We study weak convergence of a sequence of point processes to a scale-invariant simple point process. For a deterministic sequence (zn)n∈N of positive real numbers increasing to infinity as n→∞ and a sequence (Xk)k∈N of independent non-negative integer-valued random variables, we consider the sequence of point processes νn=∞∑k=1Xkδzk/zn,n∈N, and prove that, under some general conditions, it converges vaguely in distribution to a scale-invariant Poisson process ηc on (0,∞) with the intensity measure having the density ct−1, t∈(0,∞). An important motivating example from probabilistic number theory relies on choosing Xk∼Geom(1−1/pk) and zk=logpk, k∈N, where (pk)k∈N is an enumeration of the primes in increasing order. We derive a general result...
This dissertation aims to investigate several aspects of the Poisson convergence: Poisson approximat...
AbstractIn this paper the convergence of suitably normalized thinning processes is considered. That ...
Abstract. Consider a time-varying collection of n points on the positive real axis, modeled as Expon...
AbstractWe give a new sufficient condition for convergence to a Poisson distribution of a sequence o...
Define the scaled empirical point process on an independent and iden-tically distributed sequence {Y...
AbstractLet ηt be a Poisson point process of intensity t≥1 on some state space Y and let f be a non-...
Let η t be a Poisson point process with intensity measure tμ , t>0 , over a Borel space X , where ...
AbstractWe give a new sufficient condition for convergence to a Poisson distribution of a sequence o...
International audienceWe study systems of simple point processes that admit stochastic intensities. ...
Pick n points independently at random in R2, according to a prescribed probability measure µ, and le...
International audienceWe study systems of simple point processes that admit stochastic intensities. ...
International audienceWe study systems of simple point processes that admit stochastic intensities. ...
Stein’s method constitutes one of the main techniques to solve some approximation problems in probab...
Stein’s method constitutes one of the main techniques to solve some approximation problems in probab...
Stein’s method constitutes one of the main techniques to solve some approximation problems in probab...
This dissertation aims to investigate several aspects of the Poisson convergence: Poisson approximat...
AbstractIn this paper the convergence of suitably normalized thinning processes is considered. That ...
Abstract. Consider a time-varying collection of n points on the positive real axis, modeled as Expon...
AbstractWe give a new sufficient condition for convergence to a Poisson distribution of a sequence o...
Define the scaled empirical point process on an independent and iden-tically distributed sequence {Y...
AbstractLet ηt be a Poisson point process of intensity t≥1 on some state space Y and let f be a non-...
Let η t be a Poisson point process with intensity measure tμ , t>0 , over a Borel space X , where ...
AbstractWe give a new sufficient condition for convergence to a Poisson distribution of a sequence o...
International audienceWe study systems of simple point processes that admit stochastic intensities. ...
Pick n points independently at random in R2, according to a prescribed probability measure µ, and le...
International audienceWe study systems of simple point processes that admit stochastic intensities. ...
International audienceWe study systems of simple point processes that admit stochastic intensities. ...
Stein’s method constitutes one of the main techniques to solve some approximation problems in probab...
Stein’s method constitutes one of the main techniques to solve some approximation problems in probab...
Stein’s method constitutes one of the main techniques to solve some approximation problems in probab...
This dissertation aims to investigate several aspects of the Poisson convergence: Poisson approximat...
AbstractIn this paper the convergence of suitably normalized thinning processes is considered. That ...
Abstract. Consider a time-varying collection of n points on the positive real axis, modeled as Expon...