This course concerns the stochastic modeling of population dynamics. In the first part, we focus on monotype populations described by one-dimensional stochastic differential …
LJS Allen - Mathematical biosciences lecture series, stochastics in …, 2015 - Springer
The intent of this monograph is to introduce graduate students to branching process applications of populations and epidemics. Deterministic models of populations and …
Y Jiao, C Ma, S Scotti, C Sgarra - Energy Economics, 2019 - Elsevier
We propose and investigate a market model for power prices, including most basic features exhibited by previous models and taking into account self-exciting properties. The model …
In this paper, we introduce branching processes in a Lévy random environment. In order to define this class of processes, we study a particular class of non-negative stochastic …
YQ Wang, QS Liu - Science China Mathematics, 2017 - Springer
Let (Z n) be a supercritical branching process with immigration in a random environment. Firstly, we prove that under a simple log moment condition on the offspring and immigration …
H He, Z Li, W Xu - Journal of Theoretical Probability, 2018 - Springer
A general continuous-state branching processes in random environment (CBRE-process) is defined as the strong solution of a stochastic integral equation. The environment is …
V Bansaye, F Simatos - Electronic Journal of Probability, 2015 - projecteuclid.org
; We establish a general sufficient condition for a sequence of Galton-Watson branching processes in varying environments to converge weakly. This condition extends previous …
S Palau, JC Pardo - Stochastic Processes and their Applications, 2017 - Elsevier
We consider continuous-state branching processes that are perturbed by a Brownian motion. These processes are constructed as the unique strong solution of a stochastic …
Z Li, W Xu - Stochastic Processes and their Applications, 2018 - Elsevier
The asymptotic behavior of expectations of some exponential functionals of a Lévy process is studied. The key point is the observation that the asymptotics only depend on the sample …