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For a class of piecewise deterministic Markov processes we introduce a stochastic calculus which is a certain non-Gaussian counterpart to the classical Malliavin calculus. As an application we investigate the regularity of densities of…

Probability · Mathematics 2023-06-21 Jörg-Uwe Löbus

We are interested in the regularity of centered Gaussian processes (Z_x), x in M indexed by compact metric spaces M. It is shown that the almost everywhere Besov space regularity of such a process is (almost) equivalent to the Besov…

Probability · Mathematics 2015-08-05 Gerard Kerkyacharian , Shigeyoshi Ogawa , Pencho Petrushev , Dominique Picard

Multifractional processes extend the concept of fractional Brownian motion by replacing the constant Hurst parameter with a time-varying Hurst function. This extension allows for modulation of the roughness of sample paths over time. The…

Probability · Mathematics 2025-03-11 Antoine Ayache , Andriy Olenko , Nemini Samarakoon

Scaling properties of time series are usually studied in terms of the scaling laws of empirical moments, which are the time average estimates of moments of the dynamic variable. Nonlinearities in the scaling function of empirical moments…

Probability · Mathematics 2023-04-24 Marco Zamparo

We consider a general honest homogeneous continuous-time Markov process with restarts. The process is forced to restart from a given distribution at time moments generated by an independent Poisson process. The motivation to study such…

Probability · Mathematics 2012-06-26 Konstantin Avrachenkov , Alexei Piunovskiy , Zhang Yi

Strongly consistent and asymptotic normal estimators of the Hurst index of a stochastic differential equation driven by a fractional Brownian motion are proposed. The estimators are based on discrete observations of the underlying process.

Probability · Mathematics 2014-02-18 K. Kubilius , V. Skorniakov , D. Melichov

Fractional Brownian motion (fBm) is a centered self-similar Gaussian process with stationary increments, which depends on a parameter $H \in (0, 1)$ called the Hurst index. The use of time-changed processes in modeling often requires the…

Probability · Mathematics 2014-08-21 Jebessa B. Mijena

We consider four prototypes of variational problems and prove the existence of fractal minimizers through the direct method in the calculus of variations. By design these minimizers are H\"older curves or H\"older parametrizations of…

Probability · Mathematics 2025-12-17 Michael Hinz , Jonas M. Tölle , Lauri Viitasaari

We show how H\"older estimates for Feller semigroups can be used to obtain regularity results for solutions to the Poisson equation $Af=g$ associated with the (extended) infinitesimal generator $A$ of a Feller process. The regularity of $f$…

Probability · Mathematics 2021-10-06 Franziska Kühn

We give a result of stability in law of the local time of the fractional Brownian motion with respect to small perturbations of the Hurst parameter. Concretely, we prove that the law (in the space of continuous functions) of the local time…

Probability · Mathematics 2007-05-23 Maria Jolis , Noèlia Viles

The times of Brownian local minima, maxima and their union are three distinct examples of local, stationary, dense, random countable sets associated with classical Wiener noise. Being local means, roughly, determined by the local behavior…

Probability · Mathematics 2022-12-13 Matija Vidmar , Jon Warren

The theory of ``Markov-up'' processes is being developed. This is a new class of stochastic processes with ``partial'' markovian features; it could also be called ``one-sided Markov''. Such a behavior may be found in the real world and in…

Probability · Mathematics 2024-07-01 D. O. Kalikaeva

We generalize the Green-Kubo approach, previously applied to bulk systems of spherically symmetric active particles [J. Chem. Phys. 145, 161101 (2016)], to include spatially inhomogeneous activity. The method is applied to predict the…

Soft Condensed Matter · Physics 2017-09-20 Abhinav Sharma , Joseph Brader

In this paper, we introduce the linear fractional self-attracting diffusion driven by a fractional Brownian motion with Hurst index 1/2<H<1, which is analogous to the linear self-attracting diffusion. For 1-dimensional process we study its…

Probability · Mathematics 2007-07-19 Litan Yan , Yu Sun , Yunsheng Lu

We introduce a new class of self-similar Gaussian stochastic processes, where the covariance is defined in terms of a fractional Brownian motion and another Gaussian process. A special case is the solution in time to the fractional-colored…

Probability · Mathematics 2015-08-28 Daniel Harnett , David Nualart

We study a particular class of moving average processes which possess a property called localisability. This means that, at any given point, they admit a ``tangent process'', in a suitable sense. We give general conditions on the kernel g…

Probability · Mathematics 2009-06-25 Kenneth Falconer , Ronan Le Guével , Jacques Lévy-Véhel

We construct the basis of a stochastic calculus for so-called Volterra processes, i.e., processes which are defined as the stochastic integral of a time-dependent kernel with respect to a standard Brownian motion. For these processes which…

Probability · Mathematics 2007-05-23 L. Decreusefond

This paper establishes the Local Asymptotic Normality (LAN) property for the mixed fractional Brownian motion under high-frequency observations with Hurst index $H \in (0, 3/4)$. The simultaneous estimation of the volatility and the Hurst…

Statistics Theory · Mathematics 2026-01-01 Chunhao Cai

We investigate a Verhulst process, which is the special functional of geometric Brownian motion and has many applications, among others in biology and in stochastic volatility models. We present an exact form of density of a one dimensional…

Probability · Mathematics 2014-08-29 Maciej Wiśniewolski , Jacek Jakubowski

This paper is concerned with the construction of several stochastic processes in a star graph, that is a non-euclidean structure where some features of the classical modelling fail. We propose a model for trapping phenomena with…

Probability · Mathematics 2023-11-14 Stefano Bonaccorsi , Mirko D'Ovidio
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