Discrete Stochastics

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  1. Modeling Discrete & Stochastic Events
  2. Description
  3. [PDF] Sensitivity analysis of discrete stochastic systems. - Semantic Scholar

For IEEE to continue sending you helpful information on our products and services, please consent to our updated Privacy Policy. Email Address. Sign In. Access provided by: anon Sign Out. Uncertainty of discrete stochastic systems: general theory and statistical inference Abstract: Uncertainty is defined in a new manner, as a function of discrete probability distributions satisfying a simple and intuitively appealing weak monotonicity condition. It is shown that every uncertainty is Schur-concave and conversely, every Schur-concave function of distributions is an uncertainty.

General properties of uncertainties are systematically studied. Many characteristics of distributions introduced previously in statistical physics, mathematical statistics, econometrics and information theory are shown to be particular examples of uncertainties.

New examples are introduced, and traditional as well as some new methods for obtaining uncertainties are discussed. Now Publishers Inc. Martingale Methods in Financial Modelling. Shreve Random Processes. A Festschrift for Herman Rubin. The Mathematical Gazette. Snyder; Michael I. Miller Random Point Processes in Time and Space. Some History of Stochastic Point Processes". International Statistical Review.

Stochastic Calculus Lecture 3 (Part 3): Ito-Isometry for Discrete stochastic processes

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Modeling Discrete & Stochastic Events

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[PDF] Sensitivity analysis of discrete stochastic systems. - Semantic Scholar

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