Abstract:We investigate multivariate regular variation in the context of time-homogeneous Markov chains on general vector spaces and in random coefficient linear models. In the first part, we show that the regular variation of the stationary distribution can be derived from that of the innovations, provided that the chain satisfies a certain monotonicity condition with respect to a gauge function.
In the second part, we study random linear models with random coefficients defined by an explicit iterative scheme. We prove that the precise structure of the underlying chain affects the form of the associated spectral measure.
From: Tamara Mika [view email]
[v1]
Wed, 22 Oct 2025 07:16:49 UTC (28 KB)
[v2]
Wed, 2 Sep 2026 09:13:22 UTC (30 KB)
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。