Sharp Threshold for the Convergence of Nonstationary Averaging
Probability
2026-03-18 v1
Abstract
We study non-stationary averaging processes, where each term of a sequence is a weighted average of previous terms, namely . Our results extend classical theory in two distinct regimes. First, we prove a sharp threshold for convergence in the regime where the weights are bounded between two envelopes . We show that the sequence necessarily converges when , while the convergence can fail. Second, we study complementary fixed shape regime, when is obtained by a fixed limiting density on . We show that under mild regularity assumptions, the sequence converges.
Keywords
Cite
@article{arxiv.2603.16678,
title = {Sharp Threshold for the Convergence of Nonstationary Averaging},
author = {Saba Lepsveridze and Elchanan Mossel},
journal= {arXiv preprint arXiv:2603.16678},
year = {2026}
}
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29 pages