AbstractA general approach for the development of multivariate survival models, based on a set of given marginal survivals, is presented. Preservation of IFR and IFRA properties and the nature of dependence among the variables are examined, and a recursive relation is suggested to obtain the resultant density function. In particular, an absolutely continuous Weibull distribution is derived and a few of its properties are studied
Freund [1961] introduced a bivariate extension of the exponential distribution that provides a model...
Ford >= 2, let X = (X(1),...,X(d)) be a vector of exchangeable continuous lifetimes with joint survi...
Multivariate survival analysis involves the study of failure times, including the influence of covar...
AbstractA general approach for the development of multivariate survival models, based on a set of gi...
A new class of bivariate survival distributions is constructed from a given family of survival distr...
AbstractA new class of bivariate survival distributions is constructed from a given family of surviv...
A Bivariate survival model is constructed.This model is based on a frailty model that acts multiplic...
A multivariate survival function of Weibull Distribution is developed by expanding the theorem by Lu...
AbstractWe extend and generalize to the multivariate set-up our earlier investigations related to ex...
AbstractThis paper introduces and studies a class of multivariate survival functions with given univ...
Multivariate modeling and analysis based on the multivariate normal distribution is well established...
AbstractNew classes of multivariate survival distribution functions based on monotonic behaviour of ...
In this paper, we introduce a new family of multivariate distributions, so called the multivariate p...
For d≥2, let X=(X1, , Xd) be a vector of exchangeable continuous lifetimes with joint survival funct...
New classes of multivariate survival distribution functions based on monotonic behaviour of a multiv...
Freund [1961] introduced a bivariate extension of the exponential distribution that provides a model...
Ford >= 2, let X = (X(1),...,X(d)) be a vector of exchangeable continuous lifetimes with joint survi...
Multivariate survival analysis involves the study of failure times, including the influence of covar...
AbstractA general approach for the development of multivariate survival models, based on a set of gi...
A new class of bivariate survival distributions is constructed from a given family of survival distr...
AbstractA new class of bivariate survival distributions is constructed from a given family of surviv...
A Bivariate survival model is constructed.This model is based on a frailty model that acts multiplic...
A multivariate survival function of Weibull Distribution is developed by expanding the theorem by Lu...
AbstractWe extend and generalize to the multivariate set-up our earlier investigations related to ex...
AbstractThis paper introduces and studies a class of multivariate survival functions with given univ...
Multivariate modeling and analysis based on the multivariate normal distribution is well established...
AbstractNew classes of multivariate survival distribution functions based on monotonic behaviour of ...
In this paper, we introduce a new family of multivariate distributions, so called the multivariate p...
For d≥2, let X=(X1, , Xd) be a vector of exchangeable continuous lifetimes with joint survival funct...
New classes of multivariate survival distribution functions based on monotonic behaviour of a multiv...
Freund [1961] introduced a bivariate extension of the exponential distribution that provides a model...
Ford >= 2, let X = (X(1),...,X(d)) be a vector of exchangeable continuous lifetimes with joint survi...
Multivariate survival analysis involves the study of failure times, including the influence of covar...