The process $(G_t) _ {t\in [0, T]} $ is referred to as a fractional Gaussian process if the first-
order partial derivative of the difference between its covariance function and that of the …

In this paper, we consider the Ornstein–Uhlenbeck (OU) process defined as solution to the
equation d X t=− 𝜃 X tdt+ d G t, X 0= 0, where {G t, t≥ 0} is a Gaussian process with …

While the statistical inference of first-order autoregressive processes driven by independent
and identically distributed noises has a long history, the statistical analysis for first-order …

The aim of this paper is twofold. First, it offers a novel formula to calculate the inner product
of the bounded variation function in the Hilbert space $\mathcal {H} $ associated with the …

\bad This paper gives a survey of several directions of research connected with Chebyshev--
Hermite polynomials on finite-dimensional and infinite-dimensional spaces, in particular, of …

This paper deals with the rate of convergence for the central limit theorem of estimators of
the drift coefficient, denoted θ, for the Ornstein-Uhlenbeck process X:={X t, t≥ 0} observed at …

In this paper, we study bounds for the total variation distance between distributions of
second order polynomials in normal random variables provided that they essentially depend …

In this paper, we are interested in the rate of convergence for the central limit theorem of the
maximum likelihood estimator of the drift coefficient for a stochastic partial differential …

The aim of this work is to estimate the drift coefficient of a fractional heat equation driven by
an additive space-time noise using the Maximum likelihood estimator (MLE). In the first part …

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 …