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Author : Alfred Müller, Dietrich Stoyan

Date : 2002-03-12

Page : 358

Rating : 5.0

Reviews : 2

Category : Book

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Comparison Methods for Stochastic Models and Risks ~ Stochastic models have a probabilitybased approach and are used when the environment is not perfectly predictable and decisions are partly influenced by the users feedback and the regulations

Comparison Methods for Stochastic Models and Risks ~ This method is based on the construction of bounding models having closedform transient and steadystate distributions by means of Stochastic Comparison technique

Comparison Methods for Stochastic Models and Risks ~ Alfred Müller is the author of Comparison Methods for Stochastic Models and Risks published by Wiley Dietrich Stoyan is a mathematician and statistician He was a student of Mathematics at Technical University Dresden and of applied research at Deutsches Brennstoffinstitut Freiberg

PDF Comparison methods for stochastic models and risks ~ Univariate Stochastic Orders Theory of Integral Stochastic Orders Multivariate Stochastic Orders Stochastic Models Comparison and Monotonicity Monotonicity and Comparability of Stochastic Processes Monotonicity Properties and Bounds for Queueing Systems Applications to Various Stochastic Models Comparing Risks

Comparison Methods for Stochastic Models and Risks ~ 4 Stochastic Models Comparison and Monotonicity 149 41 General Considerations Concerning Stochastic Models 149 42 Monotonicity and Comparability 154 421 Monotonicity 154 422 Comparability 154 43 Methods for Establishing Monotonicity and Comparability Properties 155 431 The Functional Method 155 432 The Mapping Method 156

Comparison Methods for Stochastic Models and Risks ~ Comparison Methods for Stochastic Models and Risks Stochastic order relations prprovide a valuable insight into the behaviour of complex stochastic random systems and enable the user to collect meaningful comparative data Application areas include queueing systems actuarial and financial risk decision making and stochastic simulation

D Comparison Methods for Stochastic Models and Risks 2002 ~ Polyhedral risk measures are defined as optimal values of certain linear stochastic programs where the arguments of the risk measure appear on the righthand side of the dynamic constraints Dual representations for polyhedral risk measures are derived and used to deduce criteria for convexity and coherence

Stochastic comparisons in frailty models ScienceDirect ~ The main motivation of this paper is the fact that it is important to compare frailty models arising from different choices of the distribution of V andor the baseline hazard rate λ 0 t Such comparisons are particularly needed when as is generally the case there is no compelling reason other than mathematical tractability to choose a frailty distribution

Comparison methods for stochastic models risks Book ~ This work covers stochastic order relations which provide insight into the behaviour of complex stochastic random systems and enables the user to collect comparative data Application areas include queuing systems actuarial and financial risk decision making and stochastic simulation

Comparison Methods for Queues and Other Stochastic Models ~ The concept of stochastic strict server not only allows us to improve the basic results i – v under the independent case but also provides a convenient way to find the stochastic service curve of a serve Moreover an approach is introduced to find the stochastic arrival curve of a flow and the stochastic service curve of a server