In this paper statistical properties of estimators of drift parameters for diffusion processes are studied by modern numerical methods for stochastic differential equations. This is a particularly useful method for discrete time samples, where estimators can be constructed by making discrete time approximations to the stochastic integrals appearing in the maximum likelihood estimators for continuously observed diffusions. A review is given of the necessary theory for parameter estimation for diffusion processes and for simulation of diffusion processes. Three examples are studied
This paper considers parameter estimation for continuous-time diffusion processes which are commonly...
Stochastic differential equations often provide a convenient way to describe the dynamics of economi...
M.Sc. (Mathematical Statistics)Stochastic Differential Equations (SDE’s) are commonly found in most ...
A short review of diffusion parameter estimations methods from discrete observations is presented. ...
A short review of diffusion parameter estimations methods from discrete observations is presented. ...
Parameter estimation problems of diffusion models are discussed. The problems of maximum likelihood ...
This paper introduces a family of recursively defined estimators of the parameters of a diffusion pr...
This paper is concerned with the approximation of the maximum likelihood estimator of parameter in t...
This paper is concerned with the approximation of the maximum likelihood estimator of parameter in t...
of complicated stochastic models such as the diffusion process, simulations of the model play an imp...
Noisy discretely observed diffusion processes with random drift function parameters are considered. ...
This paper considers parameter estimation for continuous-time diffusion processes which are commonly...
This paper considers parameter estimation for continuous-time diffusion processes which are commonly...
The maximum likelihood approach is adapted to the problem of estimation of drift and diffusion funct...
In applications such as molecular dynamics it is of interest to fit Smoluchowski and Langevin equat...
This paper considers parameter estimation for continuous-time diffusion processes which are commonly...
Stochastic differential equations often provide a convenient way to describe the dynamics of economi...
M.Sc. (Mathematical Statistics)Stochastic Differential Equations (SDE’s) are commonly found in most ...
A short review of diffusion parameter estimations methods from discrete observations is presented. ...
A short review of diffusion parameter estimations methods from discrete observations is presented. ...
Parameter estimation problems of diffusion models are discussed. The problems of maximum likelihood ...
This paper introduces a family of recursively defined estimators of the parameters of a diffusion pr...
This paper is concerned with the approximation of the maximum likelihood estimator of parameter in t...
This paper is concerned with the approximation of the maximum likelihood estimator of parameter in t...
of complicated stochastic models such as the diffusion process, simulations of the model play an imp...
Noisy discretely observed diffusion processes with random drift function parameters are considered. ...
This paper considers parameter estimation for continuous-time diffusion processes which are commonly...
This paper considers parameter estimation for continuous-time diffusion processes which are commonly...
The maximum likelihood approach is adapted to the problem of estimation of drift and diffusion funct...
In applications such as molecular dynamics it is of interest to fit Smoluchowski and Langevin equat...
This paper considers parameter estimation for continuous-time diffusion processes which are commonly...
Stochastic differential equations often provide a convenient way to describe the dynamics of economi...
M.Sc. (Mathematical Statistics)Stochastic Differential Equations (SDE’s) are commonly found in most ...