In this paper, we consider the univariate generalized t (GT) distribution, which is introduced by McDonald and Newey ((1988) Partially adaptive estimation of regression models via the generalized t distribution. Econometric Theory 4:428-457.). We show that the maximum likelihood estimators for the location and the scale parameters of a GT distribution with known shape parameters can provide alternative robust estimators for the location and scale parameters of a data set. We investigate the existence and the uniqueness of the maximum likelihood estimators. We show that the likelihood function can be unimodal or multimodal depending on the different choices of the shape parameters
WOS: 000269603600004In this paper, we consider the family of skew generalized t (SGT) distributions ...
The paper considers statistical inference for R = P(X \u3c Y) in the case when both X and Y have gen...
In this paper, we study the robustness properties of several procedures for the joint estimation of ...
WOS: 000184372700002In this paper, we consider the univariate generalized I (GT) distribution, which...
This paper considers M-estimators of regression parameters that make use of a generalized functional...
We propose robust estimators of the generalized log-gamma distribution and, more generally, of locat...
Joint modelling of location and scale parameters has generally been confined to exponential families...
AbstractDawid (1973,Biometrika60, 664–666) stated conditions in the univariate location model with k...
Examining the robustness properties of maximum likelihood (ML) estimators of parameters in exponenti...
We propose robust estimators of the generalized log-gamma distribution and, more generally, of locat...
This article proposes a robust way to estimate the scale parameter of a generalised centered Gaussia...
A three parameter (location, scale, shape) generalization of the lo- gistic distribution is fitted t...
In this study, we consider the estimation of the location parameter ...
In this paper, we consider the family of skew generalized t (SGT) distributions originally introduce...
This thesis considers location and scale parameter modelling of the heteroscedastic t-distribution. ...
WOS: 000269603600004In this paper, we consider the family of skew generalized t (SGT) distributions ...
The paper considers statistical inference for R = P(X \u3c Y) in the case when both X and Y have gen...
In this paper, we study the robustness properties of several procedures for the joint estimation of ...
WOS: 000184372700002In this paper, we consider the univariate generalized I (GT) distribution, which...
This paper considers M-estimators of regression parameters that make use of a generalized functional...
We propose robust estimators of the generalized log-gamma distribution and, more generally, of locat...
Joint modelling of location and scale parameters has generally been confined to exponential families...
AbstractDawid (1973,Biometrika60, 664–666) stated conditions in the univariate location model with k...
Examining the robustness properties of maximum likelihood (ML) estimators of parameters in exponenti...
We propose robust estimators of the generalized log-gamma distribution and, more generally, of locat...
This article proposes a robust way to estimate the scale parameter of a generalised centered Gaussia...
A three parameter (location, scale, shape) generalization of the lo- gistic distribution is fitted t...
In this study, we consider the estimation of the location parameter ...
In this paper, we consider the family of skew generalized t (SGT) distributions originally introduce...
This thesis considers location and scale parameter modelling of the heteroscedastic t-distribution. ...
WOS: 000269603600004In this paper, we consider the family of skew generalized t (SGT) distributions ...
The paper considers statistical inference for R = P(X \u3c Y) in the case when both X and Y have gen...
In this paper, we study the robustness properties of several procedures for the joint estimation of ...