This paper deals with the identification and maximum likelihood estimation of the parameters of a stochastic differential equation from discrete time sampling. Score function and maximum likelihood equations are derived explicitly. The stochastic differential equation system is extended to allow for random effects and the analysis of panel data. In addition, we investigate the identifiability of the continuous time parameters, in particular the impact of the inclusion of exogenous variables
This paper presents theory, algorithms and validation results for system identification of continuou...
Stochastic system identification is of great interest in the areas of control and communication. In ...
Stochastic system identification is of great interest in the areas of control and communication. In ...
This paper deals with the identification and maximum likelihood estimation of the parameters of a st...
This paper deals with the identification and maximum likelihood estimation of the parameters of a st...
In this paper we consider the problem of estimating parameters in ordinary differential equations gi...
In this paper we consider the problem of estimating parameters in ordinary differential equations gi...
This contribution reviews theory, algorithms, and validation results for system identification of co...
Parameter estimation in stochastic differential equations and stochastic partial differential equati...
The problem of estimating continuous--time stochastic models from discrete-- time data is addressed....
The unknown structural parameters of a continuous/discrete state space model are estimated by maximu...
This paper presents theory, algorithms and validation results for system identification of continuou...
This contribution reviews theory, algorithms, and validation results for system identification of co...
This article gives a short review of key issues and of existing estimation methods in differen-tial ...
This contribution reviews theory, algorithms, and validation results for system identification of co...
This paper presents theory, algorithms and validation results for system identification of continuou...
Stochastic system identification is of great interest in the areas of control and communication. In ...
Stochastic system identification is of great interest in the areas of control and communication. In ...
This paper deals with the identification and maximum likelihood estimation of the parameters of a st...
This paper deals with the identification and maximum likelihood estimation of the parameters of a st...
In this paper we consider the problem of estimating parameters in ordinary differential equations gi...
In this paper we consider the problem of estimating parameters in ordinary differential equations gi...
This contribution reviews theory, algorithms, and validation results for system identification of co...
Parameter estimation in stochastic differential equations and stochastic partial differential equati...
The problem of estimating continuous--time stochastic models from discrete-- time data is addressed....
The unknown structural parameters of a continuous/discrete state space model are estimated by maximu...
This paper presents theory, algorithms and validation results for system identification of continuou...
This contribution reviews theory, algorithms, and validation results for system identification of co...
This article gives a short review of key issues and of existing estimation methods in differen-tial ...
This contribution reviews theory, algorithms, and validation results for system identification of co...
This paper presents theory, algorithms and validation results for system identification of continuou...
Stochastic system identification is of great interest in the areas of control and communication. In ...
Stochastic system identification is of great interest in the areas of control and communication. In ...