summary:On bounded or unbounded intervals of the real line, we introduce classes of regular statistical families, called Johnson families because they are obtained using generalized Johnson transforms. We study in a rigorous manner the formerly introduced concept of core function of a distribution from a Johnson family, which is a modification of the well known score function and which in a one-to-one manner represents the distribution. Further, we study Johnson parametrized families obtained by Johnson transforms of location and scale families, where the location is replaced by a new parameter called Johnson location. We show that Johnson parametrized families contain many important statistical models. One form appropriately normalized $L_...
In the past couple of years, statistical models have been extensively used in applied areas for anal...
In this paper, we propose a new method for generating families of continuous distributions based on ...
summary:Standard properties of $\phi$-divergences of probability measures are widely applied in vari...
summary:On bounded or unbounded intervals of the real line, we introduce classes of regular statisti...
summary:We propose a simple method of construction of new families of $\phi$%-divergences. This meth...
We demonstrate that questions of convergence and divergence regarding shapes of distributions can be...
Let Z1,..., Zn be a random sample of size n2 from a d-variate continuous distribution function H, an...
Divergence measures are widely used in various applications of pattern recognition, signal processin...
summary:This paper deals with four types of point estimators based on minimization of information-th...
Univariate continuous distributions are one of the fundamental components on which statistical model...
In this paper, we propose a generalization of Rényi divergence, and then we investigate its induced ...
AbstractLetZ1, …, Znbe a random sample of sizen⩾2 from ad-variate continuous distribution functionH,...
We describe a framework to build distances by measuring the tightness of inequalities and introduce ...
There are many applications that benefit from computing the exact divergence between 2 discrete prob...
The power divergence (PD) and the density power divergence (DPD) families have proven to be useful t...
In the past couple of years, statistical models have been extensively used in applied areas for anal...
In this paper, we propose a new method for generating families of continuous distributions based on ...
summary:Standard properties of $\phi$-divergences of probability measures are widely applied in vari...
summary:On bounded or unbounded intervals of the real line, we introduce classes of regular statisti...
summary:We propose a simple method of construction of new families of $\phi$%-divergences. This meth...
We demonstrate that questions of convergence and divergence regarding shapes of distributions can be...
Let Z1,..., Zn be a random sample of size n2 from a d-variate continuous distribution function H, an...
Divergence measures are widely used in various applications of pattern recognition, signal processin...
summary:This paper deals with four types of point estimators based on minimization of information-th...
Univariate continuous distributions are one of the fundamental components on which statistical model...
In this paper, we propose a generalization of Rényi divergence, and then we investigate its induced ...
AbstractLetZ1, …, Znbe a random sample of sizen⩾2 from ad-variate continuous distribution functionH,...
We describe a framework to build distances by measuring the tightness of inequalities and introduce ...
There are many applications that benefit from computing the exact divergence between 2 discrete prob...
The power divergence (PD) and the density power divergence (DPD) families have proven to be useful t...
In the past couple of years, statistical models have been extensively used in applied areas for anal...
In this paper, we propose a new method for generating families of continuous distributions based on ...
summary:Standard properties of $\phi$-divergences of probability measures are widely applied in vari...