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
We study the concept of self-similarity with respect to stochastic time change. The negative binomia...
AbstractWolfe (Stochastic Process. Appl. 12(3) (1982) 301) and Sato (Probab. Theory Related Fields 8...
Wolfe (Stochastic Process. Appl. 12(3) (1982) 301) and Sato (Probab. Theory Related Fields 89(3) (19...
Abstract. In this paper, we consider two classes of symmetric α-stable (1 < α < 2), H-self-sim...
We consider an important subclass of self-similar, non-Gaussian stable processes with stationary inc...
and X# be a symmetric #-stable (S#S) process with stationary increments given by the mixed moving av...
Non-Gaussian stable stochastic models have attracted growing interest in recent years, due to their ...
This work is concerned with the analysis of self-similar stochastic pro-cesses, where statistical se...
Self-similar processes are very natural generalization of stable Levy Motions, we introduce the new ...
Non-Gaussian stable stochastic models have attracted growing interest in recent years, due to their ...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
AbstractIn this note we settle a question posed by Kasahara, Maejima, and Vervaat. We show that the ...
This thesis is composed of five chapters, regarding several models for dependence in stochastic proc...
We define a new type of self-similarity for one-parameter families of stochastic processes, which ap...
Abstract: This note surveys some recent results on self-similar Markov processes. Since the research...
We study the concept of self-similarity with respect to stochastic time change. The negative binomia...
AbstractWolfe (Stochastic Process. Appl. 12(3) (1982) 301) and Sato (Probab. Theory Related Fields 8...
Wolfe (Stochastic Process. Appl. 12(3) (1982) 301) and Sato (Probab. Theory Related Fields 89(3) (19...
Abstract. In this paper, we consider two classes of symmetric α-stable (1 < α < 2), H-self-sim...
We consider an important subclass of self-similar, non-Gaussian stable processes with stationary inc...
and X# be a symmetric #-stable (S#S) process with stationary increments given by the mixed moving av...
Non-Gaussian stable stochastic models have attracted growing interest in recent years, due to their ...
This work is concerned with the analysis of self-similar stochastic pro-cesses, where statistical se...
Self-similar processes are very natural generalization of stable Levy Motions, we introduce the new ...
Non-Gaussian stable stochastic models have attracted growing interest in recent years, due to their ...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
AbstractIn this note we settle a question posed by Kasahara, Maejima, and Vervaat. We show that the ...
This thesis is composed of five chapters, regarding several models for dependence in stochastic proc...
We define a new type of self-similarity for one-parameter families of stochastic processes, which ap...
Abstract: This note surveys some recent results on self-similar Markov processes. Since the research...
We study the concept of self-similarity with respect to stochastic time change. The negative binomia...
AbstractWolfe (Stochastic Process. Appl. 12(3) (1982) 301) and Sato (Probab. Theory Related Fields 8...
Wolfe (Stochastic Process. Appl. 12(3) (1982) 301) and Sato (Probab. Theory Related Fields 89(3) (19...