Stochastic Models for Fractional Calculus 2nd edition by Mark Meerschaert 9783110559149 3110559145

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ISBN 10: 3110559145
ISBN 13: 9783110559149 
Author: Mark M. Meerschaert

Fractional calculus is a rapidly growing field of research, at the interface between probability, differential equations, and mathematical physics. It is used to model anomalous diffusion, in which a cloud of particles spreads in a different manner than traditional diffusion. This monograph develops the basic theory of fractional calculus and anomalous diffusion, from the point of view of probability. In this book, we will see how fractional calculus and anomalous diffusion can be understood at a deep and intuitive level, using ideas from probability. It covers basic limit theorems for random variables and random vectors with heavy tails. This includes regular variation, triangular arrays, infinitely divisible laws, random walks, and stochastic process convergence in the Skorokhod topology. The basic ideas of fractional calculus and anomalous diffusion are closely connected with heavy tail limit theorems. Heavy tails are applied in finance, insurance, physics, geophysics, cell biology, ecology, medicine, and computer engineering. The goal of this book is to prepare graduate students in probability for research in the area of fractional calculus, anomalous diffusion, and heavy tails. Many interesting problems in this area remain open. This book will guide the motivated reader to understand the essential background needed to read and unerstand current research papers, and to gain the insights and techniques needed to begin making their own contributions to this rapidly growing field.

Stochastic Models for Fractional Calculus 2nd Table of contents:

1. Introduction
1.1 The traditional diffusion model
1.2 Fractional diffusion

2. Fractional Derivatives
2.1 The Grünwald formula
2.2 More fractional derivatives
2.3 The Caputo derivative
2.4 Time-fractional diffusion

3. Stable Limit Distributions
3.1 Infinitely divisible laws
3.2 Stable characteristic functions
3.3 Semigroups
3.4 Poisson approximation
3.5 Shifted Poisson approximation
3.6 Triangular arrays
3.7 One-sided stable limits
3.8 Two-sided stable limits

4. Continuous Time Random Walks
4.1 Regular variation
4.2 Stable Central Limit Theorem
4.3 Continuous time random walks
4.4 Convergence in Skorokhod space
4.5 CTRW governing equations

5. Computations in R
5.1 R codes for fractional diffusion
5.2 Sample path simulations

6. Vector Fractional Diffusion
6.1 Vector random walks
6.2 Vector random walks with heavy tails
6.3 Triangular arrays of random vectors
6.4 Stable random vectors
6.5 Vector fractional diffusion equation
6.6 Operator stable laws
6.7 Operator regular variation
6.8 Generalized domains of attraction

7. Applications and Extensions
7.1 The fractional Poisson process
7.2 LePage series representation
7.3 Tempered stable laws
7.4 Tempered fractional derivatives
7.5 Distributed order fractional derivatives
7.6 Pearson diffusions
7.7 Fractional Pearson diffusions
7.8 Correlation structure of fractional processes
7.9 Fractional Brownian motion
7.10 Fractional random fields
7.11 Applications of fractional diffusion
7.12 Applications of vector fractional diffusion

Bibliography
Index

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Mark Meerschaert,Stochastic ModelsmFractional Calculus