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We establish asymptotic properties of $M$-estimators, defined in terms of a contrast function and observations from a continuous-time locally stationary process. Using the stationary approximation of the sequence, $\theta$-weak dependence,…

Statistics Theory · Mathematics 2021-05-11 Bennet Ströh

Influenced mixed moving average fields are a versatile modeling class for spatio-temporal data. However, their predictive distribution is not generally known. Under this modeling assumption, we define a novel spatio-temporal embedding and a…

Machine Learning · Statistics 2024-08-05 Imma Valentina Curato , Orkun Furat , Lorenzo Proietti , Bennet Stroeh

In this paper we present a parametric estimation method for certain multi-parameter heavy-tailed L\'evy-driven moving averages. The theory relies on recent multivariate central limit theorems obtained in [3] via Malliavin calculus on…

Statistics Theory · Mathematics 2021-04-20 Mathias Mørck Ljungdahl , Mark Podolskij

In this work, we study the class of stochastic process that generalizes the Ornstein-Uhlenbeck processes, hereafter called by \emph{Generalized Ornstein-Uhlenbeck Type Process} and denoted by GOU type process. We consider them driven by the…

Statistics Theory · Mathematics 2021-08-17 J. Stein , S. R. C. Lopes , A. V. Medino

The local structure of $q$-Ornstein-Uhlenbeck processes and $q$-Brownian motions are investigated, for all $q\in(-1,1)$. These are the classical Markov processes corresponding to the noncommutative $q$-Gaussian processes. These processes…

Probability · Mathematics 2019-12-30 Włodzimierz Bryc , Yizao Wang

We prove some efficient inference results concerning estimation of a Ornstein-Uhlenbeck regression model, which is driven by a non-Gaussian stable Levy process and where the output process is observed at high-frequency over a fixed time…

Statistics Theory · Mathematics 2023-01-18 Hiroki Masuda

We consider an Ornstein-Uhlenbeck process with values in R^n driven by a L\'evy process (Z_t) taking values in R^d with d possibly smaller than n. The L\'evy noise can have a degenerate or even vanishing Gaussian component. Under a…

Probability · Mathematics 2014-02-26 Enrico Priola , Jerzy Zabczyk

Stable distributions are a celebrated class of probability laws used in various fields. The $\alpha$-stable process, and its exponentially tempered counterpart, the Classical Tempered Stable (CTS) process, are also prominent examples of…

Probability · Mathematics 2024-12-10 Taher Jalal

We define a random-matrix ensemble given by the infinite-time covariance matrices of Ornstein-Uhlenbeck processes at different temperatures coupled by a Gaussian symmetric matrix. The spectral properties of this ensemble are shown to be in…

Statistical Finance · Quantitative Finance 2015-06-22 Paolo Barucca

We give an explicit representation for the transition law of a tempered stable Ornstein-Uhlenbeck process and use it to develop a rejection sampling algorithm for exact simulation of increments from this process. Our results apply to…

Probability · Mathematics 2020-05-19 Michael Grabchak

It is considered Ornstein-Uhlenbeck process $ x_t = x_0 e^{-\theta t} + \mu (1-e^{-\theta t}) + \sigma \int_0^t e^{-\theta (t-s)} dW_s$, where $x_0 \in R$, $\theta>0$, $ \mu \in R$ and $\sigma > 0$ are parameters. By use values $(z_k)_{k…

Statistics Theory · Mathematics 2016-08-30 Levan Labadze , Gogi Pantsulaia

We present a class of Gauss-Markov processes which can be represented as space-time scaled stationary Ornstein-Uhlenbeck processes defined on the real line. We give several explicit examples of the representation for certain Gauss bridge…

Probability · Mathematics 2019-01-28 Matyas Barczy , Peter Kern

We develop efficient methods for simulating processes of Ornstein-Uhlenbeck type related to the class of $p$-tempered $\alpha$-stable ($\ts$) distributions. Our results hold for both the univariate and multivariate cases and we consider…

Probability · Mathematics 2022-03-02 Michael Grabchak , Piergiacomo Sabino

The paper considers random motion of a point on the surface of a sphere, in the case where the angular velocity is determined by an Ornstein-Uhlenbeck process. The solution is fully characterized by only one dimensionless number, the…

Fluid Dynamics · Physics 2015-05-28 Michael Wilkinson , Alain Pumir

We combine earlier investigations of linear systems with L\'{e}vy fluctuations [Physica {\bf 113A}, 203, (1982)] with recent discussions of L\'{e}vy flights in external force fields [Phys.Rev. {\bf E 59},2736, (1999)]. We give a complete…

chao-dyn · Physics 2015-06-24 Piotr Garbaczewski , Robert Olkiewicz

Multistable L\'evy motions are extensions of L\'evy motions where the stability index is allowed to vary in time. Several constructions of these processes have been introduced recently, based on Poisson and Ferguson-Klass-LePage series…

Probability · Mathematics 2015-03-24 Xiequan Fan , Jacques Lévy Véhel

We construct `self-stabilizing' processes {Z(t), t $\in [t_0,t_1)$}. These are random processes which when `localized', that is scaled around t to a fine limit, have the distribution of an $\alpha$(Z(t))-stable process, where $\alpha$ is…

Probability · Mathematics 2018-09-10 K. J. Falconer , J. Lévy Véhel

Studying sample path behaviour of stochastic fields/processes is a classical research topic in probability theory and related areas such as fractal geometry. To this end, many methods have been developed since a long time in Gaussian…

Probability · Mathematics 2016-06-13 Antoine Ayache , Geoffrey Boutard

A transient stochastic process is considered strongly transient if conditioned on returning to the starting location, the expected time it takes to return the the starting location is finite. We characterize strong transience for a…

Probability · Mathematics 2016-06-14 Jonathon Peterson

In this note we show that the locally stationary wavelet process can be decomposed into a sum of signals, each of which following a moving average process with time-varying parameters. We then show that such moving average processes are…

Methodology · Statistics 2009-01-27 K. Triantafyllopoulos , G. P. Nason