Add to ORKGThe aim of this paper is the derivation of the maximum likelihood estimators of the Marshal-Olkin copula. This copula comes from the Marshall-Olkin Bivariate Exponential (MOBE) distribution, that has been proposed in reliability analysis to study complex systems in which the components are not independent and it is also used in the extreme value theory. We find the likelihood estimators considering the cases of complete and Type-II censored samples. The Marshall-Olkin copula likelihood function is presented in both cases. A simulation study in the particular context of the MOBE shows the properties of the proposed estimators for full or censored data. Finally, we analyze some data sets for illustrative purpose
summary:In the paper we investigate properties of maximum pseudo-likelihood estimators for the copul...
A copula density is the joint probability density function (PDF) of a random vector with uniform mar...
The paper considers likelihood-based estimation of multivariate models, in which only marginal distr...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
In this paper we discuss the problem on parametric and non parametric estimation of the distributio...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
Extreme value copulas are the limiting copulas of component-wise maxima. A bivariate extreme value c...
Quantitative studies in many fields involve the analysis of multivariate data of diverse types, incl...
This article deals with robust inference for parametric copula models. Estimation using canonical ma...
Whenever multivariate data has to be modelled, a copula approach naturally comes into play. As a dis...
A copula density is the joint probability density function (PDF) of a random vector with uniform mar...
A copula density is the joint probability density function (PDF) of a random vector with uniform mar...
We study a new distribution called the Marshall-Olkin Power Lomax distribution. A comprehensive acco...
In this article, we defined and studied a new distribution for modeling extreme value. Some of its m...
summary:In the paper we investigate properties of maximum pseudo-likelihood estimators for the copul...
A copula density is the joint probability density function (PDF) of a random vector with uniform mar...
The paper considers likelihood-based estimation of multivariate models, in which only marginal distr...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
In this paper we discuss the problem on parametric and non parametric estimation of the distributio...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
In this paper we discuss the problem on parametric and non parametric estimation of the distribution...
Extreme value copulas are the limiting copulas of component-wise maxima. A bivariate extreme value c...
Quantitative studies in many fields involve the analysis of multivariate data of diverse types, incl...
This article deals with robust inference for parametric copula models. Estimation using canonical ma...
Whenever multivariate data has to be modelled, a copula approach naturally comes into play. As a dis...
A copula density is the joint probability density function (PDF) of a random vector with uniform mar...
A copula density is the joint probability density function (PDF) of a random vector with uniform mar...
We study a new distribution called the Marshall-Olkin Power Lomax distribution. A comprehensive acco...
In this article, we defined and studied a new distribution for modeling extreme value. Some of its m...
summary:In the paper we investigate properties of maximum pseudo-likelihood estimators for the copul...
A copula density is the joint probability density function (PDF) of a random vector with uniform mar...
The paper considers likelihood-based estimation of multivariate models, in which only marginal distr...