On convergence of Baum-Katz series for elements of linear autoregression
Maryna Ilienko
TL;DR
This paper investigates the conditions under which the Baum-Katz series converges for linear autoregression sequences, establishing criteria based on moments that align with classical independent cases for weakly dependent sequences.
Contribution
It provides new convergence criteria for Baum-Katz series in linear autoregression sequences, extending classical results to dependent data.
Findings
Criteria for convergence based on moment conditions
Results applicable to weakly dependent sequences
Extension of classical independent case results
Abstract
We study complete convergence and closely related Hsu-Robbins-Erd\H{o}s-Spitzer-Baum-Katz series for sums whose terms are elements of linear autoregression sequences. We obtain criterions for convergence of this series expressed in moment assumptions, which for "weakly dependent" sequences are the same as in classical results concerning independent case.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.