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We study the bias and the mean-squared error of the maximum likelihood estimators (MLE) of parameters associated with a two-parameter mean-reverting process for a finite time $T$. Using the likelihood ratio process, we derive the…

Statistics Theory · Mathematics 2025-04-01 Jun S. Han , Nino Kordzakhia

We consider the problem of modelling restricted interactions between continuously-observed time series as given by a known static graph (or network) structure. For this purpose, we define a parametric multivariate Graph Ornstein-Uhlenbeck…

Statistics Theory · Mathematics 2021-07-08 Valentin Courgeau , Almut E. D. Veraart

We study statistical inference of the drift parameters for the Volterra Ornstein-Uhlenbeck process on R in the ergodic regime. For continuous-time observations, we derive the corresponding maximum likelihood estimators and show that they…

Statistics Theory · Mathematics 2025-09-30 Mohamed Ben Alaya , Martin Friesen , Jonas Kremer

We consider a problem of parameter estimation for the state space model described by linear stochastic differential equations. We assume that an unobservable Ornstein-Uhlenbeck process drives another observable process by the linear…

Statistics Theory · Mathematics 2022-03-25 Masahiro Kurisaki

We investigate the asymptotic properties of the minimum $L_1$-norm estimator of the drift parameter for fractional Ornstein-Uhlenbeck type process driven by a Hermite process.

Statistics Theory · Mathematics 2025-11-25 B. L. S. Prakasa Rao

We obtain the almost sure strong consistency and the Berry-Esseen type bound for the maximum likelihood estimator Ln of the ensemble L for determinantal point processes (DPPs), strengthening and completing previous work initiated in Brunel,…

Statistics Theory · Mathematics 2024-07-10 Yaozhong Hu , Haiyi Shi

We investigate the sharp large deviation properties of the energy and the maximum likelihood estimator for the Ornstein-Uhlenbeck process driven by a fractional Brownian motion with Hurst index greater than one half.

Probability · Mathematics 2008-12-19 Bernard Bercu , Laure Coutin , Nicolas Savy

The goal of this paper is to construct ergodic estimators for the parameters in the double exponential Ornstein-Uhlenbeck process, observed at discrete time instants with time step size h. The existence and uniqueness, the strong…

Statistics Theory · Mathematics 2021-11-19 Yaozhong Hu , Neha Sharma

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

We investigate the asymptotic properties of the minimum $L_1$-norm estimator of the drift parameter for fractional Ornstein-Uhlenbeck type process driven by a general Gaussian process.

Probability · Mathematics 2022-08-10 B. L. S. Prakasa Rao

The Ornstein-Uhlenbeck process is interpreted as Brownian motion in a harmonic potential. This Gaussian Markov process has a bounded variance and admits a stationary probability distribution, in contrast to the standard Brownian motion. It…

Statistical Mechanics · Physics 2023-06-07 Pece Trajanovski , Petar Jolakoski , Kiril Zelenkovski , Alexander Iomin , Ljupco Kocarev , Trifce Sandev

In this paper we introduce the well-balanced L\'{e}vy driven Ornstein-Uhlenbeck process as a moving average process of the form $X_t=\int \exp(-\lambda |t-u|)dL_u$. In contrast to L\'{e}vy driven Ornstein-Uhlenbeck processes the…

Probability · Mathematics 2013-01-08 Alexander Schnurr , Jeannette H. C. Woerner

Our goal is to establish large deviations and concentration inequalities for the maximum likelihood estimator of the drift parameter of the Ornstein-Uhlenbeck process without tears. We propose a new strategy to establish large deviation…

Statistics Theory · Mathematics 2016-02-09 Bernard Bercu , Adrien Richou

We investigate ergodic properties of generalized Ornstein--Uhlenbeck processes. In particular, we provide sufficient conditions for ergodicity, and for subexponential and exponential convergence to the invariant probability measure. We use…

Probability · Mathematics 2016-06-06 Peter Kevei

We study sparsity-regularized maximum likelihood estimation for the drift parameter of high-dimensional non-stationary Ornstein--Uhlenbeck processes given repeated measurements of i.i.d. paths. In particular, we show that Lasso and Slope…

Statistics Theory · Mathematics 2025-10-29 Shogo Nakakita

We consider the fractional Ornstein-Uhlenbeck process with an unknown drift parameter and known Hurst parameter $H$. We propose a new method to test the hypothesis of the sign of the parameter and prove the consistency of the test. Contrary…

Probability · Mathematics 2016-04-12 Alexander Kukush , Yuliya Mishura , Kostiantyn Ralchenko

In the present paper we study the asymptotic behavior of the auto-covariance function for Ornstein-Uhlenbeck (OU) processes driven by Gaussian noises with stationary and non-stationary increments and for Hermite OU processes. Our results…

Probability · Mathematics 2022-01-19 Khalifa Es-Sebaiy

The main objective of this work is to study a natural class of catalytic Ornstein-Uhlenbeck (O-U) processes with a measure-valued random catalyst, for example, super-Brownian motion. We relate this to the class of affine processes that…

Probability · Mathematics 2014-11-19 Juan-Manuel Perez-Abarca , Donald A. Dawson

New results on functional prediction of the Ornstein-Uhlenbeck process in an autoregressive Hilbert-valued and Banach-valued frameworks are derived. Specifically, consistency of the maximum likelihood estimator of the autocorrelation…

Statistics Theory · Mathematics 2018-09-05 J. Álvarez-Liébana , D. Bosq , M. D. Ruiz-Medina

We consider a transformed Ornstein-Uhlenbeck process model that can be a good candidate for modelling real-life processes characterized by a combination of time-reverting behaviour with heavy distribution tails. We begin with presenting the…

Probability · Mathematics 2011-03-01 K. Borovkov , G. Decrouez