Part 7: AlgorithmsInternational audienceThe moment method (MM) estimator for the shape parameter of generalized Gaussian distribution (GGD) assume asymptotic case when there is available infinite number of observations, but with the smaller sample size the variance of the estimator increases and the moment method equation may not converge to a real solution for some sample sets. The higher order moments can be expanded into series in the moment method equation leading to a drop in the relative mean square error (RMSE) and assuring a solution for a smaller sample size comparing to the moment method without modification
We describe an intuitive, simple, and systematic approach to generating moment conditions for genera...
Generalized Method of Moments(GMM) is an estimation procedure that allows econometric models especia...
Using many moment conditions can improve efficiency but makes the usual generalized method of moment...
Part 7: AlgorithmsInternational audienceThe moment method (MM) estimator for the shape parameter of ...
Most estimators of the shape parameter of generalized Gaussian distribution (GGD) assume asymptotic ...
Four new moment-based estimators are proposed for the shape parameter of the generalized Gaussian di...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimato...
The generalized method of moments (GMM) is a very popular estimation and inference procedure based o...
This paper proposes an estimator combining empirical likelihood (EL) and the generalized method of m...
Procedures based on the Generalized Method of Moments (GMM) are basic tools in modern econometrics. ...
This article establishes the asymptotic distributions of generalized method of moments (GMM) estima-...
In this article we propose for a generalized gamma population method of moment estimators for the th...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
The generalized method of moments (GMM) is the centrepiece of semiparametric estimation frameworks. ...
This paper describes estimation methods, based on the generalized method of moments (GMM), applicabl...
We describe an intuitive, simple, and systematic approach to generating moment conditions for genera...
Generalized Method of Moments(GMM) is an estimation procedure that allows econometric models especia...
Using many moment conditions can improve efficiency but makes the usual generalized method of moment...
Part 7: AlgorithmsInternational audienceThe moment method (MM) estimator for the shape parameter of ...
Most estimators of the shape parameter of generalized Gaussian distribution (GGD) assume asymptotic ...
Four new moment-based estimators are proposed for the shape parameter of the generalized Gaussian di...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimato...
The generalized method of moments (GMM) is a very popular estimation and inference procedure based o...
This paper proposes an estimator combining empirical likelihood (EL) and the generalized method of m...
Procedures based on the Generalized Method of Moments (GMM) are basic tools in modern econometrics. ...
This article establishes the asymptotic distributions of generalized method of moments (GMM) estima-...
In this article we propose for a generalized gamma population method of moment estimators for the th...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
The generalized method of moments (GMM) is the centrepiece of semiparametric estimation frameworks. ...
This paper describes estimation methods, based on the generalized method of moments (GMM), applicabl...
We describe an intuitive, simple, and systematic approach to generating moment conditions for genera...
Generalized Method of Moments(GMM) is an estimation procedure that allows econometric models especia...
Using many moment conditions can improve efficiency but makes the usual generalized method of moment...