AbstractLet X1,…,Xn be a random sample from an absolutely continuous distribution with non-negative support, and let Y1,…,Yn be mutually independent lifetimes with proportional hazard rates. Let also X(1)<⋯<X(n) and Y(1)<⋯<Y(n) be their associated order statistics. It is shown that the pair (X(1),X(n)) is then more dependent than the pair (Y(1),Y(n)), in the sense of the right-tail increasing ordering of Avérous and Dortet-Bernadet [LTD and RTI dependence orderings, Canad. J. Statist. 28 (2000) 151–157]. Elementary consequences of this fact are highlighted
Given a random sample from a continuous variable, it is observed that the copula linking any pair of...
AbstractLet X=(X1,X2,…,Xn) be a random vector, and denote by X1:n,X2:n,…,Xn:n the corresponding orde...
We study the characteristics of the Pickands' dependence function for bivariate extreme distribution...
Let X1,…,Xn be mutually independent exponential random variables with distinct hazard rates λ1,…,λn ...
Abstract. Independent random variables Y1,..., Yn belongs to the pro-portional reversed hazard rate ...
AbstractLet (Xi, Yi) i=1, 2, …, n be n independent and identically distributed random variables from...
AbstractIfX1, …,Xnare random variables we denote byX(1)⩽X(2)⩽…⩽X(n)their respective order statistics...
For a sample of iid observations {(Xi, Yi)} from an absolutely continuous distribution, the multiva...
Given a bivariate sample [special characters omitted], the rth order statistic [special characters o...
AbstractFor a sample of iid observations {(Xi, Yi)} from an absolutely continuous distribution, the ...
Let (X1, . . . ,Xn) be a random vector distributed according to a time-transformed exponential model...
AbstractGiven a random sample from a continuous variable, it is observed that the copula linking any...
AbstractLet Rn be the range of a random sample X1,…,Xn of exponential random variables with hazard r...
Using the concept of r-extremal dependence, which generalizes Lai and Robbins (1976) maximal depende...
In many practical applications, mathematical models of ordered random variables play an important ro...
Given a random sample from a continuous variable, it is observed that the copula linking any pair of...
AbstractLet X=(X1,X2,…,Xn) be a random vector, and denote by X1:n,X2:n,…,Xn:n the corresponding orde...
We study the characteristics of the Pickands' dependence function for bivariate extreme distribution...
Let X1,…,Xn be mutually independent exponential random variables with distinct hazard rates λ1,…,λn ...
Abstract. Independent random variables Y1,..., Yn belongs to the pro-portional reversed hazard rate ...
AbstractLet (Xi, Yi) i=1, 2, …, n be n independent and identically distributed random variables from...
AbstractIfX1, …,Xnare random variables we denote byX(1)⩽X(2)⩽…⩽X(n)their respective order statistics...
For a sample of iid observations {(Xi, Yi)} from an absolutely continuous distribution, the multiva...
Given a bivariate sample [special characters omitted], the rth order statistic [special characters o...
AbstractFor a sample of iid observations {(Xi, Yi)} from an absolutely continuous distribution, the ...
Let (X1, . . . ,Xn) be a random vector distributed according to a time-transformed exponential model...
AbstractGiven a random sample from a continuous variable, it is observed that the copula linking any...
AbstractLet Rn be the range of a random sample X1,…,Xn of exponential random variables with hazard r...
Using the concept of r-extremal dependence, which generalizes Lai and Robbins (1976) maximal depende...
In many practical applications, mathematical models of ordered random variables play an important ro...
Given a random sample from a continuous variable, it is observed that the copula linking any pair of...
AbstractLet X=(X1,X2,…,Xn) be a random vector, and denote by X1:n,X2:n,…,Xn:n the corresponding orde...
We study the characteristics of the Pickands' dependence function for bivariate extreme distribution...