Let (X1, . . . ,Xn) be a random vector distributed according to a time-transformed exponential model. This is a special class of exchangeable models, which, in particular, includes multivariate distributions with Schur-constant survival functions and with identical marginals. Let for 1 ≤ i ≤ n, Xi:n denote the corresponding ith order statistic. We consider the problem of comparing the strength of dependence between any pair of Xi’s with that of the corresponding order statistics. It is proved that for m = 2, . . . , n, the dependence of X2:m on X1:m is more than that of X2 on X1 according to more stochastic increasingness (positive monotone regression) order, which in turn implies that (X1:m,X2:m) is more concordant than (X1,X2). It will be...
In this note we compare bivariate additive models with respect to their Pearson correlation coecient...
AbstractLet X1,…,Xn be a random sample from an absolutely continuous distribution with non-negative ...
This paper presents a framework for comparing bivariate distributions according to their degree of r...
AbstractGiven a random sample from a continuous variable, it is observed that the copula linking any...
Given a random sample from a continuous variable, it is observed that the copula linking any pair of...
AbstractFor a sample of iid observations {(Xi, Yi)} from an absolutely continuous distribution, the ...
AbstractIn this paper, we introduce a new copula-based dependence order to compare the relative degr...
AbstractIfX1, …,Xnare random variables we denote byX(1)⩽X(2)⩽…⩽X(n)their respective order statistics...
AbstractLet (Xi, Yi) i=1, 2, …, n be n independent and identically distributed random variables from...
AbstractLet X=(X1,X2,…,Xn) be a random vector, and denote by X1:n,X2:n,…,Xn:n the corresponding orde...
Let X1,…,Xn be mutually independent exponential random variables with distinct hazard rates λ1,…,λn ...
Given a bivariate sample [special characters omitted], the rth order statistic [special characters o...
AbstractEvery univariate random variable is smaller, with respect to the ordinary stochastic order a...
For a sample of iid observations {(Xi, Yi)} from an absolutely continuous distribution, the multiva...
Different sufficient conditions for stochastic comparisons between random vectors have been describe...
In this note we compare bivariate additive models with respect to their Pearson correlation coecient...
AbstractLet X1,…,Xn be a random sample from an absolutely continuous distribution with non-negative ...
This paper presents a framework for comparing bivariate distributions according to their degree of r...
AbstractGiven a random sample from a continuous variable, it is observed that the copula linking any...
Given a random sample from a continuous variable, it is observed that the copula linking any pair of...
AbstractFor a sample of iid observations {(Xi, Yi)} from an absolutely continuous distribution, the ...
AbstractIn this paper, we introduce a new copula-based dependence order to compare the relative degr...
AbstractIfX1, …,Xnare random variables we denote byX(1)⩽X(2)⩽…⩽X(n)their respective order statistics...
AbstractLet (Xi, Yi) i=1, 2, …, n be n independent and identically distributed random variables from...
AbstractLet X=(X1,X2,…,Xn) be a random vector, and denote by X1:n,X2:n,…,Xn:n the corresponding orde...
Let X1,…,Xn be mutually independent exponential random variables with distinct hazard rates λ1,…,λn ...
Given a bivariate sample [special characters omitted], the rth order statistic [special characters o...
AbstractEvery univariate random variable is smaller, with respect to the ordinary stochastic order a...
For a sample of iid observations {(Xi, Yi)} from an absolutely continuous distribution, the multiva...
Different sufficient conditions for stochastic comparisons between random vectors have been describe...
In this note we compare bivariate additive models with respect to their Pearson correlation coecient...
AbstractLet X1,…,Xn be a random sample from an absolutely continuous distribution with non-negative ...
This paper presents a framework for comparing bivariate distributions according to their degree of r...