Statistical inference for critical continuous state and continuous time branching processes with immigration
Matyas Barczy, Krist\'of K\"ormendi, Gyula Pap
TL;DR
This paper investigates the asymptotic properties of conditional least squares estimators for critical continuous state and continuous time branching processes with immigration, using discrete low-frequency observations.
Contribution
It provides new theoretical insights into the behavior of estimators for a specific class of stochastic processes under discrete observation schemes.
Findings
Asymptotic behavior characterized for estimators
Results applicable to critical branching processes with immigration
Theoretical framework for low frequency data analysis
Abstract
We study asymptotic behavior of conditional least squares estimators for critical continuous state and continuous time branching processes with immigration based on discrete time (low frequency) observations.
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Taxonomy
TopicsStochastic processes and statistical mechanics · Bayesian Methods and Mixture Models · Markov Chains and Monte Carlo Methods