the most current applications.

Comprehensive coverage of the theory and applications of stochastic orders.
Employs a systematic approach with detailed explanation of each concept.
Features coverage of univariate and multivariate stochastic orders.
Covers a range of applications, from queueing theory, reliability theory, statistical physics, actuarial and financial risk, and economics.
Written by authors with many years experience in researching stochastic orders.

Researchers and graduate students studying stochastic orders will find the comprehensive coverage of the subject ideal for their needs. The range of applications will benefit those working in applied probability and statistics, reliability, actuarial science, economics and finance.

Contents

Univariate Stochastic Orders
Theory of Integral Stochastic Orders
Multivariate Stochastic Orders
Stochastic Models, Comparison and Monotonicity
Monotonicity and Comparibility of Stochastic Processes
Monotonicity Properties and Bounds for Queueing Systems
Applications to Various Stochastic Models
Comparing Risks

Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Parution	03/05/2002
Nb. de pages	330
Format	15,5 x 23,5
Couverture	Relié
Poids	670g
Intérieur	Noir et Blanc
EAN13	9780471494461
ISBN13	978-0-471-49446-1