We consider the tail behavior of the product of two independent nonnegative random variables X and Y. Breiman (1965) has considered this problem assuming that X is regularly varying with index α and that E{Y α+} < ∞ for some > 0. We investigate when the condition on Y can be weakened and apply our findings to analyze a class of random difference equations
AbstractFrom simple and natural assumptions, we study the functional asymptotic behavior in law of s...
Existence and stability of stationary solutions of nonlinear random difference equations are studied...
AbstractLet τ: [0, 1] → [0, 1] possess a unique invariant density f∗. Then given any ϵ > 0, we can f...
We consider the tail behavior of the product of two independent nonnegative random variables X and Y...
AbstractIn this paper we study the distributional tail behavior of the solution to a linear stochast...
International audienceIn this paper we study the dsitributional tail behavior of the solution to a l...
Abstract: It is shown that the tail behavior of the function of nonnegative random variables can be ...
Let X and Y be two nonnegative and dependent random variables following a generalized Farlie-Gumbel-...
Consider the series ¿n CnZn where Zn are iid -valued random vectors and Cn are random matrices indep...
Let {ξ1, ξ2, . . .} be a sequence of independent random variables, and η be a counting random variab...
Consider the problem of approximating the tail probability of randomly weighted sums and their maxim...
We consider the equation Rn=Qn+MnRn-1, with random non-i.i.d. coefficients , and show that the distr...
© 2015 Springer Science+Business Media New York. Let {X, Xi, i = 1, 2, . . . } be independent nonneg...
AbstractA classic result in probability theory states that two independent real-valued random variab...
Existence and stability of stationary solutions of nonlinear random difference equations are studied...
AbstractFrom simple and natural assumptions, we study the functional asymptotic behavior in law of s...
Existence and stability of stationary solutions of nonlinear random difference equations are studied...
AbstractLet τ: [0, 1] → [0, 1] possess a unique invariant density f∗. Then given any ϵ > 0, we can f...
We consider the tail behavior of the product of two independent nonnegative random variables X and Y...
AbstractIn this paper we study the distributional tail behavior of the solution to a linear stochast...
International audienceIn this paper we study the dsitributional tail behavior of the solution to a l...
Abstract: It is shown that the tail behavior of the function of nonnegative random variables can be ...
Let X and Y be two nonnegative and dependent random variables following a generalized Farlie-Gumbel-...
Consider the series ¿n CnZn where Zn are iid -valued random vectors and Cn are random matrices indep...
Let {ξ1, ξ2, . . .} be a sequence of independent random variables, and η be a counting random variab...
Consider the problem of approximating the tail probability of randomly weighted sums and their maxim...
We consider the equation Rn=Qn+MnRn-1, with random non-i.i.d. coefficients , and show that the distr...
© 2015 Springer Science+Business Media New York. Let {X, Xi, i = 1, 2, . . . } be independent nonneg...
AbstractA classic result in probability theory states that two independent real-valued random variab...
Existence and stability of stationary solutions of nonlinear random difference equations are studied...
AbstractFrom simple and natural assumptions, we study the functional asymptotic behavior in law of s...
Existence and stability of stationary solutions of nonlinear random difference equations are studied...
AbstractLet τ: [0, 1] → [0, 1] possess a unique invariant density f∗. Then given any ϵ > 0, we can f...