AbstractIn this paper we investigate the problem of parametric estimation for multidimensional linear autonomous homogeneous stochastic differential equations. We prove the Local Asymptotical Normality (LAN) property, find the Maximum Likelihood Estimator (MLE), and prove an asymptotical efficiency of MLE for bounded loss functions, when the observation time tends to infinity
In the Thesis the problem of estimating an unknown parameter in a stochastic dif- ferential equation...
Stochastic partial differential equations (SPDE) are used for stochastic modelling, for in-stance, i...
This paper is concerned with parametric inference for a stochastic differential equation driven by a...
For the stochastic differential equation dX(t) = faX(t) + bX(t \Gamma 1)g dt +dW (t); t 0; the loc...
We consider the problem of maximum likelihood estimation of the common trend parameter for a linear ...
We consider parameter estimation for linear stochastic differential equations with independent exper...
Suppose on a probability space ([Omega], F, P), a partially observable random process (xt, yt), t >=...
The thesis contributes to the numerical analysis on statistical inference for stochastic partial dif...
AbstractSuppose on a probability space (Ω, F, P), a partially observable random process (xt, yt), t ...
Parameter estimation in stochastic differential equations and stochastic partial differential equati...
We investigate asymptotic properties of the maximum likelihood estimator for parameters occuring in ...
We investigate the asymptotic properties of the maximum likelihood estimator and Bayes estimator of ...
A review is given of parametric estimation methods for discretely sampled mul- tivariate diffusion p...
maximum likelihood estimator, asymptotic efficiency, stochastic partial differential equations,
The paper is concerned with the study of the rate of convergence of the distribution of a maximum li...
In the Thesis the problem of estimating an unknown parameter in a stochastic dif- ferential equation...
Stochastic partial differential equations (SPDE) are used for stochastic modelling, for in-stance, i...
This paper is concerned with parametric inference for a stochastic differential equation driven by a...
For the stochastic differential equation dX(t) = faX(t) + bX(t \Gamma 1)g dt +dW (t); t 0; the loc...
We consider the problem of maximum likelihood estimation of the common trend parameter for a linear ...
We consider parameter estimation for linear stochastic differential equations with independent exper...
Suppose on a probability space ([Omega], F, P), a partially observable random process (xt, yt), t >=...
The thesis contributes to the numerical analysis on statistical inference for stochastic partial dif...
AbstractSuppose on a probability space (Ω, F, P), a partially observable random process (xt, yt), t ...
Parameter estimation in stochastic differential equations and stochastic partial differential equati...
We investigate asymptotic properties of the maximum likelihood estimator for parameters occuring in ...
We investigate the asymptotic properties of the maximum likelihood estimator and Bayes estimator of ...
A review is given of parametric estimation methods for discretely sampled mul- tivariate diffusion p...
maximum likelihood estimator, asymptotic efficiency, stochastic partial differential equations,
The paper is concerned with the study of the rate of convergence of the distribution of a maximum li...
In the Thesis the problem of estimating an unknown parameter in a stochastic dif- ferential equation...
Stochastic partial differential equations (SPDE) are used for stochastic modelling, for in-stance, i...
This paper is concerned with parametric inference for a stochastic differential equation driven by a...