It is shown that the suitably normalized maximum likelihood estimators of some parameters of multidimensional Ornstein-Uhlenbeck processes with coefficient matrix of a special structure have exactly a normal distribution. This result provides a generalization to an arbitrary dimension of the well-known behaviour of the estimator of the period of a complex AR(1) process (see [2], [3], [4], [5], [8], [9])
Abstract. We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown...
https://doi.org/10.1111/sjos.12552Generalizations of the Ornstein-Uhlenbeck process defined through ...
We consider an estimation problem with observations from a Gaussian process. The problem arises from...
AbstractIt is shown that the suitably normalized maximum likelihood estimators of some parameters of...
It is shown that the suitably normalized maximum likelihood estimators of some parameters of multidi...
AbstractIt is shown that the suitably normalized maximum likelihood estimates of the parameters of p...
AbstractThe exact distribution of the maximum-likelihood estimator of the drift (damping) parameter ...
32 pagesInternational audienceIn this paper we investigate the large-sample behaviour of the maximum...
AbstractThe maximum likelihood estimator of a parameter vector is obtained for some multidimensional...
This paper considers parameter estimation in the Ornstein–Uhlenbeck process observed in the presence...
We study moderate deviations for maximum likelihood estimators of parameters in generalized squared ...
AbstractAn asymptotic analysis is presented for estimation in the three-parameter Ornstein-Uhlenbeck...
We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown parameter...
In this thesis, the extension of the Ornstein-Uhlenbeck process is studied by first driving this mo...
In this article we propose a maximum likelihood methodology to estimate the parameters of a one-dime...
Abstract. We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown...
https://doi.org/10.1111/sjos.12552Generalizations of the Ornstein-Uhlenbeck process defined through ...
We consider an estimation problem with observations from a Gaussian process. The problem arises from...
AbstractIt is shown that the suitably normalized maximum likelihood estimators of some parameters of...
It is shown that the suitably normalized maximum likelihood estimators of some parameters of multidi...
AbstractIt is shown that the suitably normalized maximum likelihood estimates of the parameters of p...
AbstractThe exact distribution of the maximum-likelihood estimator of the drift (damping) parameter ...
32 pagesInternational audienceIn this paper we investigate the large-sample behaviour of the maximum...
AbstractThe maximum likelihood estimator of a parameter vector is obtained for some multidimensional...
This paper considers parameter estimation in the Ornstein–Uhlenbeck process observed in the presence...
We study moderate deviations for maximum likelihood estimators of parameters in generalized squared ...
AbstractAn asymptotic analysis is presented for estimation in the three-parameter Ornstein-Uhlenbeck...
We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown parameter...
In this thesis, the extension of the Ornstein-Uhlenbeck process is studied by first driving this mo...
In this article we propose a maximum likelihood methodology to estimate the parameters of a one-dime...
Abstract. We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown...
https://doi.org/10.1111/sjos.12552Generalizations of the Ornstein-Uhlenbeck process defined through ...
We consider an estimation problem with observations from a Gaussian process. The problem arises from...