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Related papers: Gaussian and Hermite Ornstein-Uhlenbeck processes

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We consider a positive stationary generalized Ornstein--Uhlenbeck process \[V_t=\mathrm{e}^{-\xi_t}\biggl(\int_0^t\mathrm{e}^{\xi_{s-}}\ ,\mathrm{d}\eta_s+V_0\biggr)\qquadfor t\geq0,\] and the increments of the integrated generalized…

Statistics Theory · Mathematics 2010-02-24 Vicky Fasen

Starting from the notion of multivariate fractional Brownian Motion introduced in [F. Lavancier, A. Philippe, and D. Surgailis. Covariance function of vector self-similar processes. Statistics & Probability Letters, 2009] we define a…

Probability · Mathematics 2025-09-16 Ranieri Dugo , Giacomo Giorgio , Paolo Pigato

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

In this paper, we consider an inference problem for an Ornstein-Uhlenbeck process driven by a general one-dimensional centered Gaussian process $(G_t)_{t\ge 0}$. The second order mixed partial derivative of the covariance function $ R(t,\,…

Probability · Mathematics 2020-02-25 Yong Chen , Hongjuan Zhou

We consider the class of all stationary Gaussian process with explicit parametric spectral density. Under some conditions on the autocovariance function, we defined a GMM estimator that satisfies consistency and asymptotic normality, using…

Statistics Theory · Mathematics 2017-01-18 Luis A. Barboza , Frederi G. Viens

In this paper, we consider the statistical inference of the drift parameter $\theta$ of non-ergodic Ornstein-Uhlenbeck~(O-U) process driven by a general Gaussian process $(G_t)_{t\ge 0}$. When $H \in (0, \frac 12) \cup (\frac 12,1) $ the…

Statistics Theory · Mathematics 2022-07-28 Yanping Lu

\noindent \textbf{Abstract}: We consider the parameter estimation problem for the Ornstein-Uhlenbeck process $X$ driven by a fractional Ornstein-Uhlenbeck process $V$, i.e. the pair of processes defined by the non-Markovian continuous-time…

Probability · Mathematics 2016-10-14 Brahim El Onsy , Khalifa Es-Sebaiy , Frederi G. Viens

In Chen and Zhou 2021, they consider an inference problem for an Ornstein-Uhlenbeck process driven by a general one-dimensional centered Gaussian process $(G_t)_{t\ge 0}$. The second order mixed partial derivative of the covariance function…

Statistics Theory · Mathematics 2021-12-30 Yong Chen , Xiangmeng Gu , Ying Li

We consider the problem of frequency estimation of the periodic signal multiplied by a stationary Gaussian process (Ornstein-Uhlenbeck) and observed in the presence of the white Gaussian noise. We show the consistency and asymptotic…

Statistics Theory · Mathematics 2017-10-10 O. V. Chernoyarov , Yu. A. Kutoyants

We propose a non-Gaussian operator-valued extension of the Barndorff-Nielsen and Shephard stochastic volatility dynamics, defined as the square-root of an operator-valued Ornstein-Uhlenbeck process with Levy noise and bounded drift. We…

Probability · Mathematics 2015-06-25 Fred Espen Benth , Barbara Ruediger , Andre Suess

The Gaussian mixed-effects model driven by a stationary integrated Ornstein-Uhlenbeck process has been used for analyzing longitudinal data having an explicit and simple serial-correlation structure in each individual. However, the…

Statistics Theory · Mathematics 2023-11-07 Takumi Imamura , Hiroki Masuda , Hayato Tajima

In this article we study the asymptotic behaviour of the realized quadratic variation of a process $\int_{0}^{t}u_{s}dG^{H}_{s}$, where $u$ is a $\beta$-H\"older continuous process with $\beta >1-H$ and $G^H$ is a self-similar Gaussian…

Probability · Mathematics 2019-09-17 Salwa Bajja , Qian Yu

This paper studies Langevin equation with random damping due to multiplicative noise and its solution. Two types of multiplicative noise, namely the dichotomous noise and fractional Gaussian noise are considered. Their solutions are…

Statistical Mechanics · Physics 2017-11-30 Chai Hok Eab , S. C. Lim

Consider a periodic, mean-reverting Ornstein-Uhlenbeck process $X=\{X_t,t\geq0\}$ of the form $d X_{t}=\left(L(t)+\alpha X_{t}\right) d t+ dB^H_{t}, \quad t \geq 0$, where $L(t)=\sum_{i=1}^{p}\mu_i\phi_i (t)$ is a periodic parametric…

Probability · Mathematics 2020-09-02 Rachid Belfadli , Khalifa Es-Sebaiy , Fatima-Ezzahra Farah

We derive the path-integral representation of the fractional Ornstein-Uhlenbeck process driven by Riemann-Liouville fractional Gaussian noise, for both the subdiffusive and superdiffusive regimes. We express the corresponding action, which…

Statistical Mechanics · Physics 2025-12-02 Bing Miao , Gleb Oshanin , Luca Peliti

In this article, we study the problem of parameter estimation for a discrete Ornstein - Uhlenbeck model driven by Poisson fractional noise. Based on random walk approximation for the noise, we study least squares and maximum likelihood…

Statistics Theory · Mathematics 2017-12-15 Héctor Araya , Natalia Bahamonde , Tania Roa , Soledad Torres

We consider an Ornstein-Uhleneck (OU) process associated to self-normalised sums in i.i.d. symmetric random variables from the domain of attraction of $N(0, 1)$ distribution. We proved the self-normalised sums converge to the OU process (in…

Probability · Mathematics 2013-02-04 Gopal K. Basak , Amites Dasgupta

We study the stationary fluctuations of independent run-and-tumble particles. We prove that the joint densities of particles with given internal state converges to an infinite dimensional Ornstein-Uhlenbeck process. We also consider an…

Probability · Mathematics 2024-03-13 Frank Redig , Hidde van Wiechen

The paper is devoted to three-parametric self-similar Gaussian Volterra processes that generalize fractional Brownian motion. We study the asymptotic growth of such processes and the properties of long- and short-range dependence. Then we…

Statistics Theory · Mathematics 2023-02-08 Yuliya Mishura , Kostiantyn Ralchenko , Sergiy Shklyar

In this study, we generalize a problem of sampling a scalar Gauss Markov Process, namely, the Ornstein-Uhlenbeck (OU) process, where the samples are sent to a remote estimator and the estimator makes a causal estimate of the observed…

Information Theory · Computer Science 2022-02-14 Tasmeen Zaman Ornee , Yin Sun
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