The book introduces classical inequalities in vector and functional spaces with applications to probability. It develops new analytical inequalities, with sharper bounds and generalizations to the sum or the supremum of random variables, to martingales, to transformed Brownian motions and diffusions
Inequalities in Analysis and Probability: 2nd Edition
โ Scribed by Odile Pons
- Publisher
- World Scientific Publishing Co
- Year
- 2017
- Tongue
- English
- Leaves
- 306
- Edition
- 2ed.
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Inequalities in Analysis and Probability is a must for graduate students and researchers with basic knowledge of Probability and Integration Theory. It introduces classical inequalities in vector and functional spaces with applications to probability. It also develops new extensions of the analytical inequalities, with sharper bounds and generalizations to the sum or the supremum of random variables, to martingales and to transformed Brownian motions. The proofs of many new results are presented in great detail. Original tools are developed for spatial point processes and stochastic integration with respect to local martingales in the plane. This second edition covers properties of random variables and time continuous local martingales with a discontinuous predictable compensator, with exponential inequalities and new inequalities for their maximum variable and their p-variations. A chapter on stochastic calculus presents the exponential sub-martingales developed for stationary processes and their properties. Another chapter devoted itself to the renewal theory of processes and to semi-markovian processes, branching processes and shock processes. The Chapman Kolmogorov equations for strong semi-markovian processes provide equations for their hitting times in a functional setting which extends the exponential properties of the markovian processes.
Readership: Graduate students and researchers in probability and integration theory
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The book is aimed at graduate students and researchers with basic knowledge of Probability and Integration Theory. It introduces classical inequalities in vector and functional spaces with applications to probability. It also develops new extensions of the analytical inequalities, with sharper bound
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