Convergence of partial sum processes to stable processes with application for aggregation of branching processes

We provide a generalization of Theorem 1 in Bartkiewicz et al. (2011) in the sense that we give sufficient conditions for weak convergence of finite dimensional distributions of the partial sum processes of a strongly stationary sequence to the corresponding finite dimensional distributions of a non-Gaussian stable process instead of weak convergence of the partial sums themselves to a non-Gaussian stable distribution. As an application, we describe the asymptotic behaviour of finite dimensional distributions of aggregation of independent copies of a strongly stationary subcritical Galton-Watson branching process with regularly varying immigration having index in (0, 1) boolean OR (1, 4/3) in a so-called iterated case, namely when first taking the limit as the time scale and then the number of copies tend to infinity.

Automated summary

This article provides a generalization of Theorem 1 in Bartkiewicz et al. (2011) by giving sufficient conditions for weak convergence of finite dimensional distributions of the partial sum processes of a strongly stationary sequence to the corresponding finite dimensional distributions of a non-Gaussian stable process. It also applies the results to the asymptotic behavior of finite dimensional distributions of aggregation of independent copies of a strongly stationary subcritical Galton-Watson branching process.