Abstract. We introduce a class of Gaussian processes with stationary in-crements which exhibit long-range dependence. The class includes fractional Brownian motion with Hurst parameter H> 1/2 as a typical example. We es-tablish infinite and finite past prediction formulas for the processes in which the predictor coefficients are given explicitly in terms of the MA(∞) and AR(∞) coefficients. We apply the formulas to prove an analogue of Baxter’s inequal-ity, which concerns the L1-estimate of the difference between the finite and infinite past predictor coefficients. 1
We study a long-range dependence Gaussian process which we call “sub-fractional Brownian motion” (su...
We describe methods for generating discretized sample paths of long-range dependent processes such a...
The fractional Brownian motion can be considered as a Gaussian field indexed by $(t,H) \in {\mathbb{...
We introduce a class of Gaussian processes with stationary increments which exhibit long-range depen...
We introduce a class of Gaussian processes with stationary increments which exhibit long-range depen...
Title: Long range dependence in time series Author: Alexander Till Department: Department of Probabi...
D.Phil. (Mathematical Statistics)Fractional Brownian motion and its increment process, fractional Ga...
We derive the exact asymptotic behavior of the ruin probability P{X(t)>x for some t>0} for the proce...
This paper aims at enhancing the understanding of long-range dependence (LRD) by focusing on mechani...
We consider the finite-past predictor coefficients of stationary time series, and establish an expli...
Fractional Brownian motion is a nontrivial generalization of standard Brownian motion (Wie- ner proc...
The goal of this paper is to establish a relation between characteristic polynomials of N ×N GUE ran...
In the paper consistent estimates of the Hurst parameter of fractional Brownian motion are obtained ...
Based on the integral relationship between Brownian motion and fractional Brownian motion, we model...
We study asymptotic expansion of the likelihood of a certain class of Gaussian processes characteriz...
We study a long-range dependence Gaussian process which we call “sub-fractional Brownian motion” (su...
We describe methods for generating discretized sample paths of long-range dependent processes such a...
The fractional Brownian motion can be considered as a Gaussian field indexed by $(t,H) \in {\mathbb{...
We introduce a class of Gaussian processes with stationary increments which exhibit long-range depen...
We introduce a class of Gaussian processes with stationary increments which exhibit long-range depen...
Title: Long range dependence in time series Author: Alexander Till Department: Department of Probabi...
D.Phil. (Mathematical Statistics)Fractional Brownian motion and its increment process, fractional Ga...
We derive the exact asymptotic behavior of the ruin probability P{X(t)>x for some t>0} for the proce...
This paper aims at enhancing the understanding of long-range dependence (LRD) by focusing on mechani...
We consider the finite-past predictor coefficients of stationary time series, and establish an expli...
Fractional Brownian motion is a nontrivial generalization of standard Brownian motion (Wie- ner proc...
The goal of this paper is to establish a relation between characteristic polynomials of N ×N GUE ran...
In the paper consistent estimates of the Hurst parameter of fractional Brownian motion are obtained ...
Based on the integral relationship between Brownian motion and fractional Brownian motion, we model...
We study asymptotic expansion of the likelihood of a certain class of Gaussian processes characteriz...
We study a long-range dependence Gaussian process which we call “sub-fractional Brownian motion” (su...
We describe methods for generating discretized sample paths of long-range dependent processes such a...
The fractional Brownian motion can be considered as a Gaussian field indexed by $(t,H) \in {\mathbb{...