Stable convergence of conditional least squares estimators for supercritical continuous state and continuous time branching processes with immigration

TL;DR

This paper proves the stable convergence of conditional least squares estimators for drift parameters in supercritical continuous state and continuous time branching processes with immigration, based on discrete observations.

Contribution

It establishes the stable convergence of estimators for a class of branching processes with immigration, a novel theoretical result.

Findings

Proves stable convergence of estimators in the specified process class

Provides theoretical foundation for parameter estimation in continuous-time branching processes

Enhances understanding of asymptotic behavior of estimators in supercritical regimes

Abstract

We prove stable convergence of conditional least squares estimators of drift parameters for supercritical continuous state and continuous time branching processes with immigration based on discrete time observations.