In this paper we consider robust and efficient estimators of the shape parameter of symmetric alpha-stable distributions obtained by using the Minimum Density Power Divergence method introduced in Basu, Harris, Hjort and Jones (1998). We established their high asymptotic efficiency and verified these results in simulations. The functionals corresponding to the estimators have bounded influence functions and simulations confirm their robustness when the sample distribution is in a vicinity of the model distribution. The simulations also show that the Minimum Density Power Divergence Estimators (MDPDEs) of the shape parameter of alpha-stable distributions have superior performance over other existing estimators. The high efficiency combined w...
summary:In this article we propose a method of parameters estimation for the class of discrete stabl...
The alpha-stable family of distributions constitutes a generalization of the Gaussian distribution, ...
Robust inference based on the minimization of statistical divergences has proved to be a useful alte...
In this paper we consider robust and efficient estimators of the shape parameter of symmetric alpha-...
Minimum density power divergence estimation provides a general framework for robust statistics, depe...
A minimum divergence estimation method is developed for robust parameter estimation. The proposed ap...
Minimum density power divergence estimation provides a general framework for robust statistics depen...
<div><p>The density power divergence (DPD) measure, defined in terms of a single parameter <i>α</i>,...
The aim of robust statistics is to develop statistical procedures which are not unduly influenced by...
The aim of robust statistics is to develop statistical procedures which are not unduly influenced by...
We propose new nonparametric, consistent Renyi-alpha and Tsallis-alpha divergence estimators for con...
summary:Point estimators based on minimization of information-theoretic divergences between empirica...
AbstractAlthough there are several software products dealing with the issue of simulating and estima...
Here we investigate the robustness properties of the class of minimum power divergence estimators fo...
The density power divergence, indexed by a single tuning parameter α, has proved to be a very useful...
summary:In this article we propose a method of parameters estimation for the class of discrete stabl...
The alpha-stable family of distributions constitutes a generalization of the Gaussian distribution, ...
Robust inference based on the minimization of statistical divergences has proved to be a useful alte...
In this paper we consider robust and efficient estimators of the shape parameter of symmetric alpha-...
Minimum density power divergence estimation provides a general framework for robust statistics, depe...
A minimum divergence estimation method is developed for robust parameter estimation. The proposed ap...
Minimum density power divergence estimation provides a general framework for robust statistics depen...
<div><p>The density power divergence (DPD) measure, defined in terms of a single parameter <i>α</i>,...
The aim of robust statistics is to develop statistical procedures which are not unduly influenced by...
The aim of robust statistics is to develop statistical procedures which are not unduly influenced by...
We propose new nonparametric, consistent Renyi-alpha and Tsallis-alpha divergence estimators for con...
summary:Point estimators based on minimization of information-theoretic divergences between empirica...
AbstractAlthough there are several software products dealing with the issue of simulating and estima...
Here we investigate the robustness properties of the class of minimum power divergence estimators fo...
The density power divergence, indexed by a single tuning parameter α, has proved to be a very useful...
summary:In this article we propose a method of parameters estimation for the class of discrete stabl...
The alpha-stable family of distributions constitutes a generalization of the Gaussian distribution, ...
Robust inference based on the minimization of statistical divergences has proved to be a useful alte...