AbstractIt 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 behavior of the estimator of the period of a complex AR(1) process
AbstractAn asymptotic analysis is presented for estimation in the three-parameter Ornstein-Uhlenbeck...
This paper considers the problem of estimating the autoregressive parameter in discretely observed O...
Abstract. We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown...
It is shown that the suitably normalized maximum likelihood estimators of some parameters of multidi...
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 maximum likelihood estimator of a parameter vector is obtained for some multidimensional...
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...
This paper considers parameter estimation in the Ornstein–Uhlenbeck process observed in the presence...
https://doi.org/10.1111/sjos.12552Generalizations of the Ornstein-Uhlenbeck process defined through ...
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...
We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown parameter...
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...
This paper considers the problem of estimating the autoregressive parameter in discretely observed O...
Abstract. We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown...
It is shown that the suitably normalized maximum likelihood estimators of some parameters of multidi...
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 maximum likelihood estimator of a parameter vector is obtained for some multidimensional...
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...
This paper considers parameter estimation in the Ornstein–Uhlenbeck process observed in the presence...
https://doi.org/10.1111/sjos.12552Generalizations of the Ornstein-Uhlenbeck process defined through ...
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...
We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown parameter...
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...
This paper considers the problem of estimating the autoregressive parameter in discretely observed O...
Abstract. We investigate the asymptotic behavior of the maximum likelihood estimators of the unknown...