International audienceWe establish a general sufficient condition for a sequence of Galton–Watson branching processes in varying environments to converge weakly. This condition extends previ- ous results by allowing offspring distributions to have infinite variance. Our assumptions are stated in terms of pointwise convergence of a triplet of two real- valued functions and a measure. The limiting process is characterized by a backwards integro-differential equation satisfied by its Laplace exponent, which generalizes the branching equation satisfied by continuous state branching processes. Several examples are discussed, namely branching processes in random environment, Feller diffusion in varying environments and branching processes with ca...
We discuss uniform infinite causal triangulations and equivalence to the size biased branching proce...
We introduce a branching process in a sparse random environment as an intermediate model between a G...
AbstractIt is shown that any real-valued sequence of random variables {Xn} converging in probability...
International audienceWe establish a general sufficient condition for a sequence of Galton–Watson br...
Renormalized sequences of Galton Watson processes converge to Continuous State Branching Processes (...
Let {Zn} be a supercritical Galton-Watson process in varying environments. It is known that Zn when ...
AbstractAllowing an offspring probability distribution that has infinite variances, we establish the...
Our motivation comes from the large population approximation of individual based models in populatio...
Abstract: We prove that the fluctuation limit of a sequence of Galton-Watson branching processes wit...
We investigate limit properties of discrete time branching processes with application of the theory...
We present some limit theorems for branching processes in random environments, which can be found in...
We consider a particle system in continuous time, discrete population, with spatial motion and nonlo...
We introduce Galton-Watson style branching processes in randomenvironments which are deteriorating r...
AbstractThe exponential limit law for the critical multitype Bienaymé-Galton-Watson process is exten...
In this paper we prove a conditional limit theorem for a critical Galton-Watson branching process {Z...
We discuss uniform infinite causal triangulations and equivalence to the size biased branching proce...
We introduce a branching process in a sparse random environment as an intermediate model between a G...
AbstractIt is shown that any real-valued sequence of random variables {Xn} converging in probability...
International audienceWe establish a general sufficient condition for a sequence of Galton–Watson br...
Renormalized sequences of Galton Watson processes converge to Continuous State Branching Processes (...
Let {Zn} be a supercritical Galton-Watson process in varying environments. It is known that Zn when ...
AbstractAllowing an offspring probability distribution that has infinite variances, we establish the...
Our motivation comes from the large population approximation of individual based models in populatio...
Abstract: We prove that the fluctuation limit of a sequence of Galton-Watson branching processes wit...
We investigate limit properties of discrete time branching processes with application of the theory...
We present some limit theorems for branching processes in random environments, which can be found in...
We consider a particle system in continuous time, discrete population, with spatial motion and nonlo...
We introduce Galton-Watson style branching processes in randomenvironments which are deteriorating r...
AbstractThe exponential limit law for the critical multitype Bienaymé-Galton-Watson process is exten...
In this paper we prove a conditional limit theorem for a critical Galton-Watson branching process {Z...
We discuss uniform infinite causal triangulations and equivalence to the size biased branching proce...
We introduce a branching process in a sparse random environment as an intermediate model between a G...
AbstractIt is shown that any real-valued sequence of random variables {Xn} converging in probability...