Stable Non-Gaussian Self-Similar Processes with Stationary Increments
-
- US$39.99
-
- US$39.99
출판사 설명
This book provides a self-contained presentation on the structure of a large class of stable processes, known as self-similar mixed moving averages. The authors present a way to describe and classify these processes by relating them to so-called deterministic flows. The first sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed moving averages and self-similarity. In-depth appendices are also included.
This book is aimed at graduate students and researchers working in probability theory and statistics.
From Stochastic Calculus to Mathematical Finance
2007년
Stochastic Analysis and Applications
2007년
Probability and Partial Differential Equations in Modern Applied Mathematics
2010년
XI Symposium on Probability and Stochastic Processes
2015년
Stochastic Calculus for Fractional Brownian Motion and Applications
2008년
Lévy Matters VI
2017년
Non-Gaussian Selfsimilar Stochastic Processes
2023년
Analytic Theory of Itô-Stochastic Differential Equations with Non-smooth Coefficients
2022년
Concentration of Maxima and Fundamental Limits in High-Dimensional Testing and Inference
2021년
Asymptotic Properties of Permanental Sequences
2021년
An Invitation to Statistics in Wasserstein Space
2020년
Zero-Sum Discrete-Time Markov Games with Unknown Disturbance Distribution
2020년