The topic covered in this book is the study of metric and other close characteristics of different spaces and classes of random variables and the application of the entropy method to the investigation of properties of stochastic processes whose values, or increments, belong to given spaces. The foll
Metric characterization of random variables and random processes
β Scribed by Buldygin, ValeriΔ Vladimirovich; Kozachenko, IοΈ UοΈ‘. V
- Publisher
- American Mathematical Society
- Year
- 2000
- Tongue
- English, Russian
- Leaves
- 270
- Series
- Translations of mathematical monographs 188
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
The topic covered in this book is the study of metric and other close characteristics of different spaces and classes of random variables and the application of the entropy method to the investigation of properties of stochastic processes whose values, or increments, belong to given spaces. The following processes appear in detail: pre-Gaussian processes, shot noise processes representable as integrals over processes with independent increments, quadratically Gaussian processes, and, in particular, correlogram-type estimates of the correlation function of a stationary Gaussian process, jointly strictly sub-Gaussian processes, etc. The book consists of eight chapters divided into four parts: The first part deals with classes of random variables and their metric characteristics. The second part presents properties of stochastic processes imbedded'' into a space of random variables discussed in the first part. The third part considers applications of the general theory. The fourth part outlines the necessary auxiliary material. Problems and solutions presented show the intrinsic relation existing between probability methods, analytic methods, and functional methods in the theory of stochastic processes. The concluding sections,Comments'' and ``References'', gives references to the literature used by the authors in writing the book
β¦ Table of Contents
Content: Sub-Gaussian and pre-Gaussian random variables --
Orlicz spaces of random variables --
Regularity of sample paths of a stochastic process --
Pre-Gaussian processes --
Shot noise processes and their properties --
Correlograms of stationary Gaussian processes --
Jointly sub-Gaussian, super-Gaussian, and pseudo-Gaussian stochastic processes.
π SIMILAR VOLUMES
<p><p>This book explores the remarkable connections between two domains that, <i>a priori</i>, seem unrelated: Random matrices (together with associated random processes) and integrable systems. The relations between random matrix models and the theory of classical integrable systems have long been
Just had this book yesterday and I can't say how wonderful it is. The current text book I am using sucks hell. So, I decided to search for an alternative book. After I read the comments and I decide to give it a try. When I start reading it, it was so helpful!!!Highly recommand!!
Just had this book yesterday and I can't say how wonderful it is. The current text book I am using sucks hell. So, I decided to search for an alternative book. After I read the comments and I decide to give it a try. When I start reading it, it was so helpful!!!Highly recommand!!